Evaluation code for paper 1

author: SoloDShelby 2024-07-19 14:41:40 +0300
committer: SoloDShelby 2024-07-19 14:41:40 +0300
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diff --git a/gnqa/paper1_eval/src/data/responses/general/answer_relevancy.json b/gnqa/paper1_eval/src/data/responses/general/answer_relevancy.json
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+A1: Air pollution is the most cited environmental factor for the onset of asthma.
+
+The given answer is: "Air pollution is the most cited environmental factor for the onset of asthma."
+
+Question: What is the most cited environmental factor for the onset of asthma?
+
+The answer is committal as it provides a specific and direct response to the question. Therefore, the noncommittal value is 0.
diff --git a/gnqa/paper1_eval/src/data/responses/general/answer_relevancy.md b/gnqa/paper1_eval/src/data/responses/general/answer_relevancy.md
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+# Answer Relevancy
+
+## 1
+
+### Prompt 1 
+Generate 3 questions from the answer [Air pollution is the most cited environmental factor for the onset of asthma.]
+
+#### Generated questions
+
+1. What is the most cited environmental factor for the onset of asthma?
+1. Which factor is most commonly linked to the development of asthma?
+1. What is the leading cause of asthma in relation to the environment?
+
+### Prompt 2
+
+Generate a question for the given answer and Identify if answer is noncommittal. Give noncommittal as 1 if the answer is noncommittal and 0 if the answer is committal. A noncommittal answer is one that is evasive, vague, or ambiguous. For example, "I don't know" or "I'm not sure" are noncommittal answers. The given answer is [Air pollution is the most cited environmental factor for the onset of asthma.]
+
+
+### Response
+The given answer is: "Air pollution is the most cited environmental factor for the onset of asthma."
+
+Question: What is the most cited environmental factor for the onset of asthma?
+
+The answer is committal as it provides a specific and direct response to the question. Therefore, the noncommittal value is 0.
+
+# 2
+
+### Prompt
+Generate a question for the given answer and Identify if answer is noncommittal. Give noncommittal as 1 if the answer is noncommittal and 0 if the answer is committal. A noncommittal answer is one that is evasive, vague, or ambiguous. For example, "I don't know" or "I'm not sure" are noncommittal answers. The given answer is [Apoptosis, also known as cell suicide or programmed cell death, is a biological process in multicellular organisms that allows specific cells to be removed during the development of complex tissues, or potentially dangerous damaged cells to be destroyed for the benefit of the whole organism. It is characterized by a sequence of well-defined events resulting in cell destruction and is necessary for normal cell turnover. It is also essential to various other biological processes.]
+
+### Response
+
+## 3
+
+### Prompt
+
+Generate a question for the given answer and Identify if answer is noncommittal. Give noncommittal as 1 if the answer is noncommittal and 0 if the answer is committal. A noncommittal answer is one that is evasive, vague, or ambiguous. For example, "I don't know" or "I'm not sure" are noncommittal answers. The given answer is []
+
+### Response
+
+
+## 4 
+
+### Prompt
+
+Generate a question for the given answer and Identify if answer is noncommittal. Give noncommittal as 1 if the answer is noncommittal and 0 if the answer is committal. A noncommittal answer is one that is evasive, vague, or ambiguous. For example, "I don't know" or "I'm not sure" are noncommittal answers. The given answer is []
+
+### Response
+
+
+## 5 
+
+### Prompt
+
+Generate a question for the given answer and Identify if answer is noncommittal. Give noncommittal as 1 if the answer is noncommittal and 0 if the answer is committal. A noncommittal answer is one that is evasive, vague, or ambiguous. For example, "I don't know" or "I'm not sure" are noncommittal answers. The given answer is []
+
+### Response
+
+
+
+## 6 
+
+### Prompt
+
+Generate a question for the given answer and Identify if answer is noncommittal. Give noncommittal as 1 if the answer is noncommittal and 0 if the answer is committal. A noncommittal answer is one that is evasive, vague, or ambiguous. For example, "I don't know" or "I'm not sure" are noncommittal answers. The given answer is []
+
+### Response
+
+
+
+## 7 
+
+### Prompt
+
+Generate a question for the given answer and Identify if answer is noncommittal. Give noncommittal as 1 if the answer is noncommittal and 0 if the answer is committal. A noncommittal answer is one that is evasive, vague, or ambiguous. For example, "I don't know" or "I'm not sure" are noncommittal answers. The given answer is []
+
+### Response
+
+
+
+
+
+## 8 
+
+### Prompt
+
+Generate a question for the given answer and Identify if answer is noncommittal. Give noncommittal as 1 if the answer is noncommittal and 0 if the answer is committal. A noncommittal answer is one that is evasive, vague, or ambiguous. For example, "I don't know" or "I'm not sure" are noncommittal answers. The given answer is []
+
+### Response
+
+
+
+## 9
+
+### Prompt
+
+Generate a question for the given answer and Identify if answer is noncommittal. Give noncommittal as 1 if the answer is noncommittal and 0 if the answer is committal. A noncommittal answer is one that is evasive, vague, or ambiguous. For example, "I don't know" or "I'm not sure" are noncommittal answers. The given answer is []
+
+### Response
+
+
+
+## 10 
+
+### Prompt
+
+Generate a question for the given answer and Identify if answer is noncommittal. Give noncommittal as 1 if the answer is noncommittal and 0 if the answer is committal. A noncommittal answer is one that is evasive, vague, or ambiguous. For example, "I don't know" or "I'm not sure" are noncommittal answers. The given answer is []
+
+### Response
+
+
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/01.json b/gnqa/paper1_eval/src/data/responses/general/experts/01.json
new file mode 100644
index 0000000..d8912cf
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/01.json
@@ -0,0 +1,408 @@
+{
+    "created_at": "2024-05-31T13:08:08.864950Z",
+    "data": {
+        "amplify": false,
+        "answer": "To determine which gene in your QTL is causal for the trait, you can follow several steps. First, narrow down the QTL interval to a reasonable size. Then, sort through the genes within the interval to identify potential Quantitative Trait Genes (QTGs). This can be challenging as more than one gene may be involved and the function of some genes may be unknown. You can use techniques like LCMS to establish causal relationships between DNA loci and transcripts. Once potential QTGs are identified, you need to prove that a particular gene is involved in the quantitative trait under study. This can be done by complementation of a QTL, which can be achieved in several ways. You can also use mediation analysis to identify the causal gene between the genetic variant and the trait-of-interest. Finally, investigate whether the expression of these genes correlates with the phenotype(s) of interest. If the gene expression strongly correlates with the QTL phenotype, this further strengthens the assumption that this gene might be causal.",
+        "context": {
+            "07d409f4-91f9-4701-bb39-1421845a6321": [
+                {
+                    "document_id": "07d409f4-91f9-4701-bb39-1421845a6321",
+                    "text": "Prior belief or knowledge about the number of true causal and true\nindependent links that might be expected in a typical QTL, depending on the study\ndesign, should be considered to safeguard against high false-positive rates (low\npositive predictive values). In studies that involve mapping gene expression (eQTL),\nprotein (pQTL) or metabolite (mQTL) traits, information about co-localization of\nQTL and genes that are functionally linked to the trait provides information about\nthe likelihood of causal links."
+                }
+            ],
+            "1a041a89-4da8-4ad5-b241-da36df917930": [
+                {
+                    "document_id": "1a041a89-4da8-4ad5-b241-da36df917930",
+                    "text": "\n\nThe next step is to investigate whether the expression of these genes correlates with the phenotype(s) of interest.This would suggest a chain of causality: a variant within a gene causes a change in its expression, and the expression of that gene correlates with expression of a phenotypic trait of interest.To do this, we created a correlation matrix between all genes within a QTL with a cis-eQTL in any brain tissue as well as the phenotypes that contributed to the QTL (Supplementary Table S6).Any gene with a cis-eQTL and a significantly correlated expression was considered a good candidate.If the gene only had a cis-eQTL and correlation in a single brain region, then it suggested that this brain region might also be of interest for the phenotype (adding another link to this chain)."
+                }
+            ],
+            "33814fad-d831-46f5-b41f-ff31626a82ca": [
+                {
+                    "document_id": "33814fad-d831-46f5-b41f-ff31626a82ca",
+                    "text": "One possible approach to facilitate this endeavor is to identify quantitative trait loci\n(QTL) that contribute to the phenotype and consequently unravel the candidate\ngenes within these loci. Each proposed candidate locus contains multiple genes and,\ntherefore, further analysis is required to choose plausible candidate genes. One of\nsuch methods is to use comparative genomics in order to narrow down the QTL to a\nregion containing only a few genes. We illustrate this strategy by applying it to\ngenetic findings regarding physical activity (PA) in mice and human."
+                }
+            ],
+            "4049da4d-c7cf-4e30-9a21-c77609fad23d": [
+                {
+                    "document_id": "4049da4d-c7cf-4e30-9a21-c77609fad23d",
+                    "text": "Network analyses\nWe now have two QTL, and we have picked potentially interesting genes within each, but now\nwe want to build up more evidence for which gene in our QTL interval is causal. The first, and\nmost obvious way, is to see what genes our trait of interest correlates with, in tissues that we\nexpect to be related to the trait. We calculated the Spearman’s correlation between the trait\nBXD_17850 and all probes with expression data in T helper cells (GN319)."
+                }
+            ],
+            "47c12133-5a30-45b9-bcb8-b96f00737f31": [
+                {
+                    "document_id": "47c12133-5a30-45b9-bcb8-b96f00737f31",
+                    "text": "Another\napproach to help to determine if a gene located near the mapped QTL would\nhave effects to influence the quantitative trait will be to use genetically engineered mice to determine if altering the expression of a candidate gene will alter\nthe phenotype of interest (38). However, it is possible that a quantitative trait is\na combined effect of multiple genes located near the QTL (39)."
+                }
+            ],
+            "547ce63b-5178-45cb-ae07-12ae66aa2967": [
+                {
+                    "document_id": "547ce63b-5178-45cb-ae07-12ae66aa2967",
+                    "text": "With a known QTL and a\nbody of evidence suggesting possible roles for the affected gene,\nphenotypes can be predicted that may be modulated as a result\nof this sequence variation. If this phenotype is of interest, it\ncan be directly measured and a traditional ‘forward’ QTL analysis carried out to confirm the prediction. Such an approach is\nextremely attractive when the enormous cost and time required\nfor phenotyping a large panel is considered."
+                }
+            ],
+            "581f83bc-3521-4cb3-ad3c-d905a90ecc29": [
+                {
+                    "document_id": "581f83bc-3521-4cb3-ad3c-d905a90ecc29",
+                    "text": "The first\nstep is to narrow down the list of\ncandidate causal genes within a\nFig\n1. Interval\nmapping\nof\noviduct\ngross\npathology\nacross\nthe\nBXD\nstrains\n\nQuantitative Trait Locus (QTL)—a\nreveals\na\nQTL\non\ndistal\nChr\n3. The\nL RS\nvalues\nare\nplotted\nin\nblue\nacross\nthe\n\nchromosomal region containing\ngenome\nand\nmeasure\nthe\nstrength\nof\nthe\nassociation\nbetween\n\nsequence variants strongly\nchromosome\nand\nMb\nposition\n(top\nand\nbottom\nX-‐axis,\nrespectively)\nand\n\nassociated with phenotypic\nphenotype\nexpression. Allele\ncontribution\nis\nshown\nby\nthe\nred\n(C57BL/6J)\n\nand\ngreen\n(DBA/2J)\nlines. Red\nand\ngrey\nhorizontal\nlines\nindicate\ngenome-‐\nvariation."
+                }
+            ],
+            "5a56fa6d-9e77-4b95-a836-04d0fa31ee2c": [
+                {
+                    "document_id": "5a56fa6d-9e77-4b95-a836-04d0fa31ee2c",
+                    "text": "A special case is the\ncorrelation of the target phenotype with the expression of the\npriorized gene(s) (RNA or protein amounts). This refers to\ncolocalization of the QTL of the target phenotype with the\neQTL position. Correlation can also be examined between the\ntarget QTL phenotype and expression of all genes in the QTL\ninterval. If the gene expression strongly correlates with the\nQTL phenotype, this further strengthens the assumption that\nthis gene might be causal (see Note 12). For performing a correlation analysis:\n–\n\nGo to the Trait Overview Page, as described in step 3, point\n1."
+                }
+            ],
+            "64886b4e-8599-4f61-84e6-9add7663a1b3": [
+                {
+                    "document_id": "64886b4e-8599-4f61-84e6-9add7663a1b3",
+                    "text": "QTL mapping of traits in mouse cohorts often ends up with a genetic locus, composed of a list of candidate\ngenes. Several studies proposed the use of mediation analysis to identify the causal gene (mediator) between\nthe genetic variant (independent variable) and the trait-of-interest (dependent variable) (Figure 1.4B) [7, 47,\n61, 77]. Mediation analysis can be used either on gene expression levels to identify the regulatory mechanisms\n[7, 47, 61], or on phenotypic traits to discover the potential causal drivers contributing to the phenotypic\nvariances [77] (Figure 1.4C upper)."
+                }
+            ],
+            "7a451204-390c-4ff2-8a1d-b4de62b73503": [
+                {
+                    "document_id": "7a451204-390c-4ff2-8a1d-b4de62b73503",
+                    "text": "1a). Second-generation offspring are then\nphenotyped and genotyped, and linkage analysis is carried out to identify a region that is\nassociated with the trait1. This approach has led to the identification of thousands of quantitative trait loci (QTLs) for\nvarious phenotypes and diseases. However, each QTL region is large, often tens of\nmegabases, and contains hundreds of genes. The process of identifying the causal variant\nand the gene involved is therefore difficult and costly. Of the thousands of QTLs identified,\nonly a small fraction of genes has been identified. NIH-PA Author Manuscript\n\n© 2012 Macmillan Publishers Limited."
+                }
+            ],
+            "7b1cecf5-a2b9-4bd9-b92b-9bd6b96ed93d": [
+                {
+                    "document_id": "7b1cecf5-a2b9-4bd9-b92b-9bd6b96ed93d",
+                    "text": "Network analyses\nWe now have two QTL, and we have picked potentially interesting genes within each, but now\nwe want to build up more evidence for which gene in our QTL interval is causal. The first, and\nmost obvious way, is to see what genes our trait of interest correlates with, in tissues that we\nexpect to be related to the trait. We calculated the Spearman’s correlation between the trait\nBXD_17850 and all probes with expression data in T helper cells (GN319)."
+                }
+            ],
+            "7d866915-9d92-4401-8340-ffdef457debe": [
+                {
+                    "document_id": "7d866915-9d92-4401-8340-ffdef457debe",
+                    "text": "10 JUNE 2016 • VOL 352 ISSUE 6291\n\naad0189-5\nR ES E A RC H | R E S EA R C H A R T I C LE\n\nSolving QTLs: Finding the quantitative\ntrait gene\nFor cis-QTLs, the causal factors can be quickly\nidentified: With few exceptions, they will be driven by variants within the gene itself or immediately adjacent. For trans-QTLs, mQTLs, and\ncQTLs, the identification of the causal quantitative trait gene (QTG) is challenging due to the\nwidth of the QTLs."
+                }
+            ],
+            "95b99c09-c336-44fd-b378-f41991edb3aa": [
+                {
+                    "document_id": "95b99c09-c336-44fd-b378-f41991edb3aa",
+                    "text": "Once the QTL interval is reduced to a reasonable size,\nthe next step in the process involves sorting through the\ngenes within the interval and attempting to determine\nwhich is the QTG. This step is daunting because more than\none gene may be involved and the function of some genes\nwithin the interval may be unknown. Until recently, this\nstep emphasized the detection of polymorphisms within\ncoding sequence (reviewed in Korstanje and Paigen, 2002\nand Glazier et al. 2002); for a polymorphism that produces\nan amino acid substitution, one can often infer and then\ntest for a functional consequence."
+                }
+            ],
+            "abea3dd4-9492-4a2b-8904-b8052e384785": [
+                {
+                    "document_id": "abea3dd4-9492-4a2b-8904-b8052e384785",
+                    "text": "To understand the genetic networks that underlie\nquantitative variation in the trait, it is also very important to\ndiscover genes whose expression is correlated with the trait\nafter accounting for the known effects of the QTL on the\ntrait. Many of these genes may have expression that is\nassociated with QTL genotype, and would therefore be\nidentified as important via the tests described above. Other\n\ngenes, however, may have expression values that are correlated with the trait but unassociated with genotype at the\nQTL."
+                },
+                {
+                    "document_id": "abea3dd4-9492-4a2b-8904-b8052e384785",
+                    "text": "The\napproach is motivated by the fact that a research project is\noften focused on a specific classical quantitative trait. If a\nmajor QTL for this classical trait has been identified, it is\noften desirable to test whether this QTL is also associated\nwith the transcription level of any genes, which will provide clues as to which genes belong to the pathway that the\nQTL uses to modulate the classical trait."
+                }
+            ],
+            "d1f04d58-2589-4183-aee4-569820dae052": [
+                {
+                    "document_id": "d1f04d58-2589-4183-aee4-569820dae052",
+                    "text": "Confirmation of Candidate Genes\nThe next step is to prove that a particular gene is involved in the quantitative trait\nunder study. This is done by complementation of a QTL, which can be achieved in\nseveral ways (9–11,40). In principle, transgenic complementation is the most straightforward. This approach has been used successfully to demonstrate that Pla2g2a was\nthe correct candidate gene for Mom1, a modifier of the apcmin allele that causes\nadenomatous polyposis coli (41)."
+                }
+            ],
+            "da485354-fcdc-49b8-9a41-0f673610156a": [
+                {
+                    "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                    "text": "So, how do you go about planning and performing a QTL study, and how\ndo you identify the responsible gene within a QTL that you have identified? Generally, one starts by performing a strain survey to find two parental inbred\nstrains that have a markedly different trait. One can now look up many different\ntraits of inbred mice online at the Mouse Phenome Database (http://phenome. jax.org/pub-cgi/phenome/mpdcgi?rtn=docs/home). However, the trait you may\nwant to study may not be present in wild type mice, so you may want to cross\na mutant (or genetically engineered) strain onto several inbred strains."
+                }
+            ],
+            "f041550e-5f2d-430e-8f46-15ebea6ca496": [
+                {
+                    "document_id": "f041550e-5f2d-430e-8f46-15ebea6ca496",
+                    "text": "Along with correlations, this tool also derives new traits representing the\nprincipal components (Figure 2d). The user can add these principal components to their Trait\nCollection and proceed to perform QTL mapping, as in the case of a single trait QTL\nmapping. The R/QTL (Broman et al. 2003) and R/CAPE (Tyler et al. 2013) packages can be\nused for deeper analysis of epistasis and pleiotropy for multiple traits and multiple\nregulatory loci. Prioritizing Candidate Genes\n7\n\nAuthor Manuscript\n\nFollowing the identification of a significant QTL, focus shifts to identifying the\nparticular gene(s) that cause the QTL."
+                }
+            ],
+            "f4e26cf0-d214-41bf-b392-9c63a903b0b8": [
+                {
+                    "document_id": "f4e26cf0-d214-41bf-b392-9c63a903b0b8",
+                    "text": "The investigators\nfirst identified all QTLs associated with\na classical phenotype and then winnowed the list of potentially associated\ngene-expression traits on the basis of\ntheir correlation or eQTL overlap with\nthe phenotype of interest. Candidate\ngenes then were ranked by applying\n\nthe LCMS technique, which uses the\neQTL data to establish causal relationships between DNA loci and transcripts as well as between transcripts\nand phenotypes and finally identifies\na model that best fits the data."
+                }
+            ],
+            "ff35f4c8-b78b-4dad-9aa8-1bb16479872d": [
+                {
+                    "document_id": "ff35f4c8-b78b-4dad-9aa8-1bb16479872d",
+                    "text": "The goal of QTL mapping is clearly the\nidentification and eventual confirmation of candidate genes\n(QTGs) underlying the phenotype. The evidence required for\nsuch confirmation has engendered much discussion (Complex\nTrait Consortium 2003; Glazier et al. 2002) and is likely to vary\ndepending on the nature of the trait and specific resources\navailable to pin down underlying genes (e.g. availability of\nknock-in or knock-outs, specific antibodies, siRNA, etc.). The\npaucity of QTGs meeting such multifaceted standards is testament to the difficulty of narrowing the confidence interval\nsufficiently to identify and test suitable candidate genes (Flint\net al."
+                }
+            ]
+        },
+        "data_source": [
+            {
+                "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                "section_type": "main",
+                "text": "So, how do you go about planning and performing a QTL study, and how\ndo you identify the responsible gene within a QTL that you have identified?\n Generally, one starts by performing a strain survey to find two parental inbred\nstrains that have a markedly different trait.  One can now look up many different\ntraits of inbred mice online at the Mouse Phenome Database (http://phenome.\n jax.org/pub-cgi/phenome/mpdcgi?rtn=docs/home).  However, the trait you may\nwant to study may not be present in wild type mice, so you may want to cross\na mutant (or genetically engineered) strain onto several inbred strains."
+            },
+            {
+                "document_id": "7b1cecf5-a2b9-4bd9-b92b-9bd6b96ed93d",
+                "section_type": "main",
+                "text": "Network analyses\nWe now have two QTL, and we have picked potentially interesting genes within each, but now\nwe want to build up more evidence for which gene in our QTL interval is causal.  The first, and\nmost obvious way, is to see what genes our trait of interest correlates with, in tissues that we\nexpect to be related to the trait.  We calculated the Spearman’s correlation between the trait\nBXD_17850 and all probes with expression data in T helper cells (GN319)."
+            },
+            {
+                "document_id": "4049da4d-c7cf-4e30-9a21-c77609fad23d",
+                "section_type": "main",
+                "text": "Network analyses\nWe now have two QTL, and we have picked potentially interesting genes within each, but now\nwe want to build up more evidence for which gene in our QTL interval is causal.  The first, and\nmost obvious way, is to see what genes our trait of interest correlates with, in tissues that we\nexpect to be related to the trait.  We calculated the Spearman’s correlation between the trait\nBXD_17850 and all probes with expression data in T helper cells (GN319)."
+            },
+            {
+                "document_id": "47c12133-5a30-45b9-bcb8-b96f00737f31",
+                "section_type": "main",
+                "text": "Another\napproach to help to determine if a gene located near the mapped QTL would\nhave effects to influence the quantitative trait will be to use genetically engineered mice to determine if altering the expression of a candidate gene will alter\nthe phenotype of interest (38).  However, it is possible that a quantitative trait is\na combined effect of multiple genes located near the QTL (39)."
+            },
+            {
+                "document_id": "7a451204-390c-4ff2-8a1d-b4de62b73503",
+                "section_type": "main",
+                "text": "1a).  Second-generation offspring are then\nphenotyped and genotyped, and linkage analysis is carried out to identify a region that is\nassociated with the trait1.\n This approach has led to the identification of thousands of quantitative trait loci (QTLs) for\nvarious phenotypes and diseases.  However, each QTL region is large, often tens of\nmegabases, and contains hundreds of genes.  The process of identifying the causal variant\nand the gene involved is therefore difficult and costly.  Of the thousands of QTLs identified,\nonly a small fraction of genes has been identified.\n\n NIH-PA Author Manuscript\n\n© 2012 Macmillan Publishers Limited."
+            },
+            {
+                "document_id": "7d866915-9d92-4401-8340-ffdef457debe",
+                "section_type": "main",
+                "text": "10 JUNE 2016 • VOL 352 ISSUE 6291\n\naad0189-5\nR ES E A RC H | R E S EA R C H A R T I C LE\n\nSolving QTLs: Finding the quantitative\ntrait gene\nFor cis-QTLs, the causal factors can be quickly\nidentified: With few exceptions, they will be driven by variants within the gene itself or immediately adjacent.  For trans-QTLs, mQTLs, and\ncQTLs, the identification of the causal quantitative trait gene (QTG) is challenging due to the\nwidth of the QTLs."
+            },
+            {
+                "document_id": "f4e26cf0-d214-41bf-b392-9c63a903b0b8",
+                "section_type": "main",
+                "text": "The investigators\nfirst identified all QTLs associated with\na classical phenotype and then winnowed the list of potentially associated\ngene-expression traits on the basis of\ntheir correlation or eQTL overlap with\nthe phenotype of interest.  Candidate\ngenes then were ranked by applying\n\nthe LCMS technique, which uses the\neQTL data to establish causal relationships between DNA loci and transcripts as well as between transcripts\nand phenotypes and finally identifies\na model that best fits the data."
+            },
+            {
+                "document_id": "95b99c09-c336-44fd-b378-f41991edb3aa",
+                "section_type": "main",
+                "text": "Once the QTL interval is reduced to a reasonable size,\nthe next step in the process involves sorting through the\ngenes within the interval and attempting to determine\nwhich is the QTG.  This step is daunting because more than\none gene may be involved and the function of some genes\nwithin the interval may be unknown.  Until recently, this\nstep emphasized the detection of polymorphisms within\ncoding sequence (reviewed in Korstanje and Paigen, 2002\nand Glazier et al.  2002); for a polymorphism that produces\nan amino acid substitution, one can often infer and then\ntest for a functional consequence."
+            },
+            {
+                "document_id": "abea3dd4-9492-4a2b-8904-b8052e384785",
+                "section_type": "main",
+                "text": "To understand the genetic networks that underlie\nquantitative variation in the trait, it is also very important to\ndiscover genes whose expression is correlated with the trait\nafter accounting for the known effects of the QTL on the\ntrait.  Many of these genes may have expression that is\nassociated with QTL genotype, and would therefore be\nidentified as important via the tests described above.  Other\n\ngenes, however, may have expression values that are correlated with the trait but unassociated with genotype at the\nQTL."
+            },
+            {
+                "document_id": "d1f04d58-2589-4183-aee4-569820dae052",
+                "section_type": "main",
+                "text": "Confirmation of Candidate Genes\nThe next step is to prove that a particular gene is involved in the quantitative trait\nunder study.  This is done by complementation of a QTL, which can be achieved in\nseveral ways (9–11,40).  In principle, transgenic complementation is the most straightforward.  This approach has been used successfully to demonstrate that Pla2g2a was\nthe correct candidate gene for Mom1, a modifier of the apcmin allele that causes\nadenomatous polyposis coli (41)."
+            },
+            {
+                "document_id": "547ce63b-5178-45cb-ae07-12ae66aa2967",
+                "section_type": "main",
+                "text": "With a known QTL and a\nbody of evidence suggesting possible roles for the affected gene,\nphenotypes can be predicted that may be modulated as a result\nof this sequence variation.  If this phenotype is of interest, it\ncan be directly measured and a traditional ‘forward’ QTL analysis carried out to confirm the prediction.  Such an approach is\nextremely attractive when the enormous cost and time required\nfor phenotyping a large panel is considered."
+            },
+            {
+                "document_id": "64886b4e-8599-4f61-84e6-9add7663a1b3",
+                "section_type": "main",
+                "text": "QTL mapping of traits in mouse cohorts often ends up with a genetic locus, composed of a list of candidate\ngenes.  Several studies proposed the use of mediation analysis to identify the causal gene (mediator) between\nthe genetic variant (independent variable) and the trait-of-interest (dependent variable) (Figure 1.4B) [7, 47,\n61, 77].  Mediation analysis can be used either on gene expression levels to identify the regulatory mechanisms\n[7, 47, 61], or on phenotypic traits to discover the potential causal drivers contributing to the phenotypic\nvariances [77] (Figure 1.4C upper)."
+            },
+            {
+                "document_id": "581f83bc-3521-4cb3-ad3c-d905a90ecc29",
+                "section_type": "main",
+                "text": "The first\nstep is to narrow down the list of\ncandidate causal genes within a\nFig\n1.\n Interval\nmapping\nof\noviduct\ngross\npathology\nacross\nthe\nBXD\nstrains\n\nQuantitative Trait Locus (QTL)—a\nreveals\na\nQTL\non\ndistal\nChr\n3.\n The\nL RS\nvalues\nare\nplotted\nin\nblue\nacross\nthe\n\nchromosomal region containing\ngenome\nand\nmeasure\nthe\nstrength\nof\nthe\nassociation\nbetween\n\nsequence variants strongly\nchromosome\nand\nMb\nposition\n(top\nand\nbottom\nX-‐axis,\nrespectively)\nand\n\nassociated with phenotypic\nphenotype\nexpression.\n Allele\ncontribution\nis\nshown\nby\nthe\nred\n(C57BL/6J)\n\nand\ngreen\n(DBA/2J)\nlines.\n Red\nand\ngrey\nhorizontal\nlines\nindicate\ngenome-‐\nvariation."
+            },
+            {
+                "document_id": "1a041a89-4da8-4ad5-b241-da36df917930",
+                "section_type": "main",
+                "text": "\n\nThe next step is to investigate whether the expression of these genes correlates with the phenotype(s) of interest.This would suggest a chain of causality: a variant within a gene causes a change in its expression, and the expression of that gene correlates with expression of a phenotypic trait of interest.To do this, we created a correlation matrix between all genes within a QTL with a cis-eQTL in any brain tissue as well as the phenotypes that contributed to the QTL (Supplementary Table S6).Any gene with a cis-eQTL and a significantly correlated expression was considered a good candidate.If the gene only had a cis-eQTL and correlation in a single brain region, then it suggested that this brain region might also be of interest for the phenotype (adding another link to this chain)."
+            },
+            {
+                "document_id": "ff35f4c8-b78b-4dad-9aa8-1bb16479872d",
+                "section_type": "main",
+                "text": "The goal of QTL mapping is clearly the\nidentification and eventual confirmation of candidate genes\n(QTGs) underlying the phenotype.  The evidence required for\nsuch confirmation has engendered much discussion (Complex\nTrait Consortium 2003; Glazier et al.  2002) and is likely to vary\ndepending on the nature of the trait and specific resources\navailable to pin down underlying genes (e.g.  availability of\nknock-in or knock-outs, specific antibodies, siRNA, etc.).  The\npaucity of QTGs meeting such multifaceted standards is testament to the difficulty of narrowing the confidence interval\nsufficiently to identify and test suitable candidate genes (Flint\net al."
+            },
+            {
+                "document_id": "abea3dd4-9492-4a2b-8904-b8052e384785",
+                "section_type": "main",
+                "text": "The\napproach is motivated by the fact that a research project is\noften focused on a specific classical quantitative trait.  If a\nmajor QTL for this classical trait has been identified, it is\noften desirable to test whether this QTL is also associated\nwith the transcription level of any genes, which will provide clues as to which genes belong to the pathway that the\nQTL uses to modulate the classical trait."
+            },
+            {
+                "document_id": "f041550e-5f2d-430e-8f46-15ebea6ca496",
+                "section_type": "main",
+                "text": "Along with correlations, this tool also derives new traits representing the\nprincipal components (Figure 2d).  The user can add these principal components to their Trait\nCollection and proceed to perform QTL mapping, as in the case of a single trait QTL\nmapping.  The R/QTL (Broman et al.  2003) and R/CAPE (Tyler et al.  2013) packages can be\nused for deeper analysis of epistasis and pleiotropy for multiple traits and multiple\nregulatory loci.\n Prioritizing Candidate Genes\n7\n\nAuthor Manuscript\n\nFollowing the identification of a significant QTL, focus shifts to identifying the\nparticular gene(s) that cause the QTL."
+            },
+            {
+                "document_id": "cb3f9967-9762-4a9b-96cb-0acccdc316d2",
+                "section_type": "main",
+                "text": "Quantitative trait loci (QTLs) can be identified in several ways, but is\nthere a definitive test of whether a candidate locus actually corresponds to a specific QTL?\n\n NIH-PA Author Manuscript\n\nMuch of the genetic variation that underlies disease susceptibility and morphology is complex\nand is governed by loci that have quantitative effects on the phenotype.  Gene-gene and geneenvironment interactions are common and make these loci difficult to analyse.  Here, we present\na community’s view on the steps that are necessary to identify genetic loci that govern\nquantitative traits, along with a set of interpretive guidelines."
+            },
+            {
+                "document_id": "47c12133-5a30-45b9-bcb8-b96f00737f31",
+                "section_type": "main",
+                "text":"Thus, simply\naltering one gene may not necessarily provide a comprehensive link of the\ncandidate genes with the quantitative trait, and in some cases, a false-positive\nresult may even be obtained using the QTL analysis approach.  Ideally, one\nFig.  8.  Quantitative trait locus (QTL) Marker regression analysis.  (A) Marker regression report provides the loci in the BXD data set that show associations with the entered\nthymic involution G1 values from BXD RI strains of mice.  All loci listed in this report\nexhibited an LRS value that is greater than the suggestive linkage value."
+            },
+            {
+                "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                "section_type": "main",
+                "text": "One can apply the method of quantitative trait locus (QTL) mapping\nto identify the chromosomal region (locus) of a gene, or genes, that have\nan effect on a trait.  This mapping is the first step in the identification of the\nresponsible gene by a method that is referred to as positional cloning.  In this\nchapter, the focus will be on the use of QTL mapping to identify genes for\ncomplex traits in mice; although, QTL mapping can be applied to any experimental system in which there is meiotic recombination and different inbred\nstrains are available."
+            },
+            {
+                "document_id": "07d409f4-91f9-4701-bb39-1421845a6321",
+                "section_type": "main",
+                "text": "Prior belief or knowledge about the number of true causal and true\nindependent links that might be expected in a typical QTL, depending on the study\ndesign, should be considered to safeguard against high false-positive rates (low\npositive predictive values).  In studies that involve mapping gene expression (eQTL),\nprotein (pQTL) or metabolite (mQTL) traits, information about co-localization of\nQTL and genes that are functionally linked to the trait provides information about\nthe likelihood of causal links."
+            },
+            {
+                "document_id": "b3e8c6d4-fc8b-4a1c-b6d8-7c0252101571",
+                "section_type": "main",
+                "text": "Often, the first step in analysis of new trait\ndata is single-marker regression across all chromosomes.  A hypothetical QTL is evaluated at\nthe location of each marker locus, and the significance of that QTL is estimated from a likelihood ratio statistic (LRS) (Haley and Knott,\n1992).  For this analysis, WebQTL automatically does a permutation test to establish genomewide significance criteria for the trait (Churchill\nand Doerge, 1994)."
+            },
+            {
+                "document_id": "2c6178fe-c05a-42e6-aafb-7408592dcc50",
+                "section_type": "main",
+                "text": "Often, the first step in analysis of new trait\ndata is single-marker regression across all chromosomes.  A hypothetical QTL is evaluated at\nthe location of each marker locus, and the significance of that QTL is estimated from a likelihood ratio statistic (LRS) (Haley and Knott,\n1992).  For this analysis, WebQTL automatically does a permutation test to establish genomewide significance criteria for the trait (Churchill\nand Doerge, 1994)."
+            },
+            {
+                "document_id": "9a882703-e0ff-4bac-b11a-d99284bf7f6c",
+                "section_type": "main",
+                "text": "Often, the first step in analysis of new trait\ndata is single-marker regression across all chromosomes.  A hypothetical QTL is evaluated at\nthe location of each marker locus, and the significance of that QTL is estimated from a likelihood ratio statistic (LRS) (Haley and Knott,\n1992).  For this analysis, WebQTL automatically does a permutation test to establish genomewide significance criteria for the trait (Churchill\nand Doerge, 1994)."
+            },
+            {
+                "document_id": "8b4276be-c77e-4e80-a5bb-54e9ff75d2ba",
+                "section_type": "main",
+                "text": "QTL mapping requires a few essential steps: initially, the trait must be measured\nin the parental (or progenitor) inbred strains that were used to create the GRP that will be\nused for the study before culminating studies in the RILs (i.e.  BXD mice).  Since the\nindividuals in GRP have polymorphic genes (i.e.  genes that exist in multiple forms), there\nis a high potential for distinctive strains to exhibit differences in phenotype.  Once a\ndifferential phenotype is established in the parents and the RILs, the next step is to\ndetermine the heritability of the variation in the trait being measured."
+            },
+            {
+                "document_id": "33814fad-d831-46f5-b41f-ff31626a82ca",
+                "section_type": "main",
+                "text": "One possible approach to facilitate this endeavor is to identify quantitative trait loci\n(QTL) that contribute to the phenotype and consequently unravel the candidate\ngenes within these loci.  Each proposed candidate locus contains multiple genes and,\ntherefore, further analysis is required to choose plausible candidate genes.  One of\nsuch methods is to use comparative genomics in order to narrow down the QTL to a\nregion containing only a few genes.  We illustrate this strategy by applying it to\ngenetic findings regarding physical activity (PA) in mice and human."
+            },
+            {
+                "document_id": "d1f04d58-2589-4183-aee4-569820dae052",
+                "section_type": "main",
+                "text": "This would be acceptable evidence that\na particular gene is indeed responsible for the quantitative trait.  Further confirmation\nof the QTL can be achieved by quantitative complementation, where the effect of a\nQTL is assessed in the context of a deficient allele of a candidate gene on the same\ngenetic background.\n Gene identification of QTL should be distinguished from identification of the quantitative trait nucleotide (QTN).  The latter is a daunting task, since SNPs are so frequent."
+            },
+            {
+                "document_id": "d3b364c4-bdd3-4c7c-8b3f-e27bd3460c37",
+                "section_type": "main",
+                "text": "For each of the QTL intervals, there are often three or\nmore candidate genes (e.g. , Cyrba4, genes labeled gene X and\ngene Y in Figure 12).  It is therefore necessary to evaluate the\nrelative merits of candidates."
+            },
+            {
+                "document_id": "c2efeeee-f71a-4292-8240-80a4518f820d",
+                "section_type": "main",
+                "text": "The method uses two pieces of information: mapping data from crosses that\ninvolve more than two inbred strains and sequence variants in the progenitor strains within the interval\ncontaining a quantitative trait locus (QTL).  By testing whether the strain distribution pattern in the progenitor strains is consistent with the observed genetic effect of the QTL we can assign a probability that any\nsequence variant is a quantitative trait nucleotide (QTN).  It is not necessary to genotype the animals except\nat a skeleton of markers; the genotypes at all other polymorphisms are estimated by a multipoint analysis."
+            },
+            {
+                "document_id": "0950746d-90b5-484d-853d-70026e85c9ce",
+                "section_type": "main",
+                "text": "Some of this analysis software is available on the\nWebQTL Web site (http://www.genenetwork.org/home).  While\nthe authors of these initial studies generated their own expression data, data for other experiments are becoming increasingly\navailable in expression databases such as NCBI GEO (http://\nwww.ncbi.nlm.nih.gov/geo/).  This approach is a powerful one\nand is likely to become a common one to use for QTL studies.\n\n Causative gene identification\nOnce strong candidates are identified, it is crucial to test them."
+            },
+            {
+                "document_id": "624ba3ed-0965-4451-a5e1-2150b68ae1b3",
+                "section_type": "main",
+                "text": "Some of this analysis software is available on the\nWebQTL Web site (http://www.genenetwork.org/home).  While\nthe authors of these initial studies generated their own expression data, data for other experiments are becoming increasingly\navailable in expression databases such as NCBI GEO (http://\nwww.ncbi.nlm.nih.gov/geo/).  This approach is a powerful one\nand is likely to become a common one to use for QTL studies.\n\n Causative gene identification\nOnce strong candidates are identified, it is crucial to test them."
+            },
+            {
+                "document_id": "a64778cd-bff8-43dd-b5a3-d608ab8f4828",
+                "section_type": "main",
+                "text": "The method uses two pieces of information: mapping data from crosses that\ninvolve more than two inbred strains and sequence variants in the progenitor strains within the interval\ncontaining a quantitative trait locus (QTL).  By testing whether the strain distribution pattern in the progenitor strains is consistent with the observed genetic effect of the QTL we can assign a probability that any\nsequence variant is a quantitative trait nucleotide (QTN).  It is not necessary to genotype the animals except\nat a skeleton of markers; the genotypes at all other polymorphisms are estimated by a multipoint analysis."
+            },
+            {
+                "document_id": "1a041a89-4da8-4ad5-b241-da36df917930",
+                "section_type": "main",
+                "text": "Candidate Causal Genes within Novel QTL\n\nWe concentrated on a subset of six novel QTL that contained less than 100 genes.These QTLs are more amenable to finding plausible candidate genes using bioinformatic methods.After reducing the likelihood of finding false positives, these large QTLs are more likely to be due to two or more variants in different genes both contributing to the phenotype.The advantage of families of isogenic strains of mice, such as the BXD, is that more strains could be phenotyped, reducing the size of these QTL regions and allowing for greater precision.S4)"
+            },
+            {
+                "document_id": "eb90c74a-60f0-4485-b1b9-bb6665469828",
+                "section_type": "main",
+                "text": "A major goal is to identify which,\namong a set of candidate genes, are the most likely regulators of trait variation.  These\nmethods are applied in an effort to identify multiple-QTL regulatory models for large\ngroups of genetically co-expressed genes, and to extrapolate the consequences of this\ngenetic variation on phenotypes observed across levels of biological scale through the\nevaluation of vertex coverage.  This approach is furthermore applied to definitions of\nhomology-based gene sets, and the incorporation of categorical data such as known\ngene pathways."
+            },
+            {
+                "document_id": "d8993417-3a27-4000-b693-6cb4662b9f80",
+                "section_type": "main",
+                "text": "This is useful, since it clearly shows that a variant in the eQTL region has a regulatory effect.\n Therefore, genes with a cis-eQTL are interesting candidate genes.\n The next step is to investigate whether the expression of these genes correlates with the\nphenotype(s) of interest.  This would suggest a chain of causality: a variant within a gene\ncauses a change in its expression, and the expression of that gene correlates with expression\nof a phenotypic trait of interest."
+            },
+            {
+                "document_id": "d0deb53b-7286-4fd0-9188-b7b9f366fd76",
+                "section_type": "main",
+                "text": "This is useful, since it clearly shows that a variant in the eQTL region has a regulatory effect.\n Therefore, genes with a cis-eQTL are interesting candidate genes.\n The next step is to investigate whether the expression of these genes correlates with the\nphenotype(s) of interest.  This would suggest a chain of causality: a variant within a gene\ncauses a change in its expression, and the expression of that gene correlates with expression\nof a phenotypic trait of interest."
+            },
+            {
+                "document_id": "835a094d-9c2b-4686-8725-d3c4123175b0",
+                "section_type": "main",
+                "text": "This poses a serious challenge, and\nto date, only a small handful of genes have been definitively identified for complex traits.\n Our own efforts to identify a causal gene were stymied by the compound nature of QTLs\nand the high gene density in Qrr1, and in Vol8a.  Furthermore, it is now becoming clear\nthat in addition to the canonical candidate genes, there are multiple spliced variants,\nmicroRNAs, and epigenetic factors to be considered.\n With what appears to be an increasingly complex genomic landscape, it is now all\nthe more necessary to apply the multipronged approach taken by systems genetics."
+            },
+            {
+                "document_id": "3f8db22e-d5f9-44ba-8f78-fc77ccf024ce",
+                "section_type": "main",
+                "text":"These candidate genes are then sequenced in the two parental inbred\nstrains looking for sequence di¡erences in coding or regulatory regions.\n After ¢ne mapping the QTL interval and shortening the list of plausible\ncandidate polymorphisms, the major challenge remains  proving de¢nitively\nwhich nucleotide polymorphism underlies the QTL.  The most direct proof\nwould be replacing one strain’s allele with another strain’s allele (creating a\nFIG.  1.  Intercross breeding strategy for mapping quantitative trait loci (QTLs).  On the right, the parental, F1 hybrid, and intercross (F2) mouse\ngenerations are depicted."
+            },
+            {
+                "document_id": "f253e087-e030-40a8-8400-3b6bf50c1fd6",
+                "section_type": "main",
+                "text":"These candidate genes are then sequenced in the two parental inbred\nstrains looking for sequence di¡erences in coding or regulatory regions.\n After ¢ne mapping the QTL interval and shortening the list of plausible\ncandidate polymorphisms, the major challenge remains  proving de¢nitively\nwhich nucleotide polymorphism underlies the QTL.  The most direct proof\nwould be replacing one strain’s allele with another strain’s allele (creating a\nFIG.  1.  Intercross breeding strategy for mapping quantitative trait loci (QTLs).  On the right, the parental, F1 hybrid, and intercross (F2) mouse\ngenerations are depicted."
+            },
+            {
+                "document_id": "5a56fa6d-9e77-4b95-a836-04d0fa31ee2c",
+                "section_type": "main",
+                "text": "A special case is the\ncorrelation of the target phenotype with the expression of the\npriorized gene(s) (RNA or protein amounts).  This refers to\ncolocalization of the QTL of the target phenotype with the\neQTL position.  Correlation can also be examined between the\ntarget QTL phenotype and expression of all genes in the QTL\ninterval.  If the gene expression strongly correlates with the\nQTL phenotype, this further strengthens the assumption that\nthis gene might be causal (see Note 12).\n For performing a correlation analysis:\n–\n\nGo to the Trait Overview Page, as described in step 3, point\n1."
+            }
+        ],
+        "document_id": "EFB8B9EF07428DA8D36EFCB6B06F9161",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "QTL",
+            "gene",
+            "trait",
+            "phenotype",
+            "eQTL",
+            "expression",
+            "cis-eQTL",
+            "quantitative&trait&locus",
+            "QTG",
+            "correlation"
+        ],
+        "metadata": [
+            {
+                "object": "Transient overexpression of WRKY79 in protoplasts results in up-regulation of Gene:542165, Gene:541974, Gene:100274033, Gene:542688, Gene:542150, Gene:542151, Gene:100273457, Gene:100285509, Gene:103626248, Gene:103646045, Gene:100217270, Gene:100279981, Gene:100281950, Gene:542476, Gene:542369, Gene:100281950, and Gene:542260.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab969966"
+            },
+            {
+                "object": "DNA sequencing demonstrated that in the absence of ectopic PAF53 expression, cells demonstrated unique means of surviving; including recombination or the utilization of alternative reading frames. We never observed a clone in which one PAF53 gene is expressed, unless there was also ectopic expression In the absence of ectopic gene expression, the gene products of both endogenous genes were expressed, irrespective of wheth",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab236437"
+            },
+            {
+                "object": "SF3B2 is a critical determinant of AR-V7 expression and is correlated with aggressive cancer phenotypes.  Pladienolide B, an inhibitor of a splicing modulator of the SF3b complex, suppressed the growth of tumors addicted to high SF3B2 expression.  SF3B2 is a critical determinant of RNA splicing and gene expression patterns and controls the expression of key genes associated with CRPC progression, such as AR-V7.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab702217"
+            },
+            {
+                "object": "These tumor samples express CD44 protein at low rather than high levels. There is no correlation between CLDN3 gene expression and protein expression in these CPTAC samples; hence, the claudin-low subtype defined by gene expression is not the same group of tumors as that defined by low expression of CLDN3 protein.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab928122"
+            },
+            {
+                "object": "expression studies revealed inverse correlation of KLF1, BCL11A reduced with gamma-globin gene expression increased in patients showing KLF1 gene mutations, thus indicating the role of KLF1 gene in regulating the gamma-globin gene expression.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab278866"
+            },
+            {
+                "object": "During early zebrafish embryonic development, p63 binds to enhancers associated to neural plate-expressing genes, where it limits Sox3 binding and neural gene expression. p63 binds enhancers associated to epidermis-expressing genes when they are in a non-accessible chromatin state, leading to its opening and epidermal gene expression.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab243624"
+            },
+            {
+                "object": "Study observed elevated EA2 gene expression in the subcutaneous compared to that in the visceral human adipose tissue. EA2 gene expression negatively correlated with adiponectin and chemerin in visceral adipose tissue, and positively correlated with TNF-alpha in subcutaneous adipose tissue. EA2 gene expression was significantly downregulated during differentiation of preadipocytes in vitro.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab745216"
+            },
+            {
+                "object": "Study indicate that the observed level of FHIT promoter methylation was not enough to suppress gene expression in non-small cell lung cancer NSCLC. Lack of negative correlation between FHIT expression and methylation, or positive correlation between gene expression and immunoexpression suggest the role of another molecular mechanisms regulating FHIT expression on mRNA and protein levels in NSCLC patients.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab744476"
+            },
+            {
+                "object": "Correlation analyses showed that 5hmC enrichment in gene body is positively associated with gene expression level in mouse kidney. Moreover, ischemia reperfusion IR injury-associated genes both up- and down-regulated genes during renal IR injury in mouse kidney exhibit significantly higher 5hmC enrichment in their gene body regions when compared to those un-changed genes.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab157853"
+            },
+            {
+                "object": "LAG-3 expression was correlated with expression of PD-1 on TILs and expression of PD-L1 on tumor cells. Higher expression of LAG-3 on TILs was significantly correlated with higher expression of PD-1 on TILs and higher expression of PD-L1 on tumor cells.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab444259"
+            }
+        ],
+        "question": "How do I determine which gene in my QTL is causal for the trait?",
+        "subquestions": null,
+        "task_id": "EFB8B9EF07428DA8D36EFCB6B06F9161",
+        "usage": {
+            "chatgpt": 4765,
+            "gpt-4": 3573,
+            "gpt-4-turbo-preview": 2599
+        },
+        "user_id": 2
+    },
+    "document_id": "EFB8B9EF07428DA8D36EFCB6B06F9161",
+    "task_id": "EFB8B9EF07428DA8D36EFCB6B06F9161"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/02.json b/gnqa/paper1_eval/src/data/responses/general/experts/02.json
new file mode 100644
index 0000000..ba248fa
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/02.json
@@ -0,0 +1,396 @@
+{
+    "created_at": "2024-06-01T14:20:28.998327Z",
+    "data": {
+        "amplify": false,
+        "answer": "Actually, males have one Y chromosome and one X chromosome, while females have two X chromosomes. This combination determines the sex of an individual.",
+        "context": {
+            "1ac23aae-2a51-4846-81ec-6db70ab6e5a4": [
+                {
+                    "document_id": "1ac23aae-2a51-4846-81ec-6db70ab6e5a4",
+                    "text": "\n\nY chromosome in peripheral blood cells increases with age in men (6) and is correlated with increased risk of cancer mortality and Alzheimer's disease (6,7).X chromosome mosaicism in women also increases with age (8), as does autosomal mosaicism in both sexes (9,10).Recent studies have shown that the prevalence of age-related mosaic abnormalities is greater in men than women (9,10); however, mechanisms underlying the sex differences observed in chromosomal mosaicism in humans are unknown."
+                }
+            ],
+            "20b466c6-004b-484f-96a1-c1b4651bc856": [
+                {
+                    "document_id": "20b466c6-004b-484f-96a1-c1b4651bc856",
+                    "text": "\n\nRecent reports suggested a role of Y chromosome loss in risk for all-cause mortality and common age-related disease such as cancer, Alzheimer disease as well as severe atherosclerosis [12][13][14][15][16][17][18][19][20].Building on such reports, we aimed to evaluate the contribution of male Y chromosome mosaicism to the risk for late-stage AMD."
+                }
+            ],
+            "3f72832b-fad9-4d38-aed8-d22e5bd12a22": [
+                {
+                    "document_id": "3f72832b-fad9-4d38-aed8-d22e5bd12a22",
+                    "text": "Box 1. Sex-specific cytonuclear interactions\n\nSeveral predictions about the nature of cytonuclear conflicts follow from the patterns of chromosomal inheritance (Table I).In a mated pair of animals, mtDNA is co-transmitted with half of the autosomal genes, two-thirds of the X-linked genes and none of the Y-linked genes [76].This predicts that, relative to the autosomal case, positive nuclear-mitochondrial interactions are more likely to evolve for X-linked loci whereas deleterious interactions between Y-linked genes and mtDNA should accumulate (or cannot be purged efficiently)."
+                }
+            ],
+            "4ad6da14-56a3-48ab-a587-42761ceac238": [
+                {
+                    "document_id": "4ad6da14-56a3-48ab-a587-42761ceac238",
+                    "text": "\n\nIn addition to genetic data, the 9p Network Cohort dataset also lists the gender for all 719 individuals.Of these individuals, 406 individuals are female and 313 are male, indicating a female bias (Binomial test p ¼ 0.0006).This result was surprising considering that no female bias has been previously reported in 9p deletion and duplication syndromes.A possible explanation for the significant bias in the 9p Network Cohort dataset is the XY sex reversal phenotype, which is commonly observed in individuals with 9p deletion syndrome.This phenotype could lead to individuals with XY sex chromosomes being listed in the dataset as having a female gender.To further examine this hypothesis, we subset our dataset to include only the 236 individuals whose sex chromosomes are listed in their genetic information.For this much smaller subset, 125 individuals had female sex chromosomes and 111 had male sex chromosomes, indicating no significant sex bias (Binomial test p ¼ 0.4).We also found no significant gender bias in this group (Binomial test p ¼ 0.2), although we did confirm that four of the individuals with XY sex chromosomes had a gender of female.This comparison suggests that the XY sex reversal phenotype may be responsible for a female gender bias, but not a sex bias, in 9p deletion and duplication syndrome cohorts."
+                }
+            ],
+            "6910b508-6d25-4804-9e47-3590b57aa061": [
+                {
+                    "document_id": "6910b508-6d25-4804-9e47-3590b57aa061",
+                    "text": "\n\nDuplicated variants with multiple alternative alleles and variants in sex chromosomes X and Y"
+                }
+            ],
+            "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa": [
+                {
+                    "document_id": "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa",
+                    "text": "\n\nAutosome-One of the numbered, or nonsex, chromosomes (1 through 22).X and Y are the sex chromosomes."
+                }
+            ],
+            "7d451e79-b698-4744-aeb2-ff319f430d96": [
+                {
+                    "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                    "text": "\n\nGiven such a high abundance of young male-biased genes, we asked whether their parental genes are also male-biased.We found that fewer parental genes of X-linked male-biased duplicates were also male-biased (20%, 2/10) compared to the parental genes of autosomal young male-biased duplicates (32%, 12/37).These data, despite the small sample sizes and being statistically not significant, may suggest that compared to autosomal young genes, X-linked young genes more often evolved novel male-biased expression.However, as the majority of young genes are the result of intrachromosomal duplication events, the pattern might also reflect the fact that X-linked old genes are less likely to be male-biased."
+                },
+                {
+                    "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                    "text": "\n\nA slight excess of X-linked female-biased genes was also detected (Fig. 2).Although most of them are old, a few recently arose on the X chromosome over 4 to 6 Myr in the common ancestor of the D. melanogaster and D. simulans clade (branch 5).This can be interpreted in the context of the dominance model of the sexual antagonism hypothesis.In this case, a dominant, X-linked gene that is favorable to females but disadvantageous for males can become fixed.The slow accumulation of female-biased genes in the X reflects an overall low rate of female gene origination, either due to a small dominance effect (the degree of dominance h!1/2), or a minor disadvantageous effect on males (the ratio of fitness effects of male relative to female k!0) along with a favorable effect on females (Vicoso and Charlesworth 2006, Equation 10)."
+                },
+                {
+                    "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                    "text": "\n\nRegarding the second step in the evolution of male-biased genes, namely X!A transposition, sexual antagonism favorable for autosomal fixation (Vicoso and Charlesworth 2006) and/or MSCI (Lifschytz and Lindsley 1972;Betran et al. 2002) may play a role in this process.On the other hand, the within-chromosomal duplication rate is higher than the between-chromosomal duplication rate (Emerson et al. 2008), which may contribute to the slow pace of X!A transposition."
+                },
+                {
+                    "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                    "text": "\n\nIt has been observed that male-biased genes in Drosophila are overrepresented on autosomes (Parisi et al. 2003;Ranz et al. 2003).Consistent with this result, a dynamic process that can explain the nonrandom autosomal distribution has also been observed, in which autosomal new genes with X-linked parental genes are often male-biased.Specifically, a significant excess of autosomal testisexpressed retrogenes were identified as RNA-duplicates of X-linked parental genes (Betran et al. 2002).Recently, similar X!A gene traffic was observed in the DNA-level duplication and relocation data set of the Drosophila genus (Vibranovski et al. 2009b), and was further confirmed for DNA-level duplications in the D. pseudoobscura neo-X chromosome (Meisel et al. 2009).In addition, selective extinction of neo-X linked male-biased genes also occurred in D. pseudoobscura (Sturgill et al. 2007).These three lines of genome-wide investigation support a common pattern of outof-X traffic for male-biased genes, resulting in an enrichment of these genes on autosomes in the long term."
+                },
+                {
+                    "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                    "text": "\n\nIt has been reported that the initial manifestations of new gene emergence, namely polymorphic duplicates, occur at a lower frequency on the X chromosome, thus indicating that these duplicates are subject to stronger purifying selection (Emerson et al. 2008).Therefore, the excessive fixation of X-linked duplicates might not occur via neutral processes.Positive selection could have facilitated the fixation of X-linked young genes in addition to driving their subsequent sequence evolution."
+                }
+            ],
+            "96cb840e-747f-4849-8354-e8764aa0a1ce": [
+                {
+                    "document_id": "96cb840e-747f-4849-8354-e8764aa0a1ce",
+                    "text": "\n\nOccasionally, Y chromosome DNA is detected in the maternal plasma, and the fetus appears to have female genitalia on sonographic examination.The underlying mechanisms for this include a twin demise, a maternal disorder of sexual differentiation, such as Swyer syndrome, or that the mother has undergone a bone marrow or solid organ transplant from a male donor (Bianchi, 2018;Hartwig, Ambye, Sorensen, & Jorgensen, 2017)."
+                }
+            ],
+            "9a5c3e73-8270-400f-8a2d-4f36b757188c": [
+                {
+                    "document_id": "9a5c3e73-8270-400f-8a2d-4f36b757188c",
+                    "text": "Because\nof the differences in sex chromosome number, the sexunmatched comparison contains internal controls, i.e. ,\nin this comparison, genes on the X-chromosome and\nY-chromosome (but not those on the autosomes) should\nshow copy number imbalances reﬂective of a single copy\nchange. We showed that the sample that is not sexmatched had readily detectable differences in aCGH\nsignals for genes on the X and Y chromosomes. No such\npatterns were evident for the autosomes of the sex\nunmatched individuals or for the sex chromosomes of the\nsex matched samples."
+                }
+            ],
+            "af3d7cd3-40ec-4a86-a473-89f83da250e4": [
+                {
+                    "document_id": "af3d7cd3-40ec-4a86-a473-89f83da250e4",
+                    "text": "Sex chromosome:\n\nThe X or Y chromosome in human beings that determines the sex of an individual.Females have two X chromosomes in diploid cells; males have an X and a Y chromosome.The sex chromosomes comprise the 23rd chromosome pair in a karyotype.See also: autosome Sex-linked: Traits or diseases associated with the X or Y chromosome; generally seen in males."
+                },
+                {
+                    "document_id": "af3d7cd3-40ec-4a86-a473-89f83da250e4",
+                    "text": "\n\nX chromosome: One of the two sex chromosomes, X and Y. See also: Y chromosome, sex chromosome Y chromosome: One of the two sex chromosomes, X and Y. See also; X chromosome, sex chromosome"
+                }
+            ],
+            "b04f2221-de28-4c4b-893e-9da982ff864c": [
+                {
+                    "document_id": "b04f2221-de28-4c4b-893e-9da982ff864c",
+                    "text": "The male heterogamety (XY) is the most\ncommon reported system, but many species\nhave female heterogamety (ZW), and more\noccasionally, multiple chromosome systems\n\n(Almeida-Toledo and Foresti, 2001; Devlin\nand Nagahama, 2002; Penman and Piferrer,\n2008). Given the low resolution of optical microscopy to differentiate sex chromosomes in\nﬁsh, researchers have looked for an alternative\nin the tenfold longer meiotic chromosomes to\ndetect mispairing tracts at the synaptonemal\ncomplex as an indication of the sex differentiated region with variable success."
+                },
+                {
+                    "document_id": "b04f2221-de28-4c4b-893e-9da982ff864c",
+                    "text": "The exclusive female\nconstitution of gynogenetic genomes provides\ninformation on the SD system, especially in a\nXX/XY system, where all female progenies are\nexpected. If ZZ/ZW is the underlying system,\nmale offspring always will be present, but the\ninterpretation is more complex and will depend\non the distance of the SD region to centromere\nand on the viability of WW offspring (Devlin\nand Nagahama, 2002; Penman and Piferrer,\n2008). Induced triploids, on the other hand, are\nconstituted by the combination of two female\nand one male genomes (Piferrer et al."
+                }
+            ],
+            "ef2c8463-5169-46aa-938b-7d04ea8da6b7": [
+                {
+                    "document_id": "ef2c8463-5169-46aa-938b-7d04ea8da6b7",
+                    "text": "\n\nThe existence of a maternally silenced X-linked imprinted locus playing a role in social cognition could explain why males (X m Y) are more vulnerable to disorders of social cognition such as autism spectrum disorders than are females (X m X p ).The absence of the expression of this gene would not lead to autism itself, but would eliminate a putative protective factor, making an individual more susceptible to the effects of other ASD-predisposing genetic mutations or environmental factors."
+                }
+            ],
+            "f051ad23-572d-4302-8dda-4d992aeaeb1a": [
+                {
+                    "document_id": "f051ad23-572d-4302-8dda-4d992aeaeb1a",
+                    "text": "\n\nWhen meiosis takes place, a pair of chromosomes may fail to separate properly, creating a sperm or egg that has either two copies or no copy of a specific chromosome.This is a sporadic event and it is called nondisjunction.Nondisjunction can lead to an extra chromosome, called trisomy, or a missing chromosome, called monosomy (GHR, 2008l).Down syndrome is an example of trisomy.Individuals who have Down syndrome have an extra chromosome number 21. Turner syndrome is an example of monosomy.Girls who have Turner syndrome have only one X chromosome.This causes them to have short stature and be infertile (NHGRI, 2008l)."
+                },
+                {
+                    "document_id": "f051ad23-572d-4302-8dda-4d992aeaeb1a",
+                    "text": "X-Linked Inheritance\n\nX-linked genetic disorders (also called sex-linked) are caused by gene mutations on the X chromosome.Most often X-linked genetic disorders are seen in males.Males inherit the X chromosome from their mother and the Y chromosome from their father.Because males have only one X chromosome, if they inherit a gene mutation on the X chromosome from their mother, they will have the disorder.Examples of X-linked genetic disorders occurring in males include hemophilia and Duchenne muscular dystrophy (GHR, 2008o)."
+                }
+            ]
+        },
+        "data_source": [
+            {
+                "document_id": "af3d7cd3-40ec-4a86-a473-89f83da250e4",
+                "section_type": "main",
+                "text": "Sex chromosome:\n\nThe X or Y chromosome in human beings that determines the sex of an individual.Females have two X chromosomes in diploid cells; males have an X and a Y chromosome.The sex chromosomes comprise the 23rd chromosome pair in a karyotype.See also: autosome Sex-linked: Traits or diseases associated with the X or Y chromosome; generally seen in males."
+            },
+            {
+                "document_id": "b04f2221-de28-4c4b-893e-9da982ff864c",
+                "section_type": "main",
+                "text": "The male heterogamety (XY) is the most\ncommon reported system, but many species\nhave female heterogamety (ZW), and more\noccasionally, multiple chromosome systems\n\n(Almeida-Toledo and Foresti, 2001; Devlin\nand Nagahama, 2002; Penman and Piferrer,\n2008).  Given the low resolution of optical microscopy to differentiate sex chromosomes in\nﬁsh, researchers have looked for an alternative\nin the tenfold longer meiotic chromosomes to\ndetect mispairing tracts at the synaptonemal\ncomplex as an indication of the sex differentiated region with variable success."
+            },
+            {
+                "document_id": "af3d7cd3-40ec-4a86-a473-89f83da250e4",
+                "section_type": "main",
+                "text": "\n\nX chromosome: One of the two sex chromosomes, X and Y. See also: Y chromosome, sex chromosome Y chromosome: One of the two sex chromosomes, X and Y. See also; X chromosome, sex chromosome"
+            },
+            {
+                "document_id": "96cb840e-747f-4849-8354-e8764aa0a1ce",
+                "section_type": "main",
+                "text": "\n\nOccasionally, Y chromosome DNA is detected in the maternal plasma, and the fetus appears to have female genitalia on sonographic examination.The underlying mechanisms for this include a twin demise, a maternal disorder of sexual differentiation, such as Swyer syndrome, or that the mother has undergone a bone marrow or solid organ transplant from a male donor (Bianchi, 2018;Hartwig, Ambye, Sorensen, & Jorgensen, 2017)."
+            },
+            {
+                "document_id": "9a5c3e73-8270-400f-8a2d-4f36b757188c",
+                "section_type": "main",
+                "text": "Because\nof the differences in sex chromosome number, the sexunmatched comparison contains internal controls, i.e. ,\nin this comparison, genes on the X-chromosome and\nY-chromosome (but not those on the autosomes) should\nshow copy number imbalances reﬂective of a single copy\nchange.  We showed that the sample that is not sexmatched had readily detectable differences in aCGH\nsignals for genes on the X and Y chromosomes.  No such\npatterns were evident for the autosomes of the sex\nunmatched individuals or for the sex chromosomes of the\nsex matched samples."
+            },
+            {
+                "document_id": "b04f2221-de28-4c4b-893e-9da982ff864c",
+                "section_type": "main",
+                "text": "The exclusive female\nconstitution of gynogenetic genomes provides\ninformation on the SD system, especially in a\nXX/XY system, where all female progenies are\nexpected.  If ZZ/ZW is the underlying system,\nmale offspring always will be present, but the\ninterpretation is more complex and will depend\non the distance of the SD region to centromere\nand on the viability of WW offspring (Devlin\nand Nagahama, 2002; Penman and Piferrer,\n2008).  Induced triploids, on the other hand, are\nconstituted by the combination of two female\nand one male genomes (Piferrer et al."
+            },
+            {
+                "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                "section_type": "main",
+                "text": "\n\nGiven such a high abundance of young male-biased genes, we asked whether their parental genes are also male-biased.We found that fewer parental genes of X-linked male-biased duplicates were also male-biased (20%, 2/10) compared to the parental genes of autosomal young male-biased duplicates (32%, 12/37).These data, despite the small sample sizes and being statistically not significant, may suggest that compared to autosomal young genes, X-linked young genes more often evolved novel male-biased expression.However, as the majority of young genes are the result of intrachromosomal duplication events, the pattern might also reflect the fact that X-linked old genes are less likely to be male-biased."
+            },
+            {
+                "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                "section_type": "main",
+                "text": "\n\nA slight excess of X-linked female-biased genes was also detected (Fig. 2).Although most of them are old, a few recently arose on the X chromosome over 4 to 6 Myr in the common ancestor of the D. melanogaster and D. simulans clade (branch 5).This can be interpreted in the context of the dominance model of the sexual antagonism hypothesis.In this case, a dominant, X-linked gene that is favorable to females but disadvantageous for males can become fixed.The slow accumulation of female-biased genes in the X reflects an overall low rate of female gene origination, either due to a small dominance effect (the degree of dominance h!1/2), or a minor disadvantageous effect on males (the ratio of fitness effects of male relative to female k!0) along with a favorable effect on females (Vicoso and Charlesworth 2006, Equation 10)."
+            },
+            {
+                "document_id": "4ad6da14-56a3-48ab-a587-42761ceac238",
+                "section_type": "main",
+                "text": "\n\nIn addition to genetic data, the 9p Network Cohort dataset also lists the gender for all 719 individuals.Of these individuals, 406 individuals are female and 313 are male, indicating a female bias (Binomial test p ¼ 0.0006).This result was surprising considering that no female bias has been previously reported in 9p deletion and duplication syndromes.A possible explanation for the significant bias in the 9p Network Cohort dataset is the XY sex reversal phenotype, which is commonly observed in individuals with 9p deletion syndrome.This phenotype could lead to individuals with XY sex chromosomes being listed in the dataset as having a female gender.To further examine this hypothesis, we subset our dataset to include only the 236 individuals whose sex chromosomes are listed in their genetic information.For this much smaller subset, 125 individuals had female sex chromosomes and 111 had male sex chromosomes, indicating no significant sex bias (Binomial test p ¼ 0.4).We also found no significant gender bias in this group (Binomial test p ¼ 0.2), although we did confirm that four of the individuals with XY sex chromosomes had a gender of female.This comparison suggests that the XY sex reversal phenotype may be responsible for a female gender bias, but not a sex bias, in 9p deletion and duplication syndrome cohorts."
+            },
+            {
+                "document_id": "6910b508-6d25-4804-9e47-3590b57aa061",
+                "section_type": "main",
+                "text": "\n\nDuplicated variants with multiple alternative alleles and variants in sex chromosomes X and Y"
+            },
+            {
+                "document_id": "1ac23aae-2a51-4846-81ec-6db70ab6e5a4",
+                "section_type": "main",
+                "text": "\n\nY chromosome in peripheral blood cells increases with age in men (6) and is correlated with increased risk of cancer mortality and Alzheimer's disease (6,7).X chromosome mosaicism in women also increases with age (8), as does autosomal mosaicism in both sexes (9,10).Recent studies have shown that the prevalence of age-related mosaic abnormalities is greater in men than women (9,10); however, mechanisms underlying the sex differences observed in chromosomal mosaicism in humans are unknown."
+            },
+            {
+                "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                "section_type": "main",
+                "text": "\n\nRegarding the second step in the evolution of male-biased genes, namely X!A transposition, sexual antagonism favorable for autosomal fixation (Vicoso and Charlesworth 2006) and/or MSCI (Lifschytz and Lindsley 1972;Betran et al. 2002) may play a role in this process.On the other hand, the within-chromosomal duplication rate is higher than the between-chromosomal duplication rate (Emerson et al. 2008), which may contribute to the slow pace of X!A transposition."
+            },
+            {
+                "document_id": "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa",
+                "section_type": "main",
+                "text": "\n\nAutosome-One of the numbered, or nonsex, chromosomes (1 through 22).X and Y are the sex chromosomes."
+            },
+            {
+                "document_id": "20b466c6-004b-484f-96a1-c1b4651bc856",
+                "section_type": "main",
+                "text": "\n\nRecent reports suggested a role of Y chromosome loss in risk for all-cause mortality and common age-related disease such as cancer, Alzheimer disease as well as severe atherosclerosis [12][13][14][15][16][17][18][19][20].Building on such reports, we aimed to evaluate the contribution of male Y chromosome mosaicism to the risk for late-stage AMD."
+            },
+            {
+                "document_id": "f051ad23-572d-4302-8dda-4d992aeaeb1a",
+                "section_type": "main",
+                "text": "\n\nWhen meiosis takes place, a pair of chromosomes may fail to separate properly, creating a sperm or egg that has either two copies or no copy of a specific chromosome.This is a sporadic event and it is called nondisjunction.Nondisjunction can lead to an extra chromosome, called trisomy, or a missing chromosome, called monosomy (GHR, 2008l).Down syndrome is an example of trisomy.Individuals who have Down syndrome have an extra chromosome number 21. Turner syndrome is an example of monosomy.Girls who have Turner syndrome have only one X chromosome.This causes them to have short stature and be infertile (NHGRI, 2008l)."
+            },
+            {
+                "document_id": "ef2c8463-5169-46aa-938b-7d04ea8da6b7",
+                "section_type": "main",
+                "text": "\n\nThe existence of a maternally silenced X-linked imprinted locus playing a role in social cognition could explain why males (X m Y) are more vulnerable to disorders of social cognition such as autism spectrum disorders than are females (X m X p ).The absence of the expression of this gene would not lead to autism itself, but would eliminate a putative protective factor, making an individual more susceptible to the effects of other ASD-predisposing genetic mutations or environmental factors."
+            },
+            {
+                "document_id": "3f72832b-fad9-4d38-aed8-d22e5bd12a22",
+                "section_type": "main",
+                "text": "Box 1. Sex-specific cytonuclear interactions\n\nSeveral predictions about the nature of cytonuclear conflicts follow from the patterns of chromosomal inheritance (Table I).In a mated pair of animals, mtDNA is co-transmitted with half of the autosomal genes, two-thirds of the X-linked genes and none of the Y-linked genes [76].This predicts that, relative to the autosomal case, positive nuclear-mitochondrial interactions are more likely to evolve for X-linked loci whereas deleterious interactions between Y-linked genes and mtDNA should accumulate (or cannot be purged efficiently)."
+            },
+            {
+                "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                "section_type": "main",
+                "text": "\n\nIt has been observed that male-biased genes in Drosophila are overrepresented on autosomes (Parisi et al. 2003;Ranz et al. 2003).Consistent with this result, a dynamic process that can explain the nonrandom autosomal distribution has also been observed, in which autosomal new genes with X-linked parental genes are often male-biased.Specifically, a significant excess of autosomal testisexpressed retrogenes were identified as RNA-duplicates of X-linked parental genes (Betran et al. 2002).Recently, similar X!A gene traffic was observed in the DNA-level duplication and relocation data set of the Drosophila genus (Vibranovski et al. 2009b), and was further confirmed for DNA-level duplications in the D. pseudoobscura neo-X chromosome (Meisel et al. 2009).In addition, selective extinction of neo-X linked male-biased genes also occurred in D. pseudoobscura (Sturgill et al. 2007).These three lines of genome-wide investigation support a common pattern of outof-X traffic for male-biased genes, resulting in an enrichment of these genes on autosomes in the long term."
+            },
+            {
+                "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                "section_type": "main",
+                "text": "\n\nIt has been reported that the initial manifestations of new gene emergence, namely polymorphic duplicates, occur at a lower frequency on the X chromosome, thus indicating that these duplicates are subject to stronger purifying selection (Emerson et al. 2008).Therefore, the excessive fixation of X-linked duplicates might not occur via neutral processes.Positive selection could have facilitated the fixation of X-linked young genes in addition to driving their subsequent sequence evolution."
+            },
+            {
+                "document_id": "f051ad23-572d-4302-8dda-4d992aeaeb1a",
+                "section_type": "main",
+                "text": "X-Linked Inheritance\n\nX-linked genetic disorders (also called sex-linked) are caused by gene mutations on the X chromosome.Most often X-linked genetic disorders are seen in males.Males inherit the X chromosome from their mother and the Y chromosome from their father.Because males have only one X chromosome, if they inherit a gene mutation on the X chromosome from their mother, they will have the disorder.Examples of X-linked genetic disorders occurring in males include hemophilia and Duchenne muscular dystrophy (GHR, 2008o)."
+            },
+            {
+                "document_id": "ef2c8463-5169-46aa-938b-7d04ea8da6b7",
+                "section_type": "main",
+                "text": "X Chromosome and Turner Syndrome\n\nThe existence on the X chromosome of imprinted gene(s) with a role in social cognition was first suggested by Skuse et al. 36 Such a gene could play a role in ASD susceptibility.The hyposthesis of Skuse et al. derives from studies of patients with Turner syndrome (TS), who are monosomic for all or part of the X chromosome.Using a socialcognition questionnaire, Skuse et al. found that females monosomic for the paternal X chromosome (X p 0) score significantly better on social adjustment and verbal skills than females monosomic for the maternal X (X m 0).Therefore, the investigators hypothesized that there is an imprinted gene on the X chromosome, expressed from the paternal X and silenced on the maternal X.To date, no such imprinted gene on the human X chromosome has been identified.The known murine X-linked imprinted genes do not have orthologues in humans. 92Notably, TS patients do have an increased risk of autism.In a series of TS patients, 5 of 150 (3%) were diagnosed with autism by ICD-10 criteria. 93This is five times higher than the 0.6% risk for the general population and 25 times higher than the 0.12% risk for XX females."
+            },
+            {
+                "document_id": "af3d7cd3-40ec-4a86-a473-89f83da250e4",
+                "section_type": "main",
+                "text": "\n\nRecessive gene: A gene, which will be expressed only if there are 2 identical copies or, for a male, if one copy is present on the X chromosome."
+            },
+            {
+                "document_id": "f4dd6a1d-062b-42bc-8e22-83fcb3135578",
+                "section_type": "main",
+                "text": "\n\nThe most widely studied age-related chromosomal abnormality that gives rise to somatic genome mosaicism, reported early in the 1970s from studying metaphases from human blood lymphocytes (Jacobs et al., 1963) and bone marrow (Pierre and Hoagland, 1972), is mosaic loss of the Y chromosome (LOY) in males during aging, which has now been widely confirmed with more advanced technology.LOY is defined as a lowerthan-expected abundance of DNA from the Y chromosome with a certain threshold of detection, for example, as 10% or more of affected cells (Dumanski et al., 2016).In a recent study of 205,011 men from the UK Biobank, LOY was found to affect from 2.5% of men at age 40 to 43.6% at age 70, which makes it the most common de novo somatic mutation over the human lifetime (Thompson et al., 2019).LOY frequency has been associated with a shorter lifespan, a higher risk of cancer, smoking, Alzheimer's disease, cardiovascular disease, diabetes, immune deficiencies, and other age-related diseases (Dumanski et al., 2016;Loftfield et al., 2018;Thompson et al., 2019).LOY has a genetic component, and in the aforementioned UK Biobank study, more than 150 autosomal genetic determinants of LOY were identified in the male cohort.LOY is most likely a general biomarker for genome instability in somatic cells.Indeed, the loci found to be genetically associated with LOY in males were themselves genetically associated, in a female cohort, with female cancers (breast, ovarian, and endometrial cancer) and age at natural menopause (Thompson et al., 2019).Of note, early menopause has been genetically associated with DNA damage response (DDR) genes (Day et al., 2015).Based on these results, it is tempting to speculate that the association of LOY with a diverse series of age-related pathologies points toward a causal role of somatic mutations in aging and age-related disease."
+            },
+            {
+                "document_id": "81c3edc4-f625-45f2-bf78-e49faf118c88",
+                "section_type": "main",
+                "text": "\n\nHow Many Inherited Disease Genes are There in the Human Genome?"
+            },
+            {
+                "document_id": "516fb027-d7ef-481b-95b2-89c25f4e4f8d",
+                "section_type": "main",
+                "text": "\n\nUsing the more advanced FISH-based methods, a dramatically more severe picture of aneuploidy levels was obtained.For example, up to 15-20% of aged human oocytes have chromosomal abnormalities, mainly aneuploidy [17] .In comparison, paternal age only causes a modest increase in the frequency of sex chromosomal aneuploidy in sperm cells [18] .Interestingly, this is the other way around for small DNA mutations, such as basepair substitutions.Virtually all genetic diseases based on point mutations are inherited from the father, most like-ly because such small mutations can arise through replication errors and sperm cells undergo many more rounds of replication than oocytes [19] .Indeed, the so-called 'paternal age effect', as observed first by Weinberg in achondroplasia, indicates that the high incidence of sporadic genetic diseases found among the youngest children in a family may reflect accelerating mutagenesis in sperms as men age [19] ."
+            },
+            {
+                "document_id": "4ad6da14-56a3-48ab-a587-42761ceac238",
+                "section_type": "main",
+                "text": "\n\nWhile DSDs have been reported in 9p deletion and duplication syndromes, we identify for the first time a significant gender bias in the full cohort with an enrichment for females.Among those with available sex chromosome information, we found individuals in the cohort with a gender of female and a sex chromosome complement of XY as expected in some DSDs.To make this a comprehensive study of phenotypes and genes in 9p deletion and duplication syndromes, we performed a meta-analysis of phenotypes observed in 9p deletion and duplication syndromes and found shared, similar, mirrored, and differing phenotypes.Several gene features were also considered for prioritization including constraint, enrichment for deletions/duplications in NDDs, and prior established disease associations.These are useful resources for the assessment of 9p-related structural variations.Recently developed genomic technologies are revolutionizing the way we assess syndromes with complex structural variations.We applied several of these technologies in this study to an individual with a complex 9p deletion, duplication, and associated translocation.We found that the classical karyotype is essential, that either a microarray or short-read WGS is critical to identify the mosaic duplication, and that long-read sequencing is the only technology able to resolve the intricate complexities of this variation."
+            },
+            {
+                "document_id": "4ba4d5e0-cb28-433d-8e9f-b09779e9d429",
+                "section_type": "main",
+                "text": "\n\nAutosomes -All of the chromosomes except for the sex chromosomes and the mitochondrial chromosome."
+            },
+            {
+                "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                "section_type": "main",
+                "text": "In 1967, Lubs (20) discovered\nexcessive genetic material extending beyond the low arm of the X chromosome in affected males.  Diagnosis was originally based on cytogenetic analysis of metaphase spreads, but less than 60% of the affected cells in affected\nindividuals showed a positive result.  With this variability in the test, the carrier\nstatus of individuals could not be determined.  Interpretation of the result is\nfurther complicated by the presence of other fragile sites in the same region\nof the X chromosome."
+            },
+            {
+                "document_id": "bf11c54e-7cc4-4fe2-97b0-70c464263846",
+                "section_type": "main",
+                "text": "\n\nAlthough abnormalities of the X chromosome have been linked to premature ovarian failure (20,21), it is not surprising that we did not identify a signal on the X chromosome (crude LOD score 0).Premature ovarian failure, defined as a decline in ovarian function by age 40 years, only occurs in approximately 1% of women in the general population.Because our sample was not enriched for women with early menopause, there were only 29 women with the onset of natural menopause at age Յ40 years in our sample.Thus we did not have the power to detect significant linkage to chromosome X.Furthermore, the largest Framingham families were selected for inclusion in the genome scan.Women with early decline in ovarian function might have difficulty with fertility and hence might be underrepresented in our sample."
+            },
+            {
+                "document_id": "f051ad23-572d-4302-8dda-4d992aeaeb1a",
+                "section_type": "main",
+                "text": "...an unexpected change in the structure of DNA can sometimes cause harm to the body. division process by which egg and sperm are formed.During the cell division process of meiosis, there is a reduction in the number of chromosomes that results in egg and sperm cells that contain 23 chromosomes, or half of the usual number of 46.Egg and sperm cells are called haploid cells because they have a single copy of each chromosome instead of the usual two copies (GHR, 2008i)."
+            },
+            {
+                "document_id": "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa",
+                "section_type": "main",
+                "text": "X-Linked Inheritance\n\nMore complicated patterns emerge if a disease mutation is present in a gene on the X chromosome.If a mutation is dominant, then a mother with the mutation (who herself should have the disease) has a 50% chance of passing the mutation  to an offspring, who in turn will have the disease.In contrast, a father with the mutation (who himself should have the disease) has a 50% chance of passing the mutation to a daughter because he passes an X chromosome to her, but he cannot transmit the mutation to a son because he passes a Y chromosome to him.Thus, the inheritance of disease depends on sex.This is X-linked dominant inheritance (Figure 11).An example of an X-linked dominant disorder is Rett syndrome.If a mutation is recessive, then a mother with the mutation (who should be a healthy carrier) has a 50% chance of passing the mutation to an offspring.A daughter who inherits the mutation will be a carrier, whereas a son who inherits the mutation will have the disease because he has only a single X chromosome and has no normal gene copy to counteract the mutant gene copy.A father with the mutation (who should have the disease) has a 50% chance of passing the mutation to a daughter, who will be a carrier, but cannot transmit the mutation to a son.The only way a daughter can have the disease is if she inherits mutant gene copies from both parents.This is X-linked recessive inheritance (Figure 11).Such diseases are much more likely to affect men than women.Classic examples of X-linked recessive disorders include red-green color blindness and hemophilia."
+            },
+            {
+                "document_id": "20b466c6-004b-484f-96a1-c1b4651bc856",
+                "section_type": "main",
+                "text": "\n\nMosaic loss of Y chromosome (mLOY) in peripheral blood is the most common acquired mutation in the process of normal aging in men, affecting about 1.8% of the genetic material in the human genome [12].The prevalence of mLOY increases with age and can exceed 20% in male populations older than 80 years [13].Furthermore, the occurrence of mLOY is strongly correlated with smoking behaviour [14].Current smokers have a more than fourfold increased risk for mLOY [13], although this effect seems to be transient as smoking cessation can result in normal mLOY levels after several years [14,15]."
+            },
+            {
+                "document_id": "76f1e8d2-15bf-4ce6-9cd0-2ab889c23664",
+                "section_type": "main",
+                "text": "\n\nBackground: Turner syndrome (TS) is caused by the absence or fragmentation of the second sex chromosome.An increased risk of diabetes mellitus (DM) has consistently been noted, but the specific phenotype and genetic etiology of this trait are unknown."
+            },
+            {
+                "document_id": "e913e8b9-7a8a-4a5e-9794-a947d94654a5",
+                "section_type": "main",
+                "text": "Marsupial Chromosomes\n\nMarsupials are famous for their low diploid numbers and large chromosomes, which offered cytologists optimal material for many classic studies of chromosome structure and behavior and of the effects of radiation.The karyotype is highly conserved across even distantly related groups.Classic work identified two modes of chromosome number (49,115), one of which, a 2n = 14 karyotype, was found to have identical G-band patterns across species in several families, including South American families (110).A fierce debate arose about whether the ancestral marsupial shared this low-diploid-number, large-chromosome karyotype, because some of the earliest offshoots in South America have a larger number of chromosomes, and interstitial telomere sequences suggested recent Robertsonian fusions to engender the lower number that is basic to Australidelphia (123).However, these sequences may be repeats that have accumulated at the centromeres and do not necessarily represent fusion points (88)."
+            },
+            {
+                "document_id": "b014e368-d0d5-4eff-a9af-abd4a4ed6d29",
+                "section_type": "main",
+                "text": "\n\nSeveral observations suggest that genetic factors could predispose to both the general baseline and age-related elevation in aneuploidy conceptions.A recent genome-wide screen for new meiotic genes in mouse oocytes revealed hundreds of genes, whose depletion by RNAi affected chromosome segregation (Pfender et al., 2015).This suggests that conducting refined analyses in human oocytes and population-based studies may yet yield new molecular targets.Studies in mice suggest that heterozygosity of SMC1β, a conserved meiosis-specific cohesin subunit, predisposes to aneuploidy (Murdoch et al., 2013).Deletion of both copies of SMC1β predisposes to agerelated loss of bivalent structures and therefore to aneuploidy in mouse oocytes (Hodges et al., 2005).The haploinsufficiency studies are important because they suggest dosage sensitivity.This is particularly relevant in human populations where complete deletions (homozygous) of gene activities are relatively rare and usually only found in consanguineous families (O'Driscoll, 2008)."
+            },
+            {
+                "document_id": "b014e368-d0d5-4eff-a9af-abd4a4ed6d29",
+                "section_type": "main",
+                "text": "\n\nSince the discovery that aneuploidy is the major cause of congenital disorders (Jacobs and Strong, 1959;Jacobs et al., 1959;Lejeune, Gautier, and Turpin, 1959;Ford et al., 1959a,b), most our knowledge has derived from population-based studies of foetal losses and rare live births.Maternal age is the major factor that influences aneuploidy, giving rise to the characteristic J curve (Erickson, 1978;Hassold and Hunt, 2001; Fig. 1A).However, individual chromosomes follow different age-dependent curves (Nagaoka et al., 2012;Franasiak et al., 2014a, b;Fig. 1B) suggesting that both chromosome-specific as well as general cellular factors conspire to shape the segregation efficiency in human oocytes."
+            },
+            {
+                "document_id": "b014e368-d0d5-4eff-a9af-abd4a4ed6d29",
+                "section_type": "main",
+                "text": "Introduction\n\nHuman conceptions are afflicted by an extraordinary rate of chromosome errors, and the majority derive from the oocyte (Hassold and Hunt, 2001).In natural conceptions that reach clinical recognition, 35% of human pregnancies are aneuploid.The rate observed in preimplantation embryos is substantially higher, in part because aneuploid embryos have poor developmental potential and are selected against during the peri-implantation stages and throughout foetal life (Capalbo et al., 2014).In natural conception, more than 90% are of meiotic origin and the majority are caused by errors in meiosis I (Hassold and Hunt, 2001;Gabriel et al., 2011).In reproductive aged women, 20-30% of occytes (and up to 70% of oocytes in advanced maternal age (AMA) women) are aneuploid, while just 1-8% of spermatozoa are afflicted (Lu et al., 2012;Wang et al., 2012).In sperm, the incidence of aneuploidy is independent of paternal age (Erickson, 1978;Hassold and Hunt, 2001;Lu et al., 2012;Wang et al., 2012).The analyses of aneuploidy in miscarriages have been invaluable for our appreciation of the serious consequences chromosomal imbalances have for embryonic and foetal development, since a much higher incidence and wider range and representation of chromosomes are detected compared to subsequent developmental stages, including live births (Hassold et al., 1980;Zaragoza et al., 1994)."
+            },
+            {
+                "document_id": "64d87c52-1185-4080-8d06-134c32dae5fd",
+                "section_type": "main",
+                "text": "\n\nThe processes of surveillance and searching for inheritance patterns may lead family members to believe that a genetic condition is transmitted through males or through females (Featherstone et al., 2006), resulting in predictions regarding who might be affected or included in conversations on the topic.Because of these assumptions, family members may ignore the importance of opposite gender relatives who may be carriers, such as in the case of HBOC."
+            },
+            {
+                "document_id": "02b1c922-a9cf-470d-b036-52c367fc1ca9",
+                "section_type": "main",
+                "text": "\n\nAnalogous to the post-natal occurrence of somatic mutations, we previously demonstrated a similar phenomenon, termed selfish spermatogonial selection, that occurs in the testes of adult men as they age.However, because the testis contains germ cells that, upon fertilization, will carry the genetic information across generations, this process has important reproductive implications, being associated with an increased prevalence of pathogenic DNMs in the next generation.Despite the relatively low average human germline point mutation rate of ∼1.2 × 10 −8 per nucleotide per generation (Kong et al. 2012;Goldmann et al. 2016;Jonsson et al. 2017), specific \"selfish\" DNMs in FGFR2, FGFR3, HRAS, PTPN11, and RET are observed up to 1000-fold more frequently in offspring (Goriely and Wilkie 2012).These pathogenic mutations, which cause developmental disorders that show an extreme paternal bias in origin and an epidemiological paternal age-effect (collectively referred to as PAE disorders; e.g., achondroplasia; Apert, Costello, and Noonan syndromes; multiple endocrine neoplasia type 2a/b), are identical (or allelic) to oncogenic driver mutations in tumors (Goriely and Wilkie 2012).We have proposed that although they arise at the normal background rate in male germline stem cells (spermatogonia), selfish mutations alter the behavior of spermatogonia within the testis.In a process akin to oncogenesis, these gain-of-function mutations provide a selective advantage that may involve increasing the rate of symmetrical divisions of the mutant spermatogonia (Qin et al. 2007;Choi et al. 2008Choi et al. , 2012;;Giannoulatou et al. 2013;Yoon et al. 2013;Martin et al. 2014), leading to their clonal expansion over time, which results in increased apparent mutation levels in sperm with age (Goriely and Wilkie 2012;Maher et al. 2014)."
+            },
+            {
+                "document_id": "f3c57cf2-da42-4833-ab8d-99517f987aea",
+                "section_type": "main",
+                "text": "\n\nChromosome copy number changes in the polar bodies and the corresponding cleavage stage embryos of 30 embryos predicted to have one or more aneuploidies of maternal meiotic origin."
+            }
+        ],
+        "document_id": "34A6BD721632631DF6D97BCA1D315B0A",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "X&chromosome",
+            "Y&chromosome",
+            "male",
+            "female",
+            "sex&chromosomes",
+            "autosome",
+            "nondisjunction",
+            "trisomy",
+            "monosomy",
+            "X-linked&inheritance"
+        ],
+        "metadata": [
+            {
+                "object": "Male schizophrenia subjects had more anterior cingulate cortex DEK protein expression compared to male controls. Female schizophrenia subjects had less DEK protein expression compared to female controls. Finally, while there were no differences in DEK protein expression between control males and control females, males with schizophrenia had higher DEK protein expression compared to females with schizophrenia.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab468329"
+            },
+            {
+                "object": "Study found robust hypersocial behavior in the dyadic interaction test in both PSD95+/- males and females. Additionally, male PSD95+/- mice exhibited higher levels of aggression and territoriality, while female PSD95+/- mice showed increased vocalization upon exposure to an anesthetized female mouse. Both male and female PSD95+/- mice revealed mild hypoactivity in the open field but no obvious motor deficit.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab741605"
+            },
+            {
+                "object": "Data suggest expression of Ptger2/Ptgs2 prostaglandin-endoperoxide synthase 2 is induced in cumulus cells of females sired by males with Y-chromosome long-arm deletion; paternal genes on Y-chromosome are involved indirectly in female reproduction.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab203335"
+            },
+            {
+                "object": "Data suggest expression of Ptgs2/Ptger2 prostaglandin E receptor 2 is induced in cumulus cells of females sired by males with Y-chromosome long-arm deletion; thus, paternal genes on Y-chromosome are involved indirectly in female reproduction.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab203337"
+            },
+            {
+                "object": "Lay summary Stress decreased vertical activity VA in female but not male rats while shock stress SS decreased serum BDNF in female but not male rats. VA was positively correlated with serum BDNF for female rats. These findings suggest sex differences in response to stress.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab445381"
+            },
+            {
+                "object": "Data identify Tudor domain containing protein 5-like Tdrd5l, which is expressed 17-fold higher in ovaries lacking Sxl. Additionally, Tdrd5l plays an important role in males as male flies that are mutant for this gene cannot make sperm properly and thus are less fertile. Tdrd5l promotes male identity in the germline and it can shift the germ cell developmental program from female to male.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab177945"
+            },
+            {
+                "object": "Aortic UCP1 content was greater in females than males and its deletion improved ex vivo aortic vasomotor function in females only. Constitutive UCP1 content in BAT was similar between females and males and loss of UCP1 did not abolish sex differences in insulin sensitivity. Metabolic disruptions caused by UCP1 ablation did not appear to be contingent upon increased oxidative stress in mice under normal dietary conditions.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab75747"
+            },
+            {
+                "object": "There was strong AR expression within the central core region of the suprachiasmatic nucleus of both XYM genetic and gonadal male and XXM genetic female, gonadal male groups. AR expression in the gonadal males was significantly higher than in females.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab889111"
+            },
+            {
+                "object": "ALPL in both male and female human liver data covaries extremely well with the unlinked PPP2R4 gene about 0.7 in both e.g.,  GSE9588 Human Liver Normal Mar11 Females. In females best linkage to rs6535513 on Chr 4 at 85.253280 with -logP of 6.56 nothing cis. In males best linkage to rs4664151 on Chr 2 at 154.336956 with -logP 7.55.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab167"
+            },
+            {
+                "object": "Disruption of Ser2 resulted in dominant heritable male sterility. Wild-type females mated with Ser2-deficient males laid eggs normally, but the eggs did not hatch. The authors detected no differences in other reproductive behaviors in the mutant males. These results support the conclusion that Ser2 gene is necessary for male reproductive success in diverse lepidopterans.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab233385"
+            }
+        ],
+        "question": "Why do males have two Y chromosomes and females only one?",
+        "subquestions": null,
+        "task_id": "34A6BD721632631DF6D97BCA1D315B0A",
+        "usage": {
+            "chatgpt": 6105,
+            "gpt-4": 3430,
+            "gpt-4-turbo-preview": 2504
+        },
+        "user_id": 2
+    },
+    "document_id": "34A6BD721632631DF6D97BCA1D315B0A",
+    "task_id": "34A6BD721632631DF6D97BCA1D315B0A"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/03.json b/gnqa/paper1_eval/src/data/responses/general/experts/03.json
new file mode 100644
index 0000000..8de2a7c
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/03.json
@@ -0,0 +1,406 @@
+{
+    "created_at": "2024-06-01T14:22:47.136754Z",
+    "data": {
+        "amplify": false,
+        "answer": "GeneNetwork utilizes datasets containing phenotypes and genotypes for QTL mapping analysis. These datasets may include genetic, genomic, and phenotypic data. The data are often formatted and normalized, and come with metadata. The database also includes data on complex phenotypes ranging from gene expression to behavior in standard inbred strains, and panels of mouse recombinant inbred strains. Rat and Arabidopsis populations are also represented in the database.",
+        "context": {
+            "071b4686-f5c4-4759-a038-14d79a45dac7": [
+                {
+                    "document_id": "071b4686-f5c4-4759-a038-14d79a45dac7",
+                    "text": "The project also provides online analysis tools to allow\nidentification of correlations within its data set. GeneNetwork (http://www.genenetwork.org), encompassing WebQTL, is a database of\ngenotypes and complex phenotypes ranging from gene expression to behaviour in standard\ninbred strains, and six panels of mouse recombinant inbred strains including the two largest\nsets (BXD and LXS) of approximately 80 strains each. Rat and Arabidopsis populations are\nalso represented. Approximately 1500 phenotypes spanning the 25 year history of these\nstrains are incorporated in this public resource, many of which were retrieved from the\nliterature."
+                }
+            ],
+            "0e6c370f-b514-4551-b6ed-9cc72e6f6b75": [
+                {
+                    "document_id": "0e6c370f-b514-4551-b6ed-9cc72e6f6b75",
+                    "text": "GN spares the\nuser most of these problem. Data are formatted and normalized, and usually come with good\nmetadata (often in the form of links to more information). This greatly simplifies QTL and\neQTL analysis, candidate gene discovery, coexpression analysis, and hypothesis testing [3,\n10]."
+                },
+                {
+                    "document_id": "0e6c370f-b514-4551-b6ed-9cc72e6f6b75",
+                    "text": "Suitable for quantitative\ngenetics (QTL mapping) and systems genetics, including correlation and\nnetwork analysis to compare associations between tissues and between\nother rodent or human data sets\n\nDescription and usage\n\n[32]\n\n[31]\n\n[30]\n\n[11]\n\nReferences\n\nMany of the Data Sets are amenable to systems genetics mapping and other methods and are accessible at GeneNetwork. The Description and Usage column provides details about the data set and potential\nusage."
+                }
+            ],
+            "2a92d7b5-946c-4a22-a4b9-26e950b0f757": [
+                {
+                    "document_id": "2a92d7b5-946c-4a22-a4b9-26e950b0f757",
+                    "text": "Bioinformatics\nAll of the genetic analyses were carried out in GeneNetwork, which\nis an open source bioinformatics resource for systems genetics that\nexists as both a repository for genetic, genomic and phenotypic\ndata together with a suite of statistical programs for data analysis that includes mapping and evaluating QTLs, examining phenotype/genotype correlations and building interaction networks. QTL mapping\nThe QTL mapping module of GeneNetwork was used to identify\nQTLs for hippocampal morphometry and radial maze trait data. This\nmodule enables interval mapping, composite interval mapping and\na pairwise scan option to identify epistatic effects."
+                }
+            ],
+            "389bdbf3-0224-4edb-a4fb-71a54971ba66": [
+                {
+                    "document_id": "389bdbf3-0224-4edb-a4fb-71a54971ba66",
+                    "text": "There\nare four options for QTL mapping on the GeneNetwork website: interval\nmapping, marker regression analysis, composite interval mapping, and pairscan analysis. In this case, interval mapping was used to compute linkage\nmaps for the entire genome. The log of odds (LOD) score was used to\nassert that a causal relation exists between a chromosomal location and a\nphenotypic variant, such as Gsto1 expression variation."
+                }
+            ],
+            "3df1bffa-3d23-4b6b-9d59-6ef8b0001f48": [
+                {
+                    "document_id": "3df1bffa-3d23-4b6b-9d59-6ef8b0001f48",
+                    "text": "Webqtl is an online database [110] of linked datasets, including genotype and expression\ndata, covering multiple species including mouse, macaque monkey, rat, drosophila,\narabidopsis, plants and humans [60]. While this tool cannot be used to calculate eQTLs, it\ncan be used to find and visualize eQTLs in different species, strains and tissues. It can\nperform single- and multiple-interval QTL mapping of up to 100 selected traits. Users can\nalso upload their own trait data for populations included in the database. It can also calculate\nand display trait-correlation matrices and network graphs (also for up to 100 traits)."
+                }
+            ],
+            "43407486-b9c2-487b-b19c-b605c4d201c6": [
+                {
+                    "document_id": "43407486-b9c2-487b-b19c-b605c4d201c6",
+                    "text": "GN spares the\nuser most of these problem. Data are formatted and normalized, and usually come with good\nmetadata (often in the form of links to more information). This greatly simplifies QTL and\neQTL analysis, candidate gene discovery, coexpression analysis, and hypothesis testing [3,\n10]."
+                },
+                {
+                    "document_id": "43407486-b9c2-487b-b19c-b605c4d201c6",
+                    "text": "Suitable for quantitative\ngenetics (QTL mapping) and systems genetics, including correlation and\nnetwork analysis to compare associations between tissues and between\nother rodent or human data sets\n\nDescription and usage\n\n[32]\n\n[31]\n\n[30]\n\n[11]\n\nReferences\n\nMany of the Data Sets are amenable to systems genetics mapping and other methods and are accessible at GeneNetwork. The Description and Usage column provides details about the data set and potential\nusage."
+                }
+            ],
+            "516cc395-4e7c-4371-9444-24edb56a7233": [
+                {
+                    "document_id": "516cc395-4e7c-4371-9444-24edb56a7233",
+                    "text": "QTL MAPPING AND QTG DISCOVERY IN THE RCC\nA variety of statistical methods and tools have been developed for QTL mapping and\nimplemented in free software for public use. These methods are well suited for simple\nbackcross and F2 RCC populations. R/qtl9,39 was developed for identiﬁcation of\nQTLs and higher order modeling. Another Web-based tool, GeneNetwork or\nWebQTL (GeneNetwork.org),40 was developed for QTL mapping and to explore\nassociations between variants, molecular traits (e.g. , gene expression), and higher order\nphenotypes (e.g. , behavior) and facilitate QTG identiﬁcation."
+                }
+            ],
+            "550c099f-88d0-483f-865a-01ef7362e2be": [
+                {
+                    "document_id": "550c099f-88d0-483f-865a-01ef7362e2be",
+                    "text": "This enables gene expression\ncorrelation and interval mapping, candidate gene searches and multitrait analyses. Each exported dataset was subject to an interval mapping analysis,\nwhich uses GeneNetwork’s embedded MapManager software\n(Manly et al . 2001) to perform Haley–Knott regression. Empirical P values were derived using 1000 permutations using the incorporated\npermutation feature of WebQTL. The peak of each statistically\nsignificant (P -value <0.05) or suggestive (P -value <0.63) (Lander\n& Kruglyak 1995) QTL was determined based on empirical P values (Doerge & Churchill 1996). A one-LOD drop-off was used\nto determine the QTL confidence interval about each peak."
+                }
+            ],
+            "581f83bc-3521-4cb3-ad3c-d905a90ecc29": [
+                {
+                    "document_id": "581f83bc-3521-4cb3-ad3c-d905a90ecc29",
+                    "text": "The peak linkage value\nand position was databased in GeneNetwork and users\ncan rapidly retrieve and view these mapping results for\nany probe set. Any of the QTL maps can also be rapidly\nregenerated using the same Haley-Knott methods, again\nusing functions imbedded in GeneNetwork. GeneNetwork also enable a search for epistatic interactions (pair\nscanning function) and composite interval mapping with\ncontrol for a single marker. Data quality control\n\nWe used two simple but effective methods to confirm\ncorrect sample identification of all data entered into\nGeneNetwork."
+                }
+            ],
+            "5bd8262b-b2cd-4098-a494-ede168941a9a": [
+                {
+                    "document_id": "5bd8262b-b2cd-4098-a494-ede168941a9a",
+                    "text": "QTL analysis\nAll QTL mapping for phenotypes was performed using the WebQTL software module of the\n\n170\n\nGeneNetwork (www.genenetwork.org) [34]. Interval mapping to evaluate potential QTLs was\ncalculated from the likelihood ratio statistics (LRS) as the software’s default measurement of\nthe association between differences in traits and differences in particular genotype markers. Another common measure score, the log of the odds (LOD) ratio, can be converted from the\nLRS (LRS/4.61). Suggestive and significant LRS values were determined by applying 1000\n\n175\n\npermutations."
+                }
+            ],
+            "80eb54fe-0d83-4300-9fba-e17ce5d1e5b4": [
+                {
+                    "document_id": "80eb54fe-0d83-4300-9fba-e17ce5d1e5b4",
+                    "text": "Unlike interval-specific haplotype analysis, which is most useful for narrowing a QTL shared by\nmultiple crosses, genome-wide haplotype analysis\nrequires only phenotype information from many inbred\nstrains and can effectively narrow a QTL identified in\nonly one experimental cross [36]. After narrowing the QTL to an interval that is !5 Mb\nusing these bioinformatics techniques or classical experimental methods, strain-specific sequence and gene\nexpression comparisons are effective for focusing on a\nfew strong candidate genes (Figure 7)."
+                }
+            ],
+            "86b86235-b7a8-4dfc-be13-d119dc31b377": [
+                {
+                    "document_id": "86b86235-b7a8-4dfc-be13-d119dc31b377",
+                    "text": "We considered QTL intervals that achieved genome-wide\nsignificance for one phenotype, and genome-wide suggestive for\nothers, as highest priority for candidate gene analysis. The January 2017 BXD genotype file was used4 . Updated linear mixed model mapping algorithms are now\navailable on GeneNetwork 25 (Sloan et al. , 2016), that account for\nkinship among strains. These new algorithms include GEMMA\n(Zhou and Stephens, 2012), pyLMM6 (Sul et al. , 2016), and\nR/qtl27 ."
+                }
+            ],
+            "9b2a48a0-f85e-4104-944f-0c47a3b03a9b": [
+                {
+                    "document_id": "9b2a48a0-f85e-4104-944f-0c47a3b03a9b",
+                    "text": "The peak linkage value\nand position was databased in GeneNetwork and users\ncan rapidly retrieve and view these mapping results for\nany probe set. Any of the QTL maps can also be rapidly\nregenerated using the same Haley-Knott methods, again\nusing functions imbedded in GeneNetwork. GeneNetwork also enable a search for epistatic interactions (pair\nscanning function) and composite interval mapping with\ncontrol for a single marker. Data quality control\n\nWe used two simple but effective methods to confirm\ncorrect sample identification of all data entered into\nGeneNetwork."
+                }
+            ],
+            "a4508fb3-c66b-4526-b2a2-a327505d085a": [
+                {
+                    "document_id": "a4508fb3-c66b-4526-b2a2-a327505d085a",
+                    "text": "There\nare four options for QTL mapping on the GeneNetwork website: interval\nmapping, marker regression analysis, composite interval mapping, and pairscan analysis. In this case, interval mapping was used to compute linkage\nmaps for the entire genome. The log of odds (LOD) score was used to\nassert that a causal relation exists between a chromosomal location and a\nphenotypic variant, such as Gsto1 expression variation."
+                }
+            ],
+            "b5c36c1e-458e-4009-818e-9c0c2ee23e45": [
+                {
+                    "document_id": "b5c36c1e-458e-4009-818e-9c0c2ee23e45",
+                    "text": "eQTL mapping\n\nQTL mapping was performed with GeneNetwork, an online bioinformatics resource\nfeaturing tools for systems genetic and complex trait analysis [9, 35]. QTL mapping\ninvolves entering VMB and CP iron data (strain means and SEM) as quantitative traits; the\nsoftware generates whole-genome interval maps for each trait. The interval maps graphically\nillustrate phenotype–genotype associations as peaks (QTL) indicating the strength of\nassociation between genomic polymorphisms and the quantitative trait throughout the\ngenome."
+                }
+            ],
+            "baacd740-efc8-42f2-af22-6f5ac9710900": [
+                {
+                    "document_id": "baacd740-efc8-42f2-af22-6f5ac9710900",
+                    "text": "Genetic Mapping\nIn this study we utilize GeneNetwork, a database containing phenotypes and genotypes,\nand also serves as an analysis engine for quantitative trait locus (QTL) mapping, genetic\ncorrelations, and phenome-wide association studies (PheWAS) (Sloan et al. , 2016; Mulligan et\nal. , 2017; Watson and Ashbrook, 2020). QTL analysis involves connecting phenotype data with\ngenotype data to examine genetic variation in traits controlled by multiple genes and their\ninteraction with the environment (also called complex traits)(Lynch et al. , 1998; Myles and\nWayne, 2008; Goddard et al. , 2016)."
+                }
+            ],
+            "beb7a242-21fe-4a66-8b44-7f228c0d3640": [
+                {
+                    "document_id": "beb7a242-21fe-4a66-8b44-7f228c0d3640",
+                    "text": "Once the resulting record set of the\nquery is returned, it can be further restricted by selecting\nrelevant records based on attached annotations before forwarding it for further analysis. To map genetic loci associated with mRNA abundance or\ntrait phenotypes, any one of the three QTL mapping functions currently employed by GeneNetwork's WebQTL\nmodule can be used. These are 1. interval mapping, 2. single-marker regression, or 3. composite mapping [29,30]."
+                }
+            ],
+            "e70f7c61-1734-4048-8a79-382e9b381686": [
+                {
+                    "document_id": "e70f7c61-1734-4048-8a79-382e9b381686",
+                    "text": "genenetwork.org/) a set of 3795 markers. Linkage is reported with\ngenome-wide significance levels based on 2000 permutation tests. Two types of QTL mapping analyses–simple mapping using the Haley–\nKnott regression equation, and composite interval mapping–were\nutilized in this study. Simple interval mapping was performed to\nillustrate the significance of any QTLs that regulate the TID. As a\nsecondary analysis, composite interval mapping which controlled for\nthe influence of Tyrp1 was also performed with the goal of identifying\nany secondary QTLs that may have been masked by the major QTL on\nChr 4."
+                }
+            ]
+        },
+        "data_source": [
+            {
+                "document_id": "baacd740-efc8-42f2-af22-6f5ac9710900",
+                "section_type": "main",
+                "text": "Genetic Mapping\nIn this study we utilize GeneNetwork, a database containing phenotypes and genotypes,\nand also serves as an analysis engine for quantitative trait locus (QTL) mapping, genetic\ncorrelations, and phenome-wide association studies (PheWAS) (Sloan et al. , 2016; Mulligan et\nal. , 2017; Watson and Ashbrook, 2020).  QTL analysis involves connecting phenotype data with\ngenotype data to examine genetic variation in traits controlled by multiple genes and their\ninteraction with the environment (also called complex traits)(Lynch et al. , 1998; Myles and\nWayne, 2008; Goddard et al. , 2016)."
+            },
+            {
+                "document_id": "550c099f-88d0-483f-865a-01ef7362e2be",
+                "section_type": "main",
+                "text": "This enables gene expression\ncorrelation and interval mapping, candidate gene searches and multitrait analyses.\n Each exported dataset was subject to an interval mapping analysis,\nwhich uses GeneNetwork’s embedded MapManager software\n(Manly et al .  2001) to perform Haley–Knott regression.  Empirical P values were derived using 1000 permutations using the incorporated\npermutation feature of WebQTL.  The peak of each statistically\nsignificant (P -value <0.05) or suggestive (P -value <0.63) (Lander\n& Kruglyak 1995) QTL was determined based on empirical P values (Doerge & Churchill 1996).  A one-LOD drop-off was used\nto determine the QTL confidence interval about each peak."
+            },
+            {
+                "document_id": "beb7a242-21fe-4a66-8b44-7f228c0d3640",
+                "section_type": "main",
+                "text": "Once the resulting record set of the\nquery is returned, it can be further restricted by selecting\nrelevant records based on attached annotations before forwarding it for further analysis.\n\n To map genetic loci associated with mRNA abundance or\ntrait phenotypes, any one of the three QTL mapping functions currently employed by GeneNetwork's WebQTL\nmodule can be used.  These are 1. interval mapping, 2. single-marker regression, or 3. composite mapping [29,30]."
+            },
+            {
+                "document_id": "86b86235-b7a8-4dfc-be13-d119dc31b377",
+                "section_type": "main",
+                "text": "We considered QTL intervals that achieved genome-wide\nsignificance for one phenotype, and genome-wide suggestive for\nothers, as highest priority for candidate gene analysis.\n The January 2017 BXD genotype file was used4 .\n Updated linear mixed model mapping algorithms are now\navailable on GeneNetwork 25 (Sloan et al. , 2016), that account for\nkinship among strains.  These new algorithms include GEMMA\n(Zhou and Stephens, 2012), pyLMM6 (Sul et al. , 2016), and\nR/qtl27 ."
+            },
+            {
+                "document_id": "516cc395-4e7c-4371-9444-24edb56a7233",
+                "section_type": "main",
+                "text": "QTL MAPPING AND QTG DISCOVERY IN THE RCC\nA variety of statistical methods and tools have been developed for QTL mapping and\nimplemented in free software for public use.  These methods are well suited for simple\nbackcross and F2 RCC populations.  R/qtl9,39 was developed for identiﬁcation of\nQTLs and higher order modeling.  Another Web-based tool, GeneNetwork or\nWebQTL (GeneNetwork.org),40 was developed for QTL mapping and to explore\nassociations between variants, molecular traits (e.g. , gene expression), and higher order\nphenotypes (e.g. , behavior) and facilitate QTG identiﬁcation."
+            },
+            {
+                "document_id": "3df1bffa-3d23-4b6b-9d59-6ef8b0001f48",
+                "section_type": "main",
+                "text": "Webqtl is an online database [110] of linked datasets, including genotype and expression\ndata, covering multiple species including mouse, macaque monkey, rat, drosophila,\narabidopsis, plants and humans [60].  While this tool cannot be used to calculate eQTLs, it\ncan be used to find and visualize eQTLs in different species, strains and tissues.  It can\nperform single- and multiple-interval QTL mapping of up to 100 selected traits.  Users can\nalso upload their own trait data for populations included in the database.  It can also calculate\nand display trait-correlation matrices and network graphs (also for up to 100 traits)."
+            },
+            {
+                "document_id": "e70f7c61-1734-4048-8a79-382e9b381686",
+                "section_type": "main",
+                "text": "genenetwork.org/) a set of 3795 markers.  Linkage is reported with\ngenome-wide significance levels based on 2000 permutation tests.\n Two types of QTL mapping analyses–simple mapping using the Haley–\nKnott regression equation, and composite interval mapping–were\nutilized in this study.  Simple interval mapping was performed to\nillustrate the significance of any QTLs that regulate the TID.  As a\nsecondary analysis, composite interval mapping which controlled for\nthe influence of Tyrp1 was also performed with the goal of identifying\nany secondary QTLs that may have been masked by the major QTL on\nChr 4."
+            },
+            {
+                "document_id": "2a92d7b5-946c-4a22-a4b9-26e950b0f757",
+                "section_type": "main",
+                "text": "Bioinformatics\nAll of the genetic analyses were carried out in GeneNetwork, which\nis an open source bioinformatics resource for systems genetics that\nexists as both a repository for genetic, genomic and phenotypic\ndata together with a suite of statistical programs for data analysis that includes mapping and evaluating QTLs, examining phenotype/genotype correlations and building interaction networks.\n\n QTL mapping\nThe QTL mapping module of GeneNetwork was used to identify\nQTLs for hippocampal morphometry and radial maze trait data.  This\nmodule enables interval mapping, composite interval mapping and\na pairwise scan option to identify epistatic effects."
+            },
+            {
+                "document_id": "0e6c370f-b514-4551-b6ed-9cc72e6f6b75",
+                "section_type": "main",
+                "text": "Suitable for quantitative\ngenetics (QTL mapping) and systems genetics, including correlation and\nnetwork analysis to compare associations between tissues and between\nother rodent or human data sets\n\nDescription and usage\n\n[32]\n\n[31]\n\n[30]\n\n[11]\n\nReferences\n\nMany of the Data Sets are amenable to systems genetics mapping and other methods and are accessible at GeneNetwork.  The Description and Usage column provides details about the data set and potential\nusage."
+            },
+            {
+                "document_id": "43407486-b9c2-487b-b19c-b605c4d201c6",
+                "section_type": "main",
+                "text": "Suitable for quantitative\ngenetics (QTL mapping) and systems genetics, including correlation and\nnetwork analysis to compare associations between tissues and between\nother rodent or human data sets\n\nDescription and usage\n\n[32]\n\n[31]\n\n[30]\n\n[11]\n\nReferences\n\nMany of the Data Sets are amenable to systems genetics mapping and other methods and are accessible at GeneNetwork.  The Description and Usage column provides details about the data set and potential\nusage."
+            },
+            {
+                "document_id": "071b4686-f5c4-4759-a038-14d79a45dac7",
+                "section_type": "main",
+                "text": "The project also provides online analysis tools to allow\nidentification of correlations within its data set.\n GeneNetwork (http://www.genenetwork.org), encompassing WebQTL, is a database of\ngenotypes and complex phenotypes ranging from gene expression to behaviour in standard\ninbred strains, and six panels of mouse recombinant inbred strains including the two largest\nsets (BXD and LXS) of approximately 80 strains each.  Rat and Arabidopsis populations are\nalso represented.  Approximately 1500 phenotypes spanning the 25 year history of these\nstrains are incorporated in this public resource, many of which were retrieved from the\nliterature."
+            },
+            {
+                "document_id": "581f83bc-3521-4cb3-ad3c-d905a90ecc29",
+                "section_type": "main",
+                "text": "The peak linkage value\nand position was databased in GeneNetwork and users\ncan rapidly retrieve and view these mapping results for\nany probe set.  Any of the QTL maps can also be rapidly\nregenerated using the same Haley-Knott methods, again\nusing functions imbedded in GeneNetwork.  GeneNetwork also enable a search for epistatic interactions (pair\nscanning function) and composite interval mapping with\ncontrol for a single marker.\n Data quality control\n\nWe used two simple but effective methods to confirm\ncorrect sample identification of all data entered into\nGeneNetwork."
+            },
+            {
+                "document_id": "9b2a48a0-f85e-4104-944f-0c47a3b03a9b",
+                "section_type": "main",
+                "text": "The peak linkage value\nand position was databased in GeneNetwork and users\ncan rapidly retrieve and view these mapping results for\nany probe set.  Any of the QTL maps can also be rapidly\nregenerated using the same Haley-Knott methods, again\nusing functions imbedded in GeneNetwork.  GeneNetwork also enable a search for epistatic interactions (pair\nscanning function) and composite interval mapping with\ncontrol for a single marker.\n Data quality control\n\nWe used two simple but effective methods to confirm\ncorrect sample identification of all data entered into\nGeneNetwork."
+            },
+            {
+                "document_id": "5bd8262b-b2cd-4098-a494-ede168941a9a",
+                "section_type": "main",
+                "text": "QTL analysis\nAll QTL mapping for phenotypes was performed using the WebQTL software module of the\n\n170\n\nGeneNetwork (www.genenetwork.org) [34].  Interval mapping to evaluate potential QTLs was\ncalculated from the likelihood ratio statistics (LRS) as the software’s default measurement of\nthe association between differences in traits and differences in particular genotype markers.\n Another common measure score, the log of the odds (LOD) ratio, can be converted from the\nLRS (LRS/4.61).  Suggestive and significant LRS values were determined by applying 1000\n\n175\n\npermutations."
+            },
+            {
+                "document_id": "389bdbf3-0224-4edb-a4fb-71a54971ba66",
+                "section_type": "main",
+                "text": "There\nare four options for QTL mapping on the GeneNetwork website: interval\nmapping, marker regression analysis, composite interval mapping, and pairscan analysis.  In this case, interval mapping was used to compute linkage\nmaps for the entire genome.  The log of odds (LOD) score was used to\nassert that a causal relation exists between a chromosomal location and a\nphenotypic variant, such as Gsto1 expression variation."
+            },
+            {
+                "document_id": "a4508fb3-c66b-4526-b2a2-a327505d085a",
+                "section_type": "main",
+                "text": "There\nare four options for QTL mapping on the GeneNetwork website: interval\nmapping, marker regression analysis, composite interval mapping, and pairscan analysis.  In this case, interval mapping was used to compute linkage\nmaps for the entire genome.  The log of odds (LOD) score was used to\nassert that a causal relation exists between a chromosomal location and a\nphenotypic variant, such as Gsto1 expression variation."
+            },
+            {
+                "document_id": "80eb54fe-0d83-4300-9fba-e17ce5d1e5b4",
+                "section_type": "main",
+                "text": "Unlike interval-specific haplotype analysis, which is most useful for narrowing a QTL shared by\nmultiple crosses, genome-wide haplotype analysis\nrequires only phenotype information from many inbred\nstrains and can effectively narrow a QTL identified in\nonly one experimental cross [36].\n After narrowing the QTL to an interval that is !5 Mb\nusing these bioinformatics techniques or classical experimental methods, strain-specific sequence and gene\nexpression comparisons are effective for focusing on a\nfew strong candidate genes (Figure 7)."
+            },
+            {
+                "document_id": "7dc4230d-c0a3-484b-9fb4-04d5ff09956b",
+                "section_type": "main",
+                "text": "Unlike interval-specific haplotype analysis, which is most useful for narrowing a QTL shared by\nmultiple crosses, genome-wide haplotype analysis\nrequires only phenotype information from many inbred\nstrains and can effectively narrow a QTL identified in\nonly one experimental cross [36].\n After narrowing the QTL to an interval that is !5 Mb\nusing these bioinformatics techniques or classical experimental methods, strain-specific sequence and gene\nexpression comparisons are effective for focusing on a\nfew strong candidate genes (Figure 7)."
+            },
+            {
+                "document_id": "1b31c086-dbd1-4b0d-8b51-c33b074b8e9d",
+                "section_type": "main",
+                "text": "Genotyping and QTL mapping\nQTL and eQTL mapping was performed using GeneNetwork http://www.genenetwork.org and a standardized set\nof 3795 genotyped markers (mapping algorithm and genotypes described at http://www.genenetwork.org/dbdoc/\nBXDGeno.html; genotypes downloadable as a text file\nfrom\nhttp://www.genenetwork.org/genotypes/\nBXD.geno).  Residuals from the model described above\n(Trait 10701) were simple interval mapped using a modified Haley-Knott algorithm [36,37], weighted by the\nwithin strain variances.  Genome-wide significance was\ncalculated by comparing the best likelihood ratio statistic\nof the original data set with the distribution of highest LRS\ncomputed for 10,000 permutations."
+            },
+            {
+                "document_id": "9d225f6f-e434-45a7-b199-f3a09eda1d04",
+                "section_type": "main",
+                "text": "Next, we used GeneNetwork2, an online analysis tool and data repository containing\nlegacy SNP and transcriptome datasets to explore gene regulatory networks (Chesler et al.  2004; Mulligan et al.\n 2017).  We conducted both eQTL and PheQTL-eQTL network analysis using several BXD RI gene expression\ndatasets from multiple brain regions (datasets documented in Supplementary Information) and using the\nentirety of > 7,000 BXD Published Phenotypes deposited in GeneNetwork2 [BXDPublish; GN602]."
+            },
+            {
+                "document_id": "4049da4d-c7cf-4e30-9a21-c77609fad23d",
+                "section_type": "main",
+                "text": "Once the data is normalized appropriately (in our case, no normalization was required), the QTL\ncan be mapped.  To do this, select the mapping tools drop down window (Figure 6).  There are\nthree methods to choose from, GEMMA, Haley-Knott Regression, and R/qtl (Figure 6).  Genomewide Efficient Mixed Model Analysis (GEMMA; github.com/genetics-statistics/GEMMA; (Zhou\nand Stephens, 2012) is a multivariate linear mixed model mapping tool that is used to map\nphenotypes with SNPs with a correction for kinship or any other covariate of interest.  This\nability to account for covariates is highly useful, but also this increases the time taken for\ncomputations."
+            },
+            {
+                "document_id": "7b1cecf5-a2b9-4bd9-b92b-9bd6b96ed93d",
+                "section_type": "main",
+                "text": "Once the data is normalized appropriately (in our case, no normalization was required), the QTL\ncan be mapped.  To do this, select the mapping tools drop down window (Figure 6).  There are\nthree methods to choose from, GEMMA, Haley-Knott Regression, and R/qtl (Figure 6).  Genomewide Efficient Mixed Model Analysis (GEMMA; github.com/genetics-statistics/GEMMA; (Zhou\nand Stephens, 2012) is a multivariate linear mixed model mapping tool that is used to map\nphenotypes with SNPs with a correction for kinship or any other covariate of interest.  This\nability to account for covariates is highly useful, but also this increases the time taken for\ncomputations."
+            },
+            {
+                "document_id": "8dad24f7-b658-44fa-af65-6f33db69c15a",
+                "section_type": "main",
+                "text": "The values were analysed by using\nthe software program MapManager QTX (KF Manley,\nhttp://www.mapmanger.org) [20] and WebQTL (http://\nwww.webqtl.org) [15, 16] in order to perform a genomewide search for mapping QTL.  In this case, the user is not\nrequired to discriminate between ‘B’ and ‘D’ phenotypes.\n Rather, the quantitative phenotypic data for each RI\nstrain serve as the starting point for analysis.  This results\nin statistics that are essentially two-tailed, more conservative than may be warranted in some situations with\nextreme differences between parental lines."
+            },
+            {
+                "document_id": "89fdce49-cd76-446e-bc47-9484071f9d3e",
+                "section_type": "main",
+                "text": "GeneNetwork and WebQTL are our group’s first attempts to embrace these\nnew opportunities (Wang et al.  2003) and to generate\nan appropriate research environment that combines\ndata sets, statistical resources, and summaries of\nfindings—a knowledgebase (www.genenetwork.org).\n Mapping traits will become far easier; cloning allelic\nvariants for molecular and cellular phenotypes will\nprogress from difficult to trivial as it already has for\nmost cis-QTL with high LOD scores."
+            },
+            {
+                "document_id": "18d12255-3cc6-415b-bd30-ff94bb087813",
+                "section_type": "main",
+                "text": "These estimates were uploaded to GeneNetwork (genenetwork.org;\nhttp://gn2.genenetwork.org; GN IDs 21497-21517) (Mulligan et al. , 2017; Parker et al. , 2017; Sloan et al. ,\n2016), and quantitative trait loci (QTL) were mapped.\n 2.14.  QTL mapping\nQTL mapping allows the identification of linkage between any region of the genome, and a phenotype of\ninterest.  The fast linear regression equations of Haley and Knott (Haley and Knott, 1992) were used for\ninitial QTL mapping.  Using 5000 permutations of the phenotypes, genome-wide significant (p < 0.05), and\nsuggestive (p < 0.63) thresholds were calculated within GeneNetwork."
+            },
+            {
+                "document_id": "4439ac39-e421-482f-9aa9-9ad11fa641c1",
+                "section_type": "main",
+                "text": "WebQTL is the primary module in the GeneNetwork online resource (www.genenetwork.org),\nand provides a powerful environment to analyze\ntraits controlled by genetic variants (Chesler et al.\n 2004; Wang et al.  2003).  It includes data from many\n\n485\n\nFig.  2.  Complexity of eQTL data.  The graph shows a threedimensional schematic view of the high dimensionality of\nthe eQTL data set generated from the BXH/HXB RI strain\npanel (Hubner et al 2005; unpublished)."
+            },
+            {
+                "document_id": "0e6c370f-b514-4551-b6ed-9cc72e6f6b75",
+                "section_type": "main",
+                "text": "GN spares the\nuser most of these problem.  Data are formatted and normalized, and usually come with good\nmetadata (often in the form of links to more information).  This greatly simplifies QTL and\neQTL analysis, candidate gene discovery, coexpression analysis, and hypothesis testing [3,\n10]."
+            },
+            {
+                "document_id": "43407486-b9c2-487b-b19c-b605c4d201c6",
+                "section_type": "main",
+                "text": "GN spares the\nuser most of these problem.  Data are formatted and normalized, and usually come with good\nmetadata (often in the form of links to more information).  This greatly simplifies QTL and\neQTL analysis, candidate gene discovery, coexpression analysis, and hypothesis testing [3,\n10]."
+            },
+            {
+                "document_id": "85ee9743-b34d-4d49-9017-d7d2e5d4b996",
+                "section_type": "main",
+                "text": "1 The\n\n2\n3\n4\n\nIntroduction\n\nModern high-throughput technologies generate large amounts of genomic, transcriptomic, proteomic and metabolomic data.  However, existing open source web-based tools for QTL analysis, such as webQTL\n[358] and QTLNetwork [377], are not easily extendable to diﬀerent settings and computationally scalable for whole genome analyses.  xQTL\nworkbench makes it easy to analyse large and complex datasets using\nstate-of-the-art QTL mapping tools and to apply these methods to millions of phenotypes using parallelized ‘Big Data’ solutions [342]."
+            },
+            {
+                "document_id": "516cc395-4e7c-4371-9444-24edb56a7233",
+                "section_type": "main",
+                "text": "In this section, we will\nfocus mainly on QTL analysis performed in F2 mice using the R package R/qtl.  For a\nreview of GeneNetwork tools and functions, see Ref.  41.\n A variety of analytical methodologies are available in the R/qtl package, including,\ne.g. , composite interval mapping or Haley-Knott regression (see Ref.  42 for discussion).\n The “scanone” function in R/qtl is used to calculate log of the odds (LOD) scores.  Permutation analysis (perm ¼ 1000) is used to establish the signiﬁcance threshold for each\nphenotype (P < .05).  Additive and/or interactive covariates can be added to the model\n(e.g."
+            },
+            {
+                "document_id": "99eb95e6-f439-453e-b90f-4752f1b66d0b",
+                "section_type": "main",
+                "text": "able to estimate the quality of the several thousand\nQTL results that each data set typically produces.\n This direct replication clearly shows that many\neQTL, particularly cis-acting QTL, are high-quality,\nreplicable observations and that eQTL data sets are a\nvaluable means of understanding gene expression\nrelationships.\n Using our data, researchers without the luxury of\na confirmatory F2 data set can estimate the fraction\nof QTL in a similar RI data set that are likely to also\nbe observed in a relatively small F2 data set, and they\ncan select significance thresholds that reflect desired\nvalues of this fraction."
+            },
+            {
+                "document_id": "bbf4a07f-b30d-4bd6-ba32-16ad470231b1",
+                "section_type": "main",
+                "text": "Genetic dissection of gene expression\n\n2.2.4\n\nDensity of the genetic grid in QTL analysis The computational\ndemand of QTL mapping can be decreased by using a sparser genetic grid\nfor a genome scan.  Most of the currently used QTL mapping strategies are\nbased on interval mapping where QTL are evaluated at regular intervals\n(e.g.  1 cM) on the genetic map.  In a situation where markers are fully informative Coffman et al.  (2003) suggest that a genome scan using single marker\ninformation can be equally or even more powerful than analyses based on\nflanking markers.  We evaluated three alternatives."
+            },
+            {
+                "document_id": "8bb7e3b1-bdb0-4c54-a916-6424237616da",
+                "section_type": "main",
+                "text": "Expression QTLs Mapping\nSince we had not any co-segregated genetical marker, a simple query in related gene\nexpression database in GeneNetwrok resources was done to find the most biologically\nrelated genes to our candidate genes.  We used the MDC/CAS/ICL Kidney 230A (Apr05)\nMAS5 database for above the purpose (for more information about this population reader\nconsult WebQtl site http://www.webqtl.org/).  Using publicly available data on gene\nexpression, SNP linkage maps and all the related software’s freely available at WebQTL\nserver (www.genenetwork.org), we ran eQTL mapping to get insights into systems\ngenetics of candidate genes."
+            },
+            {
+                "document_id": "f0bf9619-6bb9-41c7-9d2b-51d9b650d5b2",
+                "section_type": "main",
+                "text": "The raw microarray data is available from the Gene Expression\nOmnibus (GSE14563) as well as from WebQTL (Wang et al.  2003).\n MDP QTL Mapping\nHigh density single nucleotide polymorphism (SNP) data was used to perform eQTL mapping\nin the MDP (McClurg et al.  2007).  Association mapping was carried out using FastMap (Gatti\net al.  2009) as detailed above.  Population structure was identified using a PCA plot of the SNP\ndata and two major strata were identified; C57BL/6J, C57BL/10J, C57BLKS/J, C57BR/cdJ &\nC57L/J were in one stratum and the remaining strains were in the other."
+            },
+            {
+                "document_id": "2845fea0-7cf7-4bb8-915e-ff13c41f0176",
+                "section_type": "main",
+                "text": "QTL mapping was performed using web-based complex\ntrait analysis (www.  genenetwork.org) which uses QTL reaper software.  A single marker regression\nacross all chromosomes was performed where a hypothetical QTL was evaluated at the location of\n8222 informative markers.  At a single chromosomal level, interval mapping evaluates potential\nQTL at regular intervals and estimates the significance at each location with a graphical\nrepresentation of the likelihood ratio statistic (LRS).  A permutation test establishes genome-wide\nsignificance criteria of 5% for the trait.\n Correlation analysis and gene network construction."
+            },
+            {
+                "document_id": "2e0bbb7b-45cd-4208-b2f0-e229df86d8ff",
+                "section_type": "main",
+                "text": "Genetical genomics analysis\nQuantitative trait locus (QTL) mapping was performed for the\nsaline and ethanol treated RMA datasets, as well as the saline vs\nethanol S-score dataset, using a subset of informative microsatellite\nand SNP markers that have been used to genotype the BXD\nfamily [37,38], and are available from GeneNetwork (genenetwork.org/genotypes/BXD.geno).  Linkage between genotypes and\nexpression phenotypes was assessed by performing Haley-Knott\nregression using R/qtl [39].  Genome-wide adjusted p-values were\nderived using distributions of maximum LOD scores obtained\nfrom 1,000 permutations of each probe-set’s expression data."
+            },
+            {
+                "document_id": "bbd1d762-faab-409d-9243-bc94023e16c0",
+                "section_type": "main",
+                "text": "WebQTL contains\ncomprehensive, manually curated, publicly available data\nfor phenotypic and gene expression proﬁling of a number\nof RI and F2 crosses in both mice and rats along with the\ndense genetic marker maps for these strains.  These data\ncan be used to search for correlations between the phenotypes, gene expression, and genetic markers, that is, to\nperform in silico genotype-phenotype association analysis.  The inherent signiﬁcance of the deﬁned reference genetic populations, such as BXD RI strains, is in the ability\nto connect historical data generated in many laboratories\nto the exact genetic map of each strain."
+            },
+            {
+                "document_id": "cc4fd4f5-b5b8-419e-9631-2df633d53570",
+                "section_type": "main",
+                "text": "QTL mapping was carried out using simple and\ncomposite interval mapping in GeneNetwork (http://\nwww.genenetwork.org).  Candidate genes in QTL regions\nwere ranked using PGMapper.  SNP genotypes of candidate genes were verified directly using PCR amplification and sequencing."
+            },
+            {
+                "document_id": "b5c36c1e-458e-4009-818e-9c0c2ee23e45",
+                "section_type": "main",
+                "text": "eQTL mapping\n\nQTL mapping was performed with GeneNetwork, an online bioinformatics resource\nfeaturing tools for systems genetic and complex trait analysis [9, 35].  QTL mapping\ninvolves entering VMB and CP iron data (strain means and SEM) as quantitative traits; the\nsoftware generates whole-genome interval maps for each trait.  The interval maps graphically\nillustrate phenotype–genotype associations as peaks (QTL) indicating the strength of\nassociation between genomic polymorphisms and the quantitative trait throughout the\ngenome."
+            },
+            {
+                "document_id": "6b5ae9e0-ea61-45e2-9b6d-663b532c1a81",
+                "section_type": "main",
+                "text": "An automated QTL mapping strategy needs to rely strictly on\nstatistical measures to highlight candidate regions because manual\ninspection of QTL results across the genome for individual traits,\nwhich is common in standard QTL mapping, is not feasible for\nevery individual gene transcript.  In this study, we will apply various\n\n© The Author 2004.  Published by Oxford University Press.  All rights reserved.  For Permissions, please email: journals.permissions@oupjournals.org\n\n2383\nÖ.Carlborg et al.\n\n standard QTL mapping scenarios to analyse data from one of the\nfirst publicly available genetical genomics datasets (Chesler et al. ,\n2005)."
+            }
+        ],
+        "document_id": "39076B38EDAF24ECEEB91924D370F4AD",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "GeneNetwork",
+            "QTL",
+            "mapping",
+            "genotype",
+            "phenotype",
+            "interval&mapping",
+            "composite&interval&mapping",
+            "marker&regression",
+            "eQTL",
+            "haplotype"
+        ],
+        "metadata": [
+            {
+                "object": "The genotype GG group had higher consumption of Remifentanil than the genotype AA group P<0.05, but the genotype AG group was not different from the genotype AA and GG groups P>0.05. The analepsia time, autonomous respiratory recovery time, and orientation recovery time in the genotype GG group were longer than in the genotype AA group P<0.05, but the genotype AG group was not different from the genotype AA and GG.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab818259"
+            },
+            {
+                "object": "We showed that Rheumatoid was more likely with the AA genotype compared with the AG genotype of SNP rs2977537, and with the TT genotype, or the GG genotype compared with the GT genotype of rs2929973, and with the AA genotype or GG genotype vs the AG genotype of rs2977530",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab1013556"
+            },
+            {
+                "object": "APOE genotype and haplotype distributions differ significantly along the age classes Genotype: p=0.014; Haplotype: p=0.005 with APOE*epsilon4 genotype status and haplotype displaying negative association Genotype: O.R.=0.377, p=0.002, Haplotype: O.R.=0.447, p=0.005",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab77498"
+            },
+            {
+                "object": "LTA4H genotype predicted survival of HIV-uninfected patients, with TT-genotype patients significantly more likely to survive tuberculous meningitis than CC-genotype patients. LTA4H genotype and HIV infection influence pretreatment inflammatory phenotype and survival from tuberculous meningitis. LTA4H genotype may predict adjunctive corticosteroid responsiveness in HIV-uninfected individuals.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab464785"
+            },
+            {
+                "object": "A haplotype block across a 24-kb region within the TOX2 gene reached genome-wide significance in haplotype-block-based regional heritability mapping. Single-SNP- and haplotype-based association tests demonstrated that five of nine genotyped SNPs and two haplotypes within this block were significantly associated with major depressive disorder.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab17193"
+            },
+            {
+                "object": "Apa1 Aa genotype compared to AA genotype had odds ratios of 1.65, 1.79 and 1.64 respectively p > 0.05. In TMJ-ID women versus healthy women Aa genotype had 2.06 fold p = 0.15 odds compared to AA genotype. In TMJ-ID women versus healthy women Aa genotype had 2.06 fold p = 0.15 odds compared to AA genotype. our results do not confirm susceptibility of VDR polymorphisms to TMJ-ID/TMJOA",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab76039"
+            },
+            {
+                "object": "DICER rs3742330 AG+GG genotype was associated with more advanced T stage compared to AA genotype  P=0.009. More patients with XPO5 rs2257082 CC genotype had poorly differentiated tumors compared with CT+TT genotype carriers.., carriers of RAN rs14035 CC genotype had higher three-year OS rate than carriers of CT+TT genotype adjusted HR 3.174; 95% CI 1.010, 9.973; P=0.048.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab229028"
+            },
+            {
+                "object": "The antiproteinuric response to olmesartan by genotype was: genotype TT: 76.8%; genotype MM: 67.3%; genotype MT: 65.8%, significantly higher P<.05 for genotype TT compared to genotypes MM and MT.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab780501"
+            },
+            {
+                "object": "A significant QTL for intraocular pressure IOP in 10-13 months-old BXD family mice maps to proximal Chr 5 15 to 18 Mb near Gnai1 Record ID 12309. Data by Monica Jablonski and Lu Lu. Gnai1 is a cis eQTL in eye LRS of 18.6. Other candidates include Cacna2d1 and Pclo and both are also cis eQTLs. Hgf is also a candidate. This is the same region as the eye weight QTL possibly Hgf of Zhou and Williams 1999. This QTL is not significant at younger ages.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab130"
+            },
+            {
+                "object": "The antiproteinuric response to olmesartan by genotype was: DD: 71.4%; genotype ID: 60.6%, genotype II: 34.8%, significantly higher P<.05 for genotype DD compared to genotypes ID and II, and also P<.05 for genotype ID compared to II.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab780500"
+            }
+        ],
+        "question": "what type of dataset is useful for qtl mapping analysis in genenetwork2?",
+        "subquestions": null,
+        "task_id": "39076B38EDAF24ECEEB91924D370F4AD",
+        "usage": {
+            "chatgpt": 5013,
+            "gpt-4": 3398,
+            "gpt-4-turbo-preview": 2412
+        },
+        "user_id": 2
+    },
+    "document_id": "39076B38EDAF24ECEEB91924D370F4AD",
+    "task_id": "39076B38EDAF24ECEEB91924D370F4AD"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/04.json b/gnqa/paper1_eval/src/data/responses/general/experts/04.json
new file mode 100644
index 0000000..2f84ab1
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/04.json
@@ -0,0 +1,392 @@
+{
+    "created_at": "2024-06-01T14:24:19.558227Z",
+    "data": {
+        "amplify": false,
+        "answer": "The ethical considerations surrounding prenatal genetic testing and selective termination of pregnancies based on genetic factors include the potential for implicit pressure on individuals to violate personal ethics to reduce financial burden on society, the risk of routinization of testing leading to social or medical expectations of testing in all eligible individuals, and the potential compromise of values of informed consent and individual autonomy. There are also cultural and religious beliefs to consider, as well as the potential psychological impact on parents who may feel guilt if they are carriers of genetic conditions. Furthermore, the decision to terminate a pregnancy based on genetic factors is a joint decision between parents, and the involvement of extended family members in this process varies greatly across different cultures.",
+        "context": {
+            "30eabd29-2f48-459a-b162-bd90d99f1411": [
+                {
+                    "document_id": "30eabd29-2f48-459a-b162-bd90d99f1411",
+                    "text": "\n\nA number of additional ethical implications must be considered.Associating financial investments with the prevention of disease, especially where reproductive decisions are involved, requires sensitivity, caution, and ethical rigor.Funding decisions based on imputed cost-savings must not result in implicit pressure on individuals to violate personal ethics to reduce financial burden on society.As discussions regarding prenatal testing have demonstrated, 35 is risk that \"routinization\" of testing may lead to social or medical expectations of testing in all eligible individuals.These expectations, if linked with financial incentives for the health system, could risk applying implicit pressure on serious, and potentially irreversible, personal decisions.Such expectations, if applied at the population level, could risk becoming normalized, compromising the values of informed consent and individual autonomy."
+                },
+                {
+                    "document_id": "30eabd29-2f48-459a-b162-bd90d99f1411",
+                    "text": "\n\nWith regard to pregnancies affected by a genetic condition identified through population carrier screening, we modeled the decision to terminate affected pregnancies conservatively (0.50).This is despite the literature suggesting rates above 0.90 for elective TOP for conditions such as Down syndrome 33 and SMA. 34We recognize this issue is controversial, and that laws and ethical positions vary considerably between countries/ jurisdictions.Variations in population attitudes based on age, religion, and other factors, as well as the criticality of preserving individual choice, were acknowledged in adopting this highly conservative estimate."
+                }
+            ],
+            "56cf7be3-8c73-498d-b48f-8d99592b0213": [
+                {
+                    "document_id": "56cf7be3-8c73-498d-b48f-8d99592b0213",
+                    "text": "\n\nThe use of genetic testing from pre-conception through adulthood is expanding rapidly.As a result of this expansion, new ethical issues are emerging related to genetic testing and informed consent.These new issues create ethical challenges for nurses and all healthcare providers.Currently expanding areas include newborn screening and genetic testing of children.These new ethical challenges will be described below."
+                },
+                {
+                    "document_id": "56cf7be3-8c73-498d-b48f-8d99592b0213",
+                    "text": "The use of genetic testing from pre-conception through adulthood is expanding rapidly. Psychological risks for parents who are carriers may include parental guilt."
+                }
+            ],
+            "64d87c52-1185-4080-8d06-134c32dae5fd": [
+                {
+                    "document_id": "64d87c52-1185-4080-8d06-134c32dae5fd",
+                    "text": "\n\nEthnic and cultural backgrounds may also play a role in the decisions that families make regarding prenatal testing.Moyer et al. (1999) concluded that Caucasian women more often undergo prenatal diagnoses than African American or Asian women, or Latinas.Furthermore, Awwad et al. (2008) found American couples less inclined to involve extended relatives in the prenatal decision-making process than Native Palestinian couples.Both of these examples clearly indicate that cultural differences can impact the ways in which families negotiate prenatal decisions.Further research needs to investigate how different families engage in such discussions and decision-making processes, especially as prenatal testing becomes more common and better able to predict or prevent a wider range of genetic conditions.Tightly closed ethnic groups remain at high risk of serving as carriers for genetic mutations, but the management of this possibility varies greatly.For example, some Ashkenazi Jewish groups use screening for mutations for Tay-Sachs disease (TSD) as the basis for rabbinical marriage advice; whereas, children born to Amish families in Pennsylvania more often present with glutaric aciduria type 1 (GA1) but, given their beliefs, parents tend not to accept prenatal testing because of the implication of abortion (McKusick, 2000)."
+                },
+                {
+                    "document_id": "64d87c52-1185-4080-8d06-134c32dae5fd",
+                    "text": "\n\nResearchers studying factors that contribute toward a couple's choice to undergo prenatal testing have determined that partners base their decision upon several factors, including, but not limited to: parental beliefs about abortion, attitudes regarding disability and their \"perceptions of the usefulness of having the information revealed by genetic tests\" (Moyer et al., 1999, p. 522).Abortion beliefs constitute a key issue in the decision-making process.Even though a majority of parents receiving abnormal prenatal test results terminate their pregnancies (Redlinger-Grosse, Bernhardt, Berg, Muenke, & Biesecker, 2002), Moyer et al. noted that, when asked, more families reported that they would make use of prenatal testing than would be willing to terminate a pregnancy.The decision to continue or terminate a pregnancy after prenatal testing Downloaded by [University of the Sunshine Coast] at 10:32 05 August 2017 comprises a joint decision between both parents (e.g., Awwad et al., 2008;Beeson & Golbus, 1985); however, the nature of the conversations leading to the decision and the involvement of extended family members in the decisionmaking process remains highly understudied."
+                },
+                {
+                    "document_id": "64d87c52-1185-4080-8d06-134c32dae5fd",
+                    "text": "The Genetic Divide(s) and Communication\n\nThe ability of scientists to \"map\" disease through several generations (Collins, 1999) raises practical and ethical issues of access to resulting opportunities and creates family communication challenges.Currently, prenatal testing for chromosomal diseases has become increasingly common (Moyer et al., 1999).Options such as pre-implantation genetic diagnosis (PGD) can identify over 1,250 disease-related mutations creating an opportunity for parents to select unaffected embryos for implantation in the womb (R. M. Green, 2008).Test results provide potential parents with information that may lead to decisions involving intervention in the genetic makeup of future children.Although some families welcome such options, others may be unable or unwilling to consider such procedures, due to fi nancial concerns or moral/ethical/religious beliefs."
+                }
+            ],
+            "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa": [
+                {
+                    "document_id": "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa",
+                    "text": "Privacy Issues\n\nFinally, privacy issues should be seriously considered when the use of genetic testing is contemplated, especially with respect to whole-genome sequencing of healthy people.It is an unanswered question under what circumstances, to what extent, and by what means genetic data should be incorporated into the medical record.Although easy access to such data could be helpful to providers in improving patient care, it remains to be seen how other parties (eg, insurance companies) might act on the data in ways that do not benefit patients.The US Congress acted to prohibit discrimination by employers and health insurers on the basis of genetic testing with the Genetic Information Nondiscrimination Act in 2008, but further safeguards will undoubtedly be needed as the health implications of genetic data become clearer."
+                }
+            ],
+            "782103fd-2cb6-44c8-9b39-d82430d335c9": [
+                {
+                    "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                    "text": "\n\nThe ethical evaluation of genetic testing in children is traditionally based on the balance of clinical benefits and risks (American Society of Human Genetics Board of Directors and the American College of Medical Genetics All correspondence concerning this article should be addressed to Benjamin Wilfond, MD, Treuman Katz Center for Pediatric Bioethics, Seattle Children's Hospital, Metropolitan Park West M/S: MPW 8-2, 1100 Olive Way, Room 876, Seattle WA 98101, USA.E-mail: benjamin.wilfond@seattlechildrens.org Board of Directors, 1995;Andrews, Fullerton, Holtzman, & Motolsky, 1994;Clarke, 1994;Wertz, Fanos, & Reilly, 1994).In the early 1990s, when there were only scant data about children who had received genetic tests results, the presumption was to give greater weight to the potential risks and to restrict testing.However, this criterion is not necessarily consistent with the general practice of respecting broad parental discretion in health care decisionmaking for and on behalf of their children.In general, parents are the presumed decision makers for their children and their decisions are respected unless they are abusive or neglectful (Buchanan & Brock, 1989;Goldstein, Freud, & Solnit, 1979;Ross, 1998).The tension between assessments of benefits and risks made by health care providers and policy makers, and the procedural respect owed to parental authority will be clearly tested as the ability to conduct and interpret whole-genome sequencing and related technologies gain in momentum."
+                },
+                {
+                    "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                    "text": "Ethical Considerations in Developing Policy for ''Comprehensive'' Genomic Testing\n\nIn the near future, genomic testing is likely to become more accessible and will provide both information about the risks of common conditions such as heart disease, diabetes, and hypertension as well as predictions about individual responses to specific pharmaceuticals and other medical therapies (Aspinall & Hamermesh, 2007).Over time, the number and range of conditions for which such testing is available is likely to expand to include more behavioral traits, ranging from information about anxiety and depression, to attention and addiction (Rothstein, 2005)."
+                },
+                {
+                    "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                    "text": "\nObjective Ethical evaluation of genetic testing in children is traditionally based on balancing clinical benefits and risks.However, this focus can be inconsistent with the general practice of respecting parental decision-making about their children's health care.We argue that respect for parental decision-making should play a larger role in shaping pediatric genetic testing practices, and play a similar role regarding decisions to use emerging genomic technologies.Methods Genomic testing involves the examination of thousands of DNA markers spanning genes throughout the genome and their interrelationships, yielding virtually limitless interpretations.We presume that parents and providers should proceed cautiously in applying genomic testing in children, as we explore how genomic testing will stress the fault lines of the traditional ethical analysis.Results Empirical data about the psychosocial risks and benefits of genetic testing of children do not reveal serious harms, yet virtually no such data exist yet about genomic testing.Unless empirical social and behavioral data indicate that genomic testing is highly likely to cause serious harms to the children, parental decisions to obtain comprehensive genomic testing in their children should be respected.Once comprehensive genomic testing of children becomes routine, resultant information may be more easily integrated by families than anticipated.Conclusions Research on the social and behavioral impact of comprehensive genomic testing on children and their families is needed to further inform parents, clinicians, and policy makers."
+                },
+                {
+                    "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                    "text": "\n\nObjective Ethical evaluation of genetic testing in children is traditionally based on balancing clinical benefits and risks.However, this focus can be inconsistent with the general practice of respecting parental decision-making about their children's health care.We argue that respect for parental decision-making should play a larger role in shaping pediatric genetic testing practices, and play a similar role regarding decisions to use emerging genomic technologies.Methods Genomic testing involves the examination of thousands of DNA markers spanning genes throughout the genome and their interrelationships, yielding virtually limitless interpretations.We presume that parents and providers should proceed cautiously in applying genomic testing in children, as we explore how genomic testing will stress the fault lines of the traditional ethical analysis.Results Empirical data about the psychosocial risks and benefits of genetic testing of children do not reveal serious harms, yet virtually no such data exist yet about genomic testing.Unless empirical social and behavioral data indicate that genomic testing is highly likely to cause serious harms to the children, parental decisions to obtain comprehensive genomic testing in their children should be respected.Once comprehensive genomic testing of children becomes routine, resultant information may be more easily integrated by families than anticipated.Conclusions Research on the social and behavioral impact of comprehensive genomic testing on children and their families is needed to further inform parents, clinicians, and policy makers."
+                },
+                {
+                    "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                    "text": "\n\nTo the extent that ''personal meaning'' gains wider acceptance as a legitimate criterion for expanding the availability of new tests and applications of genomic technology, the current policies and practices of restricting some genetic testing of children and mandating other tests will need to be reevaluated.There will be some parents who will find the information that becomes available through new technologies and data useful in shaping their parenting practices, while others will be more skeptical of their value.These disparate parental judgments may be independent of professional assessments of clinical validity and utility.Extrapolating from the empirical data about predictive genetic testing of children in at-risk families discussed earlier, we speculate that once comprehensive genomic testing of children becomes routine, the information may be more easily integrated by families than might be predicted.This is not meant to imply that whatever information parents want about their children should be provided carte blanche.Clearly, education and counseling will be crucial to ensure that families understand the limitations of the information.However, restrictions and mandates should be based on a criterion of risk of serious harm (Diekema, 2004).Given the lack of data confirming harm and the related data that indicate children may fare better than anticipated, such restrictions and mandates cannot be justified.Policies and practices will also need to clarify the role of the older adolescent in the decision-making process, although the issues related to balancing and assessing parental and adolescent interests and preferences goes beyond the focus of this article.This is also not meant to ignore the professional and moral obligation to educate parents and to help parents make good decisions on behalf of their children.It is morally appropriate for providers to strongly recommend particular tests in infancy and young childhood (i.e., PKU testing), and to strongly discourage other tests (e.g., ApoE testing of children for adult onset Alzheimer disease and heart disease because ApoE is not predictive but only provides an increased relative risk and has limited sensitivity and specificity) (Roberts, Cupples, Relkin, Whitehouse, & Green, 2005).Selective and directive recommendations are a routine aspect of pediatric practice.However, it will become increasingly important for professional organizations to begin to reconcile their support for mandatory genetic testing for some conditions and their support for restrictions for other conditions with the broad discretion that parents have and need in the health care arena in order to promote their children's well-being."
+                },
+                {
+                    "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                    "text": "\n\nWhat limits should be imposed, if any, need to be determined prior to commercial feasibility.In this article, we consider how genetic testing decisions for children have been made traditionally and how the anticipation of comprehensive genomic testing in the near future will stress the fault lines of traditional approaches.The potential for comprehensive genomic testing in children could shift the equilibrium towards expanding or reducing parental discretion, and forces us to reexamine the evidence for our genetic testing policies and practices.We will highlight specific domains where further empirical social and behavioral research is necessary to inform policy and practice."
+                }
+            ],
+            "93dc581e-5e45-48b4-b82f-35e32d7bd58e": [
+                {
+                    "document_id": "93dc581e-5e45-48b4-b82f-35e32d7bd58e",
+                    "text": "\n\nPrenatal genetics is largely practiced by maternal-fetal medicine specialists due to severe deficiency in the number of qualified clinical geneticists.Recent years have witnessed a tremendous growth in the demand for chorionic villous sampling and amniocentesis for the diagnosis of single gene disorders.At KFSHRC alone, the number of prenatal samples that are tested for single gene disorders has increased from 5 in 2004 to 250 in 2013.Therapeutic abortion is permitted by law if performed within 120 days from the time of fertilization in order to comply with the Islamic view of the timing of ensoulment (Alkuraya and Kilani 2001).However, the approved indication for the procedure, which is \"severe malformation\", must be authorized by three attending-level physicians.The definition of \"severe\" is left to the discretion of the medical team after consulting with the family.For example, intellectual disability is a common indication for many therapeutic abortion procedures.Contrary to commonly held views, we have shown that early prenatal diagnosis is the method of choice for couples who had one or more children with single gene disorders, as long as they are provided with a culturally sensitive genetic counseling that addresses their religious and cultural concerns (Alkuraya and Kilani 2001).Nearly 45% of these couples opt for early prenatal diagnosis compared to 35% who choose preimplantation genetic diagnosis (PGD) (Alkuraya 2013a).PGD is available freely at KFSHRC but is also provided by the private sector.Noninvasive prenatal screening using cell-free fetal DNA in maternal blood is quickly becoming integrated in prenatal care.KFSHRC offers this test routinely to all pregnant women regardless of their perceived risk and the MOH is considering making this test available throughout its vast network of hospitals and medical centers."
+                }
+            ],
+            "9f21007a-1487-46d8-8e9e-cde8df4af6d5": [
+                {
+                    "document_id": "9f21007a-1487-46d8-8e9e-cde8df4af6d5",
+                    "text": "\n\nSocial and psychological implications of accessing genetic services and information."
+                }
+            ],
+            "a4b0655d-895c-4368-9401-ee2903b15d42": [
+                {
+                    "document_id": "a4b0655d-895c-4368-9401-ee2903b15d42",
+                    "text": "\n\nA corollary of the predictive power of genetic information is the limited ability to prevent or treat many conditions with significant genetic factors involved.Indeed, virtually all of the complex ethical and legal issues relevant to genetic testing would disappear if there were effective preventions or treatments available for genetic conditions.The ability to predict future disease in conjunction with a limited ability to do much about it has important social and psychological implications that must be addressed in conducting genetic research."
+                }
+            ],
+            "b0b60080-2338-411b-bc44-1f5626a3c442": [
+                {
+                    "document_id": "b0b60080-2338-411b-bc44-1f5626a3c442",
+                    "text": "\n\nInterpretations of the literature will likely mirror the priorities and evaluative tendencies of the reader.Are you willing to accept the overall trends in genetic and genomic testing evaluation and to trust that the existing clinical approaches will apply informed consent appropriately while identifying and supporting the rare individual who has a serious adverse response to the testing?If so, you might advocate that attention be turned more toward other issues relevant to the effective implementation of genetic and genomic testing.Or do you feel a strong need to understand in more detail the possible psychosocial harms of the testing, particularly the subtler impacts or responses of individuals who do not fit the norm?In that case, you would likely encourage renewed and innovative efforts to study the psychosocial consequences of the receipt of risk information from genetic and genomic testing."
+                }
+            ],
+            "f7fe5d02-ee7c-4ec2-b6c4-ca9aa5efb41f": [
+                {
+                    "document_id": "f7fe5d02-ee7c-4ec2-b6c4-ca9aa5efb41f",
+                    "text": "\n\nOther social issues require our attention if genomic medicine is to benefit our patients.How should genetic tests be regulated?What, if any, are the appropriate uses of direct-to-consumer marketing of genetic tests?The Internet has recently had a proliferation of genetic-testing sites that feature claims grounded in greed and pseudoscience, rather than in data or reality.How will health care providers and the public distinguish between these and responsible testing services, whether they are available through the Internet or in the hospital?"
+                }
+            ],
+            "f97246cb-7a71-409b-bb1a-dd01a5ef5c5e": [
+                {
+                    "document_id": "f97246cb-7a71-409b-bb1a-dd01a5ef5c5e",
+                    "text": "Environmental Factors\n\nAs widespread use of genetic testing increases, it is the responsibility of the medical community to ensure its equitable use across socioeconomic and cultural spectrums."
+                }
+            ]
+        },
+        "data_source": [
+            {
+                "document_id": "30eabd29-2f48-459a-b162-bd90d99f1411",
+                "section_type": "main",
+                "text": "\n\nA number of additional ethical implications must be considered.Associating financial investments with the prevention of disease, especially where reproductive decisions are involved, requires sensitivity, caution, and ethical rigor.Funding decisions based on imputed cost-savings must not result in implicit pressure on individuals to violate personal ethics to reduce financial burden on society.As discussions regarding prenatal testing have demonstrated, 35 is risk that \"routinization\" of testing may lead to social or medical expectations of testing in all eligible individuals.These expectations, if linked with financial incentives for the health system, could risk applying implicit pressure on serious, and potentially irreversible, personal decisions.Such expectations, if applied at the population level, could risk becoming normalized, compromising the values of informed consent and individual autonomy."
+            },
+            {
+                "document_id": "56cf7be3-8c73-498d-b48f-8d99592b0213",
+                "section_type": "main",
+                "text": "\n\nThe use of genetic testing from pre-conception through adulthood is expanding rapidly.As a result of this expansion, new ethical issues are emerging related to genetic testing and informed consent.These new issues create ethical challenges for nurses and all healthcare providers.Currently expanding areas include newborn screening and genetic testing of children.These new ethical challenges will be described below."
+            },
+            {
+                "document_id": "64d87c52-1185-4080-8d06-134c32dae5fd",
+                "section_type": "main",
+                "text": "\n\nResearchers studying factors that contribute toward a couple's choice to undergo prenatal testing have determined that partners base their decision upon several factors, including, but not limited to: parental beliefs about abortion, attitudes regarding disability and their \"perceptions of the usefulness of having the information revealed by genetic tests\" (Moyer et al., 1999, p. 522).Abortion beliefs constitute a key issue in the decision-making process.Even though a majority of parents receiving abnormal prenatal test results terminate their pregnancies (Redlinger-Grosse, Bernhardt, Berg, Muenke, & Biesecker, 2002), Moyer et al. noted that, when asked, more families reported that they would make use of prenatal testing than would be willing to terminate a pregnancy.The decision to continue or terminate a pregnancy after prenatal testing Downloaded by [University of the Sunshine Coast] at 10:32 05 August 2017 comprises a joint decision between both parents (e.g., Awwad et al., 2008;Beeson & Golbus, 1985); however, the nature of the conversations leading to the decision and the involvement of extended family members in the decisionmaking process remains highly understudied."
+            },
+            {
+                "document_id": "30eabd29-2f48-459a-b162-bd90d99f1411",
+                "section_type": "main",
+                "text": "\n\nWith regard to pregnancies affected by a genetic condition identified through population carrier screening, we modeled the decision to terminate affected pregnancies conservatively (0.50).This is despite the literature suggesting rates above 0.90 for elective TOP for conditions such as Down syndrome 33 and SMA. 34We recognize this issue is controversial, and that laws and ethical positions vary considerably between countries/ jurisdictions.Variations in population attitudes based on age, religion, and other factors, as well as the criticality of preserving individual choice, were acknowledged in adopting this highly conservative estimate."
+            },
+            {
+                "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                "section_type": "main",
+                "text": "\n\nThe ethical evaluation of genetic testing in children is traditionally based on the balance of clinical benefits and risks (American Society of Human Genetics Board of Directors and the American College of Medical Genetics All correspondence concerning this article should be addressed to Benjamin Wilfond, MD, Treuman Katz Center for Pediatric Bioethics, Seattle Children's Hospital, Metropolitan Park West M/S: MPW 8-2, 1100 Olive Way, Room 876, Seattle WA 98101, USA.E-mail: benjamin.wilfond@seattlechildrens.org Board of Directors, 1995;Andrews, Fullerton, Holtzman, & Motolsky, 1994;Clarke, 1994;Wertz, Fanos, & Reilly, 1994).In the early 1990s, when there were only scant data about children who had received genetic tests results, the presumption was to give greater weight to the potential risks and to restrict testing.However, this criterion is not necessarily consistent with the general practice of respecting broad parental discretion in health care decisionmaking for and on behalf of their children.In general, parents are the presumed decision makers for their children and their decisions are respected unless they are abusive or neglectful (Buchanan & Brock, 1989;Goldstein, Freud, & Solnit, 1979;Ross, 1998).The tension between assessments of benefits and risks made by health care providers and policy makers, and the procedural respect owed to parental authority will be clearly tested as the ability to conduct and interpret whole-genome sequencing and related technologies gain in momentum."
+            },
+            {
+                "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                "section_type": "main",
+                "text": "Ethical Considerations in Developing Policy for ''Comprehensive'' Genomic Testing\n\nIn the near future, genomic testing is likely to become more accessible and will provide both information about the risks of common conditions such as heart disease, diabetes, and hypertension as well as predictions about individual responses to specific pharmaceuticals and other medical therapies (Aspinall & Hamermesh, 2007).Over time, the number and range of conditions for which such testing is available is likely to expand to include more behavioral traits, ranging from information about anxiety and depression, to attention and addiction (Rothstein, 2005)."
+            },
+            {
+                "document_id": "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa",
+                "section_type": "main",
+                "text": "Privacy Issues\n\nFinally, privacy issues should be seriously considered when the use of genetic testing is contemplated, especially with respect to whole-genome sequencing of healthy people.It is an unanswered question under what circumstances, to what extent, and by what means genetic data should be incorporated into the medical record.Although easy access to such data could be helpful to providers in improving patient care, it remains to be seen how other parties (eg, insurance companies) might act on the data in ways that do not benefit patients.The US Congress acted to prohibit discrimination by employers and health insurers on the basis of genetic testing with the Genetic Information Nondiscrimination Act in 2008, but further safeguards will undoubtedly be needed as the health implications of genetic data become clearer."
+            },
+            {
+                "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                "section_type": "abstract",
+                "text": "\nObjective Ethical evaluation of genetic testing in children is traditionally based on balancing clinical benefits and risks.However, this focus can be inconsistent with the general practice of respecting parental decision-making about their children's health care.We argue that respect for parental decision-making should play a larger role in shaping pediatric genetic testing practices, and play a similar role regarding decisions to use emerging genomic technologies.Methods Genomic testing involves the examination of thousands of DNA markers spanning genes throughout the genome and their interrelationships, yielding virtually limitless interpretations.We presume that parents and providers should proceed cautiously in applying genomic testing in children, as we explore how genomic testing will stress the fault lines of the traditional ethical analysis.Results Empirical data about the psychosocial risks and benefits of genetic testing of children do not reveal serious harms, yet virtually no such data exist yet about genomic testing.Unless empirical social and behavioral data indicate that genomic testing is highly likely to cause serious harms to the children, parental decisions to obtain comprehensive genomic testing in their children should be respected.Once comprehensive genomic testing of children becomes routine, resultant information may be more easily integrated by families than anticipated.Conclusions Research on the social and behavioral impact of comprehensive genomic testing on children and their families is needed to further inform parents, clinicians, and policy makers."
+            },
+            {
+                "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                "section_type": "main",
+                "text": "\n\nObjective Ethical evaluation of genetic testing in children is traditionally based on balancing clinical benefits and risks.However, this focus can be inconsistent with the general practice of respecting parental decision-making about their children's health care.We argue that respect for parental decision-making should play a larger role in shaping pediatric genetic testing practices, and play a similar role regarding decisions to use emerging genomic technologies.Methods Genomic testing involves the examination of thousands of DNA markers spanning genes throughout the genome and their interrelationships, yielding virtually limitless interpretations.We presume that parents and providers should proceed cautiously in applying genomic testing in children, as we explore how genomic testing will stress the fault lines of the traditional ethical analysis.Results Empirical data about the psychosocial risks and benefits of genetic testing of children do not reveal serious harms, yet virtually no such data exist yet about genomic testing.Unless empirical social and behavioral data indicate that genomic testing is highly likely to cause serious harms to the children, parental decisions to obtain comprehensive genomic testing in their children should be respected.Once comprehensive genomic testing of children becomes routine, resultant information may be more easily integrated by families than anticipated.Conclusions Research on the social and behavioral impact of comprehensive genomic testing on children and their families is needed to further inform parents, clinicians, and policy makers."
+            },
+            {
+                "document_id": "64d87c52-1185-4080-8d06-134c32dae5fd",
+                "section_type": "main",
+                "text": "The Genetic Divide(s) and Communication\n\nThe ability of scientists to \"map\" disease through several generations (Collins, 1999) raises practical and ethical issues of access to resulting opportunities and creates family communication challenges.Currently, prenatal testing for chromosomal diseases has become increasingly common (Moyer et al., 1999).Options such as pre-implantation genetic diagnosis (PGD) can identify over 1,250 disease-related mutations creating an opportunity for parents to select unaffected embryos for implantation in the womb (R. M. Green, 2008).Test results provide potential parents with information that may lead to decisions involving intervention in the genetic makeup of future children.Although some families welcome such options, others may be unable or unwilling to consider such procedures, due to fi nancial concerns or moral/ethical/religious beliefs."
+            },
+            {
+                "document_id": "64d87c52-1185-4080-8d06-134c32dae5fd",
+                "section_type": "main",
+                "text": "\n\nEthnic and cultural backgrounds may also play a role in the decisions that families make regarding prenatal testing.Moyer et al. (1999) concluded that Caucasian women more often undergo prenatal diagnoses than African American or Asian women, or Latinas.Furthermore, Awwad et al. (2008) found American couples less inclined to involve extended relatives in the prenatal decision-making process than Native Palestinian couples.Both of these examples clearly indicate that cultural differences can impact the ways in which families negotiate prenatal decisions.Further research needs to investigate how different families engage in such discussions and decision-making processes, especially as prenatal testing becomes more common and better able to predict or prevent a wider range of genetic conditions.Tightly closed ethnic groups remain at high risk of serving as carriers for genetic mutations, but the management of this possibility varies greatly.For example, some Ashkenazi Jewish groups use screening for mutations for Tay-Sachs disease (TSD) as the basis for rabbinical marriage advice; whereas, children born to Amish families in Pennsylvania more often present with glutaric aciduria type 1 (GA1) but, given their beliefs, parents tend not to accept prenatal testing because of the implication of abortion (McKusick, 2000)."
+            },
+            {
+                "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                "section_type": "main",
+                "text": "\n\nTo the extent that ''personal meaning'' gains wider acceptance as a legitimate criterion for expanding the availability of new tests and applications of genomic technology, the current policies and practices of restricting some genetic testing of children and mandating other tests will need to be reevaluated.There will be some parents who will find the information that becomes available through new technologies and data useful in shaping their parenting practices, while others will be more skeptical of their value.These disparate parental judgments may be independent of professional assessments of clinical validity and utility.Extrapolating from the empirical data about predictive genetic testing of children in at-risk families discussed earlier, we speculate that once comprehensive genomic testing of children becomes routine, the information may be more easily integrated by families than might be predicted.This is not meant to imply that whatever information parents want about their children should be provided carte blanche.Clearly, education and counseling will be crucial to ensure that families understand the limitations of the information.However, restrictions and mandates should be based on a criterion of risk of serious harm (Diekema, 2004).Given the lack of data confirming harm and the related data that indicate children may fare better than anticipated, such restrictions and mandates cannot be justified.Policies and practices will also need to clarify the role of the older adolescent in the decision-making process, although the issues related to balancing and assessing parental and adolescent interests and preferences goes beyond the focus of this article.This is also not meant to ignore the professional and moral obligation to educate parents and to help parents make good decisions on behalf of their children.It is morally appropriate for providers to strongly recommend particular tests in infancy and young childhood (i.e., PKU testing), and to strongly discourage other tests (e.g., ApoE testing of children for adult onset Alzheimer disease and heart disease because ApoE is not predictive but only provides an increased relative risk and has limited sensitivity and specificity) (Roberts, Cupples, Relkin, Whitehouse, & Green, 2005).Selective and directive recommendations are a routine aspect of pediatric practice.However, it will become increasingly important for professional organizations to begin to reconcile their support for mandatory genetic testing for some conditions and their support for restrictions for other conditions with the broad discretion that parents have and need in the health care arena in order to promote their children's well-being."
+            },
+            {
+                "document_id": "f97246cb-7a71-409b-bb1a-dd01a5ef5c5e",
+                "section_type": "main",
+                "text": "Environmental Factors\n\nAs widespread use of genetic testing increases, it is the responsibility of the medical community to ensure its equitable use across socioeconomic and cultural spectrums."
+            },
+            {
+                "document_id": "93dc581e-5e45-48b4-b82f-35e32d7bd58e",
+                "section_type": "main",
+                "text": "\n\nPrenatal genetics is largely practiced by maternal-fetal medicine specialists due to severe deficiency in the number of qualified clinical geneticists.Recent years have witnessed a tremendous growth in the demand for chorionic villous sampling and amniocentesis for the diagnosis of single gene disorders.At KFSHRC alone, the number of prenatal samples that are tested for single gene disorders has increased from 5 in 2004 to 250 in 2013.Therapeutic abortion is permitted by law if performed within 120 days from the time of fertilization in order to comply with the Islamic view of the timing of ensoulment (Alkuraya and Kilani 2001).However, the approved indication for the procedure, which is \"severe malformation\", must be authorized by three attending-level physicians.The definition of \"severe\" is left to the discretion of the medical team after consulting with the family.For example, intellectual disability is a common indication for many therapeutic abortion procedures.Contrary to commonly held views, we have shown that early prenatal diagnosis is the method of choice for couples who had one or more children with single gene disorders, as long as they are provided with a culturally sensitive genetic counseling that addresses their religious and cultural concerns (Alkuraya and Kilani 2001).Nearly 45% of these couples opt for early prenatal diagnosis compared to 35% who choose preimplantation genetic diagnosis (PGD) (Alkuraya 2013a).PGD is available freely at KFSHRC but is also provided by the private sector.Noninvasive prenatal screening using cell-free fetal DNA in maternal blood is quickly becoming integrated in prenatal care.KFSHRC offers this test routinely to all pregnant women regardless of their perceived risk and the MOH is considering making this test available throughout its vast network of hospitals and medical centers."
+            },
+            {
+                "document_id": "9f21007a-1487-46d8-8e9e-cde8df4af6d5",
+                "section_type": "main",
+                "text": "\n\nSocial and psychological implications of accessing genetic services and information."
+            },
+            {
+                "document_id": "a4b0655d-895c-4368-9401-ee2903b15d42",
+                "section_type": "main",
+                "text": "\n\nA corollary of the predictive power of genetic information is the limited ability to prevent or treat many conditions with significant genetic factors involved.Indeed, virtually all of the complex ethical and legal issues relevant to genetic testing would disappear if there were effective preventions or treatments available for genetic conditions.The ability to predict future disease in conjunction with a limited ability to do much about it has important social and psychological implications that must be addressed in conducting genetic research."
+            },
+            {
+                "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                "section_type": "main",
+                "text": "\n\nWhat limits should be imposed, if any, need to be determined prior to commercial feasibility.In this article, we consider how genetic testing decisions for children have been made traditionally and how the anticipation of comprehensive genomic testing in the near future will stress the fault lines of traditional approaches.The potential for comprehensive genomic testing in children could shift the equilibrium towards expanding or reducing parental discretion, and forces us to reexamine the evidence for our genetic testing policies and practices.We will highlight specific domains where further empirical social and behavioral research is necessary to inform policy and practice."
+            },
+            {
+                "document_id": "b0b60080-2338-411b-bc44-1f5626a3c442",
+                "section_type": "main",
+                "text": "\n\nInterpretations of the literature will likely mirror the priorities and evaluative tendencies of the reader.Are you willing to accept the overall trends in genetic and genomic testing evaluation and to trust that the existing clinical approaches will apply informed consent appropriately while identifying and supporting the rare individual who has a serious adverse response to the testing?If so, you might advocate that attention be turned more toward other issues relevant to the effective implementation of genetic and genomic testing.Or do you feel a strong need to understand in more detail the possible psychosocial harms of the testing, particularly the subtler impacts or responses of individuals who do not fit the norm?In that case, you would likely encourage renewed and innovative efforts to study the psychosocial consequences of the receipt of risk information from genetic and genomic testing."
+            },
+            {
+                "document_id": "f7fe5d02-ee7c-4ec2-b6c4-ca9aa5efb41f",
+                "section_type": "main",
+                "text": "\n\nOther social issues require our attention if genomic medicine is to benefit our patients.How should genetic tests be regulated?What, if any, are the appropriate uses of direct-to-consumer marketing of genetic tests?The Internet has recently had a proliferation of genetic-testing sites that feature claims grounded in greed and pseudoscience, rather than in data or reality.How will health care providers and the public distinguish between these and responsible testing services, whether they are available through the Internet or in the hospital?"
+            },
+            {
+                "document_id": "56cf7be3-8c73-498d-b48f-8d99592b0213",
+                "section_type": "main",
+                "text": "The use of genetic testing from pre-conception through adulthood is expanding rapidly. Psychological risks for parents who are carriers may include parental guilt."
+            },
+            {
+                "document_id": "3992d979-8089-49a5-b0f1-84d04eaf79ad",
+                "section_type": "main",
+                "text": "\n\nAttitudes Toward Genetics Research and Testing"
+            },
+            {
+                "document_id": "a4e27158-1e54-4ee2-9cc1-049489a628bc",
+                "section_type": "main",
+                "text": "Return of Genetic Results to an Individual or Family\n\nOne of the most pertinent ethical challenges in genomics care and research relates to whether, when and which genetic results ought to be fed back to patients or research participants.In section 3.1 some considerations about the consent process in relation to incidental findings are detailed and this issue in relation to governance is addressed.The ongoing development of genomic tools has led to a significant decrease in the cost of running large diagnostic and research platforms resulting in the generation of a large volume of data for each individual, including potentially important clinical information about susceptibility to selected conditions that were not originally screened for (in the case of a diagnostic test) or investigated (in the case of research).The question is whether and when such unsolicited results should be shared with patients and participants."
+            },
+            {
+                "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                "section_type": "main",
+                "text": "\n\nThere is also a more fundamental criticism towards these normative claims against pediatric genetic testing.Both deviate from the moral position that parents should have the authority to decide which medical interventions are appropriate for their children (McConkie-Rosell & Spiridigliozzi, 2004;Pelias, 2006;Rhodes, 2006;Robertson & Savulescu, 2001).It is not necessary to argue that parental authority is limitless or unconstrained for this consideration to gain moral traction; it is only necessary to show that genetic testing is consistent with the types of health care decisions that typically belong to parents (Ross, 1998).Further, respecting parental authority does not imply that providers should refrain from making explicit directive recommendations to parents about health care decisions."
+            },
+            {
+                "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                "section_type": "main",
+                "text": "Conclusion\n\nWhile it is important to acknowledge potential harms when developing policy, one of the lessons of our recent genetic testing social history is that it has been neither the ''best of times, nor the worst of times. ''To date, the positive impact on population-based clinical practice has been less than imagined, but many concerns about adverse sideeffects have also turned out to be overstated.Respect for parental decision-making implies that the primary justification to restrict parents from obtaining genomic data would be that the harms clearly outweigh the benefits.Given that such data are lacking, the presumption should be to respect parental discretion.Parents will need advice and guidance about the potential benefits and limitations of such information, and health care providers should be proactive about engaging parents in these discussions."
+            },
+            {
+                "document_id": "9f21007a-1487-46d8-8e9e-cde8df4af6d5",
+                "section_type": "main",
+                "text": "\n\nPsychosocial issues and impact of genetic/genomic information on individual and the family (such as emotional distress, discrimination)."
+            },
+            {
+                "document_id": "1f5f2923-ca25-496c-b70e-5d15825c5575",
+                "section_type": "main",
+                "text": "\n\nA number of professional healthcare organizations have voiced concern about the clinical validity and the clinical utility of PG and PGM testing 12,26,27 and have developed position statements on DTC marketing that address the performance characteristics of the tests and the ethical, legal, and social implications (ELSI) of these technologies.Overall, there is broad agreement among the organizations that companies offering DTC PG and PGM testing should comply with existing practice and ethical standards of genetic testing.All agree that basic elements of informed consent for predisposition testing should include:"
+            },
+            {
+                "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                "section_type": "main",
+                "text": "Ethical Considerations for Comprehensive Genomic Testing in Children\n\nOnce testing an individual's entire genome becomes feasible, interest in using this technology with children can be anticipated.There are already proposals, based primarily on technical feasibility and potential public interest, for expanding NBS to include conditions for which early and effective treatments are not yet available (Alexander & van Dyck, 2006).Health-related information from comprehensive genomic testing in children raises the same concerns about clinical benefits and risks that have been associated with ''traditional'' genetic testing.However, the range of health information will be much broader and will include information about adult onset conditions and carrier status.The concerns about how parents will use this information and how it will impact children's self-identity, selfconcept, social and behavioral functioning, and lifestyle choices need to be empirically studied.Child health psychologists, in particular, have much to contribute to this process in light of their background and training in child development, clinical assessment, and the relationship between health and behavior."
+            },
+            {
+                "document_id": "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa",
+                "section_type": "main",
+                "text": "Clinical, Social, and Ethical Implications\n\nThere are 2 methods by which genetic testing can occur: specific gene sequencing or genotyping arranged by providers for patients with clinical diagnoses for which the likelihood of a genetic cause is high (ie, risk prediction) or for patients for whom the appropriateness of a specific treatment is being evaluated (ie, pharmacogenetics), and direct-toconsumer genome-wide SNP genotyping services.In either case, although there may be no immediate physical harm for a patient in undergoing genetic testing, which typically involves only swabbing of the inside of a cheek, collection of saliva, or drawing of a blood sample, there are important long-term consequences to consider.Specific gene testing often occurs at the discretion of the provider rather than the patient (although it should not occur without the patient's permission).Such testing may be informative because the presence of particular mutations may have diagnostic and therapeutic implications.For example, the finding of a BRCA1 or BRCA2 mutation that indicates increased risk of breast cancer may result in a management plan (made jointly by the provider and patient) in which the patient chooses to undergo prophylactic mastectomy.The finding of a mutation that augurs heightened risk of sudden cardiac death in a cardiomyopathy patient may result in the provider and patient opting for the placement of an implantable cardioverter-defibrillator.Typically, these sorts of decisions are driven by the presence of mutations that, on the basis of prior research, are likely to have large clinical effects.However, this is not always the case, and the premature use of a genetic test may carry risks.In 1 example, a company marketed a test for a variant in the KIF6 gene that initial research studies had found to predict patient response to statin therapy.Many providers used the test, presumably to help decide whether to prescribe statins to patients.Subsequent larger studies failed to replicate the KIF6 association with statin response, undermining the validity of the indication for the marketed test and suggesting that use of the test may have adversely affected patient management (if a provider had chosen not to prescribe a statin to a patient who otherwise met guidelines for statin therapy)."
+            },
+            {
+                "document_id": "df1cc001-06bb-4070-84ed-dc48d12395fc",
+                "section_type": "main",
+                "text": "\n\nIn clinical practice, genetic tests based on the ana lysis of genetic material (typically chromosomes, DNA or RNA) are carried out in the context of: diagnostic testing for genetic conditions, carrier testing for autosomal or X-linked recessive conditions and presymptomatic testing for autosomal dominant conditions.In addition, prenatal diagnosis of a fetus at risk of a genetic condition is available for many disorders.It is strongly recommended that appropriate counseling accompanies all such testing to enable patients to make informed decisions about whether to accept or decline such a test.For example, the European guidelines for presymptomatic testing developed as part of the EuroGentest project [5] emphasize the need for pre-and post-test counseling by trained health professionals to enable patients to determine whether the test is appropriate for them in the context of their own beliefs, values and lifestyle.European guidance on prenatal testing [9] includes the same requirements.To achieve this, an individualized approach to each patient is required.However, an ethical question can be raised by this requirement; if a patient does not wish to have counseling, is this simply an expression of their individual choice and should the health professional insist?Patients may feel that they have given sufficient thought to the decision over years or even decades [10], while the health professional who is offering an intervention in the form of a test has a responsibility to ensure as far as possible (within the boundaries of professional practice) that the intervention PersPective Skirton, Jackson, Goldsmith & O'Connor causes no harm to the patient [11].While the need for informed consent is paramount in the health professional's perception of ethical practice, evidence suggests that the public place more emphasis on the access to appropriate information [12], which is of course one component (alongside voluntariness and capacity of the patient to make a decision) of informed consent [13].This does, however, emphasize the expectation of patients that health professionals are knowledgeable about both genetic and genomic testing offered within the health service [14,15], and they may also expect them to understand health-related tests offered by private companies."
+            },
+            {
+                "document_id": "35e7b535-f3ed-4de4-a323-f1880a5873c2",
+                "section_type": "main",
+                "text": "\n\nIn addition to considering the effectiveness and the cost-effectiveness of stratified-screening programs, there are additional organizational, ethical, legal and social considerations before risk-tailored screening can be translated into policy and practice.It is not known how the public and professionals will respond to genetic testing.Would it be acceptable to health professionals, policy-makers and the public to have eligibility for screening based on absolute risk that is dependent on genetic profile in addition to age and possibly other environmental and lifestyle risk factors?Would it be acceptable to offer more sensitive and more expensive screening technology, such as MRI, instead of mammography for breast cancer screening, to those at high risk?How would the workforce be trained to understand genetic profiles and to communicate the test results and the management options effectively to the patients?A major organizational challenge will be to incorporate the advances of the rapidly evolving fields of genomics and the changes in environmental and lifestyle risk factors over an individual's lifetime into a dynamic risk estimation tool.How would the professionals organizing the screening programs and the public react to changing a bsolute risk levels? (HEALTH-F2-2009-223175).The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials d iscussed in the manuscript apart from those disclosed."
+            },
+            {
+                "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                "section_type": "main",
+                "text": "\n\nThere is also an inconsistency between the restrictions regarding genetic testing of children and the policies permitting prenatal testing for these same conditions.Although parents are discouraged from testing their young children for adult onset conditions, pregnant women are allowed to test their fetus, and providers may be reluctant to discourage them from doing so out of respect for reproductive freedom.In the prenatal context, providers are traditionally ''nondirective'' and ''offer options,'' rather than explicitly recommending which tests to undergo, or what actions to take based on the results.Consider, then, an expectant couple who seeks prenatal testing for Huntington disease (HD; an autosomal dominant cause of early-onset dementia) because one partner carries the gene associated with HD.Although it was historically assumed that parents would test a fetus for a condition like HD and then terminate an affected pregnancy (International Huntington Association [IHA] and the World Federation of Neurology [WFN] Research Group on Huntington's Chorea, 1994), a small number of parents do not terminate at-risk fetuses (Simpson et al., 2002).In light of current pediatric practice that proscribes testing of children, prenatal testing is the only option for parents who really want to know if their child has inherited the risk for HD, even though the medical risks of amniocentesis are greater (and therefore less desirable) than collecting a blood sample from a small child."
+            },
+            {
+                "document_id": "56cf7be3-8c73-498d-b48f-8d99592b0213",
+                "section_type": "main",
+                "text": "\n\nFurthermore, many genetic conditions are still difficult to treat or prevent, which means that the information gained from newborn screening may be of limited value in terms of treatment.Given these concerns, the American Academy of Pediatrics ( 2001) noted \"detailed counseling, informed consent and confidentiality should be key aspects of the genetic testing process, particularly when the benefits are uncertain\" (p.2)."
+            },
+            {
+                "document_id": "b0b60080-2338-411b-bc44-1f5626a3c442",
+                "section_type": "main",
+                "text": "\n\nA different interpretation of the systematic reviews would likely encourage more research on psychosocial impacts of genetic and genomic testing.One could argue that it is risky to overgeneralize given the many limitations to the evidence base.Furthermore, there are enough data showing that people are influenced by such testing, even if more subtly than is detected with many general, validated measures, to justify concern that we may be missing important implications of applied genetic and genomic testing.These factors might be revealed with broader use of qualitative methods, improved condition-specific measures in quantitative studies, greater attention to diverse study samples, and efforts to understand subpopulations or outliers who might be at higher risk."
+            },
+            {
+                "document_id": "f6baaabe-5856-4be5-8fe5-cd2b935ebacf",
+                "section_type": "main",
+                "text": "\n\nEthically, it is not reasonable to screen for certain genetic diseases while being unable to treat or effectively manage already diagnosed patients.A targeted screening and prevention strategy toward high-risk families at risk to have another affected child can be adopted to avoid this possible fact."
+            },
+            {
+                "document_id": "a4e27158-1e54-4ee2-9cc1-049489a628bc",
+                "section_type": "main",
+                "text": "\n\nOn the other hand, from a legal and ethical point of view information that could influence an individual's health or alter the course of a disease should not be withheld.In an under-resourced setting, however, the feeding back of an incidental genomic diagnosis with specific health implications to an individual who does not have access to relevant health care services to treat such a condition further seems unethical.Where possible however, steps could for example be taken around career and family planning.In contrast to the situation where genomic information may have positive health benefits to those who have access to treatment, the same information will not be helpful to those who do not, and may create anxiety and result in social ostracism and stigmatisation and therefore affect their quality of life negatively.The inclusion of a question in the consent form that requires participants to indicate whether they wish to be informed of incidental findings needs to be debated (De Vries et al., 2012aVries et al., , 2012b))."
+            },
+            {
+                "document_id": "b0b60080-2338-411b-bc44-1f5626a3c442",
+                "section_type": "main",
+                "text": "General Considerations for Assessing the Psychosocial Impacts\n\nG enetic and genomic applications are diverse, and generalizing about the psychosocial harms of testing in these areas is challenging.At least four interrelated factors about genetic and genomic testing must be understood.The first regards the characteristics of the genetic variants themselves, including penetrance (the likelihood of developing a health condition when the variant is present) and expressivity (the range of severity in the health outcome when the variant is present).These bear on what risk information would be conveyed"
+            },
+            {
+                "document_id": "56cf7be3-8c73-498d-b48f-8d99592b0213",
+                "section_type": "main",
+                "text": "Preventing Genetic Discrimination\n\nGenetic discrimination was identified early on in the Human Genome Project by the Ethical, Legal, and Social Implications program at the National Human Genome Research Institute as an ethical issue that needed to be addressed before the benefits of the Human Genome Project could be fully implemented.Although many are hopeful about the use of genetic information to improve health and combat disease, many are concerned about the potential for misuse, involving, for example, insurance and employment discrimination.Individual concerns include worries that genetic information may be used to deny or limit insurance coverage or to determine who is hired or fired.There is concern voiced that some insurers may choose not to insure people who are healthy but genetically pre-disposed to future disease onset (National Human Genome Research Institute, 2007)."
+            },
+            {
+                "document_id": "f051ad23-572d-4302-8dda-4d992aeaeb1a",
+                "section_type": "main",
+                "text": "\n\nGenetic testing is now used in prenatal, pediatric, and adult populations.Prenatal genetic testing is used to screen for and diagnose genetic conditions, such as Down syndrome.Carrier testing helps to identify people who carry one copy of a gene mutation that, when present in two copies, causes a genetic disorder, such as cystic fibrosis.Carrier testing is offered to people who come from certain ethnic groups that have an increased risk of specific genetic disorders, such as Tay-Sachs disease among Ashkenazi Jewish populations.When both parents are tested, the test gives information about a couple's chance of having a child with a genetic disorder (GHR, 2008n)."
+            },
+            {
+                "document_id": "68c109d7-cfef-4a50-8f22-f0b16a5cb52c",
+                "section_type": "main",
+                "text": "\n\nGenetic diseases are sometimes shocking and may cause substantial disability and even death in infant [27].The prenatal finding of genetic diseases permits parents to take choices about whether to continue with the pregnancy, or to permit initial diagnosis and probable treatment in utero or at birth.Whereas earlier methods to prenatal diagnosis could place the pregnancy at danger, new approaches utilizing genomic technology can aspect directly at the DNA of the fetus from a motherly body fluid test, without growing the risk of miscarriage."
+            },
+            {
+                "document_id": "936ddcae-95ca-496a-9ef0-182a6aa62a33",
+                "section_type": "main",
+                "text": "incidental findings in children\n\n4][25] However, these recommendations can be inconsistent with the general practice of respecting parental decision making about their children's health, and questions have been raised about the sustainability of these standards in an era of comprehensive genomic testing. 26One of these recent policy statements noted \"results from genetic testing of a child may have implications for the parents and other family members.Health-care providers have an obligation to inform parents and the child, when appropriate, about these potential implications.\" 24 This statement suggests an important consideration in the era of genomic medicine because after sequencing a child for a primary indication it becomes relatively easy for a laboratory to report a limited number of variants for conditions that could be medically important to that child's future or to the rest of the family."
+            }
+        ],
+        "document_id": "F7FF28704C5239FB329F508530F982CC",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "Tay-Sachs&disease",
+            "glutaric&aciduria&type&1",
+            "Ashkenazi&Jewish",
+            "Amish",
+            "Down&syndrome",
+            "SMA",
+            "PGD",
+            "KFSHRC",
+            "Genetic&Information&Nondiscrimination&Act",
+            "Islamic"
+        ],
+        "metadata": [
+            {
+                "object": "we describe patients with craniosynostosis and Noonan syndrome due to de novo mutations in PTPN11 and patients with craniosynostosis and CFC syndrome due to de novo mutations in BRAF or KRAS. All of these patients had cranial deformities in addition to the typical phenotypes of CFC syndrome and Noonan syndrome.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab1002469"
+            },
+            {
+                "object": "Gain-of-function mutations in the PCNA domain of CDKN1C have been reported as the genetic basis of various growth-retarded syndromes including IMAGe syndrome, Russell Silver syndrome as well as a novel undergrowth syndrome that additionally exhibited early adulthood onset diabetes. {review]",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab310461"
+            },
+            {
+                "object": "analysis of SALL4 defects and associated syndromes including Okihiro syndrome Duane-radial ray syndrome, acro-renal-ocular syndrome and description of the clinical distinctions with similar phenotypes caused by other gene defects",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab69830"
+            },
+            {
+                "object": "we describe the phenotype of a patient with Varadi syndrome who is homozygous for a previously reported mutation in TCTN1 NM_001082538.2:c.342-2A>G, p.Gly115Lysfs*8 and suggest that allelic disorders linked to TCTN1 include Varadi syndrome, in addition to Joubert syndrome and Meckel-Gruber syndrome.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab1002562"
+            },
+            {
+                "object": "We identified a HUWE1 mutation in an affected male with Juberg-Marsidi and Brooks syndromes from the original family reported by Juberg and Marsidi; it is evident the syndrome does not result from a mutation in ATRX as reported in the literature. Additionally, the data indicated that Juberg-Marsidi syndrome and Brooks syndromes are allelic having the same HUWE1 mutation.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab1007295"
+            },
+            {
+                "object": "The dermatological features of Costello syndrome, a Ras dysregulation syndrome, share many features with cutaneous paraneoplastic syndromes. This may provide further insight into the role of Ras signalling in cutaneous paraneoplastic syndromes.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab800527"
+            },
+            {
+                "object": "The BCSIL gene mutation is responsible for GRACILE syndrome, Bjornstad syndrome and complex III deficiency. Bjomstad syndrome is characterized by sensorineural hearing loss and abnormal flat twisted hair shafts. The case is GRACILE syndrome with Bjomstad phenotype in neonatal period due to BCSL1 gene mutation.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab785878"
+            },
+            {
+                "object": "We suggest that patients with Perrault syndrome are screened for variants in RMND1 along side the known Perrault syndrome genes.Renal phenotypes in women with Perrault syndrome features may indicate the causative variant is in RMND1 but the absence of renal dysfunction should not preclude RMND1 screening",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab1014038"
+            },
+            {
+                "object": "Three Smad genes, sma-2, sma-3 and sma-4, are all required for signal transduction, suggesting that the functional complex could be a heterotrimer.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab954432"
+            },
+            {
+                "object": "CHD7 mutations have also been found in some patients with Kallmann syndrome, hypogonadotrophic hypogonadism, and anosmia, and we discuss the overlap between this syndrome and CHARGE syndrome.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab137452"
+            }
+        ],
+        "question": "What are the ethical considerations surrounding prenatal genetic testing and the selective termination of pregnancies based on genetic factors?",
+        "subquestions": null,
+        "task_id": "F7FF28704C5239FB329F508530F982CC",
+        "usage": {
+            "chatgpt": 6791,
+            "gpt-4": 4502,
+            "gpt-4-turbo-preview": 3567
+        },
+        "user_id": 2
+    },
+    "document_id": "F7FF28704C5239FB329F508530F982CC",
+    "task_id": "F7FF28704C5239FB329F508530F982CC"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/05.json b/gnqa/paper1_eval/src/data/responses/general/experts/05.json
new file mode 100644
index 0000000..e4a5968
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/05.json
@@ -0,0 +1,396 @@
+{
+    "created_at": "2024-06-01T14:26:03.986157Z",
+    "data": {
+        "amplify": false,
+        "answer": "The potential benefits of gene editing technologies like CRISPR-Cas9 include the ability to modify genes for the treatment of diseases, improvement of crop species, and the development of personalized drug or cell therapies. It can also be used for functional screening in the development of therapies and for the study of molecular causes of ageing. However, there are risks associated with these technologies. These include off-target effects, which can lead to unwanted mutations, and the potential for wide-ranging deletions or recombination events. There's also a risk of triggering a P53 response leading to apoptosis in cycling cells, and the potential for subjects to generate antibodies to Cas9, which could limit gene therapies. Furthermore, the long-term safety of CRISPR genome editing in humans is yet to be determined.",
+        "context": {
+            "03110c8a-1232-40c2-8380-c9feb8b6468c": [
+                {
+                    "document_id": "03110c8a-1232-40c2-8380-c9feb8b6468c",
+                    "text": "\n\nGene editing has gained considerable interest with the identification of the CRISPR-Cas9 system, 27 which allows for a targeted modification in the DNA sequence of an organism.Researchers can utilize their knowledge of the basic biology of the gene and its protein function to precisely change the DNA sequence, thus altering the protein function of the gene and allowing for edits to stay within the species.Researchers at the University of Missouri used the CRISPR-Cas9 system to modify the CD163 gene such that the PRRS virus is not able to replicate inside the pig. 28This slight modification of the swine genome through gene editing keeps the pigs from succumbing to PRRS which has an annual estimated loss to the United States swine industry of over $660 million per year.Despite this benefit, given the public's concerns over food safety, it is likely that approval for such technology is years away in the US, Canada and Europe.However, in some cultures, there is a wide range of non-livestock species that are consumed.Therefore, it is conceivable that these countries and cultures may be open to transgenic/gene edited livestock.They may see the importance of useful gene editing which may lead to approval and consumption of reasonable genetically edited animal products such as those with modifications that are already found in nature or those that offer a substantial welfare benefit to society."
+                }
+            ],
+            "1942712a-a39d-44f7-9b2d-609926374cbd": [
+                {
+                    "document_id": "1942712a-a39d-44f7-9b2d-609926374cbd",
+                    "text": "\n\nAs a researcher who has devoted an entire career since 1994 to the development of genome editing tools and methods, I have been amazed by the rapid progress in the field over the last few years.Considering the widespread use of the tools, I am sure that the pace will continue to accelerate.Indeed, programmable nucleases, may eventually enable humans-products of evolution-to become masters of evolution.delivered preassembled recombinant Cas9-guide RNA ribonucleoproteins (RNPs) into animal embryos 6,9 and plant 11 and mammalian cells [73][74][75] .Indeed, Cas9 RNPs were rapidly turned over in cells 73 , reducing off-target effects and mosaicism in gene-edited organisms 11 .Cas9 RNPs can be delivered into cells by various methods, including microinjection 6,9 , electroporation 73 , lipofection 74 and protein transduction 75 .Importantly-and unlike in conventional gene therapy, where therapeutic genes are delivered via plasmids or viral vectors-Cas9 RNP delivery does not involve the use of exogenous DNA; host innate immune responses against foreign DNA are not elicited, and undesired integration of foreign DNA into the host genome is avoided."
+                }
+            ],
+            "33f1abde-a821-483b-b8b4-785f499db09d": [
+                {
+                    "document_id": "33f1abde-a821-483b-b8b4-785f499db09d",
+                    "text": "\n\nIn comparison to a transgenic approach, a gene editing technique such as CRISPR-Cas9 offers the advantage that gene-edited crops are not considered genetically modified organism (GMO) in some countries, such as the US, where the demand for natural food colorants such as anthocyanins is high.Indeed, the use of GMO crops as a source of natural pigments may be inconsistent with consumer interests.However, carrot cultivars engineered with either the transgenic or gene editing approach have not been reported so far, but their development is possible."
+                }
+            ],
+            "4f709611-ea0b-4bcc-a634-df5d518ccb54": [
+                {
+                    "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                    "text": "\n\nThe notable accuracy and versatility of CRISPR-Cas for genome editing also opened the door to its use in preclinical and translational settings.In the latter case, CRISPR in vivo gene editing has led to several proof-of-concept studies that would have been unachievable without it, as in the first ever correction of inherited pathogenic mutations linked to degenerative disease in a living organism [22] and even shown to be possible in human embryos [23,24].It also has great potential in the field of precision medicine as large-scale population DNA sequencing studies have provided vast amounts of information linking particular diseases with specific genetic mutations which could, in theory, be targeted through CRISPR [25,26].This could be used during the identification and validation of potential DNA targets during the development of personalised drug or cell therapies, which will require the generation of engineered cell lines and/or animal models.Techniques such as HDR-mediated gene targeting are too labour intensive, with low targeting efficiencies and long times necessary for their establishment, and consequently are not ideally suited for drug discovery purposes.Conversely, CRISPR-Cas has been proven to be efficient for editing virtually any kind of cell line, from primary immune cells to induced pluripotent stem cells (iPSCs) [27,28].Additionally, CRISPR can also be used for functional screening in the development of combined inhibitory therapy aimed at strengthening the efficiency of targeted therapeutics.An example of the latter is shown in a study where a variation of the technology known as CRISPR interference (CRISPRi) was used in genome-wide scale to identify different survival pathways used by cancer cells after oncogene inactivation and allowing the identification of successful combination therapies [29].In terms of translational applications, the overall safety of CRISPR genome editing in humans will require long-term scrutiny before its adoption in the clinic.Nonetheless, a number of CRISPR-based clinical trials are currently in progress, including studies focused on targeting patients' own T cells in order to improve the immune response towards some forms of malignant cancer [30,31], and others aimed at correcting pathogenic mutations in the hematopoietic cells of patients with beta-thalassemia and sickle cell disease [32]."
+                },
+                {
+                    "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                    "text": "Caveats and Ethical Concerns of CRISPR-Cas Applications\n\nDespite the presence of both a PAM sequence and a specific gRNA, the CRISPR-Cas9 system is not infallible.In fact, DSBs can occur at different sites in the genome, potentially causing so-called \"off-target\" effects.This eventuality remains to date the biggest concern in the field, as possible undesirable modifications must be properly identified and followed in order to guarantee safety for medical purposes.Nevertheless, there is still little evidence of the biological consequence of Cas9 off-target effects.Two recent studies describe new methods to investigate potential off-target effects in both mammals and plants [33,34].In both cases, whole-genome sequencing revealed that selective nucleotide changes, such as conversion of an adenine to a guanine, caused off-target occurrence very rarely, with a frequency comparable to the one of spontaneous mutations.However, substitution of a cytosine with a thymidine was linked to a sizable number of off-target mutations.This newly acquired information adds to the plethora of studies conducted on the safety of CRISPR, which altogether highlight the need for the establishment of clinical standards for the future use of genome-editing techniques in the clinic.Despite this and other technical challenges still ahead for CRISPR genome editing, the pace at which this technology has developed in recent years suggests many of these concerns could be addressed soon, as long as proper ethical guidelines and regulatory mechanisms are established."
+                },
+                {
+                    "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                    "text": "Conclusions\n\nThere is no reason to doubt that the development of CRISPR-Cas genome editing represents an unprecedented breakthrough in modern science, as it has potential applications in a wide array of disciplines ranging from agriculture, zoology and renewable energy to biomedicine and synthetic biology.This powerful tool holds promise for further elucidating the molecular causes of ageing by allowing scientists to probe genetic and epigenetic pathways with a level of sophistication that was unattainable just a few years ago.It will allow so in traditional animal and cell models of ageing, but it will also drastically accelerate the generation of refined versions of those models or even allow the development of new research approaches in non-model organisms.Moreover, CRISPR-based genome editing is already having a significant impact in research aiming to understand the cellular and molecular origins of age-related diseases, as well as developing potential treatments against them.The application of CRISPR-Cas gene editing for the treatment of age-related diseases is not over the horizon yet, as it will require the identification of causative genes and their role under a variety of contexts that could be as diverse as the ageing process is across individuals.However, CRISPR-Cas might also hold the key for solving such conundrum, as it has opened the way for achieving true personalised medicine by providing both the precision and scalability required for conducting genome-wide functional screens during the refinement of drug-and cell-based therapies for age-related diseases."
+                },
+                {
+                    "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                    "text": "\n\nSince its discovery, CRISPR-Cas technology has ignited a biological revolution by providing a highly versatile platform that allows fast and efficient genome editing in an ever-growing list of organisms.In this chapter we will first describe the most recent advances in the development and application of the CRISPR-Cas platform in biomedical research.Then we will discuss the most recent and notable basic research applications of this technology in the study of the molecular causes of ageing.Finally, we will review how CRISPR-Cas has been used for creating new models for the study of age-related diseases, as well as for manipulating diseaseassociated gene pathways."
+                }
+            ],
+            "50c72e55-b5fe-42a6-b837-64c28620a4c0": [
+                {
+                    "document_id": "50c72e55-b5fe-42a6-b837-64c28620a4c0",
+                    "text": "Caveats of advanced genome editing tools\n\nOff-target effects.The DNA-binding domains of ZFNs and TALENs need to be very specific for the target site to avoid off-target cleavage, which results in unwanted mutations and potentially cytotoxic effects [27].CRISPR/Cas9 is also known to generate off-target alterations, albeit apparently at low incidence [28,29], since mispairing is allowed between the guide RNA and the genomic DNA.Nonetheless, caution is required in their design and use.Some strategies involving the optimization of the guide RNA/Cas9 include using of software tools to predict potential off-target sites (http://omictools.com/crispr-cas9-Figure1: Genome editing methodologies which can be applied to human pluripotent stem cells.Homologous recombination (HR), or the more advanced tools such as zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) or clustered regularly interspaced short palindromic repeat (CRISPR)/Cas system can be applied to human pluripotent stem cells (hPSCs) either to 1) create naturally occurring mutations or 2) repair a mutation to generate isogenic controls in hPSCs, to understand the function of a gene of interest.c1268-p1.html),truncating the guide RNA (<20 nucleotides) to decrease off-target mutagenesis [30], lowering the dosage of guide RNA and Cas9 plasmids, and decreasing the number of mismatches between the guide RNA and the genomic DNA.A \"double nick\" system with Cas9 nickase, which contains a single inactive catalytic domain, may also be used [31e33]."
+                }
+            ],
+            "52480703-5353-4e55-a06b-110fd59db3a6": [
+                {
+                    "document_id": "52480703-5353-4e55-a06b-110fd59db3a6",
+                    "text": "CRISPR screening technologies\n\nThe discovery of CRISPR-Cas9 as a sequence-specific programmable nuclease democratized gene editing and fueled progress in forward genetic screening [20 , 66] .Genetic screens using Cas9 with a pooled singleguide RNA (sgRNA) library allow the interrogation of seemingly all genes in a genome in a single experiment [96 , 97] [null] .Engineered Cas9 variants further extend the versatility of forward genetic screening.Catalytically inactive Cas9 (dCas9) fused with chromatin effector domains permit specific activation (CRISPRa) or inhibition (CRISPRi) of gene expression [37 , 54] .Recently developed and emerging technologies -base editors, prime editors, and Cas transposases -are beginning to enable new types of genetic screens with directed, controlled, and on demand mutations by allowing the creation of user specified modifications, such as single base conversion, deletions, and insertions [4 , 42 , 58] ."
+                }
+            ],
+            "801c9288-70c9-4d14-b8bc-13ee6708803a": [
+                {
+                    "document_id": "801c9288-70c9-4d14-b8bc-13ee6708803a",
+                    "text": "\n\nComing on the heels of engineered nucleases, CRISPR-Cas9 tools have accelerated the pace of genomic research by permitting highly efficient knockouts or edits of virtually any gene in cells or model organisms.Multiple CRISPR-Cas9-based clinical trials are in progress or are expected to begin soon.Although Cas9engineered cells haven't yet demonstrated efficacy at scale, early trial results suggest that such cells are stable and don't cause acute adverse reactions in humans.Long-term safety is yet to be determined.Current applications largely focus on single-gene disorders for which gene editing can be carried out ex vivo on appropriate cells, such as bone marrow hematopoietic stem cells in the case of sickle cell anemia.Exploration is under way to develop delivery systems that can target the gene-editing apparatus to the appropriate tissue in vivo."
+                },
+                {
+                    "document_id": "801c9288-70c9-4d14-b8bc-13ee6708803a",
+                    "text": "\n\nOver the past 8 years, CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 (CRISPR-associated protein 9) technologies have emerged as accessible and adaptable tools for studying and altering genomes. 5RISPR-Cas9 can be used to induce genome edits by creating targeted DNA breaks that trigger site-specific DNA repair.In nextgeneration formats, it can also control the transcriptional output of genes or alter genome sequences using a process of nucleotide base editing that does not require repair of DNA breaks.As these technologies continue to mature, it will become increasingly possible to alter cellular genomes efficiently and accurately."
+                }
+            ],
+            "a7f21808-dce3-4110-8e7c-ceb2437e72ff": [
+                {
+                    "document_id": "a7f21808-dce3-4110-8e7c-ceb2437e72ff",
+                    "text": "\n\nThe type II CRISPR-Cas9 systems, repurposed from prokaryotic adaptive immune responses, are now widely used for targeted genome modifications in plants, animals, and human cells (Kim et al. 2014;Woo et al. 2015;Zuris et al. 2015).In particular, Cas9 nucleases have shown promise for gene and cell therapy (Maeder and Gersbach 2016).Typically, these nucleases are expressed or delivered in vivo using plasmid DNA or viruses (Yin et al. 2014;Ran et al. 2015).However, plasmid DNA delivery is often inefficient, especially in vivo, and can cause integration of small plasmid fragments degraded by endogenous nucleases at on-target and offtarget sites in the genome (Kim et al. 2014).Viral delivery of Cas9 can be highly efficient in vivo (Ran et al. 2015;Long et al. 2016;Nelson et al. 2016;Tabebordbar et al. 2016), but may be hampered by antibodies or T cells induced against the protein (Shankar et al. 2007;Calcedo et al. 2015;Chew et al. 2016).We and others have shown that preassembled Cas9 ribonucleoproteins (RNPs) can be delivered to human primary and stem cells and mice to modify target genes (Kim et al. 2014;Schumann et al. 2015;Zuris et al. 2015).Cas9 RNPs are rapidly turned over in cells, reducing off-target effects.Furthermore, Cas9 RNPs are unlikely to be limited by host immune systems because they function and disappear before the generation of antibodies and T cells directed against them.Currently, despite these advantages of RNPs, the difficult delivery of Cas9 RNPs in vivo limits its utility for therapeutic applications (Zuris et al. 2015).Here, we show that in vivo genome editing of an wild-type gene, whose up-regulation is responsible for pathogenesis, could be a new therapeutic modality for the treatment of nongenetic degenerative diseases.Our ultimate goal is to harness Cas9 RNPs for a clinical application of therapeutic genome surgery in patients with AMD."
+                }
+            ],
+            "ac00c552-7514-49d4-9e90-ab01c22472ae": [
+                {
+                    "document_id": "ac00c552-7514-49d4-9e90-ab01c22472ae",
+                    "text": "\n\nClustered regularly interspaced short palindromic repeat (CRISPR)-Cas nucleases have revolutionized the field of gene editing and have tremendous application in the field of molecular medicine [98][99][100][101][102].Despite a significant surge in CRISPR/Cas9mediated genome editing in various disease models, the progress in the field of AD has lagged behind substantially.We believe that genome editing can significantly improve the development of AD models and also create novel opportunities for the development of the next generation precision targeted AD gene and stem cell therapies.Since there are several excellent review articles on CRISPR/Cas9-mediated genome editing, here we will limit our focus on select recent articles that are noteworthy.CRISPR/Cas9 system can be engineered to either activate transcription (gain-of-function) or achieve gene silencing (Loss-of-function).Dahlman et al. have developed a CRISPR-based system that uses catalytically active Cas9 and distinct single guide (sgRNA) constructs to activate and knockout different genes in the same cell [103].Konermann et al. have used structure-guided engineering of a CRISPR-Cas9 complex to mediate efficient transcriptional activation at endogenous genomic loci [104].Using crystallographic studies, they have engineered a combination of sgRNA2.0,NLS-dCas9-VP64 and MS2-p65-HSF1 to develop one of the most effective transcription activation system."
+                }
+            ],
+            "b72eb0d1-50e3-4def-94bc-abf77891f519": [
+                {
+                    "document_id": "b72eb0d1-50e3-4def-94bc-abf77891f519",
+                    "text": "Limitations of CRISPR-Cas9\n\nCRISPR provides a simple and easy tool not only for in vitro use but potentially also for in vivo genome editing.However, there are limitations and downsides to this approach.First, and despite considerable improvements in the technology, the risk of the offtarget effect remains and must be considered carefully.Second, DSB may lead to wide-ranging deletions or recombination events involving the on-target site (204).Third, in cycling cells, DNA double strand breaks caused by Cas9 cleavage may trigger a P53 response leading to apoptosis and enrichment for potentially oncogenic P53-deficient cells (205,206).Fourth, subjects may generate antibodies to Cas9, potentially limiting gene therapies (207,208)."
+                },
+                {
+                    "document_id": "b72eb0d1-50e3-4def-94bc-abf77891f519",
+                    "text": "\n\nGenome editing tools that target the desired genomic region and allow for variants to be altered (e.g. from risk to protective), or for more substantial changes to be made (e.g. the deletion of a longer stretch of DNA harbouring a number of variants) and can help to answer each of these questions.These technologies are evolving rapidly (Figure 1 and Table 2).The most recently developed of these, Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) technology, originally developed by Doudna, Charpentier and their colleagues (72,73) and Zhang and his colleagues (50) has become a widely used tool for this purpose.Engineered CRISPR/Cas9 technology uses a guide RNA (gRNA) to direct CRISPR-associated endonuclease (Cas) to the target DNA and generate a double strand DNA break.Correction of a mutation or variant in the target DNA sequence can then be carried out by homology-directed DNA repair (HDR) with a donor template.Since its discovery eight years ago, CRISPR technology has evolved quickly to be a critical part of the molecular biologist's toolbox."
+                }
+            ],
+            "c3ae2186-ef48-46a5-b214-dc944366df8f": [
+                {
+                    "document_id": "c3ae2186-ef48-46a5-b214-dc944366df8f",
+                    "text": "INTRODUCTION\n\nGenome editing technologies based on the clustered regularly interspaced short palindromic repeats (CRISPR)-associated endonuclease Cas9 enable rapid and efficient modification of endogenous genes in a variety of cell types, allowing for analysis of gene function in many organs in vivo.CRISPR-Cas9 induces DNA double strand breaks (DSBs) at single-guide RNA (sgRNA)-specific loci in the genome, which are repaired through either non-homologous end-joining (NHEJ) or homology-directed repair (HDR) pathways.While NHEJ introduces unpredictable pattern of insertion or deletion (indel) mutations, HDR directs a precise recombination event between a homologous DNA donor template and the damaged DNA site (Cong et al., 2013;Cox et al., 2015;Doudna and Charpentier, 2014;Heidenreich and Zhang, 2016;Jinek et al., 2012;Mali et al., 2013;Sander and Joung, 2014;Wang et al., 2013;Yang et al., 2013).Thus, HDR can be used to precisely introduce sequence insertions, deletions or mutations by encoding the desired changes in the donor template DNA."
+                }
+            ],
+            "d14e93b5-01de-4208-8255-baae7898a7bb": [
+                {
+                    "document_id": "d14e93b5-01de-4208-8255-baae7898a7bb",
+                    "text": "\nCRISPR technology has rapidly changed the face of biological research, such that precise genome editing has now become routine for many labs within several years of its initial development.What makes CRISPR/Cas9 so revolutionary is the ability to target a protein (Cas9) to an exact genomic locus, through designing a specific short complementary nucleotide sequence, that together with a common scaffold sequence, constitute the guide RNA bridging the protein and the DNA.Wild-type Cas9 cleaves both DNA strands at its target sequence, but this protein can also be modified to exert many other functions.For instance, by attaching an activation domain to catalytically inactive Cas9 and targeting a promoter region, it is possible to stimulate the expression of a specific endogenous gene.In principle, any genomic region can be targeted, and recent efforts have successfully generated pooled guide RNA libraries for coding and regulatory regions of human, mouse and Drosophila genomes with high coverage, thus facilitating functional phenotypic screening.In this review, we will highlight recent developments in the area of CRISPR-based functional genomics and discuss potential future directions, with a special focus on mammalian cell systems and arrayed library screening."
+                },
+                {
+                    "document_id": "d14e93b5-01de-4208-8255-baae7898a7bb",
+                    "text": "\n\nCRISPR technology has rapidly changed the face of biological research, such that precise genome editing has now become routine for many labs within several years of its initial development.What makes CRISPR/Cas9 so revolutionary is the ability to target a protein (Cas9) to an exact genomic locus, through designing a specific short complementary nucleotide sequence, that together with a common scaffold sequence, constitute the guide RNA bridging the protein and the DNA.Wild-type Cas9 cleaves both DNA strands at its target sequence, but this protein can also be modified to exert many other functions.For instance, by attaching an activation domain to catalytically inactive Cas9 and targeting a promoter region, it is possible to stimulate the expression of a specific endogenous gene.In principle, any genomic region can be targeted, and recent efforts have successfully generated pooled guide RNA libraries for coding and regulatory regions of human, mouse and Drosophila genomes with high coverage, thus facilitating functional phenotypic screening.In this review, we will highlight recent developments in the area of CRISPR-based functional genomics and discuss potential future directions, with a special focus on mammalian cell systems and arrayed library screening."
+                },
+                {
+                    "document_id": "d14e93b5-01de-4208-8255-baae7898a7bb",
+                    "text": "\n\nThe recent development of clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 for experimental purposes has dismantled the perception that genome editing technology is off-limits for screening in mammalian systems (Heintze et al., 2013).Since this system employs the basic principle of Watson-Crick base pairing for gene targeting, generation of libraries with whole-genome target coverage is relatively easy and cost-effective.For instance, simple protocols are available to synthesize pooled lentiviral libraries by in silico design of oligonucleotides, which can then be cloned, packaged and delivered to cells by viral transduction (Paddison et al., 2004;LeProust et al., 2010).Similarly, the generation of arrayed libraries can be achieved by following protocols originally developed for arrayed shRNA library production that have been in use for a number of years (Moffat et al., 2006).All in all, the stage is set for CRISPR to make an enormous impact on genomic screening and thus scientific discovery in the coming years, and recent demonstrations of this system have shown great promise (Shalem et al., 2015).However, a number of technical challenges must be addressed in order to maximize the benefit of this technology.In this review, we will discuss current applications of CRISPR in functional genomics and provide a perspective on future developments in this area."
+                }
+            ],
+            "e5cf067c-8be0-4b0a-b376-7882cdc9d96c": [
+                {
+                    "document_id": "e5cf067c-8be0-4b0a-b376-7882cdc9d96c",
+                    "text": "Genome editing for crop improvement\n\nReports of CRISPR-Cas9-based genome editing first appeared in 2013 (Cong et al., 2013;Feng et al., 2013;Mao et al., 2013).Since then, genome editing technologies have proven to be powerful and efficient tools for the improvement of many crop species.At present, genome editing has been widely used to introduce/modify agronomically important traits, such as increased yield, improved nutritional quality, and resistance to biotic and abiotic stresses, in multiple crops, including rice, wheat, maize, tomato, and potato (Lu et al., 2017;Soyk et al., 2017;Tang et al., 2017;D'Ambrosio et al., 2018;Ye et al., 2018;Miao et al., 2019;Zhang et al., 2019;Zhong et al., 2019;Butt et al., 2020;Zhang et al., 2020c;Li et al., 2021b;Zhan et al., 2021).CRISPR-Cas-based genome editing has been extended to targeted mutagenesis, base editing, and precisely targeted gene/allele replacement or tagging in plants.mportantly, using CRISPR-Cas9 technology, transgenes present in the genomes of genome-edited plants can be removed by chromosomal segregation via a simple self-pollination or hybridization step.Gene editing technologies continue to be developed and utilized (Mao et al., 2013;Lu and Zhu, 2017;Lu et al., 2020)."
+                }
+            ]
+        },
+        "data_source": [
+            {
+                "document_id": "b72eb0d1-50e3-4def-94bc-abf77891f519",
+                "section_type": "main",
+                "text": "Limitations of CRISPR-Cas9\n\nCRISPR provides a simple and easy tool not only for in vitro use but potentially also for in vivo genome editing.However, there are limitations and downsides to this approach.First, and despite considerable improvements in the technology, the risk of the offtarget effect remains and must be considered carefully.Second, DSB may lead to wide-ranging deletions or recombination events involving the on-target site (204).Third, in cycling cells, DNA double strand breaks caused by Cas9 cleavage may trigger a P53 response leading to apoptosis and enrichment for potentially oncogenic P53-deficient cells (205,206).Fourth, subjects may generate antibodies to Cas9, potentially limiting gene therapies (207,208)."
+            },
+            {
+                "document_id": "801c9288-70c9-4d14-b8bc-13ee6708803a",
+                "section_type": "main",
+                "text": "\n\nComing on the heels of engineered nucleases, CRISPR-Cas9 tools have accelerated the pace of genomic research by permitting highly efficient knockouts or edits of virtually any gene in cells or model organisms.Multiple CRISPR-Cas9-based clinical trials are in progress or are expected to begin soon.Although Cas9engineered cells haven't yet demonstrated efficacy at scale, early trial results suggest that such cells are stable and don't cause acute adverse reactions in humans.Long-term safety is yet to be determined.Current applications largely focus on single-gene disorders for which gene editing can be carried out ex vivo on appropriate cells, such as bone marrow hematopoietic stem cells in the case of sickle cell anemia.Exploration is under way to develop delivery systems that can target the gene-editing apparatus to the appropriate tissue in vivo."
+            },
+            {
+                "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                "section_type": "main",
+                "text": "Caveats and Ethical Concerns of CRISPR-Cas Applications\n\nDespite the presence of both a PAM sequence and a specific gRNA, the CRISPR-Cas9 system is not infallible.In fact, DSBs can occur at different sites in the genome, potentially causing so-called \"off-target\" effects.This eventuality remains to date the biggest concern in the field, as possible undesirable modifications must be properly identified and followed in order to guarantee safety for medical purposes.Nevertheless, there is still little evidence of the biological consequence of Cas9 off-target effects.Two recent studies describe new methods to investigate potential off-target effects in both mammals and plants [33,34].In both cases, whole-genome sequencing revealed that selective nucleotide changes, such as conversion of an adenine to a guanine, caused off-target occurrence very rarely, with a frequency comparable to the one of spontaneous mutations.However, substitution of a cytosine with a thymidine was linked to a sizable number of off-target mutations.This newly acquired information adds to the plethora of studies conducted on the safety of CRISPR, which altogether highlight the need for the establishment of clinical standards for the future use of genome-editing techniques in the clinic.Despite this and other technical challenges still ahead for CRISPR genome editing, the pace at which this technology has developed in recent years suggests many of these concerns could be addressed soon, as long as proper ethical guidelines and regulatory mechanisms are established."
+            },
+            {
+                "document_id": "03110c8a-1232-40c2-8380-c9feb8b6468c",
+                "section_type": "main",
+                "text": "\n\nGene editing has gained considerable interest with the identification of the CRISPR-Cas9 system, 27 which allows for a targeted modification in the DNA sequence of an organism.Researchers can utilize their knowledge of the basic biology of the gene and its protein function to precisely change the DNA sequence, thus altering the protein function of the gene and allowing for edits to stay within the species.Researchers at the University of Missouri used the CRISPR-Cas9 system to modify the CD163 gene such that the PRRS virus is not able to replicate inside the pig. 28This slight modification of the swine genome through gene editing keeps the pigs from succumbing to PRRS which has an annual estimated loss to the United States swine industry of over $660 million per year.Despite this benefit, given the public's concerns over food safety, it is likely that approval for such technology is years away in the US, Canada and Europe.However, in some cultures, there is a wide range of non-livestock species that are consumed.Therefore, it is conceivable that these countries and cultures may be open to transgenic/gene edited livestock.They may see the importance of useful gene editing which may lead to approval and consumption of reasonable genetically edited animal products such as those with modifications that are already found in nature or those that offer a substantial welfare benefit to society."
+            },
+            {
+                "document_id": "801c9288-70c9-4d14-b8bc-13ee6708803a",
+                "section_type": "main",
+                "text": "\n\nOver the past 8 years, CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 (CRISPR-associated protein 9) technologies have emerged as accessible and adaptable tools for studying and altering genomes. 5RISPR-Cas9 can be used to induce genome edits by creating targeted DNA breaks that trigger site-specific DNA repair.In nextgeneration formats, it can also control the transcriptional output of genes or alter genome sequences using a process of nucleotide base editing that does not require repair of DNA breaks.As these technologies continue to mature, it will become increasingly possible to alter cellular genomes efficiently and accurately."
+            },
+            {
+                "document_id": "ac00c552-7514-49d4-9e90-ab01c22472ae",
+                "section_type": "main",
+                "text": "\n\nClustered regularly interspaced short palindromic repeat (CRISPR)-Cas nucleases have revolutionized the field of gene editing and have tremendous application in the field of molecular medicine [98][99][100][101][102].Despite a significant surge in CRISPR/Cas9mediated genome editing in various disease models, the progress in the field of AD has lagged behind substantially.We believe that genome editing can significantly improve the development of AD models and also create novel opportunities for the development of the next generation precision targeted AD gene and stem cell therapies.Since there are several excellent review articles on CRISPR/Cas9-mediated genome editing, here we will limit our focus on select recent articles that are noteworthy.CRISPR/Cas9 system can be engineered to either activate transcription (gain-of-function) or achieve gene silencing (Loss-of-function).Dahlman et al. have developed a CRISPR-based system that uses catalytically active Cas9 and distinct single guide (sgRNA) constructs to activate and knockout different genes in the same cell [103].Konermann et al. have used structure-guided engineering of a CRISPR-Cas9 complex to mediate efficient transcriptional activation at endogenous genomic loci [104].Using crystallographic studies, they have engineered a combination of sgRNA2.0,NLS-dCas9-VP64 and MS2-p65-HSF1 to develop one of the most effective transcription activation system."
+            },
+            {
+                "document_id": "d14e93b5-01de-4208-8255-baae7898a7bb",
+                "section_type": "abstract",
+                "text": "\nCRISPR technology has rapidly changed the face of biological research, such that precise genome editing has now become routine for many labs within several years of its initial development.What makes CRISPR/Cas9 so revolutionary is the ability to target a protein (Cas9) to an exact genomic locus, through designing a specific short complementary nucleotide sequence, that together with a common scaffold sequence, constitute the guide RNA bridging the protein and the DNA.Wild-type Cas9 cleaves both DNA strands at its target sequence, but this protein can also be modified to exert many other functions.For instance, by attaching an activation domain to catalytically inactive Cas9 and targeting a promoter region, it is possible to stimulate the expression of a specific endogenous gene.In principle, any genomic region can be targeted, and recent efforts have successfully generated pooled guide RNA libraries for coding and regulatory regions of human, mouse and Drosophila genomes with high coverage, thus facilitating functional phenotypic screening.In this review, we will highlight recent developments in the area of CRISPR-based functional genomics and discuss potential future directions, with a special focus on mammalian cell systems and arrayed library screening."
+            },
+            {
+                "document_id": "d14e93b5-01de-4208-8255-baae7898a7bb",
+                "section_type": "main",
+                "text": "\n\nCRISPR technology has rapidly changed the face of biological research, such that precise genome editing has now become routine for many labs within several years of its initial development.What makes CRISPR/Cas9 so revolutionary is the ability to target a protein (Cas9) to an exact genomic locus, through designing a specific short complementary nucleotide sequence, that together with a common scaffold sequence, constitute the guide RNA bridging the protein and the DNA.Wild-type Cas9 cleaves both DNA strands at its target sequence, but this protein can also be modified to exert many other functions.For instance, by attaching an activation domain to catalytically inactive Cas9 and targeting a promoter region, it is possible to stimulate the expression of a specific endogenous gene.In principle, any genomic region can be targeted, and recent efforts have successfully generated pooled guide RNA libraries for coding and regulatory regions of human, mouse and Drosophila genomes with high coverage, thus facilitating functional phenotypic screening.In this review, we will highlight recent developments in the area of CRISPR-based functional genomics and discuss potential future directions, with a special focus on mammalian cell systems and arrayed library screening."
+            },
+            {
+                "document_id": "e5cf067c-8be0-4b0a-b376-7882cdc9d96c",
+                "section_type": "main",
+                "text": "Genome editing for crop improvement\n\nReports of CRISPR-Cas9-based genome editing first appeared in 2013 (Cong et al., 2013;Feng et al., 2013;Mao et al., 2013).Since then, genome editing technologies have proven to be powerful and efficient tools for the improvement of many crop species.At present, genome editing has been widely used to introduce/modify agronomically important traits, such as increased yield, improved nutritional quality, and resistance to biotic and abiotic stresses, in multiple crops, including rice, wheat, maize, tomato, and potato (Lu et al., 2017;Soyk et al., 2017;Tang et al., 2017;D'Ambrosio et al., 2018;Ye et al., 2018;Miao et al., 2019;Zhang et al., 2019;Zhong et al., 2019;Butt et al., 2020;Zhang et al., 2020c;Li et al., 2021b;Zhan et al., 2021).CRISPR-Cas-based genome editing has been extended to targeted mutagenesis, base editing, and precisely targeted gene/allele replacement or tagging in plants.mportantly, using CRISPR-Cas9 technology, transgenes present in the genomes of genome-edited plants can be removed by chromosomal segregation via a simple self-pollination or hybridization step.Gene editing technologies continue to be developed and utilized (Mao et al., 2013;Lu and Zhu, 2017;Lu et al., 2020)."
+            },
+            {
+                "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                "section_type": "main",
+                "text": "Conclusions\n\nThere is no reason to doubt that the development of CRISPR-Cas genome editing represents an unprecedented breakthrough in modern science, as it has potential applications in a wide array of disciplines ranging from agriculture, zoology and renewable energy to biomedicine and synthetic biology.This powerful tool holds promise for further elucidating the molecular causes of ageing by allowing scientists to probe genetic and epigenetic pathways with a level of sophistication that was unattainable just a few years ago.It will allow so in traditional animal and cell models of ageing, but it will also drastically accelerate the generation of refined versions of those models or even allow the development of new research approaches in non-model organisms.Moreover, CRISPR-based genome editing is already having a significant impact in research aiming to understand the cellular and molecular origins of age-related diseases, as well as developing potential treatments against them.The application of CRISPR-Cas gene editing for the treatment of age-related diseases is not over the horizon yet, as it will require the identification of causative genes and their role under a variety of contexts that could be as diverse as the ageing process is across individuals.However, CRISPR-Cas might also hold the key for solving such conundrum, as it has opened the way for achieving true personalised medicine by providing both the precision and scalability required for conducting genome-wide functional screens during the refinement of drug-and cell-based therapies for age-related diseases."
+            },
+            {
+                "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                "section_type": "main",
+                "text": "\n\nThe notable accuracy and versatility of CRISPR-Cas for genome editing also opened the door to its use in preclinical and translational settings.In the latter case, CRISPR in vivo gene editing has led to several proof-of-concept studies that would have been unachievable without it, as in the first ever correction of inherited pathogenic mutations linked to degenerative disease in a living organism [22] and even shown to be possible in human embryos [23,24].It also has great potential in the field of precision medicine as large-scale population DNA sequencing studies have provided vast amounts of information linking particular diseases with specific genetic mutations which could, in theory, be targeted through CRISPR [25,26].This could be used during the identification and validation of potential DNA targets during the development of personalised drug or cell therapies, which will require the generation of engineered cell lines and/or animal models.Techniques such as HDR-mediated gene targeting are too labour intensive, with low targeting efficiencies and long times necessary for their establishment, and consequently are not ideally suited for drug discovery purposes.Conversely, CRISPR-Cas has been proven to be efficient for editing virtually any kind of cell line, from primary immune cells to induced pluripotent stem cells (iPSCs) [27,28].Additionally, CRISPR can also be used for functional screening in the development of combined inhibitory therapy aimed at strengthening the efficiency of targeted therapeutics.An example of the latter is shown in a study where a variation of the technology known as CRISPR interference (CRISPRi) was used in genome-wide scale to identify different survival pathways used by cancer cells after oncogene inactivation and allowing the identification of successful combination therapies [29].In terms of translational applications, the overall safety of CRISPR genome editing in humans will require long-term scrutiny before its adoption in the clinic.Nonetheless, a number of CRISPR-based clinical trials are currently in progress, including studies focused on targeting patients' own T cells in order to improve the immune response towards some forms of malignant cancer [30,31], and others aimed at correcting pathogenic mutations in the hematopoietic cells of patients with beta-thalassemia and sickle cell disease [32]."
+            },
+            {
+                "document_id": "d14e93b5-01de-4208-8255-baae7898a7bb",
+                "section_type": "main",
+                "text": "\n\nThe recent development of clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 for experimental purposes has dismantled the perception that genome editing technology is off-limits for screening in mammalian systems (Heintze et al., 2013).Since this system employs the basic principle of Watson-Crick base pairing for gene targeting, generation of libraries with whole-genome target coverage is relatively easy and cost-effective.For instance, simple protocols are available to synthesize pooled lentiviral libraries by in silico design of oligonucleotides, which can then be cloned, packaged and delivered to cells by viral transduction (Paddison et al., 2004;LeProust et al., 2010).Similarly, the generation of arrayed libraries can be achieved by following protocols originally developed for arrayed shRNA library production that have been in use for a number of years (Moffat et al., 2006).All in all, the stage is set for CRISPR to make an enormous impact on genomic screening and thus scientific discovery in the coming years, and recent demonstrations of this system have shown great promise (Shalem et al., 2015).However, a number of technical challenges must be addressed in order to maximize the benefit of this technology.In this review, we will discuss current applications of CRISPR in functional genomics and provide a perspective on future developments in this area."
+            },
+            {
+                "document_id": "b72eb0d1-50e3-4def-94bc-abf77891f519",
+                "section_type": "main",
+                "text": "\n\nGenome editing tools that target the desired genomic region and allow for variants to be altered (e.g. from risk to protective), or for more substantial changes to be made (e.g. the deletion of a longer stretch of DNA harbouring a number of variants) and can help to answer each of these questions.These technologies are evolving rapidly (Figure 1 and Table 2).The most recently developed of these, Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) technology, originally developed by Doudna, Charpentier and their colleagues (72,73) and Zhang and his colleagues (50) has become a widely used tool for this purpose.Engineered CRISPR/Cas9 technology uses a guide RNA (gRNA) to direct CRISPR-associated endonuclease (Cas) to the target DNA and generate a double strand DNA break.Correction of a mutation or variant in the target DNA sequence can then be carried out by homology-directed DNA repair (HDR) with a donor template.Since its discovery eight years ago, CRISPR technology has evolved quickly to be a critical part of the molecular biologist's toolbox."
+            },
+            {
+                "document_id": "52480703-5353-4e55-a06b-110fd59db3a6",
+                "section_type": "main",
+                "text": "CRISPR screening technologies\n\nThe discovery of CRISPR-Cas9 as a sequence-specific programmable nuclease democratized gene editing and fueled progress in forward genetic screening [20 , 66] .Genetic screens using Cas9 with a pooled singleguide RNA (sgRNA) library allow the interrogation of seemingly all genes in a genome in a single experiment [96 , 97] [null] .Engineered Cas9 variants further extend the versatility of forward genetic screening.Catalytically inactive Cas9 (dCas9) fused with chromatin effector domains permit specific activation (CRISPRa) or inhibition (CRISPRi) of gene expression [37 , 54] .Recently developed and emerging technologies -base editors, prime editors, and Cas transposases -are beginning to enable new types of genetic screens with directed, controlled, and on demand mutations by allowing the creation of user specified modifications, such as single base conversion, deletions, and insertions [4 , 42 , 58] ."
+            },
+            {
+                "document_id": "c3ae2186-ef48-46a5-b214-dc944366df8f",
+                "section_type": "main",
+                "text": "INTRODUCTION\n\nGenome editing technologies based on the clustered regularly interspaced short palindromic repeats (CRISPR)-associated endonuclease Cas9 enable rapid and efficient modification of endogenous genes in a variety of cell types, allowing for analysis of gene function in many organs in vivo.CRISPR-Cas9 induces DNA double strand breaks (DSBs) at single-guide RNA (sgRNA)-specific loci in the genome, which are repaired through either non-homologous end-joining (NHEJ) or homology-directed repair (HDR) pathways.While NHEJ introduces unpredictable pattern of insertion or deletion (indel) mutations, HDR directs a precise recombination event between a homologous DNA donor template and the damaged DNA site (Cong et al., 2013;Cox et al., 2015;Doudna and Charpentier, 2014;Heidenreich and Zhang, 2016;Jinek et al., 2012;Mali et al., 2013;Sander and Joung, 2014;Wang et al., 2013;Yang et al., 2013).Thus, HDR can be used to precisely introduce sequence insertions, deletions or mutations by encoding the desired changes in the donor template DNA."
+            },
+            {
+                "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                "section_type": "main",
+                "text": "\n\nSince its discovery, CRISPR-Cas technology has ignited a biological revolution by providing a highly versatile platform that allows fast and efficient genome editing in an ever-growing list of organisms.In this chapter we will first describe the most recent advances in the development and application of the CRISPR-Cas platform in biomedical research.Then we will discuss the most recent and notable basic research applications of this technology in the study of the molecular causes of ageing.Finally, we will review how CRISPR-Cas has been used for creating new models for the study of age-related diseases, as well as for manipulating diseaseassociated gene pathways."
+            },
+            {
+                "document_id": "1942712a-a39d-44f7-9b2d-609926374cbd",
+                "section_type": "main",
+                "text": "\n\nAs a researcher who has devoted an entire career since 1994 to the development of genome editing tools and methods, I have been amazed by the rapid progress in the field over the last few years.Considering the widespread use of the tools, I am sure that the pace will continue to accelerate.Indeed, programmable nucleases, may eventually enable humans-products of evolution-to become masters of evolution.delivered preassembled recombinant Cas9-guide RNA ribonucleoproteins (RNPs) into animal embryos 6,9 and plant 11 and mammalian cells [73][74][75] .Indeed, Cas9 RNPs were rapidly turned over in cells 73 , reducing off-target effects and mosaicism in gene-edited organisms 11 .Cas9 RNPs can be delivered into cells by various methods, including microinjection 6,9 , electroporation 73 , lipofection 74 and protein transduction 75 .Importantly-and unlike in conventional gene therapy, where therapeutic genes are delivered via plasmids or viral vectors-Cas9 RNP delivery does not involve the use of exogenous DNA; host innate immune responses against foreign DNA are not elicited, and undesired integration of foreign DNA into the host genome is avoided."
+            },
+            {
+                "document_id": "50c72e55-b5fe-42a6-b837-64c28620a4c0",
+                "section_type": "main",
+                "text": "Caveats of advanced genome editing tools\n\nOff-target effects.The DNA-binding domains of ZFNs and TALENs need to be very specific for the target site to avoid off-target cleavage, which results in unwanted mutations and potentially cytotoxic effects [27].CRISPR/Cas9 is also known to generate off-target alterations, albeit apparently at low incidence [28,29], since mispairing is allowed between the guide RNA and the genomic DNA.Nonetheless, caution is required in their design and use.Some strategies involving the optimization of the guide RNA/Cas9 include using of software tools to predict potential off-target sites (http://omictools.com/crispr-cas9-Figure1: Genome editing methodologies which can be applied to human pluripotent stem cells.Homologous recombination (HR), or the more advanced tools such as zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) or clustered regularly interspaced short palindromic repeat (CRISPR)/Cas system can be applied to human pluripotent stem cells (hPSCs) either to 1) create naturally occurring mutations or 2) repair a mutation to generate isogenic controls in hPSCs, to understand the function of a gene of interest.c1268-p1.html),truncating the guide RNA (<20 nucleotides) to decrease off-target mutagenesis [30], lowering the dosage of guide RNA and Cas9 plasmids, and decreasing the number of mismatches between the guide RNA and the genomic DNA.A \"double nick\" system with Cas9 nickase, which contains a single inactive catalytic domain, may also be used [31e33]."
+            },
+            {
+                "document_id": "b72eb0d1-50e3-4def-94bc-abf77891f519",
+                "section_type": "main",
+                "text": "\n\nIn addition to gene knock-out and HDR repair, genome-wide pooled CRISPR-Cas9 libraries have been used to systematically delete genes responsible for diverse phenotypes.Recent studies have shown that such loss-of-function screens using libraries comprising tens of thousands of sgRNAs can be used to identify genes involved in tumour growth and metastasis (171).In the diabetes field, similar approaches have also been used recently to identify key insulin gene regulators (172) and the genes involving in auto-immune killing of b cell transplants (173).Screens based on transcriptional interference (CRISPRi) and activation (CRISPRa) have also harnessed Cas9-based technologies for use in genome-wide studies (59,174).In addition, recent improvements in lentiviral library generation and propagation, as well as large-scale DNA and RNA synthesis, have allowed CRISPR-Cas9 technology to be exploited across multiple model platforms (59,(175)(176)(177)(178)."
+            },
+            {
+                "document_id": "a7f21808-dce3-4110-8e7c-ceb2437e72ff",
+                "section_type": "main",
+                "text": "\n\nThe type II CRISPR-Cas9 systems, repurposed from prokaryotic adaptive immune responses, are now widely used for targeted genome modifications in plants, animals, and human cells (Kim et al. 2014;Woo et al. 2015;Zuris et al. 2015).In particular, Cas9 nucleases have shown promise for gene and cell therapy (Maeder and Gersbach 2016).Typically, these nucleases are expressed or delivered in vivo using plasmid DNA or viruses (Yin et al. 2014;Ran et al. 2015).However, plasmid DNA delivery is often inefficient, especially in vivo, and can cause integration of small plasmid fragments degraded by endogenous nucleases at on-target and offtarget sites in the genome (Kim et al. 2014).Viral delivery of Cas9 can be highly efficient in vivo (Ran et al. 2015;Long et al. 2016;Nelson et al. 2016;Tabebordbar et al. 2016), but may be hampered by antibodies or T cells induced against the protein (Shankar et al. 2007;Calcedo et al. 2015;Chew et al. 2016).We and others have shown that preassembled Cas9 ribonucleoproteins (RNPs) can be delivered to human primary and stem cells and mice to modify target genes (Kim et al. 2014;Schumann et al. 2015;Zuris et al. 2015).Cas9 RNPs are rapidly turned over in cells, reducing off-target effects.Furthermore, Cas9 RNPs are unlikely to be limited by host immune systems because they function and disappear before the generation of antibodies and T cells directed against them.Currently, despite these advantages of RNPs, the difficult delivery of Cas9 RNPs in vivo limits its utility for therapeutic applications (Zuris et al. 2015).Here, we show that in vivo genome editing of an wild-type gene, whose up-regulation is responsible for pathogenesis, could be a new therapeutic modality for the treatment of nongenetic degenerative diseases.Our ultimate goal is to harness Cas9 RNPs for a clinical application of therapeutic genome surgery in patients with AMD."
+            },
+            {
+                "document_id": "1942712a-a39d-44f7-9b2d-609926374cbd",
+                "section_type": "main",
+                "text": "Genome editing comes of age\n\nJin-Soo Kim 1,2 Genome editing harnesses programmable nucleases to cut and paste genetic information in a targeted manner in living cells and organisms.Here, I review the development of programmable nucleases, including zinc finger nucleases (ZFNs), TAL (transcription-activator-like) effector nucleases (TALENs) and CRISPR (cluster of regularly interspaced palindromic repeats)-Cas9 (CRISPR-associated protein 9) RNA-guided endonucleases (RGENs).I specifically highlight the key advances that set the foundation for the rapid and widespread implementation of CRISPR-Cas9 genome editing approaches that has revolutionized the field."
+            },
+            {
+                "document_id": "1942712a-a39d-44f7-9b2d-609926374cbd",
+                "section_type": "main",
+                "text": "\n\nThe ability to genetically modify living cells and organisms is a fundamental tool for biological research, but achieving highly specific targeted changes has been technically demanding.Genome editing has been recently democratized by the development of RGENs (see Glossary in Box 1), repurposed from the type II CRISPR-Cas9 prokaryotic adaptive immune system 1 .Unlike other programmable nucleases, namely ZFNs and TALENs, whose target specificities are determined by modifying their DNA-binding domains, CRISPR-Cas9 can be customized by replacing guide RNAs, making the system much more affordable and scalable.Cas9 nucleases have been successfully used for modifying genomes in human cells [2][3][4][5] , animals [6][7][8][9] and plants 10,11 , heralding the age of genome editing.Furthermore, Cas9 or guide RNAs have been linked to various effector proteins to enable targeted gene regulation 12,13 and epigenome modifications 14,15 .It is worth noting, however, that many of these feats had been demonstrated previously using other nucleases or DNA-binding proteins 1,16 .In this Perspective, I shed light on early genome editing platforms that laid the groundwork for the widespread use of CRISPR-Cas9 in research and medicine (Fig. 1)."
+            },
+            {
+                "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                "section_type": "main",
+                "text": "\n\nGenome editing has always been a challenging area to provide more efficient ways to create a meaningful change in the genome.Today, the CRISPR (clustered regularly interspaced short palindromic repeat) restoration system is considered as one of the suitable and promising options for genome editing.Compared to the previous systems, CRISPR can deactivate or eliminate a gene without interfering with intracellular mechanisms.The system could be used in the treatment of diseases and in related research by identifying the performance of defective genes in these diseases.CRISPR seems to have more potential and applications compared to previous systems.Among these applications, we can note the use of CRISPR in understanding complex genetic and epigenetic conditions such as aging or cancer.The complex interactions between several genetic and epigenetic mechanisms that characterize aging pose significant challenges to scientists attempting to understand this phenomenon and its causes and still constitute a barrier to a better understanding of aging and the ability to develop effective application of CRISPR-cas to aging research."
+            },
+            {
+                "document_id": "b72eb0d1-50e3-4def-94bc-abf77891f519",
+                "section_type": "main",
+                "text": "Cas9\n\nDue to its simplicity and adaptability, CRISPR has rapidly become the most popular genome editing tool available for the mammalian genome (50,63).Because NHEJ DNA repair often introduces unwanted indels at the Cas9 cutting site, CRISPR has been used to knock-out genes by introducing frameshift mutations, resulting in protein depletion (156,157).In the diabetes field, CRISPR has also been adopted to study several genes in b cell lines and in human ES-derived b cells (21,151,158,159) as well as in animals (160,161)."
+            },
+            {
+                "document_id": "e2d1d559-d48f-4e57-8372-04d31f0f9da3",
+                "section_type": "main",
+                "text": "\n\nSome believe genome editing tools provide the best imaginable technology for mutating the germline.Indeed it is hard at the moment to imagine what could be better.Nevertheless there are remaining challenges.We need to improve efficiency of editing within a given population of cells (destined for SCNT) and in the zygote and overcome mosaicism.In our work with zygotes we regularly achieve 30 % editing frequency with delivery of editors-ZFN, TALEN and CRISPR/ Cas9-to the cytoplasm of livestock.We should aspire to at least [50 % and why not frequencies approaching or even achieving 100 %."
+            },
+            {
+                "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                "section_type": "main",
+                "text": "\n\nThe application of CRISPR-Cas in epigenome editing is currently in its infancy.However, the technique holds significant promise for providing clarity to the myriad of epigenetic mechanisms that may impact on the ageing process.In this regard, it must be noted that in comparison to other hallmarks of ageing, the range of discrepancies observed across model species is the broadest in the case of some epigenetic alterations.This prevents the use of many of the most time-cost efficient in vivo models of ageing such as yeast, worms and flies, as they can even lack some of those alterations.Therefore, the use of CRISPR-Cas for the fast and efficient generation of in vitro and in vivo models of higher species will prove invaluable for studying epigenetic mechanisms of ageing that are of relevance to humans."
+            },
+            {
+                "document_id": "33f1abde-a821-483b-b8b4-785f499db09d",
+                "section_type": "main",
+                "text": "\n\nIn comparison to a transgenic approach, a gene editing technique such as CRISPR-Cas9 offers the advantage that gene-edited crops are not considered genetically modified organism (GMO) in some countries, such as the US, where the demand for natural food colorants such as anthocyanins is high.Indeed, the use of GMO crops as a source of natural pigments may be inconsistent with consumer interests.However, carrot cultivars engineered with either the transgenic or gene editing approach have not been reported so far, but their development is possible."
+            },
+            {
+                "document_id": "b72eb0d1-50e3-4def-94bc-abf77891f519",
+                "section_type": "main",
+                "text": "\n\nApplications of gene/genome editing tools."
+            },
+            {
+                "document_id": "d14e93b5-01de-4208-8255-baae7898a7bb",
+                "section_type": "main",
+                "text": "\n\nKey characteristics in CRISPR and siRNA technologies."
+            },
+            {
+                "document_id": "d14e93b5-01de-4208-8255-baae7898a7bb",
+                "section_type": "main",
+                "text": "CRISPR/Cas9 Screening\n\nA growing number of published studies have utilized CRISPR technology for screening (see Table 3 for a comparison).CRISPR  For an overview of key differences between siRNA and CRISPR technologies, please see Taylor and Woodcock (2015)."
+            },
+            {
+                "document_id": "d14e93b5-01de-4208-8255-baae7898a7bb",
+                "section_type": "main",
+                "text": "\n\nFinally, CRISPR screening has become a possibility in 3D models, tissues and whole organisms (Platt et al., 2014;Chen et al., 2015).The generation of a Cre-dependent Cas9 knockin mouse enables the manipulation of genes in specific tissues, for instance by viral or non-viral delivery of sgRNA to the brain or other tissues.Importantly, this technology for the first time enables complex studies of acute modulation of brainspecific phenotypes, which will be key to develop a more thorough understanding of neuronal diseases.Using tissuespecific expression systems, it is thus possible to target a functionalized protein to any location within a whole organism.This truly is a new age in functional genomics."
+            },
+            {
+                "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                "section_type": "main",
+                "text": "The Molecular Basis of CRISPR-Cas Technology and Its Variants\n\nDuring the last decade, a more robust system in terms of targeting efficiency and ease of design was developed and rapidly became the most widely used gene-editing technique in the life sciences.CRISPR stands for clustered regularly interspaced short palindromic repeat DNA sequences.These short repeat elements were first observed in E. coli in 1987 and were later determined to be part of the bacterial adaptive immune system [9].However, the first concrete experimental evidence of the potential widespread application of CRISPR came with the demonstration that following viral infection, bacteria could integrate specific sequences of the viral genome into their own.These sequences would then be used by bacteria to produce short RNAs able to recognise the viral DNA in subsequent infections and guide the Cas9 nuclease to it.The RNA/Cas9 complex would then induce a DSB in the viral DNA, disabling it [10].This defence mechanism can be easily exploited in an experimental set-up, where short RNA sequences (around 20 base pairs), named gRNA (guide RNA), can be designed to bind any determined DNA sequence in virtually any kind of cell.gRNAs then become complexed to the Cas9 enzyme and will dictate the specificity of its enzymatic action, which in turn will lead to the generation of a DSB in the targeted genome."
+            },
+            {
+                "document_id": "b72eb0d1-50e3-4def-94bc-abf77891f519",
+                "section_type": "main",
+                "text": "\n\nIn view of the above, genome editing tools need to be carefully selected.The newly developed nCas9-RT holds great potential: 1.The nCas9 nicks the DNA rather than induces DSB and therefore avoids indel formation at the cutting site; 2. The use of pegRNA, which is a combination of gRNA, reverse transcription template and primer-binding sites, increases the specificity of target DNA binding hence reduces off-targets (62); 3.While multiplex pegRNAs could target various variants including SNPs, deletions or insertions without separating DNA donors as templates, it is possible the nCas9-RT will be able to convert all variants at once.This new technique, however, is still in early development, and its editing efficiency and sideeffects remain to be seen."
+            },
+            {
+                "document_id": "f28111d5-fe88-4668-8699-f02f907af80a",
+                "section_type": "main",
+                "text": "\n\n146 Genome studies and molecular genetics Features of Cas9-mediated gene editing methods in wheat.The top graph shows the percentages of on-target mutagenesis using the different methods across independent experiments as defined by their target genes or genotypes [39 ,42 ,43].Features include the method of delivery of the Cas9 and gRNA, the stable or transient expression of the system and the possibility of nuclear DNA integration.The target genes used in each method are shown, although the detailed homoeolog specificity of each experiment is not always reported.The number of different hexaploid (6x) bread wheat and tetraploid (4x) pasta wheat varieties used for each method is also shown in parenthesis.Abbreviations: Transiently expressing CRISPR/Cas9 DNA (TECCDNA) or RNA (TECCRNA), ribonucleoprotein (RNP).Original publications for stable transformation [39 ,42 ], TECCDNA [42 ,43], TECCRNA [42 ] and RNP [43].15, 2017, 367-378.effectively between disciplines and appreciate the potential of genomics and field-based research to complement each other. 'Reaping the benefits' [57] of the latest genomic developments will ultimately depend on our success in translating this knowledge into improved wheat cultivars for farmers and consumers."
+            },
+            {
+                "document_id": "d14e93b5-01de-4208-8255-baae7898a7bb",
+                "section_type": "main",
+                "text": "Conclusion and Outlook\n\nOverall, the use of CRISPR based methods in high-throughput functional genomics screening is still in its infancy.The first pooled libraries show encouraging results, but many technical considerations need to be explored for the development of arrayed libraries.The generation of large-scale libraries is possible not only for human and mouse, but virtually any organism.In the past, siRNA libraries have mostly focused on Drosophila, C. elegans, human, mouse, and rat genomes, though in principle has always been possible to design and produce libraries for other organisms as well.It is uncertain which model organisms will be targeted with whole genome or focused libraries using CRISPR as the availability of whole-genome sequence information expands."
+            },
+            {
+                "document_id": "429abfc1-f628-48ff-bfe8-f7be6d1419a8",
+                "section_type": "main",
+                "text": "Effective protocols that exist for gene editing use\nguide RNA in combination with the enzyme recombinase\n(CRISPR/Cas9), zinc finger nuclease, or zinc finger protein in combination with a nuclease (TALEN) (Gupta and\nMusunuru, 2014).  Although these methods can be applied\neasily to livestock species, the mouse still has the unequal\nadvantage of a short generation interval, which shortens the\ntime for testing the effects of the introduced mutation several\nfold."
+            },
+            {
+                "document_id": "ac00c552-7514-49d4-9e90-ab01c22472ae",
+                "section_type": "main",
+                "text": "\n\nAs compared to the complete gene knockout mouse models, CRISPR/Cas9 based gene editing provides only a partial knockout in a fraction of targeted cells.Therefore, it is important to improve the current gene editing efficiency of the CRISPR/Cas9 systems.Another caveat is that using a ubiquitous promoter to drive the expression of CRISPR/Cas9 can lead to gene editing in the non-target cells.This can be achieved using a highly tissue specific promoter to drive the expression of CRISPR/Cas9.However, despite utilizing a tissue specific promoter, it is still not desirable to have constitutive expression of CRISPR/Cas9 as it may lead to off-target effects.This potential drawback can be overcome by utilizing a conditional expression system wherein the expression levels as well as the duration of CRISPR/Cas9 can be tightly regulated.This has been recently demonstrated by de Solis et al. who have developed a doxycycline-inducible AAV based system for gene editing [118].Their strategy involved generating two separate AAV/DJ vectors such that the vector harbors a TRE Tight promoter driving the expression of CRISPR/Cas9 while the second vector contains a U6 promoter driving Tet2 sgRNA and a CMV promoter driving the expression of rtTA (Tet-On Advanced and an IRES driven GFP.Surprisingly, their results indicate doxycycline-inducible expression of CRISPR but Tet2 gene editing in a doxycycline independent manner due to leakiness.To overcome the issue of leakiness, they have significantly modified their vectors by utilizing a combination of hybrid H1/TO promoter to drive the expression of Tet2-sgRNA and a CMV promoter controlling the expression of TetR in frame with a self-cleaving P2A sequence followed by a GFP ORF fused to a KASH domain.In this system in the absence of doxycycline, TetR binds to H1/TO promoter and represses the gRNA transcription.However, addition of doxycycline inhibits TetR binding and induces gRNA expression.This system allowed doxycycline dependent genome editing of Tet2 in N2A cells in vitro.Besides, doxycycline inducible system there are several other inducible systems available including rapamycin, mifepristone, tamoxifen, and ecdysone inducible systems that can be engineered to overcome the leakiness of the dinducible system."
+            },
+            {
+                "document_id": "d14e93b5-01de-4208-8255-baae7898a7bb",
+                "section_type": "main",
+                "text": "From Genome Editing to Genome Functionalization\n\nThe Cas9 protein has been engineered to obtain various properties that range from transcriptional repression to endogenous gene tagging (Table 1).In a more simplified view, Cas9 can be seen as the adaptor between the target sequence and a variety of functions.This reveals the most powerful concept of CRISPR technology: the ability to target a function to an exact genomic position.With this view in mind, it is conceivable to be able to design a minimal Cas9 protein with all extraneous regions deleted so that the protein simply binds the target DNA, and this would provide the most basic possible template for protein engineering.To date, successful CRISPR-based genome functionalization techniques have been based on fusing one or several functional domain to full-length catalytically inactive Cas9 (dCas9), which binds to the target locus but does not cleave the DNA.An important experimental consideration to take into account when following these approaches is that different sgRNAs must be designed for each functionalization in order to target the correct genomic features and achieve the desired output.For instance, transcriptional regulation requires sgRNAs that target promoter or regulatory regions, whereas sgRNAs used for knockouts most commonly target exons.Furthermore, the location of targeting within an individual gene can have a significant impact on the functional effect of the resulting mutation.For example, when using wild-type Cas9, targeting a coding region corresponding to a functional protein domain has been shown to be result in loss-of-function even for in-frame mutations, compared to exclusively targeting early exon regions, which often require frameshift mutations to achieve loss-of-function (Shi et al., 2015).Deliberately targeting certain gene regions can be used for achieving specific outcomes, such as knocking out a specific splice variant."
+            },
+            {
+                "document_id": "9a12db75-1efa-46b1-9da4-d2fc8d828f42",
+                "section_type": "main",
+                "text": "\n\nIn addition to DNA-targeting CRISPR systems, RNA-targeting Cas9 enzymes are also available, such as CasRx which showed robust knockdown of gene expression (Konermann et al., 2018).Interestingly, CasRx can also be used to target pre-mRNA to manipulate alternative splicing et al., 2018).Deregulation of alternative splicing has been implicated in the aging process (Li et al., 2017) and observed in several ageassociated diseases such as amyotrophic lateral sclerosis and Alzheimer's disease (Lin et al., 1998;Spillantini et al., 1998;Glatz et al., 2006).In regards to AMD, Allikmets et al. (1997) have shown that a point mutation (G5196A) in the Stargardt disease gene ABCA4, eliminates a 5 donor splice site and increases the risk of AMD.However, a subsequent GWAS study with larger cohorts could not confirm this association between ABCA4 and AMD (Fritsche et al., 2016).Overall, the association of AMD pathophysiology with alternative splicing regulation remains unclear and CasRx technology could facilitate research in this understudied area.In summary, recent development of CRISPR/Cas technology has greatly expanded the toolbox to carry out functional study of AMD-associated genes, providing new tools that can modulate gene expression by targeting at the DNA level, RNA level as well as the splicing variants."
+            },
+            {
+                "document_id": "b72eb0d1-50e3-4def-94bc-abf77891f519",
+                "section_type": "main",
+                "text": "\n\nManipulation of hESC/iPSC cells via CRISPR-Cas9 technology provides a platform for the correction of genomic mutations not only in diabetes but in other disease fields as well (276)(277)(278)(279).Through CRISPR-mediated HDR and base editing, it is possible to correct the vast majority of genetic variants, if not all.Conversion of GWAS-identified non-coding variants has not been conducted/documented in the diabetes field, but it seems inevitable that such work will be carried out in the near future given its importance in basic research and potential clinical application.Variants identified by GWAS are often clustered in the genome (134).Although an individual variant may change transcription factor binding on its own, neighbouring risk variants might cooperate to change the transcriptional landscape of local chromatin and thus the activity of the enhancer cluster leading to changes in the expression of multiple genes whose aggregate effect is to impair b cell function.Hence, multiplex genome-editing needs to be carried out to convert multiple risk variants into protective (non-risk) variants in hESC or iPSC cells.In this case, the off-target effects brought by multiplex gRNAs may have a large impact on the rest of the genome and raise major concerns."
+            }
+        ],
+        "document_id": "38E097866214E3EEFE346FB836ABF345",
+        "engine": "gpt-4",
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+        "focus": "api",
+        "keywords": [
+            "CRISPR-Cas9",
+            "gene&editing",
+            "off-target&effects",
+            "genome",
+            "clinical&trials",
+            "agriculture",
+            "biomedicine",
+            "precision&medicine",
+            "transgenic",
+            "ethical&concerns"
+        ],
+        "metadata": [
+            {
+                "object": "Genome-wide association analyses in 22,981 participants 2280 shingles cases from the electronic Medical Records and Genomics Network identified a genomic region in the combined and European ancestry groups that has an age of onset effect reaching genome-wide significance region tags the non-coding gene HCP5 HLA Complex P5.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab319975"
+            },
+            {
+                "object": "Study show that CXCL9 and CXCL10 are overexpressed in skin of HPV16 E7 transgenic mice when compared with non-transgenic animals. Immune cell infiltration to E7 transgenic skin is a consequence of epidermal hyperplasia, and that hyperplasia induces CXCL9 and CXCL10 production to recruit a subset of CXCR3+ T cells, promoting rejection of grafted E7 transgenic skin depleted of immunosuppressive lymphocytes.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab749071"
+            },
+            {
+                "object": "shRNAs targeting MSTN were expressed in muscles of transgenic sheep. MSTN expression was inhibited in muscle tissues of transgenics compared with controls. Moreover, transgenic sheep showed a tendency to faster increase in body weight than control sheep.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab705362"
+            },
+            {
+                "object": "ompounding a previously described Bmi1-transgene and Pten-deficiency prostate cancer mouse model with the Ezh2 transgene did not enhance tumour progression or drive metastasis formation. In conclusion, we here report the generation of a wildtype Ezh2 overexpression mouse model that allows for intravital surveillance of tissues with activated transgene",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab546432"
+            },
+            {
+                "object": "Using a series of transgenic constructs with various Alk1 genomic fragments joined to a reporter, it seems a 9.2-kb genomic fragment including the 2.7-kb promoter region & the whole intron 2 is sufficient for arterial endothelium-specific expression.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab988637"
+            },
+            {
+                "object": "Data including data from studies using transgenic plants or cells from transgenic plants suggest crucial role for UreG in nickel delivery for urease multimerization/activation. These studies were conducted using recombinant Arabidopsis thaliana proteins expressed in transgenic Nicotiana benthamiana cloned cells or hydroponic plants. UreG = urease accessory protein UreG",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab173373"
+            },
+            {
+                "object": "TaWRKY33 transgenic Arabidopsis lines showed lower rates of water loss than TaWRKY1 transgenic Arabidopsis lines and wild type plants during dehydration. Most importantly, TaWRKY33 transgenic lines exhibited enhanced tolerance to heat stress. [WRKY33]",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab766040"
+            },
+            {
+                "object": "Study tracked the post-weaning development of a motor phenotype that arose in mice after random insertion of a transgene into the genome. The transgene was later found to have disrupted the beta-IV spectrin gene, which was confirmed by reduced expression of betaIV spectrin protein in brain homogenates. The motor phenotype was recessive, occurring in 20% of L25+/-xL25+/- progeny.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab752806"
+            },
+            {
+                "object": "eight of 11 Sox10 genomic elements direct reporter gene expression in transgenic zebrafish similar to patterns observed in transgenic mice, despite an absence of observable sequence conservation between mice and zebrafish.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab252134"
+            },
+            {
+                "object": "More oligodendrocytes and less demyelination were observed after SCI in p35 transgenic mice than in controls which did not carry the p35 transgene. Motor function recovered more in the cre/p35 transgenic mice than in the control cre mice.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab501036"
+            }
+        ],
+        "question": "What are the potential benefits and risks associated with gene editing technologies like CRISPR-Cas9?",
+        "subquestions": null,
+        "task_id": "38E097866214E3EEFE346FB836ABF345",
+        "usage": {
+            "chatgpt": 9104,
+            "gpt-4": 6248,
+            "gpt-4-turbo-preview": 5340
+        },
+        "user_id": 2
+    },
+    "document_id": "38E097866214E3EEFE346FB836ABF345",
+    "task_id": "38E097866214E3EEFE346FB836ABF345"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/06.json b/gnqa/paper1_eval/src/data/responses/general/experts/06.json
new file mode 100644
index 0000000..894ee69
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/06.json
@@ -0,0 +1,398 @@
+{
+    "created_at": "2024-06-01T14:27:38.978700Z",
+    "data": {
+        "amplify": false,
+        "answer": "Human centromeres contain the CENP-B box, a 17-bp motif that is bound by the centromere protein CENP-B. This motif is present on every chromosome except for the Y chromosome. It is necessary for the formation of de novo centromeres on artificial chromosomes, but it is not essential for the formation of neocentromeres. Mice lacking CENP-B are viable and fertile.",
+        "context": {
+            "395a51ba-bd2a-4160-8396-b13a3bf762ff": [
+                {
+                    "document_id": "395a51ba-bd2a-4160-8396-b13a3bf762ff",
+                    "text": "\n\nPrimate and mouse centromeric DNA contain the CENP-B box, a 17-bp motif that is bound by the centromere protein CENP-B.In humans, the CENP-B box is present on every chromosome except for the Y chromosome [20].It is paradoxically necessary for formation of de novo centromeres on artificial chromosomes, but it is not essential for the formation of neocentromeres, and mice lacking CENP-B are viable and fertile [21,22]."
+                }
+            ],
+            "3dfe0ec3-b3a6-4a08-8929-e54cab3ec262": [
+                {
+                    "document_id": "3dfe0ec3-b3a6-4a08-8929-e54cab3ec262",
+                    "text": "Box 3 Mechanism of homologous recombination and end joining\n\nThe severe phenotype of the mouse mutants and the highly cancer-prone human syndromes highlight the importance of homologous recombination.Mouse KU mutants display sensitivity to agents that lead to breaks in DNA, and have immunological problems because the KU proteins are involved in V(D)J recombination of antibody gene sequences.In addition, these mutants display poor development, several features of premature ageing and increased apoptosis of postmitotic neurons in the developing brain.Mice with defects in DNA-PK cs (SCID mice) display a similar but generally milder phenotype.In contrast, XRCC4-and ligase IV-knockout mice seem more severe, with late embryonic lethality resulting from massive ATM-and p53-dependent neuronal apoptosis 33,38 ."
+                },
+                {
+                    "document_id": "3dfe0ec3-b3a6-4a08-8929-e54cab3ec262",
+                    "text": "\n\nCells in G1 have only the homologous chromosome for recombination repair.However, this may be difficult to find in the complex genome.Moreover, it is potentially dangerous as a template for repair as it may lead to homozygosity for recessive mutations.As an alternative, the end-joining reaction simply links ends of a DSB together, without any template, using the end-binding KU70/80 complex and DNA-PK cs , followed by ligation by XRCC4-ligase4 (reviewed by 27,33; see the right panel of the figure, stages V-VII).The function of KU70/80 might involve end protection and approximating the ends, in addition to a signalling function by DNA-PK cs .End joining may be further facilitated when the ends are still held together through nucleosomes or other structures.End joining is sometimes associated with gain or loss of a few nucleotides if internal microhomologies are used for annealing before sealing.This implies the involvement of DNA polymerases and/or nucleases.Note that the KU complex is also involved in telomere metabolism 27,62 .found to be lethal 34 .Inactivation of ATR by itself is inviable already at the blastocyst stage.Inactivation of BRCA1 and BRCA2 in mice is also embryonically lethal; cell lines display defects in homologous recombination [35][36][37] ."
+                },
+                {
+                    "document_id": "3dfe0ec3-b3a6-4a08-8929-e54cab3ec262",
+                    "text": "371\n\nA tentative scenario for the homologousrecombination reaction is depicted in the left panel of the figure.To promote strand invasion into homologous sequences, the 5፱-3፱ exonuclease activity of the RAD50/MRE11/NBS1 complex (also a substrate for ATM phosphorylation) exposes both 3፱ ends 30 (I).RPA facilitates assembly of a RAD51 nucleoprotein filament that probably includes RAD51-related proteins XRCC2, XRCC3, RAD51B, C and D. RAD52 stimulates filament assembly (II).RAD51 has, like its Escherichia coli RecA counterpart, the ability to exchange the single strand with the same sequence from a double-stranded DNA molecule.Correct positioning of the sister chromatids by cohesins probably facilitates the identification of a homologous sequence.A candidate for the complex chromatin transactions associated with these DNA gymnastics is RAD54, a member of the SWI/SNF family of DNA-dependent ATPases.After identification of the identical sister chromatid sequence, the intact double-stranded copy is used as a template to properly heal the broken ends by DNA synthesis (III).Finally, the so-called Hollidayjunctions are resolved by resolvases 27,33,60 (IV).Homologous recombination involves the simultaneous action of large numbers of the same molecules, which are found to be concentrated in radiation-induced nuclear foci.These depend on, and also include, the BRCA1 and BRCA2 proteins 36 .Recent evidence implicates BRCA2 directly or indirectly in nuclear translocation of RAD51 (ref.61)."
+                }
+            ],
+            "748cfe7e-e4f2-453f-8575-50dfe84e2538": [
+                {
+                    "document_id": "748cfe7e-e4f2-453f-8575-50dfe84e2538",
+                    "text": "\n\nThis picture poses more questions than it seeks to answer.Is the grouping of the regions by product rather than by type of region correct?Given that the recombina- tion fraction between HLA-A and HLA-B is of the order of .08%,and that this is likely to represent a distance of at least hundreds of thousands of nucleotides, how are the pieces put together over such relatively long distances?Is it possible that regions of the DNA loop out, so that transcripts can be made directly from noncon- tiguous DNA sequences, the loops being held in place by small RNAs as suggested for the control of splicing by Steitz, and her colleagues [24] and by others [25]?If these small RNAs are coded for well outside the HLA region, does this provide a mechanism for control of expression of products by unlinked genes, as may be the case for one of the constituent polypeptides of the HLA-DR product?What might be the nature of the signals that control which of a multiple set of alternative regions is expressed by any given chromosome?"
+                }
+            ],
+            "7a451204-390c-4ff2-8a1d-b4de62b73503": [
+                {
+                    "document_id": "7a451204-390c-4ff2-8a1d-b4de62b73503",
+                    "text": "Mamm Genome. 2006; 17:220–229. [PubMed: 16518689]\n72. Romanoski CE, et al. Systems genetics analysis of gene-by-environment interactions in human\ncells. Am J Hum Genet. 2010; 86:399–410. [PubMed: 20170901]\n73. Myers S, Freeman C, Auton A, Donnelly P, McVean G. A common sequence motif associated\nwith recombination hot spots and genome instability in humans. Nature Genet. 2008; 40:1124–\n1129. [PubMed: 19165926]\n74. Myers S, et al. Drive against hotspot motifs in primates implicates the PRDM9 gene in meiotic\nrecombination. Science. 2010; 327:876–879. [PubMed: 20044541]\n75. Cordell HJ. Detecting gene-gene interactions that underlie human diseases. Nature Rev Genet. 2009; 10:392–404."
+                }
+            ],
+            "8604652e-2477-4552-8f43-f5f19e421df2": [
+                {
+                    "document_id": "8604652e-2477-4552-8f43-f5f19e421df2",
+                    "text": "Classification of common conserved sequences in mammalian\nintergenic regions. Hum. Mol. Genet. 2002, 11, 669–674. 25. Zhu, L.; Swergold, G.D.; Seldin, M.F. Examination of sequence homology between human\nchromosome 20 and the mouse genome: Intense conservation of many genomic elements. Hum. Genet. 2003, 113, 60–70. 26. Pevzner, P.; Tesler, G. Human and mouse genomic sequences reveal extensive breakpoint reuse in\nmammalian evolution. Proc. Natl. Acad. Sci. USA 2003, 100, 7672–7677. 27. Christmann, R.B. ; Sampaio-Barros, P.; Stifano, G.; Borges, C.L. ; de Carvalho, C.R. ; Kairalla, R.;\nParra, E.R. ; Spira, A.; Simms, R.; Capellozzi, V.L. ; et al."
+                }
+            ],
+            "9d82958a-45b0-4f1d-b765-38d018e4b140": [
+                {
+                    "document_id": "9d82958a-45b0-4f1d-b765-38d018e4b140",
+                    "text": "\n\na The table lists proteins in which mutations have been shown to increase homologous recombination (HR), gross chromosomal rearrangements (GCRs), chromosomal instability (CIN), sister chromatid exchanges (SCEs), tri-nucleotide repeat expansions and contractions (TNR), telomere fusions (Tel fusion), or fragile telomeres (Tel fragility).A phenotype inside brackets ([ ]) indicates that it is caused by overexpression of the protein.For further details and references see Supplementary Table1.Abbreviations: DSB, double-strand break; PCNA, proliferating cell nuclear antigen; RFC, replication factor C complex; SCF, Skp1-Cdc53/Cullin-F-box."
+                },
+                {
+                    "document_id": "9d82958a-45b0-4f1d-b765-38d018e4b140",
+                    "text": "\n\nFigure 3 Intermediates and chromosome structural alterations, as observed by different techniques. (a) Replication fork stalling, as monitored by 2D-gel electrophoresis and Southern analysis in yeast (for details about the technique, see Reference 161). (b) Slower human replication forks covering shorter DNA synthesis tracks, as determined by incorporation of IdU and CldU via DNA combing (52), which permits visualization of the process of replication on DNA fibers. (c) Accumulation of double-strand breaks (DSBs) or replicative stress, as inferred by γH2AX foci or by γH2AX pan staining, respectively, in human cells. (d ) DSBs or ssDNA (single-stranded DNA) gaps as seen directly by nuclear \"comet tails\" via single-cell electrophoresis assays in human cells (52). (e) Sister-chromatid exchanges (SCEs), as determined by Giemsa staining in human cells (207). ( f ) Hyper-recombination, as determined by colony sectoring in yeast (5). ( g) Gross chromosomal rearrangements (GCRs), as determined by spectral karyotyping in mouse cells (118). (h) Translocations, as visualized by pulse-field gel electrophoresis in yeast (168). (i ) Fragile sites, as detected by mitotic spreads in human cells (109). ( j) Telomere fusions, as determined by CO-FISH (chromosome-orientation fluorescent in situ hybridization) in mouse cells (124). (k) Anaphase bridges, presumably resulting from unfinished replication, dicentric chromosomes, and sister-chromatid nondisjunction, as detected by fluorescence microscopy in mouse cells.Arrows indicate the specific structural alterations referred to in each panel; in panel h, closed and open arrows indicate the position where the translocated or missing parental chromosome migrate or should migrate, respectively.When necessary, a normal control is shown on top of the panel, with the exception of panel a, which is shown on the left.Detailed description of each technique can be found in the references provided.Photos are from the laboratories of A. Nussenzweig ( g), A. Losada (k), M. Blasco ( j), L. Tora (i ), and ours (all others).Abbreviations: HR, homologous recombination; NHEJ, nonhomologous end-joining."
+                }
+            ],
+            "9ee491f4-5f16-4cb2-b803-54f2fdee1dba": [
+                {
+                    "document_id": "9ee491f4-5f16-4cb2-b803-54f2fdee1dba",
+                    "text": "\n\nIn humans, the pericentromeric region of chromosome 9 is densely packed with segmental genomic duplications (segdups) and is prone to microdeletions and microduplications. 5In order to evaluate this region for microdeletions and microduplications in family T, we screened genomic DNA from affected individual II-7 by arrayCGH with the Nimblegen HD2 platform with the previously described CHP-SKN sample 6 as the reference.Data were normalized and CNVs were called by identifying regions where Z-scores consistently deviated from the diploid mean.At 9q21.11, a genomic duplication of ~270 kb was apparent in the genomic DNA of II-7 (Figure 1D).The Genomic duplications may or may not be in tandem with their parent segment and may be either in the same or inverted orientation. 7We developed primers that would uniquely amplify genomic DNA with the duplication under each of these conditions.Forward (5 0 -CCCAGCAGA AGCAATGGTGGTAGCC-3 0 ) and reverse (5 0 -GGTGGTGAA TCCAAAAACACAAGAACAAAGTC-3 0 ) primers diagnostic for a tandem inverted duplication (Figure 2A) yielded products of expected size in family T relatives with hearing loss, but yielded no product in unaffected family T relatives (Figure 2B).Genotypes of all 58 participating relatives in family T indicated that the tandem inverted duplication was coinherited with hearing loss.The duplication spans approximately positions 71,705,804 to 71,974,823 (hg19) on chromosome 9 for a size of ~269,023 bp.The duplication includes the entire locus for the tight junction protein TJP2, which spans positions 71,788,971 to 71,870,124 (hg19)."
+                }
+            ],
+            "ab0a3234-c3b3-46be-8954-01eda9bc962e": [
+                {
+                    "document_id": "ab0a3234-c3b3-46be-8954-01eda9bc962e",
+                    "text": "Chromosomal context of human NORs\n\nHuman NORs are positioned on the short arms of the acrocentric chromosomes that still remain unsequenced and thus missing from the current human genome draft, GRCh38.p7.Seeking an understanding of the chromosomal context of human NORs and to identify potential NOR regulatory elements, my laboratory has begun to characterize the sequences on both proximal (centromeric) and distal (telomeric) sides of the rDNA arrays (Fig. 3A; Floutsakou et al. 2013).Building on earlier reports of sequences distal and proximal to the rDNA array on HSA21 and HSA22, respectively (Worton et al. 1988;Sakai et al. 1995;Gonzalez and Sylvester 1997), 207 kb of sequence immediately proximal and 379 kb distal to rDNA arrays have been reported recently (Floutsakou et al. 2013).Consensus proximal junction (PJ) and distal junction (DJ) sequences were constructed mostly from chromosome 21 BACs (bacterial artificial chromosomes).Comparison of these sequences with BACs and cosmids derived from the other acrocentrics revealed that the PJ and DJ sequences are, respectively, ∼95% and 99% identical between all five acrocentric chromosomes.Conservation of DJ sequences among the acrocentrics is consistent with frequent recombination between the rDNA arrays on each of the acrocentric chromosomes (Worton et al. 1988).However, conservation of PJ sequences suggests that there must also be frequent recombination events in the interval between the centromere and rDNA arrays.Proximal sequences are almost entirely segmentally duplicated, similar to the regions bordering centromeres.Consequently, they are unlikely to contain any specific elements that would regulate the activity of the linked NOR.In contrast, the distal sequence is predominantly unique to the acrocentric short arms and is dominated by a very large inverted repeat.Each arm of the inverted repeat is >100 kb, and they share an average sequence identity of 80%.There is a large (∼40-kb) block of a 48base-pair (bp) satellite repeat, CER, at the distal end of the DJ (Fig. 3A).CER blocks are found distal to the rDNA on all acrocentric chromosomes, with additional pericentromeric blocks on chromosomes 14 and 22. Finally, there are two blocks of a novel 138-bp tandem repeat, ACRO138, present within the DJ."
+                },
+                {
+                    "document_id": "ab0a3234-c3b3-46be-8954-01eda9bc962e",
+                    "text": "\n\nThe conservation of DJ sequence between the five human acrocentric chromosomes provides a unique opportunity to visualize NORs by FISH.Whereas the rDNA content of NORs can vary greatly, probing of human metaphase chromosome spreads with a DJ BAC results in signal that is consistent between NORs (Floutsakou et al. 2013).Using this probing scheme, it was observed that in most human cell lines analyzed, including multiple primary lines, at least one and sometimes as many as four of the NORs present have very little or no detectable rDNA (C van Vuuren and B McStay, unpubl. ).Many studies have used silver staining of metaphase spreads prepared from stimulated human peripheral blood lymphocytes to determine how many NORs are active in normal human cells.The number of active NORs ranges from seven to 10, with an average of eight (Heliot et al. 2000).Possibly, NORs with low rDNA content are active but fall below a detection threshold in silver staining.At this point, it is worth considering the distribution of active versus silent rDNA repeats in humans and other mammals.If 50% of rDNA repeats are truly repressed, there are insufficient \"silent\" NORs to house them.We must conclude that active NORs are a mosaic of active and silent repeats."
+                }
+            ],
+            "b04f2221-de28-4c4b-893e-9da982ff864c": [
+                {
+                    "document_id": "b04f2221-de28-4c4b-893e-9da982ff864c",
+                    "text": "However, excluding some cases, recombination\nsuppression occurs in a small genomic tract\nwhere these genes are located, and it does\nnot extend over most of the sex chromosome\npair, as occurs in mammals and birds (Bergero\nand Charlesworth, 2009). It is not clear if this\nsuppression occurs by the presence of inversions or as a modulation of the recombination\nmechanism itself, but both could be involved\n(Bergero and Charlesworth, 2009). Evidence of\nrecombination in the SD region in sex reversal\nindividuals supports the second hypothesis."
+                }
+            ],
+            "d4fb56e4-06ab-4c01-b7a0-a193c4a40800": [
+                {
+                    "document_id": "d4fb56e4-06ab-4c01-b7a0-a193c4a40800",
+                    "text": "\n\nOrthologous chromosomes between baboon and human"
+                }
+            ],
+            "da485354-fcdc-49b8-9a41-0f673610156a": [
+                {
+                    "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                    "text": "Lichter P, Cremer T, Borden J, Manuelidis L, Ward DC (1988) Delineation of\nindividual human chromosomes in metaphase and interphase cells by in situ suppression hybridization using recombinant DNA libraries. Hum Genet 80:224–234\n3. Jang W, Yonescu R, Knutsen T, Brown T, Reppert T, Sirotkin K, Schuler GD, Ried\nT, Kirsch IR (2006) Linking the human cytogenetic map with nucleotide sequence:\nthe CCAP clone set. Cancer Genet Cytogenet 168:89–97\n4."
+                },
+                {
+                    "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                    "text": "Nature\nGenet 1:222–225\n55. Foote S, Vollrath D, Hilton A, Page DC (1992) The human Y chromosome: overlapping DNA clones spanning the euchromatic region. Science 258:60–66\n56. Chumakov IM, Rigault P, Le Gall I et al (1995) A YAC contig map of the human\ngenome. Nature 377:175–297\n57. Hudson TJ, Stein LD, Gerety SS et al (1995) An STS-based map of the human\ngenome. Science 270:1945–1954\n58. Coffey AJ, Roberts RG, Green ED et al (1992) Construction of a 2.6-Mb contig in\nyeast artificial chromosomes spanning the human dystrophin gene using an STSbased approach. Genomics 12:474–484\n59."
+                }
+            ],
+            "e4541c0c-53fb-4c2c-b550-40728c356549": [
+                {
+                    "document_id": "e4541c0c-53fb-4c2c-b550-40728c356549",
+                    "text": "\n\nFigure 4 Schematic depiction of proposed mechanisms for observed intrachromosomal rearrangements.The blue and red arrows indicate the orientation of the integrated plasmid loci and the recovered mouse sequences, respectively, on the original non-rearranged chromosome (left column).All four combinations are given for an arbitrarily orientated chromosome (green line).The middle column shows how two breakpoints (lightning signs) could lead to the inversion or deletion of the encompassed chromosomal sequence (yellow-orange dual tone line) and result in a recoverable mutation in the right column.The last row indicates the two options for a transposition, in which either the transgene locus or the recovered mouse sequence is copied or excised (as indicated by the pink and light blue arrows) and integrates in the breakpoint at the other location."
+                },
+                {
+                    "document_id": "e4541c0c-53fb-4c2c-b550-40728c356549",
+                    "text": "\n\nAs mentioned above, by taking into account that for a genome rearrangement to be detected, the 5Ј plasmid sequence of the breakpoint in lacZ must remain intact and end immediately in front of the recovered mouse sequence, the simplest intrachromosomal mutation that could have taken place was inferred (Fig. 4).Rearrangements with breakpoints in the mouse genome on either site of the integrated plasmid concatamer, but with reversely orientated sequences, could be inversions (Fig. 4).Rearrangements in the direction of the integrated plasmids, proximal for chromosome 3 and distal for chromosome 4 (Fig. 3), with similarly orientated breakpoints in the mouse genome, could be deletions (Fig. 4).Rearrangements in the reverse direction of the integrated plasmids, with reversely orientated mouse sequences, are more complicated and might be owing to transpositions (Fig. 4).According to these schemes, half of the intrachromosomal rearrangements would have been inversions, whereas deletions and transpositions each made up one fourth (Fig. 3).Alternatively, these rearrangements could be explained by translocations involving the transgene clusters integrated on either the homolog or the other chromosome."
+                }
+            ],
+            "f08c0391-2d72-491c-a472-5db71bf11ac8": [
+                {
+                    "document_id": "f08c0391-2d72-491c-a472-5db71bf11ac8",
+                    "text": "\n\nFIGURE 3. Telomere arrays of chicken and human chromosomes: the chicken genome contains more telomere sequence than the human genome.Chicken (a) and human (b) metaphase chromosomes and interphase cells hybridized with a telomeric sequence-peptide nucleic acid (PNA)-fluorescein probe.Human and chicken slide preparations were processed, and images were captured using the same parameters.Qualitatively, the telomere-positive fluorescent signals (white spots) from chicken cells and chromosomes have greater intensity than those of human (4′,6 diamidino-2-phenylindole, DAPI counterstain)."
+                }
+            ],
+            "f4762690-64e9-4f6d-9031-c249dc4a6d85": [
+                {
+                    "document_id": "f4762690-64e9-4f6d-9031-c249dc4a6d85",
+                    "text": "\n\nIn a previous study on the accumulation of spontaneous genome rearrangements in normal mice with aging, we discovered that 50% of the events were intrachromosomal, i.e., large deletions or inversions [22].In contrast, in this present study most of the rearrangements resulted from inter-chromosomal recombination, in both the Ercc1-mutant and control animals (Table 3).Previously, we used lacZ-plasmid line 60 mice with integration sites on Chromosomes 3 and 4, while in the present study line 30 mice were used with a single integration site on Chromosome 11.This indicates that the relative frequency of translocations is founder line specific and could be due to the position of the lacZ-plasmid cluster on the chromosome.Indeed, the chromosomal integration sites in line 60 mice are in the E1 region of Chromosome 3 (half way along the chromosome) and the C5 region of Chromosome 4 (two-thirds of the way along the chromosome) [22], while the integration site of founder line 30 (used in this study) is on the centromeric tip of Chromosome 11 (region A1-A2; not shown).The proximal location on Chromosome 11 prevents the detection of all but relatively small intra-chromosomal recombinations; larger events would lead to loss of the centromere and, therefore, the entire chromosome.If the orientation of the integration site in line 30, which is currently unknown, is towards the centromere, transpositions and inversions towards the distal end are the only detectable large intra-chromosomal rearrangements (for a detailed explanation of the different chromosomal events that can occur at the lacZ locus, see [22])."
+                }
+            ]
+        },
+        "data_source": [
+            {
+                "document_id": "f4762690-64e9-4f6d-9031-c249dc4a6d85",
+                "section_type": "main",
+                "text": "\n\nIn a previous study on the accumulation of spontaneous genome rearrangements in normal mice with aging, we discovered that 50% of the events were intrachromosomal, i.e., large deletions or inversions [22].In contrast, in this present study most of the rearrangements resulted from inter-chromosomal recombination, in both the Ercc1-mutant and control animals (Table 3).Previously, we used lacZ-plasmid line 60 mice with integration sites on Chromosomes 3 and 4, while in the present study line 30 mice were used with a single integration site on Chromosome 11.This indicates that the relative frequency of translocations is founder line specific and could be due to the position of the lacZ-plasmid cluster on the chromosome.Indeed, the chromosomal integration sites in line 60 mice are in the E1 region of Chromosome 3 (half way along the chromosome) and the C5 region of Chromosome 4 (two-thirds of the way along the chromosome) [22], while the integration site of founder line 30 (used in this study) is on the centromeric tip of Chromosome 11 (region A1-A2; not shown).The proximal location on Chromosome 11 prevents the detection of all but relatively small intra-chromosomal recombinations; larger events would lead to loss of the centromere and, therefore, the entire chromosome.If the orientation of the integration site in line 30, which is currently unknown, is towards the centromere, transpositions and inversions towards the distal end are the only detectable large intra-chromosomal rearrangements (for a detailed explanation of the different chromosomal events that can occur at the lacZ locus, see [22])."
+            },
+            {
+                "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                "section_type": "main",
+                "text": "Lichter P, Cremer T, Borden J, Manuelidis L, Ward DC (1988) Delineation of\nindividual human chromosomes in metaphase and interphase cells by in situ suppression hybridization using recombinant DNA libraries.  Hum Genet 80:224–234\n3.  Jang W, Yonescu R, Knutsen T, Brown T, Reppert T, Sirotkin K, Schuler GD, Ried\nT, Kirsch IR (2006) Linking the human cytogenetic map with nucleotide sequence:\nthe CCAP clone set.  Cancer Genet Cytogenet 168:89–97\n4."
+            },
+            {
+                "document_id": "9d82958a-45b0-4f1d-b765-38d018e4b140",
+                "section_type": "main",
+                "text": "\n\na The table lists proteins in which mutations have been shown to increase homologous recombination (HR), gross chromosomal rearrangements (GCRs), chromosomal instability (CIN), sister chromatid exchanges (SCEs), tri-nucleotide repeat expansions and contractions (TNR), telomere fusions (Tel fusion), or fragile telomeres (Tel fragility).A phenotype inside brackets ([ ]) indicates that it is caused by overexpression of the protein.For further details and references see Supplementary Table1.Abbreviations: DSB, double-strand break; PCNA, proliferating cell nuclear antigen; RFC, replication factor C complex; SCF, Skp1-Cdc53/Cullin-F-box."
+            },
+            {
+                "document_id": "395a51ba-bd2a-4160-8396-b13a3bf762ff",
+                "section_type": "main",
+                "text": "\n\nPrimate and mouse centromeric DNA contain the CENP-B box, a 17-bp motif that is bound by the centromere protein CENP-B.In humans, the CENP-B box is present on every chromosome except for the Y chromosome [20].It is paradoxically necessary for formation of de novo centromeres on artificial chromosomes, but it is not essential for the formation of neocentromeres, and mice lacking CENP-B are viable and fertile [21,22]."
+            },
+            {
+                "document_id": "3dfe0ec3-b3a6-4a08-8929-e54cab3ec262",
+                "section_type": "main",
+                "text": "Box 3 Mechanism of homologous recombination and end joining\n\nThe severe phenotype of the mouse mutants and the highly cancer-prone human syndromes highlight the importance of homologous recombination.Mouse KU mutants display sensitivity to agents that lead to breaks in DNA, and have immunological problems because the KU proteins are involved in V(D)J recombination of antibody gene sequences.In addition, these mutants display poor development, several features of premature ageing and increased apoptosis of postmitotic neurons in the developing brain.Mice with defects in DNA-PK cs (SCID mice) display a similar but generally milder phenotype.In contrast, XRCC4-and ligase IV-knockout mice seem more severe, with late embryonic lethality resulting from massive ATM-and p53-dependent neuronal apoptosis 33,38 ."
+            },
+            {
+                "document_id": "7a451204-390c-4ff2-8a1d-b4de62b73503",
+                "section_type": "main",
+                "text": "Mamm Genome.  2006; 17:220–229.  [PubMed: 16518689]\n72.  Romanoski CE, et al.  Systems genetics analysis of gene-by-environment interactions in human\ncells.  Am J Hum Genet.  2010; 86:399–410.  [PubMed: 20170901]\n73.  Myers S, Freeman C, Auton A, Donnelly P, McVean G. A common sequence motif associated\nwith recombination hot spots and genome instability in humans.  Nature Genet.  2008; 40:1124–\n1129.  [PubMed: 19165926]\n74.  Myers S, et al.  Drive against hotspot motifs in primates implicates the PRDM9 gene in meiotic\nrecombination.  Science.  2010; 327:876–879.  [PubMed: 20044541]\n75.  Cordell HJ.  Detecting gene-gene interactions that underlie human diseases.  Nature Rev Genet.\n 2009; 10:392–404."
+            },
+            {
+                "document_id": "d4fb56e4-06ab-4c01-b7a0-a193c4a40800",
+                "section_type": "main",
+                "text": "\n\nOrthologous chromosomes between baboon and human"
+            },
+            {
+                "document_id": "748cfe7e-e4f2-453f-8575-50dfe84e2538",
+                "section_type": "main",
+                "text": "\n\nThis picture poses more questions than it seeks to answer.Is the grouping of the regions by product rather than by type of region correct?Given that the recombina- tion fraction between HLA-A and HLA-B is of the order of .08%,and that this is likely to represent a distance of at least hundreds of thousands of nucleotides, how are the pieces put together over such relatively long distances?Is it possible that regions of the DNA loop out, so that transcripts can be made directly from noncon- tiguous DNA sequences, the loops being held in place by small RNAs as suggested for the control of splicing by Steitz, and her colleagues [24] and by others [25]?If these small RNAs are coded for well outside the HLA region, does this provide a mechanism for control of expression of products by unlinked genes, as may be the case for one of the constituent polypeptides of the HLA-DR product?What might be the nature of the signals that control which of a multiple set of alternative regions is expressed by any given chromosome?"
+            },
+            {
+                "document_id": "e4541c0c-53fb-4c2c-b550-40728c356549",
+                "section_type": "main",
+                "text": "\n\nFigure 4 Schematic depiction of proposed mechanisms for observed intrachromosomal rearrangements.The blue and red arrows indicate the orientation of the integrated plasmid loci and the recovered mouse sequences, respectively, on the original non-rearranged chromosome (left column).All four combinations are given for an arbitrarily orientated chromosome (green line).The middle column shows how two breakpoints (lightning signs) could lead to the inversion or deletion of the encompassed chromosomal sequence (yellow-orange dual tone line) and result in a recoverable mutation in the right column.The last row indicates the two options for a transposition, in which either the transgene locus or the recovered mouse sequence is copied or excised (as indicated by the pink and light blue arrows) and integrates in the breakpoint at the other location."
+            },
+            {
+                "document_id": "f08c0391-2d72-491c-a472-5db71bf11ac8",
+                "section_type": "main",
+                "text": "\n\nFIGURE 3. Telomere arrays of chicken and human chromosomes: the chicken genome contains more telomere sequence than the human genome.Chicken (a) and human (b) metaphase chromosomes and interphase cells hybridized with a telomeric sequence-peptide nucleic acid (PNA)-fluorescein probe.Human and chicken slide preparations were processed, and images were captured using the same parameters.Qualitatively, the telomere-positive fluorescent signals (white spots) from chicken cells and chromosomes have greater intensity than those of human (4′,6 diamidino-2-phenylindole, DAPI counterstain)."
+            },
+            {
+                "document_id": "e4541c0c-53fb-4c2c-b550-40728c356549",
+                "section_type": "main",
+                "text": "\n\nAs mentioned above, by taking into account that for a genome rearrangement to be detected, the 5Ј plasmid sequence of the breakpoint in lacZ must remain intact and end immediately in front of the recovered mouse sequence, the simplest intrachromosomal mutation that could have taken place was inferred (Fig. 4).Rearrangements with breakpoints in the mouse genome on either site of the integrated plasmid concatamer, but with reversely orientated sequences, could be inversions (Fig. 4).Rearrangements in the direction of the integrated plasmids, proximal for chromosome 3 and distal for chromosome 4 (Fig. 3), with similarly orientated breakpoints in the mouse genome, could be deletions (Fig. 4).Rearrangements in the reverse direction of the integrated plasmids, with reversely orientated mouse sequences, are more complicated and might be owing to transpositions (Fig. 4).According to these schemes, half of the intrachromosomal rearrangements would have been inversions, whereas deletions and transpositions each made up one fourth (Fig. 3).Alternatively, these rearrangements could be explained by translocations involving the transgene clusters integrated on either the homolog or the other chromosome."
+            },
+            {
+                "document_id": "ab0a3234-c3b3-46be-8954-01eda9bc962e",
+                "section_type": "main",
+                "text": "Chromosomal context of human NORs\n\nHuman NORs are positioned on the short arms of the acrocentric chromosomes that still remain unsequenced and thus missing from the current human genome draft, GRCh38.p7.Seeking an understanding of the chromosomal context of human NORs and to identify potential NOR regulatory elements, my laboratory has begun to characterize the sequences on both proximal (centromeric) and distal (telomeric) sides of the rDNA arrays (Fig. 3A; Floutsakou et al. 2013).Building on earlier reports of sequences distal and proximal to the rDNA array on HSA21 and HSA22, respectively (Worton et al. 1988;Sakai et al. 1995;Gonzalez and Sylvester 1997), 207 kb of sequence immediately proximal and 379 kb distal to rDNA arrays have been reported recently (Floutsakou et al. 2013).Consensus proximal junction (PJ) and distal junction (DJ) sequences were constructed mostly from chromosome 21 BACs (bacterial artificial chromosomes).Comparison of these sequences with BACs and cosmids derived from the other acrocentrics revealed that the PJ and DJ sequences are, respectively, ∼95% and 99% identical between all five acrocentric chromosomes.Conservation of DJ sequences among the acrocentrics is consistent with frequent recombination between the rDNA arrays on each of the acrocentric chromosomes (Worton et al. 1988).However, conservation of PJ sequences suggests that there must also be frequent recombination events in the interval between the centromere and rDNA arrays.Proximal sequences are almost entirely segmentally duplicated, similar to the regions bordering centromeres.Consequently, they are unlikely to contain any specific elements that would regulate the activity of the linked NOR.In contrast, the distal sequence is predominantly unique to the acrocentric short arms and is dominated by a very large inverted repeat.Each arm of the inverted repeat is >100 kb, and they share an average sequence identity of 80%.There is a large (∼40-kb) block of a 48base-pair (bp) satellite repeat, CER, at the distal end of the DJ (Fig. 3A).CER blocks are found distal to the rDNA on all acrocentric chromosomes, with additional pericentromeric blocks on chromosomes 14 and 22. Finally, there are two blocks of a novel 138-bp tandem repeat, ACRO138, present within the DJ."
+            },
+            {
+                "document_id": "b04f2221-de28-4c4b-893e-9da982ff864c",
+                "section_type": "main",
+                "text": "However, excluding some cases, recombination\nsuppression occurs in a small genomic tract\nwhere these genes are located, and it does\nnot extend over most of the sex chromosome\npair, as occurs in mammals and birds (Bergero\nand Charlesworth, 2009).  It is not clear if this\nsuppression occurs by the presence of inversions or as a modulation of the recombination\nmechanism itself, but both could be involved\n(Bergero and Charlesworth, 2009).  Evidence of\nrecombination in the SD region in sex reversal\nindividuals supports the second hypothesis."
+            },
+            {
+                "document_id": "3dfe0ec3-b3a6-4a08-8929-e54cab3ec262",
+                "section_type": "main",
+                "text": "\n\nCells in G1 have only the homologous chromosome for recombination repair.However, this may be difficult to find in the complex genome.Moreover, it is potentially dangerous as a template for repair as it may lead to homozygosity for recessive mutations.As an alternative, the end-joining reaction simply links ends of a DSB together, without any template, using the end-binding KU70/80 complex and DNA-PK cs , followed by ligation by XRCC4-ligase4 (reviewed by 27,33; see the right panel of the figure, stages V-VII).The function of KU70/80 might involve end protection and approximating the ends, in addition to a signalling function by DNA-PK cs .End joining may be further facilitated when the ends are still held together through nucleosomes or other structures.End joining is sometimes associated with gain or loss of a few nucleotides if internal microhomologies are used for annealing before sealing.This implies the involvement of DNA polymerases and/or nucleases.Note that the KU complex is also involved in telomere metabolism 27,62 .found to be lethal 34 .Inactivation of ATR by itself is inviable already at the blastocyst stage.Inactivation of BRCA1 and BRCA2 in mice is also embryonically lethal; cell lines display defects in homologous recombination [35][36][37] ."
+            },
+            {
+                "document_id": "9d82958a-45b0-4f1d-b765-38d018e4b140",
+                "section_type": "main",
+                "text": "\n\nFigure 3 Intermediates and chromosome structural alterations, as observed by different techniques. (a) Replication fork stalling, as monitored by 2D-gel electrophoresis and Southern analysis in yeast (for details about the technique, see Reference 161). (b) Slower human replication forks covering shorter DNA synthesis tracks, as determined by incorporation of IdU and CldU via DNA combing (52), which permits visualization of the process of replication on DNA fibers. (c) Accumulation of double-strand breaks (DSBs) or replicative stress, as inferred by γH2AX foci or by γH2AX pan staining, respectively, in human cells. (d ) DSBs or ssDNA (single-stranded DNA) gaps as seen directly by nuclear \"comet tails\" via single-cell electrophoresis assays in human cells (52). (e) Sister-chromatid exchanges (SCEs), as determined by Giemsa staining in human cells (207). ( f ) Hyper-recombination, as determined by colony sectoring in yeast (5). ( g) Gross chromosomal rearrangements (GCRs), as determined by spectral karyotyping in mouse cells (118). (h) Translocations, as visualized by pulse-field gel electrophoresis in yeast (168). (i ) Fragile sites, as detected by mitotic spreads in human cells (109). ( j) Telomere fusions, as determined by CO-FISH (chromosome-orientation fluorescent in situ hybridization) in mouse cells (124). (k) Anaphase bridges, presumably resulting from unfinished replication, dicentric chromosomes, and sister-chromatid nondisjunction, as detected by fluorescence microscopy in mouse cells.Arrows indicate the specific structural alterations referred to in each panel; in panel h, closed and open arrows indicate the position where the translocated or missing parental chromosome migrate or should migrate, respectively.When necessary, a normal control is shown on top of the panel, with the exception of panel a, which is shown on the left.Detailed description of each technique can be found in the references provided.Photos are from the laboratories of A. Nussenzweig ( g), A. Losada (k), M. Blasco ( j), L. Tora (i ), and ours (all others).Abbreviations: HR, homologous recombination; NHEJ, nonhomologous end-joining."
+            },
+            {
+                "document_id": "8604652e-2477-4552-8f43-f5f19e421df2",
+                "section_type": "main",
+                "text": "Classification of common conserved sequences in mammalian\nintergenic regions.  Hum.  Mol.  Genet.  2002, 11, 669–674.\n 25.  Zhu, L.; Swergold, G.D.; Seldin, M.F.  Examination of sequence homology between human\nchromosome 20 and the mouse genome: Intense conservation of many genomic elements.  Hum.  Genet.\n 2003, 113, 60–70.\n 26.  Pevzner, P.; Tesler, G. Human and mouse genomic sequences reveal extensive breakpoint reuse in\nmammalian evolution.  Proc.  Natl.  Acad.  Sci.  USA 2003, 100, 7672–7677.\n 27.  Christmann, R.B. ; Sampaio-Barros, P.; Stifano, G.; Borges, C.L. ; de Carvalho, C.R. ; Kairalla, R.;\nParra, E.R. ; Spira, A.; Simms, R.; Capellozzi, V.L. ; et al."
+            },
+            {
+                "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                "section_type": "main",
+                "text": "Nature\nGenet 1:222–225\n55.  Foote S, Vollrath D, Hilton A, Page DC (1992) The human Y chromosome: overlapping DNA clones spanning the euchromatic region.  Science 258:60–66\n56.  Chumakov IM, Rigault P, Le Gall I et al (1995) A YAC contig map of the human\ngenome.  Nature 377:175–297\n57.  Hudson TJ, Stein LD, Gerety SS et al (1995) An STS-based map of the human\ngenome.  Science 270:1945–1954\n58.  Coffey AJ, Roberts RG, Green ED et al (1992) Construction of a 2.6-Mb contig in\nyeast artificial chromosomes spanning the human dystrophin gene using an STSbased approach.  Genomics 12:474–484\n59."
+            },
+            {
+                "document_id": "9ee491f4-5f16-4cb2-b803-54f2fdee1dba",
+                "section_type": "main",
+                "text": "\n\nIn humans, the pericentromeric region of chromosome 9 is densely packed with segmental genomic duplications (segdups) and is prone to microdeletions and microduplications. 5In order to evaluate this region for microdeletions and microduplications in family T, we screened genomic DNA from affected individual II-7 by arrayCGH with the Nimblegen HD2 platform with the previously described CHP-SKN sample 6 as the reference.Data were normalized and CNVs were called by identifying regions where Z-scores consistently deviated from the diploid mean.At 9q21.11, a genomic duplication of ~270 kb was apparent in the genomic DNA of II-7 (Figure 1D).The Genomic duplications may or may not be in tandem with their parent segment and may be either in the same or inverted orientation. 7We developed primers that would uniquely amplify genomic DNA with the duplication under each of these conditions.Forward (5 0 -CCCAGCAGA AGCAATGGTGGTAGCC-3 0 ) and reverse (5 0 -GGTGGTGAA TCCAAAAACACAAGAACAAAGTC-3 0 ) primers diagnostic for a tandem inverted duplication (Figure 2A) yielded products of expected size in family T relatives with hearing loss, but yielded no product in unaffected family T relatives (Figure 2B).Genotypes of all 58 participating relatives in family T indicated that the tandem inverted duplication was coinherited with hearing loss.The duplication spans approximately positions 71,705,804 to 71,974,823 (hg19) on chromosome 9 for a size of ~269,023 bp.The duplication includes the entire locus for the tight junction protein TJP2, which spans positions 71,788,971 to 71,870,124 (hg19)."
+            },
+            {
+                "document_id": "3dfe0ec3-b3a6-4a08-8929-e54cab3ec262",
+                "section_type": "main",
+                "text": "371\n\nA tentative scenario for the homologousrecombination reaction is depicted in the left panel of the figure.To promote strand invasion into homologous sequences, the 5፱-3፱ exonuclease activity of the RAD50/MRE11/NBS1 complex (also a substrate for ATM phosphorylation) exposes both 3፱ ends 30 (I).RPA facilitates assembly of a RAD51 nucleoprotein filament that probably includes RAD51-related proteins XRCC2, XRCC3, RAD51B, C and D. RAD52 stimulates filament assembly (II).RAD51 has, like its Escherichia coli RecA counterpart, the ability to exchange the single strand with the same sequence from a double-stranded DNA molecule.Correct positioning of the sister chromatids by cohesins probably facilitates the identification of a homologous sequence.A candidate for the complex chromatin transactions associated with these DNA gymnastics is RAD54, a member of the SWI/SNF family of DNA-dependent ATPases.After identification of the identical sister chromatid sequence, the intact double-stranded copy is used as a template to properly heal the broken ends by DNA synthesis (III).Finally, the so-called Hollidayjunctions are resolved by resolvases 27,33,60 (IV).Homologous recombination involves the simultaneous action of large numbers of the same molecules, which are found to be concentrated in radiation-induced nuclear foci.These depend on, and also include, the BRCA1 and BRCA2 proteins 36 .Recent evidence implicates BRCA2 directly or indirectly in nuclear translocation of RAD51 (ref.61)."
+            },
+            {
+                "document_id": "ab0a3234-c3b3-46be-8954-01eda9bc962e",
+                "section_type": "main",
+                "text": "\n\nThe conservation of DJ sequence between the five human acrocentric chromosomes provides a unique opportunity to visualize NORs by FISH.Whereas the rDNA content of NORs can vary greatly, probing of human metaphase chromosome spreads with a DJ BAC results in signal that is consistent between NORs (Floutsakou et al. 2013).Using this probing scheme, it was observed that in most human cell lines analyzed, including multiple primary lines, at least one and sometimes as many as four of the NORs present have very little or no detectable rDNA (C van Vuuren and B McStay, unpubl. ).Many studies have used silver staining of metaphase spreads prepared from stimulated human peripheral blood lymphocytes to determine how many NORs are active in normal human cells.The number of active NORs ranges from seven to 10, with an average of eight (Heliot et al. 2000).Possibly, NORs with low rDNA content are active but fall below a detection threshold in silver staining.At this point, it is worth considering the distribution of active versus silent rDNA repeats in humans and other mammals.If 50% of rDNA repeats are truly repressed, there are insufficient \"silent\" NORs to house them.We must conclude that active NORs are a mosaic of active and silent repeats."
+            },
+            {
+                "document_id": "e4541c0c-53fb-4c2c-b550-40728c356549",
+                "section_type": "main",
+                "text": "\n\nOne possible explanation for the high number of genome rearrangements observed in this present study is that some or even most of the events scored by us as genome rearrangements are artifacts of the procedure applied to recover the mutant plasmids (Fig. 1).Although it is impossible to completely rule this out, we have addressed the possibility of artifacts extensively in a previous paper in which various control experiments had been performed on plasmids grown in E. coli, mixed with nontransgenic mouse genomic DNA, and mock-rescued into E. coli.Such experiments generally indicated significantly lower mutation frequencies in E. coli than in the mouse and no evidence for genome rearrangements as indicated by a mouse sequence at a lacZ breakpoint (Dolle ´et al. 1999b).Also, enhanced instability caused by the artificial nature of the lacZ-plasmid cluster in the mouse genome is unlikely to be responsible for the observed mutations.Indeed, neither the mutation frequencies nor their spectra are dramatically different from results reported with endogenous reporter genes such as HPRT, APRT, or HLA.Mutation frequencies at these loci were generally in the same range as our own values and also indicated a significant fraction of all mutations caused by genome rearrangements (Grist Significance between age groups within organs for genome rearrangements using the Wilcoxon rank sum test.et al. 1992;Dempsey et al. 1993;Stambrook et al. 1996;Albertini 2001).In general, mutation frequencies at HPRT were among the lowest, possibly because of selection against HPRT mutant lymphocytes in vivo.Interestingly, although virtually all results obtained with HPRT and other endogenous reporters involved lymphocytes, in a study using human kidney cells, significantly higher mutation frequencies were found, that is, up to ∼4 ‫ן‬ 10 ‫4מ‬ , than in lymphocytes (Martin et al. 1996;Colgin et al. 2002).This could reflect a significantly lower selection pressure operating on kidney cells than in lymphocytes.About 15% of these HPRT mutations were genome rearrangements such as deletions.Based on the 44-kb target size of HPRT, a similar extrapolation as performed for the lacZ-reporter gene resulted in up to four genome rearrangements per kidney cell, which might be an underestimate owing to the lethality of such events at this X-linked locus.Preliminary data on the same lacZ-reporter construct, but now integrated as a single copy transgene, in Drosophila show a similar or even higher frequency of genome rearrangements, also indicating that the concatamer of constructs in the current mouse model is not intrinsically less stable than a single copy transgene.Finally, the observed organ specificities and age-related increase make it highly unlikely that a significant fraction of the mutants scored in our system as genome rearrangements are artifacts."
+            },
+            {
+                "document_id": "ab37ae93-c6dd-41a2-a9d0-35666249c057",
+                "section_type": "main",
+                "text": "\n\nUnfortunately, flanking regions of 80 bp in length, that could be synthesized as oligonucleotide primers and used in a one-step PCR strategy as in S. cerevisiae (Baudin et al. 1993;Lorenz et al. 1995), appear to be insufficient to allow efficient homologous recombination in U. maydis (A. Brachmann, unpublished).Therefore we designed primers to amplify flanking regions for homologous recombination that are between 0.8 and 1 kb in length.Flanking sequences of this length have been shown to be sufficient to generate gene disruption mutants in eight different cases in two wild type strains each.The rate of homologous integration varied between 3% and 40%, with an average of 13% (P.Becht and M. Feldbru¨gge, unpublished).Using the SfiI sites that are introduced by PCR, the flanking regions can be combined with any gene replacement insert from our collection."
+            },
+            {
+                "document_id": "bd0f30e8-81e1-4553-bf88-762bc49197a3",
+                "section_type": "main",
+                "text": "\n\nEven with a large amount of human genomic DNA surrounding the repeat, the third characteristic (range of amplifications) remains moderate in our models, in the mice carrying 45 CAG in the AR YAC (44) and in the transgenic mice carrying 78 CAG in the DRPLA gene (45).In all CAG repeat models, the range of amplification is smaller in mice and there is often a tendency towards contraction after female transmissions.Using a large repeat surrounded by extensive human genomic flanking sequences, we obtained a higher range of expansions, and CTG repeat instability was remarkably similar in its characteristics and dynamics to the CTG repeat instability observed in DM patients.However, even with > 300 CTG, the largest amplification observed in a single generation was 60 CTG.Enlargements of several hundred repeats (or 'big jumps'), which are observed in DM families, were not observed in mice.If intergenerational instability results from the mosaicism observed in the germline, with enlargement of the CTG repeat throughout life, then the lower level of amplification in mice may result from their shorter reproductive life-span, as suggested previously (45).Alternatively, the mechanisms involved in trinucleotide repeat instability may act at a greater repeat length in mice than in humans.The DNA repair system may be more efficient and the repeat size threshold for 'big jumps' may be higher in mice.We found a negative correlation between the size of the repeat and the range of expansions after male but not after female transmission.Therefore, we will continue to breed DM300 transgenic females to determine the extent to which the repeat can be expanded in mouse and whether a threshold can be reached to obtain big jumps in amplification."
+            },
+            {
+                "document_id": "f0db8a37-76fc-4eaf-a667-4d2422ecc32f",
+                "section_type": "main",
+                "text": "\n\nFigure 1.The density of interspersed repeats and processed pseudogenes in (a) the mouse and (b) the human genomes.Pseudogene and the repeats are grouped according to the G þ C content of the surrounding 100-kb DNA.TRENDS in Genetics"
+            },
+            {
+                "document_id": "9588738f-b0d2-4b37-9554-f0699a66c4fb",
+                "section_type": "main",
+                "text": "[PMID: 19426536]\nWong AC, Shkolny D, Dorman A, Willingham D, Roe BA,\nMcDermid HE.  Two novel human RAB genes with near\nidentical sequence each map to a telomere-associated region:\nthe subtelomeric region of 22q13.3 and the ancestral telomere\nband 2q13.  Genomics 1999; 59:326-34.  [PMID: 10444334]\nMah N, Stoehr H, Schulz HL, White K, Weber BH.\n Identification of a novel retina-specific gene located in a\nsubtelomeric region with polymorphic distribution among\nmultiple human chromosomes.  Biochim Biophys Acta 2001;\n1522:167-74.  [PMID: 11779631]\nMalone K, Sohocki MM, Sullivan LS, Daiger SP.  Identifying\nand mapping novel retinal-expressed ESTs from humans.  Mol\nVis 1999; 5:5."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "Proc Natl Acad Sci U S A 102, 4795–4800.\n Martin, J., Han, C., Gordon, L. A. et al.  (2004).  The sequence and analysis of duplication-rich\nhuman chromosome 16.  Nature 432, 988–994.\n Mattick, J. S. (2004).  RNA regulation: a new genetics?  Nat Rev Genet 5, 316–323.\n Mayor, C., Brudno, M., Schwartz, J. R. et al.  (2000).  VISTA: visualizing global DNA sequence\nalignments of arbitrary length.  Bioinformatics 16, 1046–1047.\n McDonald, J. H. and Kreitman, M. (1991).  Adaptive protein evolution at the Adh locus in\nDrosophila.  Nature 351, 652–654.\n Miles, C., Elgar, G., Coles, E. et al.  (1998)."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "Proc Natl Acad Sci U S A 102, 4795–4800.\n Martin, J., Han, C., Gordon, L. A. et al.  (2004).  The sequence and analysis of duplication-rich\nhuman chromosome 16.  Nature 432, 988–994.\n Mattick, J. S. (2004).  RNA regulation: a new genetics?  Nat Rev Genet 5, 316–323.\n Mayor, C., Brudno, M., Schwartz, J. R. et al.  (2000).  VISTA: visualizing global DNA sequence\nalignments of arbitrary length.  Bioinformatics 16, 1046–1047.\n McDonald, J. H. and Kreitman, M. (1991).  Adaptive protein evolution at the Adh locus in\nDrosophila.  Nature 351, 652–654.\n Miles, C., Elgar, G., Coles, E. et al.  (1998)."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "Proc Natl Acad Sci U S A 102, 4795–4800.\n Martin, J., Han, C., Gordon, L. A. et al.  (2004).  The sequence and analysis of duplication-rich\nhuman chromosome 16.  Nature 432, 988–994.\n Mattick, J. S. (2004).  RNA regulation: a new genetics?  Nat Rev Genet 5, 316–323.\n Mayor, C., Brudno, M., Schwartz, J. R. et al.  (2000).  VISTA: visualizing global DNA sequence\nalignments of arbitrary length.  Bioinformatics 16, 1046–1047.\n McDonald, J. H. and Kreitman, M. (1991).  Adaptive protein evolution at the Adh locus in\nDrosophila.  Nature 351, 652–654.\n Miles, C., Elgar, G., Coles, E. et al.  (1998)."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "Proc Natl Acad Sci U S A 102, 4795–4800.\n Martin, J., Han, C., Gordon, L. A. et al.  (2004).  The sequence and analysis of duplication-rich\nhuman chromosome 16.  Nature 432, 988–994.\n Mattick, J. S. (2004).  RNA regulation: a new genetics?  Nat Rev Genet 5, 316–323.\n Mayor, C., Brudno, M., Schwartz, J. R. et al.  (2000).  VISTA: visualizing global DNA sequence\nalignments of arbitrary length.  Bioinformatics 16, 1046–1047.\n McDonald, J. H. and Kreitman, M. (1991).  Adaptive protein evolution at the Adh locus in\nDrosophila.  Nature 351, 652–654.\n Miles, C., Elgar, G., Coles, E. et al.  (1998)."
+            },
+            {
+                "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                "section_type": "main",
+                "text": "Kim UJ, Shizuya H, de Jong, PJ, Birren B, and Simon MI (1992) Stable propagation of cosmid sized human DNA inserts in an F factor based vector.  Nucleic Acids\nRes 20:1083–1085\n17.  Hoskins RA, Nelson CR, Berman BP et al (2000) A BAC-based physical map of\nthe major autosomes of Drosophila melanogaster.  Science 287:2271–2274\n18.  Morton NE.  (1991) Parameters of the human genome Proc Natl Acad Sci USA\n88:7474–6\n19. International Human Genome Sequencing Consortium (2001) Initial sequencing\nand analysis of the human genome.  Nature 409:860–921\n20."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "(2004) were selected, from chromosome\n21, on the basis of a simple threshold identity in man to mouse alignment, and also\non the ability to PCR amplify homologous sequences from 14 mammalian species.\n 134\n\nCH 6 COMPARATIVE GENOMICS\n\nConsequently, these sequences should represent the subset of CNGs that both have\nthe highest nucleotide identity and are the most constrained through mammalian\nevolution.  Ironically, a whole-genome analysis of non-coding conservation has since\nshown that human chromosome 21 is the only autosome devoid of so-called ultraconserved elements (Bejerano et al. , 2004)."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "(2004) were selected, from chromosome\n21, on the basis of a simple threshold identity in man to mouse alignment, and also\non the ability to PCR amplify homologous sequences from 14 mammalian species.\n 134\n\nCH 6 COMPARATIVE GENOMICS\n\nConsequently, these sequences should represent the subset of CNGs that both have\nthe highest nucleotide identity and are the most constrained through mammalian\nevolution.  Ironically, a whole-genome analysis of non-coding conservation has since\nshown that human chromosome 21 is the only autosome devoid of so-called ultraconserved elements (Bejerano et al. , 2004)."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "(2004) were selected, from chromosome\n21, on the basis of a simple threshold identity in man to mouse alignment, and also\non the ability to PCR amplify homologous sequences from 14 mammalian species.\n 134\n\nCH 6 COMPARATIVE GENOMICS\n\nConsequently, these sequences should represent the subset of CNGs that both have\nthe highest nucleotide identity and are the most constrained through mammalian\nevolution.  Ironically, a whole-genome analysis of non-coding conservation has since\nshown that human chromosome 21 is the only autosome devoid of so-called ultraconserved elements (Bejerano et al. , 2004)."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "(2004) were selected, from chromosome\n21, on the basis of a simple threshold identity in man to mouse alignment, and also\non the ability to PCR amplify homologous sequences from 14 mammalian species.\n 134\n\nCH 6 COMPARATIVE GENOMICS\n\nConsequently, these sequences should represent the subset of CNGs that both have\nthe highest nucleotide identity and are the most constrained through mammalian\nevolution.  Ironically, a whole-genome analysis of non-coding conservation has since\nshown that human chromosome 21 is the only autosome devoid of so-called ultraconserved elements (Bejerano et al. , 2004)."
+            },
+            {
+                "document_id": "bd0f30e8-81e1-4553-bf88-762bc49197a3",
+                "section_type": "main",
+                "text": "\n\nIn all mouse models generated so far, the mutability of the CAG/CTG repeat appears to be strongly correlated with the size of the repeat but also with the presence of human flanking sequences.Long repeats (>100 CAG/CTG) are very unstable in mice (40,41,46); however, human flanking sequences seem to be necessary to reproduce instability for moderate amplifications such as 55 CTG in our mice, 45 CAG in the YAC carrying the SBMA gene or 78 CAG in the cosmid carrying the DRPLA gene (39,44,45).It has been observed that, for the CAG repeat involved in Huntington's disease (HD), the 48 repeats carried by a 4.6 kb fragment of human genomic flanking DNA are moderately unstable in transgenic mice, with 2% of meioses resulting in repeat changes.Interestingly, this 48 CAG repeat shows a similar frequency of mutation in knock-in experiments and a larger repeat of 109 CAG has a higher mutation frequency (73%) (46).These results also demonstrate the determinant effect of the size of the repeat for trinucleotide repeat mutability.In addition, comparison of these knock-in models with transgenic mice carrying stable 79 CAG repeats (37) suggests that, to some extent, the mouse hd cis-sequences allow some mutability of the CAG repeat.Such mutability probably depends on cross-species conservation of sequences and/or functional elements (like origin of replication) involved in the instability mechanisms.This crossspecies conservation may differ for the various loci involved in trinucleotide diseases."
+            },
+            {
+                "document_id": "e074ba47-cd7a-4bb2-8bcb-9a15da69cc2d",
+                "section_type": "main",
+                "text": "Effect of SNPs overlapping p53-RE half-sites\nUsing the p53-REs as a test case, we sought to assess the impact of human non-coding\nsingle nucleotide polymorphisms (SNPs) on the p53-RE transactivation capability.  To do\nthis, using the UCSC genome browser [99], we made an intersection of 199 validated\np53-REs and human non-coding SNPs.  There were 36 non-coding SNPs overlapping\nwith a known validated p53-RE (Table 2).  Of these 33 overlapped with dimers, out of\nwhich 10 SNPs were predicted to impact the transactivation capacity by our predictor."
+            },
+            {
+                "document_id": "ab0a3234-c3b3-46be-8954-01eda9bc962e",
+                "section_type": "main",
+                "text": "\n\nFigure 3.The chromosomal context of human NORs located on acrocentric short arms. (A) Schematic human acrocentric chromosome short arm showing the NOR (rDNA array), expanded below into rDNA repeats, and the PJ (orange) and DJ (green) regions.The DJ region is further expanded to show the location of inverted repeats (light green arrows), DJ promoters and transcripts, Acro138 repeat blocks (red), and CER satellite (blue). (B) Cartoonshowing the transition from normal nucleolar organization to segregated nucleolar organization in response to AMD treatment or the introduction of rDNA double-strand breaks (DSBs).rDNA (red) retreats from the nucleolar interior (black) to the nucleolar periphery, forming caps adjacent to DJ sequences (green) that are embedded in PNH (dark blue)(Floutsakou et al. 2013;van Sluis and McStay 2015)."
+            },
+            {
+                "document_id": "7a7773ed-2548-4297-86ad-b7ce115448e0",
+                "section_type": "main",
+                "text": "At the recombination joint points formed at the site of deletion, the IS-elements (or other transposable genetic elements), or\nrepeated sequences have been found in different species of bac-\n\nG. B. Smirnov\n\nteria (13, 45).  This means that the integrations of genetic material and deletions are facilitated by the listed types of nucleotide\nsequences forming the preferable recombination sites."
+            },
+            {
+                "document_id": "ad14b0c4-2a38-411b-9bb1-cacf9203f29d",
+                "section_type": "main",
+                "text": "At the recombination joint points formed at the site of deletion, the IS-elements (or other transposable genetic elements), or\nrepeated sequences have been found in different species of bac-\n\nG. B. Smirnov\n\nteria (13, 45).  This means that the integrations of genetic material and deletions are facilitated by the listed types of nucleotide\nsequences forming the preferable recombination sites."
+            },
+            {
+                "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                "section_type": "main",
+                "text": "Shao Z, Zhao H, Giver L, Arnold FH (1998) Random-priming in vitro recombination: an effective tool for directed evolution.  Nucleic Acids Res 26:\n681–683\n18.  Volkov AA, Shao Z, Arnold FH (1999) Recombination and chimeragenesis by in\nvitro heteroduplex formation and in vivo repair.  Nucleic Acids Res 27:e18\n19.  Voigt CA, Martinez C, Wang ZG, Mayo SL, Arnold FH (2002) Protein building\nblocks preserved by recombination.  Nat Struct Biol 9:553–558\n20.  Ostermeier M, Shim JH, Benkovic SJ (1999) A combinatorial approach to hybrid\nenzymes independent of DNA homology.  Nat Biotechnol 17:1205–1209\n21."
+            }
+        ],
+        "document_id": "575BE8FB36E8D520760A31B2CAE92034",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "CENP-B&box",
+            "human&centromeres",
+            "recombination",
+            "chromosome&11",
+            "Ercc1-mutant",
+            "lacZ-plasmid",
+            "inversions",
+            "translocations",
+            "NORs",
+            "rDNA"
+        ],
+        "metadata": [
+            {
+                "object": "we show that Wnt5a rapidly represses rDNA gene transcription in breast cancer cells and generates a chromatin state with reduced transcription of rDNA by RNA polymerase I Pol I. These effects were specifically dependent on Dishevelled1 DVL1, which accumulates in nucleolar organizer regions NORs and binds to rDNA regions of the chromosome.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab1013349"
+            },
+            {
+                "object": "W22A, W22K, W22D, W22Y, and W22F substitutions were made in Munc13-1. The GFP-tagged constructs were expressed in Neuro-2a cells. Their membrane translocation in response to phorbol ester was observed in live cells by confocal microscopy. Munc13-1 translocated to the plasma membrane, the C1 domain translocated to internal membranes in response to phorbol ester. Trp-588 is important for ligand binding and translocation.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab997956"
+            },
+            {
+                "object": "results suggest that histone H1 represses recombination at the rDNA by a mechanism that is independent of the recombination pathways regulated by Sir2",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab669454"
+            },
+            {
+                "object": "during AID-induced class switch recombination, UNG in association with recombination factors may facilitate the stabilization of the S-S synapse to facilitate efficient recombination.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab243376"
+            },
+            {
+                "object": "Study found that HIF1alpha overexpression led to an enhanced betacatenin nuclear translocation, while betacatenin silencing inhibited betacatenin nuclear translocation. The enhanced betacatenin nuclear translocation induced resulted in an enhanced cell proliferation and cell invasion, an altered cell cycle distribution, decreased apoptosis, and improved nonhomologous end joining repair under normal and irradiation cond...",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab741909"
+            },
+            {
+                "object": "Beckwith-Wiedemann syndrome patients that inherited a maternal translocation or inversion of chromosome 11 also demonstrated reduced expression of the growth suppressing imprinted gene, CDKN1C.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab98104"
+            },
+            {
+                "object": "The amount of multiprotein complex UAF determines the rDNA copy number that is stably maintained. UAF ensures rDNA production not only by rDNA transcription activation but also by its copy-number maintenance.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab779628"
+            },
+            {
+                "object": "Here, recombinant fowlicidin-2 was successfully produced by E. coli recombinant expression system.The recombinant peptide exhibited high antibacterial activity against the Gram-positive and Gram-negative bacteria, and even drug-resistant strains.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab338954"
+            },
+            {
+                "object": "Our results suggest that macroscopic rate of UvrD monomer translocation is not limited by each ATPase cycle but by a slow step pause in each translocation cycle that occurs after four to five rapid 1 nt translocation steps.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab563146"
+            },
+            {
+                "object": "this study shows that Sox2 is expressed in activated B cells, but almost exclusively in those that have undergone IgH class switch recombination, enforced expression of Sox2 in splenic B cells severely inhibits AID expression and IgH class switch recombination, and that deletion of Sox2 increases the frequency of IgH:c-Myc translocations",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab949995"
+            }
+        ],
+        "question": "What about recombination in human centromeres?",
+        "subquestions": null,
+        "task_id": "575BE8FB36E8D520760A31B2CAE92034",
+        "usage": {
+            "chatgpt": 8855,
+            "gpt-4": 5918,
+            "gpt-4-turbo-preview": 4935
+        },
+        "user_id": 2
+    },
+    "document_id": "575BE8FB36E8D520760A31B2CAE92034",
+    "task_id": "575BE8FB36E8D520760A31B2CAE92034"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/07.json b/gnqa/paper1_eval/src/data/responses/general/experts/07.json
new file mode 100644
index 0000000..007dd4d
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/07.json
@@ -0,0 +1,394 @@
+{
+    "created_at": "2024-06-01T14:29:54.405039Z",
+    "data": {
+        "amplify": false,
+        "answer": "The text mentions the application of site-specific recombinase technology, which allows investigators to engineer genes in the mouse that will allow for the deletion, insertion, inversion, or exchange of chromosomal DNA with high fidelity. However, it does not provide specific details about recombination in the human genome.",
+        "context": {
+            "081924f4-cdcc-4fce-9223-744c6ecffe4e": [
+                {
+                    "document_id": "081924f4-cdcc-4fce-9223-744c6ecffe4e",
+                    "text": "Genome Res, 2011, 21: 1769–1776\nMattick JS, Dinger ME. The extent of functionality in the human\ngenome. HUGO J, 2013, 7, doi:10.1186/1877-6566-1187-1182\nENCODE Project Consortium, Bernstein BE, Birney E, Dunham I,\nGreen ED, Gunter C, Snyder M. An integrated encyclopedia of DNA\nelements in the human genome. Nature, 2012, 489: 57–74\nPheasant M, Mattick JS. Raising the estimate of functional human\nsequences. Genome Res, 2007, 17: 1245–1253\nHu T, Long M, Yuan D, Zhu Z, Huang Y, Huang S. The genetic\nequidistance result, misreading by the molecular clock and neutral\ntheory and reinterpretation nearly half of a century later."
+                }
+            ],
+            "33814fad-d831-46f5-b41f-ff31626a82ca": [
+                {
+                    "document_id": "33814fad-d831-46f5-b41f-ff31626a82ca",
+                    "text": "This approach enables, on the one hand, studying the process of\nmammalian evolution and, on the other hand, translational studies using model\norganisms of complex human phenotypes. Detection of regions conserved between\ndistant species points to high functional importance of these fragments of the DNA\nsequence. Human and mouse developmental lines diverged about 75 million years ago, and\never since evolutionary forces shaped the two genotypes in a different manner\n(Waterston et al. , 2002). Nevertheless, the extent of the changes is, however, small\nenough for conservation of local gene order (Waterston et al. , 2002)."
+                }
+            ],
+            "3cafb9e7-b3d9-4e8e-a727-da79282d2b14": [
+                {
+                    "document_id": "3cafb9e7-b3d9-4e8e-a727-da79282d2b14",
+                    "text": "First, the human and mouse genome projects\nelucidated the sequences of over 20,000 genes [Lander et al. ,\n2001; Venter et al. , 2001], and most are expressed in the CNS. The availability of gene sequences has allowed rapid analysis of\ncandidate human disease and disorder genes and the isolation of\nthe mouse homologues. Second, the application of site-speciﬁc\nrecombinase technology provides investigators with the opportunity to engineer genes in the mouse that will allow for the\ndeletion, insertion, inversion, or exchange of chromosomal\nDNA with high ﬁdelity (for review see Branda and Dymechi,\n2004]."
+                }
+            ],
+            "5edf84d0-c2d9-45eb-91b9-c35743b6a463": [
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text": "In some cases, structural variations, such as copy number polymorphisms,\nexist (Feuk et al. , 2006); however, because of the nature of the genome assembly\nprocess, these will invariably be collapsed into a single contig that does not reflect\nthe natural sequence. To address the technical challenges of whole-genome assembly,\nthe human genome is released as defined ‘builds’ on a quarterly basis (Lander et al. ,\n2001; reviewed in Chapter 4). The increasing complexity of processes that map\ndata to the genome implicitly involves some lag in availability of the most current\nsequence assembly."
+                },
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text": "In\npractical terms, this has meant that we acquire many fragments, from a few hundred\nbases to a few hundred kilobases in length, of a genome that must then be assembled computationally to produce a continuous sequence. In the case of the human\ngenome, two unfinished ‘draft’ sequences were produced by different methods, one\nby the International Human Genome Sequencing Consortium (IHGSC) and one by\nCelera Genomics (CG). The IHGSC began with a BAC (bacterial artificial chromosome) clone-based physical map of the genome (IHGSC, 2001)."
+                },
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text": "4\nAssembling a View of the\nHuman Genome\nColin A. M. Semple\nBioinformatics, MRC Human Genetics Unit, Edinburgh EH4 2XU, UK\n\n4.1 Introduction\nThe miraculous birth of the draft human genome sequence took place against\nthe odds. It was only made possible by parallel revolutions in the technologies\nused to produce, store and analyse the sequence data, and by the development of\nnew, large-scale consortia to organize and obtain funding for the work (Watson,\n1990). The initial flood of human sequence has subsided as the sequencing centres have sequenced genomes from other mammalian orders and beyond."
+                }
+            ],
+            "74f148ef-696c-4e25-80e5-1d44ae70540e": [
+                {
+                    "document_id": "74f148ef-696c-4e25-80e5-1d44ae70540e",
+                    "text": "\nTHE HUMAN GENOME PROJECT IS generating vast amounts of new information at breakneck speed and causing a fundamental shift in disease research.Now with the availability of a nearly complete, high-accuracy sequence of the mouse genome (7), a new and powerful paradigm for biomedical research is established.The remarkable similarity of mouse and human genomes, in both synteny and sequence, unconditionally validates the mouse as an exceptional model organism for understanding human biology.The discovery among inbred mouse strains of defined regions of high and low genomic variation inherited primarily from two ancestral Mus subspecies (6) holds great promise to make mapping and positional cloning more rapid and feasible.Haplotype maps of inbred mouse strains combined with sophisticated delineation of their phenotypic variation and gene expression patterns will enable complex trait analysis on an unprecedented scale.This issue of Journal of Applied Physiology highlights inbred strain surveys exploring phenotypic variation in drug responses [see Crabbe et al. (1) and Watters et al. (8)  in this issue].These mouse initiatives demonstrate a viable, cost-effective alternative to human research requiring family studies, population linkage analysis, or genome-wide genotyping on a multitude of individuals for association mapping."
+                }
+            ],
+            "81c3edc4-f625-45f2-bf78-e49faf118c88": [
+                {
+                    "document_id": "81c3edc4-f625-45f2-bf78-e49faf118c88",
+                    "text": "\n\nHow Many Genes are There in the Human Genome?"
+                }
+            ],
+            "b1656249-5f62-428f-8b71-7549cc2886ff": [
+                {
+                    "document_id": "b1656249-5f62-428f-8b71-7549cc2886ff",
+                    "text": "\n\nThe Landscape of Human Genome Variation"
+                }
+            ],
+            "c12e853e-4f0d-48f9-93af-15db9ad2dfae": [
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "In some cases, structural variations, such as copy number polymorphisms,\nexist (Feuk et al. , 2006); however, because of the nature of the genome assembly\nprocess, these will invariably be collapsed into a single contig that does not reflect\nthe natural sequence. To address the technical challenges of whole-genome assembly,\nthe human genome is released as defined ‘builds’ on a quarterly basis (Lander et al. ,\n2001; reviewed in Chapter 4). The increasing complexity of processes that map\ndata to the genome implicitly involves some lag in availability of the most current\nsequence assembly."
+                },
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "In\npractical terms, this has meant that we acquire many fragments, from a few hundred\nbases to a few hundred kilobases in length, of a genome that must then be assembled computationally to produce a continuous sequence. In the case of the human\ngenome, two unfinished ‘draft’ sequences were produced by different methods, one\nby the International Human Genome Sequencing Consortium (IHGSC) and one by\nCelera Genomics (CG). The IHGSC began with a BAC (bacterial artificial chromosome) clone-based physical map of the genome (IHGSC, 2001)."
+                },
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "4\nAssembling a View of the\nHuman Genome\nColin A. M. Semple\nBioinformatics, MRC Human Genetics Unit, Edinburgh EH4 2XU, UK\n\n4.1 Introduction\nThe miraculous birth of the draft human genome sequence took place against\nthe odds. It was only made possible by parallel revolutions in the technologies\nused to produce, store and analyse the sequence data, and by the development of\nnew, large-scale consortia to organize and obtain funding for the work (Watson,\n1990). The initial flood of human sequence has subsided as the sequencing centres have sequenced genomes from other mammalian orders and beyond."
+                }
+            ],
+            "da485354-fcdc-49b8-9a41-0f673610156a": [
+                {
+                    "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                    "text": "Science 291:1304–\n1351\n3. Lander ES et al (2001) Initial sequencing and analysis of the human genome. Nature 409:860–921\n4. Engle LJ, Simpson CL, Landers JE (2006) Using high-throughput SNP technologies to study cancer. Oncogene 25:1594–1601\n5. Elston RC, Anne Spence M (2006) Advances in statistical human genetics over the\nlast 25 years. Stat Med 25:3049–3080\n6. Larson GP et al (2005) Genetic linkage of prostate cancer risk to the chromosome\n3 region bearing FHIT. Cancer Res 65:805–814\n7. Botstein D, Risch N (2003) Discovering genotypes underlying human phenotypes:\npast successes for mendelian disease, future approaches for complex disease."
+                },
+                {
+                    "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                    "text": "McPherson JD, Marra M, Hillier L et al (2001) A physical map of the human\ngenome. Nature 409:934–941\n13. Burke DT, Carle GF, Olson MV. (1987) Cloning of large segments of exogenous\nDNA into yeast by means of artificial chromosome vectors. Science 236:806–812\n14. Fleischmann RD, Adams MD, White O et al (1995) Whole-genome random\nsequencing and assembly of Haemophilus influenzae Rd Science 269:496–512\n15. Arabidopsis Genome Initiative (2000) Analysis of the genome sequence of the\nflowering plant Arabidopsis thaliana. Nature 408:796–815\n16."
+                }
+            ],
+            "e17ef791-e77a-486b-a3c1-c7f037fa530c": [
+                {
+                    "document_id": "e17ef791-e77a-486b-a3c1-c7f037fa530c",
+                    "text": "\n\nT he human genome has been cracked wide open in recent years and is spilling many of its secrets.More than 100 genome wide association studies have been conducted for scores of hu man diseases, identifying hun dreds of polymorphisms that are widely seen to influence disease risk.After many years in which the study of complex human traits was mired in false claims and methodologic inconsistencies, ge nomics has brought not only com prehensive representation of com mon variation but also welcome rigor in the interpretation of sta tistical evidence.Researchers now know how to properly account for most of the multiple hypothesis testing involved in mining the ge nome for associations, and most reported associations reflect real biologic causation.But do they matter?"
+                }
+            ],
+            "f35e02a1-3314-4663-913f-38a3fc072aa8": [
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text": "In some cases, structural variations, such as copy number polymorphisms,\nexist (Feuk et al. , 2006); however, because of the nature of the genome assembly\nprocess, these will invariably be collapsed into a single contig that does not reflect\nthe natural sequence. To address the technical challenges of whole-genome assembly,\nthe human genome is released as defined ‘builds’ on a quarterly basis (Lander et al. ,\n2001; reviewed in Chapter 4). The increasing complexity of processes that map\ndata to the genome implicitly involves some lag in availability of the most current\nsequence assembly."
+                },
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text": "In\npractical terms, this has meant that we acquire many fragments, from a few hundred\nbases to a few hundred kilobases in length, of a genome that must then be assembled computationally to produce a continuous sequence. In the case of the human\ngenome, two unfinished ‘draft’ sequences were produced by different methods, one\nby the International Human Genome Sequencing Consortium (IHGSC) and one by\nCelera Genomics (CG). The IHGSC began with a BAC (bacterial artificial chromosome) clone-based physical map of the genome (IHGSC, 2001)."
+                }
+            ],
+            "fca531d0-d45b-495f-a02c-fbd437617b20": [
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "In some cases, structural variations, such as copy number polymorphisms,\nexist (Feuk et al. , 2006); however, because of the nature of the genome assembly\nprocess, these will invariably be collapsed into a single contig that does not reflect\nthe natural sequence. To address the technical challenges of whole-genome assembly,\nthe human genome is released as defined ‘builds’ on a quarterly basis (Lander et al. ,\n2001; reviewed in Chapter 4). The increasing complexity of processes that map\ndata to the genome implicitly involves some lag in availability of the most current\nsequence assembly."
+                },
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "In\npractical terms, this has meant that we acquire many fragments, from a few hundred\nbases to a few hundred kilobases in length, of a genome that must then be assembled computationally to produce a continuous sequence. In the case of the human\ngenome, two unfinished ‘draft’ sequences were produced by different methods, one\nby the International Human Genome Sequencing Consortium (IHGSC) and one by\nCelera Genomics (CG). The IHGSC began with a BAC (bacterial artificial chromosome) clone-based physical map of the genome (IHGSC, 2001)."
+                },
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "4\nAssembling a View of the\nHuman Genome\nColin A. M. Semple\nBioinformatics, MRC Human Genetics Unit, Edinburgh EH4 2XU, UK\n\n4.1 Introduction\nThe miraculous birth of the draft human genome sequence took place against\nthe odds. It was only made possible by parallel revolutions in the technologies\nused to produce, store and analyse the sequence data, and by the development of\nnew, large-scale consortia to organize and obtain funding for the work (Watson,\n1990). The initial flood of human sequence has subsided as the sequencing centres have sequenced genomes from other mammalian orders and beyond."
+                }
+            ]
+        },
+        "data_source": [
+            {
+                "document_id": "81c3edc4-f625-45f2-bf78-e49faf118c88",
+                "section_type": "main",
+                "text": "\n\nHow Many Genes are There in the Human Genome?"
+            },
+            {
+                "document_id": "3cafb9e7-b3d9-4e8e-a727-da79282d2b14",
+                "section_type": "main",
+                "text": "First, the human and mouse genome projects\nelucidated the sequences of over 20,000 genes [Lander et al. ,\n2001; Venter et al. , 2001], and most are expressed in the CNS.\n The availability of gene sequences has allowed rapid analysis of\ncandidate human disease and disorder genes and the isolation of\nthe mouse homologues.  Second, the application of site-speciﬁc\nrecombinase technology provides investigators with the opportunity to engineer genes in the mouse that will allow for the\ndeletion, insertion, inversion, or exchange of chromosomal\nDNA with high ﬁdelity (for review see Branda and Dymechi,\n2004]."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "In some cases, structural variations, such as copy number polymorphisms,\nexist (Feuk et al. , 2006); however, because of the nature of the genome assembly\nprocess, these will invariably be collapsed into a single contig that does not reflect\nthe natural sequence.  To address the technical challenges of whole-genome assembly,\nthe human genome is released as defined ‘builds’ on a quarterly basis (Lander et al. ,\n2001; reviewed in Chapter 4).  The increasing complexity of processes that map\ndata to the genome implicitly involves some lag in availability of the most current\nsequence assembly."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "In some cases, structural variations, such as copy number polymorphisms,\nexist (Feuk et al. , 2006); however, because of the nature of the genome assembly\nprocess, these will invariably be collapsed into a single contig that does not reflect\nthe natural sequence.  To address the technical challenges of whole-genome assembly,\nthe human genome is released as defined ‘builds’ on a quarterly basis (Lander et al. ,\n2001; reviewed in Chapter 4).  The increasing complexity of processes that map\ndata to the genome implicitly involves some lag in availability of the most current\nsequence assembly."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "In some cases, structural variations, such as copy number polymorphisms,\nexist (Feuk et al. , 2006); however, because of the nature of the genome assembly\nprocess, these will invariably be collapsed into a single contig that does not reflect\nthe natural sequence.  To address the technical challenges of whole-genome assembly,\nthe human genome is released as defined ‘builds’ on a quarterly basis (Lander et al. ,\n2001; reviewed in Chapter 4).  The increasing complexity of processes that map\ndata to the genome implicitly involves some lag in availability of the most current\nsequence assembly."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "In some cases, structural variations, such as copy number polymorphisms,\nexist (Feuk et al. , 2006); however, because of the nature of the genome assembly\nprocess, these will invariably be collapsed into a single contig that does not reflect\nthe natural sequence.  To address the technical challenges of whole-genome assembly,\nthe human genome is released as defined ‘builds’ on a quarterly basis (Lander et al. ,\n2001; reviewed in Chapter 4).  The increasing complexity of processes that map\ndata to the genome implicitly involves some lag in availability of the most current\nsequence assembly."
+            },
+            {
+                "document_id": "e17ef791-e77a-486b-a3c1-c7f037fa530c",
+                "section_type": "main",
+                "text": "\n\nT he human genome has been cracked wide open in recent years and is spilling many of its secrets.More than 100 genome wide association studies have been conducted for scores of hu man diseases, identifying hun dreds of polymorphisms that are widely seen to influence disease risk.After many years in which the study of complex human traits was mired in false claims and methodologic inconsistencies, ge nomics has brought not only com prehensive representation of com mon variation but also welcome rigor in the interpretation of sta tistical evidence.Researchers now know how to properly account for most of the multiple hypothesis testing involved in mining the ge nome for associations, and most reported associations reflect real biologic causation.But do they matter?"
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "In\npractical terms, this has meant that we acquire many fragments, from a few hundred\nbases to a few hundred kilobases in length, of a genome that must then be assembled computationally to produce a continuous sequence.  In the case of the human\ngenome, two unfinished ‘draft’ sequences were produced by different methods, one\nby the International Human Genome Sequencing Consortium (IHGSC) and one by\nCelera Genomics (CG).\n The IHGSC began with a BAC (bacterial artificial chromosome) clone-based physical map of the genome (IHGSC, 2001)."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "In\npractical terms, this has meant that we acquire many fragments, from a few hundred\nbases to a few hundred kilobases in length, of a genome that must then be assembled computationally to produce a continuous sequence.  In the case of the human\ngenome, two unfinished ‘draft’ sequences were produced by different methods, one\nby the International Human Genome Sequencing Consortium (IHGSC) and one by\nCelera Genomics (CG).\n The IHGSC began with a BAC (bacterial artificial chromosome) clone-based physical map of the genome (IHGSC, 2001)."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "In\npractical terms, this has meant that we acquire many fragments, from a few hundred\nbases to a few hundred kilobases in length, of a genome that must then be assembled computationally to produce a continuous sequence.  In the case of the human\ngenome, two unfinished ‘draft’ sequences were produced by different methods, one\nby the International Human Genome Sequencing Consortium (IHGSC) and one by\nCelera Genomics (CG).\n The IHGSC began with a BAC (bacterial artificial chromosome) clone-based physical map of the genome (IHGSC, 2001)."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "In\npractical terms, this has meant that we acquire many fragments, from a few hundred\nbases to a few hundred kilobases in length, of a genome that must then be assembled computationally to produce a continuous sequence.  In the case of the human\ngenome, two unfinished ‘draft’ sequences were produced by different methods, one\nby the International Human Genome Sequencing Consortium (IHGSC) and one by\nCelera Genomics (CG).\n The IHGSC began with a BAC (bacterial artificial chromosome) clone-based physical map of the genome (IHGSC, 2001)."
+            },
+            {
+                "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                "section_type": "main",
+                "text": "Science 291:1304–\n1351\n3.  Lander ES et al (2001) Initial sequencing and analysis of the human genome.\n Nature 409:860–921\n4.  Engle LJ, Simpson CL, Landers JE (2006) Using high-throughput SNP technologies to study cancer.  Oncogene 25:1594–1601\n5.  Elston RC, Anne Spence M (2006) Advances in statistical human genetics over the\nlast 25 years.  Stat Med 25:3049–3080\n6.  Larson GP et al (2005) Genetic linkage of prostate cancer risk to the chromosome\n3 region bearing FHIT.  Cancer Res 65:805–814\n7.  Botstein D, Risch N (2003) Discovering genotypes underlying human phenotypes:\npast successes for mendelian disease, future approaches for complex disease."
+            },
+            {
+                "document_id": "081924f4-cdcc-4fce-9223-744c6ecffe4e",
+                "section_type": "main",
+                "text": "Genome Res, 2011, 21: 1769–1776\nMattick JS, Dinger ME.  The extent of functionality in the human\ngenome.  HUGO J, 2013, 7, doi:10.1186/1877-6566-1187-1182\nENCODE Project Consortium, Bernstein BE, Birney E, Dunham I,\nGreen ED, Gunter C, Snyder M. An integrated encyclopedia of DNA\nelements in the human genome.  Nature, 2012, 489: 57–74\nPheasant M, Mattick JS.  Raising the estimate of functional human\nsequences.  Genome Res, 2007, 17: 1245–1253\nHu T, Long M, Yuan D, Zhu Z, Huang Y, Huang S. The genetic\nequidistance result, misreading by the molecular clock and neutral\ntheory and reinterpretation nearly half of a century later."
+            },
+            {
+                "document_id": "b1656249-5f62-428f-8b71-7549cc2886ff",
+                "section_type": "main",
+                "text": "\n\nThe Landscape of Human Genome Variation"
+            },
+            {
+                "document_id": "33814fad-d831-46f5-b41f-ff31626a82ca",
+                "section_type": "main",
+                "text": "This approach enables, on the one hand, studying the process of\nmammalian evolution and, on the other hand, translational studies using model\norganisms of complex human phenotypes.  Detection of regions conserved between\ndistant species points to high functional importance of these fragments of the DNA\nsequence.\n Human and mouse developmental lines diverged about 75 million years ago, and\never since evolutionary forces shaped the two genotypes in a different manner\n(Waterston et al. , 2002).  Nevertheless, the extent of the changes is, however, small\nenough for conservation of local gene order (Waterston et al. , 2002)."
+            },
+            {
+                "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                "section_type": "main",
+                "text": "McPherson JD, Marra M, Hillier L et al (2001) A physical map of the human\ngenome.  Nature 409:934–941\n13.  Burke DT, Carle GF, Olson MV.  (1987) Cloning of large segments of exogenous\nDNA into yeast by means of artificial chromosome vectors.  Science 236:806–812\n14.  Fleischmann RD, Adams MD, White O et al (1995) Whole-genome random\nsequencing and assembly of Haemophilus influenzae Rd Science 269:496–512\n15.  Arabidopsis Genome Initiative (2000) Analysis of the genome sequence of the\nflowering plant Arabidopsis thaliana.  Nature 408:796–815\n16."
+            },
+            {
+                "document_id": "74f148ef-696c-4e25-80e5-1d44ae70540e",
+                "section_type": "abstract",
+                "text": "\nTHE HUMAN GENOME PROJECT IS generating vast amounts of new information at breakneck speed and causing a fundamental shift in disease research.Now with the availability of a nearly complete, high-accuracy sequence of the mouse genome (7), a new and powerful paradigm for biomedical research is established.The remarkable similarity of mouse and human genomes, in both synteny and sequence, unconditionally validates the mouse as an exceptional model organism for understanding human biology.The discovery among inbred mouse strains of defined regions of high and low genomic variation inherited primarily from two ancestral Mus subspecies (6) holds great promise to make mapping and positional cloning more rapid and feasible.Haplotype maps of inbred mouse strains combined with sophisticated delineation of their phenotypic variation and gene expression patterns will enable complex trait analysis on an unprecedented scale.This issue of Journal of Applied Physiology highlights inbred strain surveys exploring phenotypic variation in drug responses [see Crabbe et al. (1) and Watters et al. (8)  in this issue].These mouse initiatives demonstrate a viable, cost-effective alternative to human research requiring family studies, population linkage analysis, or genome-wide genotyping on a multitude of individuals for association mapping."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "4\nAssembling a View of the\nHuman Genome\nColin A. M. Semple\nBioinformatics, MRC Human Genetics Unit, Edinburgh EH4 2XU, UK\n\n4.1 Introduction\nThe miraculous birth of the draft human genome sequence took place against\nthe odds.  It was only made possible by parallel revolutions in the technologies\nused to produce, store and analyse the sequence data, and by the development of\nnew, large-scale consortia to organize and obtain funding for the work (Watson,\n1990).  The initial flood of human sequence has subsided as the sequencing centres have sequenced genomes from other mammalian orders and beyond."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "4\nAssembling a View of the\nHuman Genome\nColin A. M. Semple\nBioinformatics, MRC Human Genetics Unit, Edinburgh EH4 2XU, UK\n\n4.1 Introduction\nThe miraculous birth of the draft human genome sequence took place against\nthe odds.  It was only made possible by parallel revolutions in the technologies\nused to produce, store and analyse the sequence data, and by the development of\nnew, large-scale consortia to organize and obtain funding for the work (Watson,\n1990).  The initial flood of human sequence has subsided as the sequencing centres have sequenced genomes from other mammalian orders and beyond."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "4\nAssembling a View of the\nHuman Genome\nColin A. M. Semple\nBioinformatics, MRC Human Genetics Unit, Edinburgh EH4 2XU, UK\n\n4.1 Introduction\nThe miraculous birth of the draft human genome sequence took place against\nthe odds.  It was only made possible by parallel revolutions in the technologies\nused to produce, store and analyse the sequence data, and by the development of\nnew, large-scale consortia to organize and obtain funding for the work (Watson,\n1990).  The initial flood of human sequence has subsided as the sequencing centres have sequenced genomes from other mammalian orders and beyond."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "4\nAssembling a View of the\nHuman Genome\nColin A. M. Semple\nBioinformatics, MRC Human Genetics Unit, Edinburgh EH4 2XU, UK\n\n4.1 Introduction\nThe miraculous birth of the draft human genome sequence took place against\nthe odds.  It was only made possible by parallel revolutions in the technologies\nused to produce, store and analyse the sequence data, and by the development of\nnew, large-scale consortia to organize and obtain funding for the work (Watson,\n1990).  The initial flood of human sequence has subsided as the sequencing centres have sequenced genomes from other mammalian orders and beyond."
+            },
+            {
+                "document_id": "937fe28b-dbaf-422b-a2de-9ffeafd94172",
+                "section_type": "main",
+                "text": "High copy number repeat sequences\n\nThe HGP revealed that repeat sequences account for at least 50 per cent of the human genome sequence.These repeats may be classified as (i) transposon-derived repeats, (ii) partially retroposed copies of genes (referred to as processed pseudogenes), (iii) simple sequence repeats, (iv) blocks of tandemly repeated sequences at centromeres, telomeres and the short arms of acrocentric chromosomes and (v) segmental duplications (SDs) or low copy number repeats."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "6.7 Challenges and future directions\nThere has been great progress in understanding the biology and functions encoded\nby the human genome since the first draft of a reference sequence was produced in\n2001 (Lander et al. , 2001; (Venter et al. , 2001), and much of this insight has been\ngained by comparison both within and between genomes.  However, as with many scientific endeavours, more questions arise with each increment in understanding."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "6.7 Challenges and future directions\nThere has been great progress in understanding the biology and functions encoded\nby the human genome since the first draft of a reference sequence was produced in\n2001 (Lander et al. , 2001; (Venter et al. , 2001), and much of this insight has been\ngained by comparison both within and between genomes.  However, as with many scientific endeavours, more questions arise with each increment in understanding."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "6.7 Challenges and future directions\nThere has been great progress in understanding the biology and functions encoded\nby the human genome since the first draft of a reference sequence was produced in\n2001 (Lander et al. , 2001; (Venter et al. , 2001), and much of this insight has been\ngained by comparison both within and between genomes.  However, as with many scientific endeavours, more questions arise with each increment in understanding."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "6.7 Challenges and future directions\nThere has been great progress in understanding the biology and functions encoded\nby the human genome since the first draft of a reference sequence was produced in\n2001 (Lander et al. , 2001; (Venter et al. , 2001), and much of this insight has been\ngained by comparison both within and between genomes.  However, as with many scientific endeavours, more questions arise with each increment in understanding."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "After the publication of the publicly available human genome draft in 2001, the\nIHGSC undertook the arduous task of ‘finishing’: producing a genome sequence\ncovering 99 per cent of the euchromatic regions sequenced to an accuracy of 99.99\nper cent.  On 14 April 2003, the IHGSC announced that this target had been reached;\nleaving less than 400 persistent gaps where highly repetitive sequences evaded current sequencing technology.  A steady trickle of papers in the journal Nature has\nmarked the emergence of each finished human chromosome sequence, along with\nthe annotation describing its notable features."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "After the publication of the publicly available human genome draft in 2001, the\nIHGSC undertook the arduous task of ‘finishing’: producing a genome sequence\ncovering 99 per cent of the euchromatic regions sequenced to an accuracy of 99.99\nper cent.  On 14 April 2003, the IHGSC announced that this target had been reached;\nleaving less than 400 persistent gaps where highly repetitive sequences evaded current sequencing technology.  A steady trickle of papers in the journal Nature has\nmarked the emergence of each finished human chromosome sequence, along with\nthe annotation describing its notable features."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "After the publication of the publicly available human genome draft in 2001, the\nIHGSC undertook the arduous task of ‘finishing’: producing a genome sequence\ncovering 99 per cent of the euchromatic regions sequenced to an accuracy of 99.99\nper cent.  On 14 April 2003, the IHGSC announced that this target had been reached;\nleaving less than 400 persistent gaps where highly repetitive sequences evaded current sequencing technology.  A steady trickle of papers in the journal Nature has\nmarked the emergence of each finished human chromosome sequence, along with\nthe annotation describing its notable features."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "After the publication of the publicly available human genome draft in 2001, the\nIHGSC undertook the arduous task of ‘finishing’: producing a genome sequence\ncovering 99 per cent of the euchromatic regions sequenced to an accuracy of 99.99\nper cent.  On 14 April 2003, the IHGSC announced that this target had been reached;\nleaving less than 400 persistent gaps where highly repetitive sequences evaded current sequencing technology.  A steady trickle of papers in the journal Nature has\nmarked the emergence of each finished human chromosome sequence, along with\nthe annotation describing its notable features."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "6.2.3 A varied landscape\nIn probably every measure that has been made of the human genome sequence, it has\nbeen found to be far from homogeneous.  We have already touched on the distinction\nbetween heterochromatic regions that perform roles in the packaging and segregation\nof chromosomes, from the remaining (euchromatic) regions.  Throughout the rest of\nthe euchromatic genome, there is considerable variation in gene density (the number\nof genes per unit sequence), IRE content, nucleotide and dinucleotide frequency, and\nthe observed rates of genetic recombination, nucleotide substitution, insertions and\ndeletions."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "6.2.3 A varied landscape\nIn probably every measure that has been made of the human genome sequence, it has\nbeen found to be far from homogeneous.  We have already touched on the distinction\nbetween heterochromatic regions that perform roles in the packaging and segregation\nof chromosomes, from the remaining (euchromatic) regions.  Throughout the rest of\nthe euchromatic genome, there is considerable variation in gene density (the number\nof genes per unit sequence), IRE content, nucleotide and dinucleotide frequency, and\nthe observed rates of genetic recombination, nucleotide substitution, insertions and\ndeletions."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "6.2.3 A varied landscape\nIn probably every measure that has been made of the human genome sequence, it has\nbeen found to be far from homogeneous.  We have already touched on the distinction\nbetween heterochromatic regions that perform roles in the packaging and segregation\nof chromosomes, from the remaining (euchromatic) regions.  Throughout the rest of\nthe euchromatic genome, there is considerable variation in gene density (the number\nof genes per unit sequence), IRE content, nucleotide and dinucleotide frequency, and\nthe observed rates of genetic recombination, nucleotide substitution, insertions and\ndeletions."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "6.2.3 A varied landscape\nIn probably every measure that has been made of the human genome sequence, it has\nbeen found to be far from homogeneous.  We have already touched on the distinction\nbetween heterochromatic regions that perform roles in the packaging and segregation\nof chromosomes, from the remaining (euchromatic) regions.  Throughout the rest of\nthe euchromatic genome, there is considerable variation in gene density (the number\nof genes per unit sequence), IRE content, nucleotide and dinucleotide frequency, and\nthe observed rates of genetic recombination, nucleotide substitution, insertions and\ndeletions."
+            },
+            {
+                "document_id": "0ecf5586-f80d-4b5e-8687-5a0d92423597",
+                "section_type": "main",
+                "text": "The precision and the power in human genetics will improve greatly over the\nnext several decades as full genome sequences, better human disease phenotyping, and\nelectronic health records are merged at the scale of millions of subjects and whole\nnations.  Therefore, we need to revamp experimental genetic resources in an era flooded\nin GWAS hits.  How are new and old mouse resources best repositioned to help deliver on\nthe still unmet and much more integrative promises of predictive genetics and\npersonalized precision health care?\n\n 25\nbioRxiv preprint doi: https://doi.org/10.1101/672097; this version posted July 8, 2019."
+            },
+            {
+                "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                "section_type": "main",
+                "text": "Resequencing\nCompletion of a single version of the human genome (2,3) has now provided\nthe substrates for direct comparison of individuals in both health and disease.\n Ideally, to better understand the genetic contributions to severe diseases, one\nwould obtain the entire human genome sequence for all disease-carrying individuals for comparison to unaffected control groups.  While these complete\ndata sets are not readily obtainable today, a strategy that is currently approachable is the re-sequencing of a large set of appropriate candidate genes in\nindividuals with a given disease to screen for potential causative/susceptibility\nalleles."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "The interplay between the adaptive benefits introduced by mutations and natural selection shapes the genome into\nunique patterns of genetic variations in different regions.  Therefore, investigating\nthe functional roles of these genetic variations provides a great opportunity for understanding complex common diseases, such as cancer.  The compilation of human\n\nBioinformatics for Geneticists, Second Edition."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "The interplay between the adaptive benefits introduced by mutations and natural selection shapes the genome into\nunique patterns of genetic variations in different regions.  Therefore, investigating\nthe functional roles of these genetic variations provides a great opportunity for understanding complex common diseases, such as cancer.  The compilation of human\n\nBioinformatics for Geneticists, Second Edition."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "The interplay between the adaptive benefits introduced by mutations and natural selection shapes the genome into\nunique patterns of genetic variations in different regions.  Therefore, investigating\nthe functional roles of these genetic variations provides a great opportunity for understanding complex common diseases, such as cancer.  The compilation of human\n\nBioinformatics for Geneticists, Second Edition."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "The interplay between the adaptive benefits introduced by mutations and natural selection shapes the genome into\nunique patterns of genetic variations in different regions.  Therefore, investigating\nthe functional roles of these genetic variations provides a great opportunity for understanding complex common diseases, such as cancer.  The compilation of human\n\nBioinformatics for Geneticists, Second Edition."
+            }
+        ],
+        "document_id": "1A879F7DD77C0462CC12FB20F7D14486",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "human&genome",
+            "recombination",
+            "genes",
+            "CNS",
+            "site-specific&recombinase",
+            "structural&variations",
+            "copy&number&polymorphisms",
+            "genome&assembly",
+            "genome&wide&association&studies",
+            "polymorphisms"
+        ],
+        "metadata": [
+            {
+                "object": "Transient overexpression of WRKY79 in protoplasts results in up-regulation of Gene:542165, Gene:541974, Gene:100274033, Gene:542688, Gene:542150, Gene:542151, Gene:100273457, Gene:100285509, Gene:103626248, Gene:103646045, Gene:100217270, Gene:100279981, Gene:100281950, Gene:542476, Gene:542369, Gene:100281950, and Gene:542260.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab969966"
+            },
+            {
+                "object": "CAT 419 C/T gene polymorphism was not informative, -89 A/T was associated with risk, and 389 C/T conferred protection against vitiligo along with AT haplotype. VDR BsmI, ApaI, and TaqI gene polymorphisms were not associated with vitiligo in Northwestern Mexicans suggesting a role for CAT gene polymorphisms in vitiligo susceptibility in the Mexican population and a lack of association with VDR gene polymorphisms.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab122773"
+            },
+            {
+                "object": "P2Y1 and P2Y12 genes were polymorphic in a Korean population; 3 intronic P2Y12 polymorphisms i-139C>T, i-744T>C, i-801insA were in complete linkage disequilibrium but not with the c.52C>T polymorphism; platelet aggregation in response to ADP associated with c.52C>T polymorphism but not with the 3 intronic polymorphisms or the P2Y1 c.1622A>T polymorphism",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab576406"
+            },
+            {
+                "object": "Uniform Mu insertion results in up-regulation of cytokinin synthesis genes and down-regulation of cytokinin degradation genes. The protein binds to Gene:103632693, Gene:100502174, Gene:100283866, Gene:542044, and Gene:100037786.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab983367"
+            },
+            {
+                "object": "No relationship was found between the studied polymorphisms 14094 ACE gene, rs1800469 gene TGFbeta1, GNB3 gene rs5443, rs5186 AGTR1 gene and the occurrence of primary vesicoureteral reflux. TT genotype polymorphism rs5443 of the GNB3 gene may be a protective factor for improved renal function in patients with primary vesicoureteral reflux.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab530514"
+            },
+            {
+                "object": "There was no association between the extended psychosis phenotype and BDNF rs6265/COMT rs4680 polymorphisms. The lack of an association between different expression levels of the extended psychosis phenotype and the BDNF rs6265/ COMT rs4680 polymorphism might be related to sample characteristics, underlying gene-gene, gene-environment and gene-environment-gene interactions.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab888369"
+            },
+            {
+                "object": "In general, the meta-analysis found no marked association between the IL-10-1082G/A gene polymorphism and HIV-1 susceptibility, IL-10-529C/A gene polymorphism might lead to a decreased risk of HIV-1 infection, and IL-10-819C/T gene polymorphism might lead to an increased risk of HIV-1 infection.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab393616"
+            },
+            {
+                "object": "When rs13154178 gene polymorphism was compared with AA homozygous individuals, fasting blood glucose levels were significantly higher in carriers of either polymorphism than in those with no polymorphism. We suggest rs13154178 gene polymorphism may lead to gestational diabetes mellitus in the Turkish society.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab1015662"
+            },
+            {
+                "object": "Study confirmed the presence of a gene-environment interaction between the rs1801516 polymorphism and radiation exposure in carcinogenesis, whereas no association was found between the rs1801516 polymorphism and cancer risk for individuals without radiation exposure. The heterogeneity observed in the meta-analysis of individuals with radiation exposure might be due to gene-ethnicity or gene-gene interactions.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab737660"
+            },
+            {
+                "object": "Genome-wide associations P < 5 x 10-8 were found at the PCSK9 gene, the APOB gene, theLPL gene, the APOA1-APOA5 locus, the LIPC gene, the CETP gene, the LDLR gene, and the APOE locus.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab320109"
+            }
+        ],
+        "question": "What about recombination in the human genome?",
+        "subquestions": null,
+        "task_id": "1A879F7DD77C0462CC12FB20F7D14486",
+        "usage": {
+            "chatgpt": 4864,
+            "gpt-4": 3728,
+            "gpt-4-turbo-preview": 2745
+        },
+        "user_id": 2
+    },
+    "document_id": "1A879F7DD77C0462CC12FB20F7D14486",
+    "task_id": "1A879F7DD77C0462CC12FB20F7D14486"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/08.json b/gnqa/paper1_eval/src/data/responses/general/experts/08.json
new file mode 100644
index 0000000..aea3464
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/08.json
@@ -0,0 +1,415 @@
+{
+    "created_at": "2024-06-01T14:31:40.882988Z",
+    "data": {
+        "amplify": false,
+        "answer": "The text does not provide specific instructions on how to add a new species to the GeneNetwork database. It is recommended to contact the administrators or operators of the GeneNetwork database for guidance on this process.",
+        "context": {
+            "0e6c370f-b514-4551-b6ed-9cc72e6f6b75": [
+                {
+                    "document_id": "0e6c370f-b514-4551-b6ed-9cc72e6f6b75",
+                    "text": "The hierarchical organization of GN’s main Select and Search menu is\nsimple and makes it relatively easy to find relevant data sets (Fig. 1). To get data, after\nopening the browser, select the most appropriate Species from the dropdown menu. For an\nopen-ended search of phenotypes you can also select All Species at the bottom of the menu. The next steps are to select the Group, Type, and Data Set from the drop-down menus. For\nmany groups, a combination of phenotypes, genotypes, and molecular data are available."
+                }
+            ],
+            "4049da4d-c7cf-4e30-9a21-c77609fad23d": [
+                {
+                    "document_id": "4049da4d-c7cf-4e30-9a21-c77609fad23d",
+                    "text": "GeneNetwork contains data from a\nwide range of species, from humans to soybeans, but most of the available phenotypic data is\nfrom mice. Within the mouse dataset there are groups of families, crosses, non-genetic\ngroupings, and individual data. The type of dataset must be selected after defining the species\nand sample population. While genotypes, mRNA, methylated DNA, protein, metagenomic, and\n2\nbioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424047; this version posted December 24, 2020. The copyright holder for this preprint\n(which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. metabolome datasets are available (i.e."
+                }
+            ],
+            "43407486-b9c2-487b-b19c-b605c4d201c6": [
+                {
+                    "document_id": "43407486-b9c2-487b-b19c-b605c4d201c6",
+                    "text": "The hierarchical organization of GN’s main Select and Search menu is\nsimple and makes it relatively easy to find relevant data sets (Fig. 1). To get data, after\nopening the browser, select the most appropriate Species from the dropdown menu. For an\nopen-ended search of phenotypes you can also select All Species at the bottom of the menu. The next steps are to select the Group, Type, and Data Set from the drop-down menus. For\nmany groups, a combination of phenotypes, genotypes, and molecular data are available."
+                }
+            ],
+            "47a15e69-dc83-452e-95d8-c605e61f43c0": [
+                {
+                    "document_id": "47a15e69-dc83-452e-95d8-c605e61f43c0",
+                    "text": "Search and Data Retrieval\nPoint your browser to www.genenetwork.org. This brings you by default to\nthe Search page, from which you can retrieve data from many GN data sets. We will focus on the default data set, defined by Species: Mouse, Group: BXD,\nType: Whole Brain, Database: INIA Brain mRNA M430 (Apr05) PDNN\nEnter “Kcnj*” into the ALL or ANY field and click the Search button. Note\nthe location and annotation of available potassium channel genes in the Search\nResults page that opens. Use the browser Back button to return to previous page."
+                }
+            ],
+            "638b3811-7054-4788-a42d-2ccc7bfce1c7": [
+                {
+                    "document_id": "638b3811-7054-4788-a42d-2ccc7bfce1c7",
+                    "text": "Add\ninformation on data provenance by giving details in Investigation, Protocols and ProtocolApplications\n\nCustomize Customize ‘my’ XGAP database with extended variants of Trait and Subject. In the online XGAP demonstrator, Probe traits have a\nsequence and genome location and Strain subjects have parent strains and (in)breeding method. Describe extensions using MOLGENIS\nlanguage and the generator automatically changes XGAP database software to your research\nUpload\n\nUpload data from measurement devices, public databases, collaborating XGAP databases, or a public XGAP repository with community\ndata."
+                },
+                {
+                    "document_id": "638b3811-7054-4788-a42d-2ccc7bfce1c7",
+                    "text": "However, a suitable and customizable integration of\nthese elements to support high throughput genotype-tophenotype experiments is still needed [34]: dbGaP, GeneNetwork and the model organism databases are\ndesigned as international repositories and not to serve\nas general data infrastructure for individual projects;\nmany of the existing bespoke data models are too complicated and specialized, hard to integrate between profiling technologies, or lack software support to easily\nconnect to new analysis tools; and customization of the\nexisting infrastructures dbGaP, GeneNetwork or other\ninternational repositories [35,36] or assembly of Bioconductor and generic model organism database components to suit particular experimental designs, organisms\nand biotechnologies still requires many minor and\nsometimes major manual changes in the software code\nthat go beyond what individual lab bioinformaticians\ncan or should do, and result in duplicated efforts\nbetween labs if attempted."
+                }
+            ],
+            "75813bc2-f0b5-400c-92d7-0958df97a04f": [
+                {
+                    "document_id": "75813bc2-f0b5-400c-92d7-0958df97a04f",
+                    "text": ", 2014; see Section 9). GeneNetwork is a database that enables searching for ∼4000 phenotypes from multiple studies in the BXD, HXB, and in other recombinant inbred rodent families, as well as in other model organisms\nand even humans (Mulligan et al. , 2017). GeneNetwork employed a\nsomewhat diﬀerent strategy than MPD in that it did not rely solely on\nresearchers submitting their data. Instead the database operators extracted the data from the scientiﬁc literature and integrated them into a\nuniform format (Chesler et al. , 2003)."
+                }
+            ],
+            "7b1cecf5-a2b9-4bd9-b92b-9bd6b96ed93d": [
+                {
+                    "document_id": "7b1cecf5-a2b9-4bd9-b92b-9bd6b96ed93d",
+                    "text": "GeneNetwork contains data from a\nwide range of species, from humans to soybeans, but most of the available phenotypic data is\nfrom mice. Within the mouse dataset there are groups of families, crosses, non-genetic\ngroupings, and individual data. The type of dataset must be selected after defining the species\nand sample population. While genotypes, mRNA, methylated DNA, protein, metagenomic, and\n2\nbioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424047; this version posted December 24, 2020. The copyright holder for this preprint\n(which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. metabolome datasets are available (i.e."
+                }
+            ],
+            "85ee9743-b34d-4d49-9017-d7d2e5d4b996": [
+                {
+                    "document_id": "85ee9743-b34d-4d49-9017-d7d2e5d4b996",
+                    "text": "However, a suitable and customizable integration of these elements\nto support high throughput genotype-to-phenotype experiments is still\nneeded[340]: dbGaP, GeneNetwork and the model organism databases\nare designed as international repositories and not to serve as general\ndata infrastructure for individual projects; many of the existing bespoke\ndata models are too complicated and specialized, hard to integrate between proﬁling technologies, or lack software support to easily connect\nto new analysis tools; and customization of the existing infrastructures\ndbGaP, GeneNetwork or other international repositories[384, 154] or\nassembly of Bioconductor and generic model organism database components to suit particular experimental designs, organisms and biotechnologies still requires many minor and sometimes major manual changes\n38\n2.1."
+                }
+            ],
+            "92fa8f50-2923-41a1-812b-32d931c71684": [
+                {
+                    "document_id": "92fa8f50-2923-41a1-812b-32d931c71684",
+                    "text": "All data presented in this paper were deposited in the online database\nGeneNetwork (www.genenetwork.org), an open web resource that contains\ngenotypic, gene expression, and phenotypic data from several genetic reference\npopulations of multiple species (e.g. mouse, rat and human) and various cell\ntypes and tissues.35;36 It provides a valuable tool to integrate gene networks and\nphenotypic traits, and also allows cross-cell type and cross-species comparative\ngene expression and eQTL analyses."
+                }
+            ],
+            "d2f9c5cf-835c-450a-bb42-a2454a99e058": [
+                {
+                    "document_id": "d2f9c5cf-835c-450a-bb42-a2454a99e058",
+                    "text": "There is a good chance that you will be able to apply these new\ntechniques to specific problems, even while you read. If you have a computer with an\nInternet connection—so much the better, and you can read and work along at the same time. This short review and primer will take you on a tour of a web site called GeneNetwork that\nembeds many large data sets that are relevant to studies of behavioral variation. GeneNetwork is an unusual site because it contains a coherent \"universe\" of data, as well as\nmany powerful analytic tools."
+                }
+            ],
+            "dbe5a781-3561-48cb-9f63-cfb4f3246434": [
+                {
+                    "document_id": "dbe5a781-3561-48cb-9f63-cfb4f3246434",
+                    "text": "The GeneNetwork database provides open access\nto BXD and other RI strain derived microarray data, single nucleotide polymorphism (SNP) data,\nand phenotypic data for quantitative trait loci analysis and gene expression correlation analyses. Gene expression data were exported for manually selected probes in the PDNN hippocampus\ndatabase (Hippocampus Consortium M430v2), and the PDNN whole brain database (INIA Brain\nmRNA M430). The Hippocampus database was chosen as one of the most elaborate brain databases,\nas well as most highly recommended dataset on GeneNetwork itself (http://www.genenetwork.org/\nwebqtl/main.py?FormID=sharinginfo&GN_AccessionId=112)."
+                }
+            ],
+            "f041550e-5f2d-430e-8f46-15ebea6ca496": [
+                {
+                    "document_id": "f041550e-5f2d-430e-8f46-15ebea6ca496",
+                    "text": "2016) and can\nalso be accessed in GeneNetwork by entering Record ID 18494 in the Get Any\nspace on the Search page and clicking on the Search button. Alternatively, enter\ndata by hand into the designated boxes provided by GeneNetwork. These latter\noptions also allow for the inclusion of trait variance. It is a good idea to name\nthe trait in the box provided. Then click Next, and manually enter the data for\neach RI strain, F1, and founder strain. 3\n\nAuthor Manuscript\n\nAfter entering the data, click on the blue plus sign button called Add."
+                },
+                {
+                    "document_id": "f041550e-5f2d-430e-8f46-15ebea6ca496",
+                    "text": "To submit multiple phenotypes at the same\ntime, select the option for Batch Submission under the Home tab. This allows\nusers to submit up to 100 traits for analysis by GeneNetwork. Here, select BXD\nas the cross or RI set to analyze from the first pull-down menu. The phenotype\nfile should follow the format described in the Sample text (http://\ngenenetwork.org/sample.txt). After uploading the appropriate file using the\nBrowse button, enter a name for the file in the Dataset space. The data will be\nstored in the GeneNetwork server for 24 hours. Click Next."
+                },
+                {
+                    "document_id": "f041550e-5f2d-430e-8f46-15ebea6ca496",
+                    "text": "Author Manuscript\n\nMaterials\nHere we will provide detailed instructions for using GeneNetwork along with some\n“worked” examples taken from the recent study of intravenous cocaine self-administration\nby Dickson et al. (2016) in BXD RI mice. A complete overview of GeneNetwork is beyond\nthe scope of this protocol, but is extensively covered in elsewhere (see Mulligan et al. 2016;\nWilliams & Mulligan 2012 for excellent reviews on GeneNetwork). A computer with an internet connection and current web browser. See the GeneNetwork.org\nsite for information on supported browser versions. Author Manuscript\n\nMethod\nEntering Data\n\nAuthor Manuscript\n\n1\n\nLink to http://www.genenetwork.org."
+                }
+            ],
+            "f2b8524b-501d-4ec7-a3d7-048aab67ce05": [
+                {
+                    "document_id": "f2b8524b-501d-4ec7-a3d7-048aab67ce05",
+                    "text": "\n\nSpecies in GenAge model organisms"
+                }
+            ],
+            "f9b2eeba-5f93-49c1-8828-311f0797d9e3": [
+                {
+                    "document_id": "f9b2eeba-5f93-49c1-8828-311f0797d9e3",
+                    "text": "Data are reviewed before entry in\nGeneNetwork by the senior author. Phenotypes are currently split into 15 broad\nphenotypic categories (Supplementary Data 1). Phenome curation and description\nwas initiated by R.W.W. and Dr Elissa Chesler in 2002 by literature review and data\nextraction. The early work is described brieﬂy in Chesler et al.51,52. Most work over\nthe past 5 years has been performed by two of the coauthors (R.W.W. and\nM.K.M.). We have used a controlled vocabulary and set of rules described here\n(http://www.genenetwork.org/faq.html#Q-22)."
+                }
+            ],
+            "fa8bba46-ce94-439a-a676-35187a3abcbf": [
+                {
+                    "document_id": "fa8bba46-ce94-439a-a676-35187a3abcbf",
+                    "text": "9) To bring your data to GeneWeaver,\nclick on the GeneWeaver icon, making sure to be previously\nlogin to your GeneWeaver account. You will be brought to the\nGeneSet upload page with the Genes Uploaded and the\nGeneweaver Analysis Platform\n\n139\n\nFig. 5 Default settings at GeneNetwork.org are set to search “Mouse”, “Phenotypes”, from among the “BXD\nPublished Phenotypes” data set. Here the term nociception was searched for\n\nFig. 6 The search results page in GeneNetwork showing the 33 records retrieved from the phenotype search\nfor nociception."
+                },
+                {
+                    "document_id": "fa8bba46-ce94-439a-a676-35187a3abcbf",
+                    "text": "Users may also share their data with other users selectively,\nmake it public, or keep it restricted to a private account. Data can be\nimported by users, uploading their gene set data directly or exporting to GeneWeaver from within another online resource such as\nNeuro Informatics Framework (NIF) [8], Grappa [9], Mouse\nPhenome Database (MPD) [10] or GeneNetwork [11]. These datasets can then be added to your collection to be analyzed together\nwith other gene sets retrieved from the GeneWeaver database. To begin a GeneWeaver analysis a user must collect “GeneSets”\ntogether in a “Project”."
+                },
+                {
+                    "document_id": "fa8bba46-ce94-439a-a676-35187a3abcbf",
+                    "text": "Alternatively the spreadsheet can be saved as a .txt file\nand uploaded by clicking on “Switch to file upload.” Once\ncomplete click on upload GeneSet. 7. Once completed you are taken to the GeneSet detail page. If\nthere are errors in your uploaded data you can correct them by\nclicking on “Edit”. 8. Use the Add Selected to Project, and create a new project, e.g. “Chronic Cocaine”. 9. Now using the Search function populate this project with additional gene sets related to this study trying Queries such as\n“Cocaine Addiction”, “Chronic Cocaine”."
+                }
+            ]
+        },
+        "data_source": [
+            {
+                "document_id": "f041550e-5f2d-430e-8f46-15ebea6ca496",
+                "section_type": "main",
+                "text": "2016) and can\nalso be accessed in GeneNetwork by entering Record ID 18494 in the Get Any\nspace on the Search page and clicking on the Search button.  Alternatively, enter\ndata by hand into the designated boxes provided by GeneNetwork.  These latter\noptions also allow for the inclusion of trait variance.  It is a good idea to name\nthe trait in the box provided.  Then click Next, and manually enter the data for\neach RI strain, F1, and founder strain.\n 3\n\nAuthor Manuscript\n\nAfter entering the data, click on the blue plus sign button called Add."
+            },
+            {
+                "document_id": "75813bc2-f0b5-400c-92d7-0958df97a04f",
+                "section_type": "main",
+                "text": ", 2014; see Section 9).\n GeneNetwork is a database that enables searching for ∼4000 phenotypes from multiple studies in the BXD, HXB, and in other recombinant inbred rodent families, as well as in other model organisms\nand even humans (Mulligan et al. , 2017).  GeneNetwork employed a\nsomewhat diﬀerent strategy than MPD in that it did not rely solely on\nresearchers submitting their data.  Instead the database operators extracted the data from the scientiﬁc literature and integrated them into a\nuniform format (Chesler et al. , 2003)."
+            },
+            {
+                "document_id": "638b3811-7054-4788-a42d-2ccc7bfce1c7",
+                "section_type": "main",
+                "text": "Add\ninformation on data provenance by giving details in Investigation, Protocols and ProtocolApplications\n\nCustomize Customize ‘my’ XGAP database with extended variants of Trait and Subject.  In the online XGAP demonstrator, Probe traits have a\nsequence and genome location and Strain subjects have parent strains and (in)breeding method.  Describe extensions using MOLGENIS\nlanguage and the generator automatically changes XGAP database software to your research\nUpload\n\nUpload data from measurement devices, public databases, collaborating XGAP databases, or a public XGAP repository with community\ndata."
+            },
+            {
+                "document_id": "fa8bba46-ce94-439a-a676-35187a3abcbf",
+                "section_type": "main",
+                "text": "9) To bring your data to GeneWeaver,\nclick on the GeneWeaver icon, making sure to be previously\nlogin to your GeneWeaver account.  You will be brought to the\nGeneSet upload page with the Genes Uploaded and the\nGeneweaver Analysis Platform\n\n139\n\nFig.  5 Default settings at GeneNetwork.org are set to search “Mouse”, “Phenotypes”, from among the “BXD\nPublished Phenotypes” data set.  Here the term nociception was searched for\n\nFig.  6 The search results page in GeneNetwork showing the 33 records retrieved from the phenotype search\nfor nociception."
+            },
+            {
+                "document_id": "f041550e-5f2d-430e-8f46-15ebea6ca496",
+                "section_type": "main",
+                "text": "To submit multiple phenotypes at the same\ntime, select the option for Batch Submission under the Home tab.  This allows\nusers to submit up to 100 traits for analysis by GeneNetwork.  Here, select BXD\nas the cross or RI set to analyze from the first pull-down menu.  The phenotype\nfile should follow the format described in the Sample text (http://\ngenenetwork.org/sample.txt).  After uploading the appropriate file using the\nBrowse button, enter a name for the file in the Dataset space.  The data will be\nstored in the GeneNetwork server for 24 hours.  Click Next."
+            },
+            {
+                "document_id": "f041550e-5f2d-430e-8f46-15ebea6ca496",
+                "section_type": "main",
+                "text": "Author Manuscript\n\nMaterials\nHere we will provide detailed instructions for using GeneNetwork along with some\n“worked” examples taken from the recent study of intravenous cocaine self-administration\nby Dickson et al.  (2016) in BXD RI mice.  A complete overview of GeneNetwork is beyond\nthe scope of this protocol, but is extensively covered in elsewhere (see Mulligan et al.  2016;\nWilliams & Mulligan 2012 for excellent reviews on GeneNetwork).\n A computer with an internet connection and current web browser.  See the GeneNetwork.org\nsite for information on supported browser versions.\n\n Author Manuscript\n\nMethod\nEntering Data\n\nAuthor Manuscript\n\n1\n\nLink to http://www.genenetwork.org."
+            },
+            {
+                "document_id": "0e6c370f-b514-4551-b6ed-9cc72e6f6b75",
+                "section_type": "main",
+                "text": "The hierarchical organization of GN’s main Select and Search menu is\nsimple and makes it relatively easy to find relevant data sets (Fig.  1).  To get data, after\nopening the browser, select the most appropriate Species from the dropdown menu.  For an\nopen-ended search of phenotypes you can also select All Species at the bottom of the menu.\n The next steps are to select the Group, Type, and Data Set from the drop-down menus.  For\nmany groups, a combination of phenotypes, genotypes, and molecular data are available."
+            },
+            {
+                "document_id": "43407486-b9c2-487b-b19c-b605c4d201c6",
+                "section_type": "main",
+                "text": "The hierarchical organization of GN’s main Select and Search menu is\nsimple and makes it relatively easy to find relevant data sets (Fig.  1).  To get data, after\nopening the browser, select the most appropriate Species from the dropdown menu.  For an\nopen-ended search of phenotypes you can also select All Species at the bottom of the menu.\n The next steps are to select the Group, Type, and Data Set from the drop-down menus.  For\nmany groups, a combination of phenotypes, genotypes, and molecular data are available."
+            },
+            {
+                "document_id": "fa8bba46-ce94-439a-a676-35187a3abcbf",
+                "section_type": "main",
+                "text": "Users may also share their data with other users selectively,\nmake it public, or keep it restricted to a private account.  Data can be\nimported by users, uploading their gene set data directly or exporting to GeneWeaver from within another online resource such as\nNeuro Informatics Framework (NIF) [8], Grappa [9], Mouse\nPhenome Database (MPD) [10] or GeneNetwork [11].  These datasets can then be added to your collection to be analyzed together\nwith other gene sets retrieved from the GeneWeaver database.\n To begin a GeneWeaver analysis a user must collect “GeneSets”\ntogether in a “Project”."
+            },
+            {
+                "document_id": "638b3811-7054-4788-a42d-2ccc7bfce1c7",
+                "section_type": "main",
+                "text": "However, a suitable and customizable integration of\nthese elements to support high throughput genotype-tophenotype experiments is still needed [34]: dbGaP, GeneNetwork and the model organism databases are\ndesigned as international repositories and not to serve\nas general data infrastructure for individual projects;\nmany of the existing bespoke data models are too complicated and specialized, hard to integrate between profiling technologies, or lack software support to easily\nconnect to new analysis tools; and customization of the\nexisting infrastructures dbGaP, GeneNetwork or other\ninternational repositories [35,36] or assembly of Bioconductor and generic model organism database components to suit particular experimental designs, organisms\nand biotechnologies still requires many minor and\nsometimes major manual changes in the software code\nthat go beyond what individual lab bioinformaticians\ncan or should do, and result in duplicated efforts\nbetween labs if attempted."
+            },
+            {
+                "document_id": "f2b8524b-501d-4ec7-a3d7-048aab67ce05",
+                "section_type": "main",
+                "text": "\n\nSpecies in GenAge model organisms"
+            },
+            {
+                "document_id": "fa8bba46-ce94-439a-a676-35187a3abcbf",
+                "section_type": "main",
+                "text": "Alternatively the spreadsheet can be saved as a .txt file\nand uploaded by clicking on “Switch to file upload.” Once\ncomplete click on upload GeneSet.\n 7.  Once completed you are taken to the GeneSet detail page.  If\nthere are errors in your uploaded data you can correct them by\nclicking on “Edit”.\n 8.  Use the Add Selected to Project, and create a new project, e.g.\n “Chronic Cocaine”.\n 9.  Now using the Search function populate this project with additional gene sets related to this study trying Queries such as\n“Cocaine Addiction”, “Chronic Cocaine”."
+            },
+            {
+                "document_id": "85ee9743-b34d-4d49-9017-d7d2e5d4b996",
+                "section_type": "main",
+                "text": "However, a suitable and customizable integration of these elements\nto support high throughput genotype-to-phenotype experiments is still\nneeded[340]: dbGaP, GeneNetwork and the model organism databases\nare designed as international repositories and not to serve as general\ndata infrastructure for individual projects; many of the existing bespoke\ndata models are too complicated and specialized, hard to integrate between proﬁling technologies, or lack software support to easily connect\nto new analysis tools; and customization of the existing infrastructures\ndbGaP, GeneNetwork or other international repositories[384, 154] or\nassembly of Bioconductor and generic model organism database components to suit particular experimental designs, organisms and biotechnologies still requires many minor and sometimes major manual changes\n38\n2.1."
+            },
+            {
+                "document_id": "4049da4d-c7cf-4e30-9a21-c77609fad23d",
+                "section_type": "main",
+                "text": "GeneNetwork contains data from a\nwide range of species, from humans to soybeans, but most of the available phenotypic data is\nfrom mice.  Within the mouse dataset there are groups of families, crosses, non-genetic\ngroupings, and individual data.  The type of dataset must be selected after defining the species\nand sample population.  While genotypes, mRNA, methylated DNA, protein, metagenomic, and\n2\nbioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424047; this version posted December 24, 2020.  The copyright holder for this preprint\n(which was not certified by peer review) is the author/funder.  All rights reserved.  No reuse allowed without permission.\n\n metabolome datasets are available (i.e."
+            },
+            {
+                "document_id": "7b1cecf5-a2b9-4bd9-b92b-9bd6b96ed93d",
+                "section_type": "main",
+                "text": "GeneNetwork contains data from a\nwide range of species, from humans to soybeans, but most of the available phenotypic data is\nfrom mice.  Within the mouse dataset there are groups of families, crosses, non-genetic\ngroupings, and individual data.  The type of dataset must be selected after defining the species\nand sample population.  While genotypes, mRNA, methylated DNA, protein, metagenomic, and\n2\nbioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424047; this version posted December 24, 2020.  The copyright holder for this preprint\n(which was not certified by peer review) is the author/funder.  All rights reserved.  No reuse allowed without permission.\n\n metabolome datasets are available (i.e."
+            },
+            {
+                "document_id": "92fa8f50-2923-41a1-812b-32d931c71684",
+                "section_type": "main",
+                "text": "All data presented in this paper were deposited in the online database\nGeneNetwork (www.genenetwork.org), an open web resource that contains\ngenotypic, gene expression, and phenotypic data from several genetic reference\npopulations of multiple species (e.g.  mouse, rat and human) and various cell\ntypes and tissues.35;36 It provides a valuable tool to integrate gene networks and\nphenotypic traits, and also allows cross-cell type and cross-species comparative\ngene expression and eQTL analyses."
+            },
+            {
+                "document_id": "f9b2eeba-5f93-49c1-8828-311f0797d9e3",
+                "section_type": "main",
+                "text": "Data are reviewed before entry in\nGeneNetwork by the senior author.  Phenotypes are currently split into 15 broad\nphenotypic categories (Supplementary Data 1).  Phenome curation and description\nwas initiated by R.W.W.  and Dr Elissa Chesler in 2002 by literature review and data\nextraction.  The early work is described brieﬂy in Chesler et al.51,52.  Most work over\nthe past 5 years has been performed by two of the coauthors (R.W.W.  and\nM.K.M.).  We have used a controlled vocabulary and set of rules described here\n(http://www.genenetwork.org/faq.html#Q-22)."
+            },
+            {
+                "document_id": "d2f9c5cf-835c-450a-bb42-a2454a99e058",
+                "section_type": "main",
+                "text": "There is a good chance that you will be able to apply these new\ntechniques to specific problems, even while you read.  If you have a computer with an\nInternet connection—so much the better, and you can read and work along at the same time.\n This short review and primer will take you on a tour of a web site called GeneNetwork that\nembeds many large data sets that are relevant to studies of behavioral variation.\n GeneNetwork is an unusual site because it contains a coherent \"universe\" of data, as well as\nmany powerful analytic tools."
+            },
+            {
+                "document_id": "47a15e69-dc83-452e-95d8-c605e61f43c0",
+                "section_type": "main",
+                "text": "Search and Data Retrieval\nPoint your browser to www.genenetwork.org.  This brings you by default to\nthe Search page, from which you can retrieve data from many GN data sets.\n We will focus on the default data set, defined by Species: Mouse, Group: BXD,\nType: Whole Brain, Database: INIA Brain mRNA M430 (Apr05) PDNN\nEnter “Kcnj*” into the ALL or ANY field and click the Search button.  Note\nthe location and annotation of available potassium channel genes in the Search\nResults page that opens.\n Use the browser Back button to return to previous page."
+            },
+            {
+                "document_id": "dbe5a781-3561-48cb-9f63-cfb4f3246434",
+                "section_type": "main",
+                "text": "The GeneNetwork database provides open access\nto BXD and other RI strain derived microarray data, single nucleotide polymorphism (SNP) data,\nand phenotypic data for quantitative trait loci analysis and gene expression correlation analyses.\n Gene expression data were exported for manually selected probes in the PDNN hippocampus\ndatabase (Hippocampus Consortium M430v2), and the PDNN whole brain database (INIA Brain\nmRNA M430).  The Hippocampus database was chosen as one of the most elaborate brain databases,\nas well as most highly recommended dataset on GeneNetwork itself (http://www.genenetwork.org/\nwebqtl/main.py?FormID=sharinginfo&GN_AccessionId=112)."
+            },
+            {
+                "document_id": "4edf9e5c-915d-4e38-b48f-2a0b82132bd0",
+                "section_type": "main",
+                "text": "Then, users can, with a single\nmouse-click, send these variables to the BNW network building\ninterface and start network modeling.  The applications of BNW\nmay go beyond systems genetics as it can be used as a general webbased engine for causal inference in various databases.\n References\n1.  The Genomes Project, C (2015) A global reference for human genetic variation.  Nature\n526:68–74\n2.  Visscher PM, Brown MA, McCarthy MI, Yang\nJ (2012) Five years of GWAS discovery.  Am\nJ Hum Genet 90:7–24\n3."
+            },
+            {
+                "document_id": "638b3811-7054-4788-a42d-2ccc7bfce1c7",
+                "section_type": "main",
+                "text": "The software behind the GUI checks the\nrelationships between subjects, traits, and data elements\nSwertz et al.  Genome Biology 2010, 11:R27\nhttp://genomebiology.com/2010/11/3/R27\n\nso no ‘orphaned’ data are loaded into the database - for\nexample, genetic fingerprint data cannot be added\nbefore all information is uploaded on the markers and\nsubjects involved.  Standard paths through the data\nupload process are employed to ensure that only complete and valid data are uploaded and to provide a consistent user experience.\n Biologists can use the graphical user interface to navigate and retrieve available data for analysis."
+            },
+            {
+                "document_id": "bec58804-181a-4683-8e51-0ec6d381da69",
+                "section_type": "main",
+                "text": "3, 2008\n\nAnother approach to helping researchers integrate data obtained\nat different levels and in different organisms is GeneNetwork,1\na Web site and resource (www.genenetwork.org) that provides\n1\nGeneNetwork is sponsored by different grants, including grants from INIA and a Human\nBrain Project funded jointly by NIAAA, the National Institute on Drug Abuse, and the\nNational Institute of Mental Health.\n\n ROBERT W. WILLIAMS, PH.D., is a professor, and LU LU,\nM.D. , is an associate professor in the Department of Anatomy\nand Neurobiology, University of Tennessee Health Science\nCenter, Memphis, Tennessee."
+            },
+            {
+                "document_id": "9d225f6f-e434-45a7-b199-f3a09eda1d04",
+                "section_type": "main",
+                "text": "GeneNetwork2 (www.genenetwork.org/) is an online data repository and tool for analyzing thousands\nof historical gene expression, physiological, and behavioral traits in the BXD recombinant inbred panel that\nsegregates C57BL/6J and DBA/2J alleles (Chesler et al.  2004; Mulligan et al.  2017).\n METHODS\nMice\nAll experiments were conducted in accordance with the NIH Guidelines for the Use of Laboratory Animals\nand were approved by the Institutional Animal Care and Use Committee at Boston University (AN-15403)."
+            },
+            {
+                "document_id": "d8993417-3a27-4000-b693-6cb4662b9f80",
+                "section_type": "main",
+                "text": "The GeneNetwork.org (http://www.genenetwork.org/,\naccessed on 2 February 2022) website allows this combination of FAIR data and reproducible\ngenomes, meaning that research teams can now go back to previous datasets and reanalyse\nthem with new data and new tools.  Every new dataset adds exponentially to the number of\npossible connections.  In this paper, we will reanalyse drug and addiction related data from\nover a decade ago, using new genometypes for the BXD family of murine strains, as well\nas new statistical tools, showing that we can identify new quantitative trait loci (QTLs),\nresulting in highly plausible candidate genes."
+            },
+            {
+                "document_id": "d0deb53b-7286-4fd0-9188-b7b9f366fd76",
+                "section_type": "main",
+                "text": "The GeneNetwork.org (http://www.genenetwork.org/,\naccessed on 2 February 2022) website allows this combination of FAIR data and reproducible\ngenomes, meaning that research teams can now go back to previous datasets and reanalyse\nthem with new data and new tools.  Every new dataset adds exponentially to the number of\npossible connections.  In this paper, we will reanalyse drug and addiction related data from\nover a decade ago, using new genometypes for the BXD family of murine strains, as well\nas new statistical tools, showing that we can identify new quantitative trait loci (QTLs),\nresulting in highly plausible candidate genes."
+            },
+            {
+                "document_id": "beb7a242-21fe-4a66-8b44-7f228c0d3640",
+                "section_type": "main",
+                "text": "By\nintegrating datasets from an unsequenced crop plant (barley) in a database that has been designed for an animal\nmodel species (mouse) with well established genome\nsequence, we prove the importance of the concept and\npractice of modular development and interoperability of\nsoftware engineering for biological data sets.\n\n Availability and requirements\nGeneNetwork usage conditions and limitations are available from here [58].  Online tutorial accompanying this\n\nPage 9 of 11\n(page number not for citation purposes)\nBMC Genetics 2008, 9:73\n\nmanuscript can be either viewed or downloaded from the\n[59]."
+            },
+            {
+                "document_id": "d2f9c5cf-835c-450a-bb42-a2454a99e058",
+                "section_type": "main",
+                "text": "Web services such as GeneNetwork and its\ncompanions—GeneWeaver (Baker et al. , 2012), WebGestalt (Zhang et al. , 2005), DAVID\n(Huang et al. , 2009a; Huang et al. , 2009b), and the Allen Brain Atlas (Lein et al. , 2007)—\ncan now be used as virtual and free laboratories to test specific biological hypothesis, or they\ncan be used to generate new ideas ab initio.\n\n Acknowledgments\nNIH-PA Author Manuscript\n\nWe would like to thank the Center for Integrative and Translational Genomics for graciously supporting the BXD\ncolony at the University of Tennessee Health Science Center."
+            },
+            {
+                "document_id": "23dcf284-7c19-4335-91e1-50c3b85e6bad",
+                "section_type": "main",
+                "text": "The Mouse\nGenome Database (MGD) has structured their mouse genomic data in terms of the Mammalian Phenotype Ontology\n[10].  Similarly, the Rat Genome Database (RGD) [11] also\ndeveloped a phenome database, integrated with its genomic\ndata.  In humans, the GeneNetwork (WebQTL) provides a\ndatabase of complex traits with mappings to quantitative trait\nloci [12].  And several studies have focused on integrating\nhuman phenome and genome resources.  For example, Butte\net al.  created a large-scale phenome–genome network by\nintegrating the Uniﬁed Medical Language System with human\nmicroarray gene expression data [13]; and Aerts et al."
+            },
+            {
+                "document_id": "7b1cecf5-a2b9-4bd9-b92b-9bd6b96ed93d",
+                "section_type": "main",
+                "text": "The authors of any related manuscript (or the lab group who gathered\nthe data) are shown, as well as the title and links to the published paper (Figure 4C).  There is\nalso a button to add the trait to a collection (see below; Figure 4D), and to view this trait in the\n4\nbioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424047; this version posted December 24, 2020.  The copyright holder for this preprint\n(which was not certified by peer review) is the author/funder.  All rights reserved.  No reuse allowed without permission.\n\n earlier version of GeneNetwork, GN1 (Figure 4E)."
+            },
+            {
+                "document_id": "4049da4d-c7cf-4e30-9a21-c77609fad23d",
+                "section_type": "main",
+                "text": "The authors of any related manuscript (or the lab group who gathered\nthe data) are shown, as well as the title and links to the published paper (Figure 4C).  There is\nalso a button to add the trait to a collection (see below; Figure 4D), and to view this trait in the\n4\nbioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424047; this version posted December 24, 2020.  The copyright holder for this preprint\n(which was not certified by peer review) is the author/funder.  All rights reserved.  No reuse allowed without permission.\n\n earlier version of GeneNetwork, GN1 (Figure 4E)."
+            },
+            {
+                "document_id": "638b3811-7054-4788-a42d-2ccc7bfce1c7",
+                "section_type": "main",
+                "text": "This option enables upload of whole lists of traits and\nsubjects from a simple tab-delimited format (3), which\ncan easily be produced with Excel or R; MOLGENIS\nautomatically generates online documentation describing\nthe expected format (4).  Subsequently, the protocol\napplications involved can be added with the resulting\nraw data (for example, genetic fingerprints, expression\nprofiles) and processed data (for example, normalized\nprofiles, QTL profiles, metabolic networks).  These data\ncan be uploaded, again using the common tab-delimited\nformat or custom parsers (5) that bioinformaticians can\n‘plug-in’ for specific file formats (for example, Affymetrix CEL files)."
+            },
+            {
+                "document_id": "638b3811-7054-4788-a42d-2ccc7bfce1c7",
+                "section_type": "main",
+                "text": "They can\nuse the advanced search options (6) to find certain\ntraits, subjects, or data.  Using menu option ‘file|download’ (7) they can download visible/selected (8) data as\ntab-delimited files to analyze them in third party software.  Bioinformaticians can ‘plug-in’ a custom-built\nscreen (see ‘customization’ section) that allows processing of selected data inside the GUI, for example, visualizing a correlation matrix as a graph (9) without the\nadditional steps of downloading data and uploading it\ninto another tool.  Biologists can create link-outs to\nrelated information, for example, to probes in GeneNetwork.org (not shown)."
+            },
+            {
+                "document_id": "f041550e-5f2d-430e-8f46-15ebea6ca496",
+                "section_type": "main",
+                "text": "If you have chosen a\nrecombinant inbred set, your data will be displayed in a form where you can\n\nCurr Protoc Neurosci.  Author manuscript; available in PMC 2018 April 10.\n Parker et al.\n\n Page 5\n\nAuthor Manuscript\n\nconfirm and/or edit them.  GeneNetwork provides sample data so that you can\nensure you have the correct format."
+            },
+            {
+                "document_id": "4a34fec8-ff56-4ec0-b51c-c21c130e53dd",
+                "section_type": "main",
+                "text": "The data are stored in a SQL-based database, and a web interface\n(http://genomics.cnr.berkeley.edu/BarleyTag/unigene result.pl) was developed to\naid in searching the results from the database.  Its availability will facilitate making\ndetailed comparisons of the protein and DNA data available for these plant species.\n Queries can be performed using various options, including species, percent identity, length of a match, sequence type (CDS or EST), or by key word.  The database\nwill be continuously updated as additional sequence information becomes available."
+            },
+            {
+                "document_id": "e17b5b05-4676-4b3d-a625-74d453c342bd",
+                "section_type": "main",
+                "text": "The data are stored in a SQL-based database, and a web interface\n(http://genomics.cnr.berkeley.edu/BarleyTag/unigene result.pl) was developed to\naid in searching the results from the database.  Its availability will facilitate making\ndetailed comparisons of the protein and DNA data available for these plant species.\n Queries can be performed using various options, including species, percent identity, length of a match, sequence type (CDS or EST), or by key word.  The database\nwill be continuously updated as additional sequence information becomes available."
+            },
+            {
+                "document_id": "fa8bba46-ce94-439a-a676-35187a3abcbf",
+                "section_type": "main",
+                "text": "If you cannot find the\ncorrect identifier or your identifier is not supported try converting at a website such as NIAID’s DAVID website (https://\ndavid.ncifcrf.gov/) which has a nice ID conversion tool [26].\n\n Acknowledgements\nGeneWeaver is currently supported by NIH AA18776 jointly\nfunded by NIAAA/NIDA.\n References\n1.  Smith CL, Eppig JT (2012) The Mammalian\nPhenotype Ontology as a unifying standard for\nexperimental and high-throughput phenotyping data.  Mamm Genome 23(9–10):653–668.\n doi:10.1007/s00335-012-9421-3\n2."
+            },
+            {
+                "document_id": "85ee9743-b34d-4d49-9017-d7d2e5d4b996",
+                "section_type": "main",
+                "text": "This option enables upload of whole lists of traits\nand subjects from a simple tab-delimited format (3), which can easily\nbe produced with Excel or R; MOLGENIS automatically generates online documentation describing the expected format (4).  Subsequently,\nthe protocol applications involved can be added with the resulting raw\ndata (for example, genetic ﬁngerprints, expression proﬁles) and processed data (for example, normalized proﬁles, QTL proﬁles, metabolic\nnetworks).  These data can be uploaded, again using the common tabdelimited format or custom parsers (5) that bioinformaticians can ‘plugin’ for speciﬁc ﬁle formats (for example, Aﬀymetrix CEL ﬁles)."
+            },
+            {
+                "document_id": "f041550e-5f2d-430e-8f46-15ebea6ca496",
+                "section_type": "main",
+                "text": "BASIC PROTOCOL TITLE: Genetic mapping and\nsystems genetics using GeneNetwork\nIntroductory paragraph\nGeneNetwork (www.genenetwork.org) is a free online resource for systems genetics that\nstores and analyzes behavioral phenotypes, physiological phenotypes, and large gene\nexpression data-sets with matched genomic data for numerous species, including mice.\n GeneNetwork can analyze a variety of mouse mapping populations, (including F2\n\nCurr Protoc Neurosci.  Author manuscript; available in PMC 2018 April 10.\n Parker et al."
+            },
+            {
+                "document_id": "bb5ed347-0f54-431a-a125-97b9d762b003",
+                "section_type": "main",
+                "text": "GeneNetwork’s WebQTL provides a direct link to the\nUniversity of California, Santa Cruz Genome Browser (URL\n\nThe UCSC Genome Browser also provides links to the\nNational Center for Biotechnology Information resources\nThe Journal of Undergraduate Neuroscience Education (JUNE), Fall 2009, 8(1):A26-A31\n\nsuch as Entrez Gene and PUBMED (URLs in References).\n These resources allow the students to discover more\ninformation about their highly expressed gene including its\nnucleotide and amino acid sequence, as well as find\narticles about their gene that provide a deeper intellectual\ninvolvement in this exercise.\n Our website has already been populated with some of\nthese materials http://mdcune.psych.ucla.edu/."
+            }
+        ],
+        "document_id": "FA1E32391509D1EEAEBB70D3014C444A",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "GeneNetwork",
+            "Record&ID&18494",
+            "Search&page",
+            "Add",
+            "Trait",
+            "RI&strain",
+            "F1",
+            "founder&strain",
+            "Batch&Submission",
+            "GeneWeaver",
+            "GeneSet",
+            "Project",
+            "Cocaine&Addiction",
+            "Chronic&Cocaine",
+            "Species",
+            "Mouse",
+            "BXD",
+            "HXB",
+            "Phenotypes",
+            "genotypes",
+            "mRNA",
+            "methylated&DNA",
+            "protein",
+            "metagenomic",
+            "metabolome"
+        ],
+        "metadata": [
+            {
+                "object": "Both ANXA11 G38R protein and ANXA11 D40G protein showed a shorter half-life than ANXA11 wild type protein, while there was no difference between ANXA11 G38R protein and ANXA11 D40G protein. There was no visible insoluble substance in the NP-40 lysates for ANXA11 wild type protein, ANXA11 G38R protein and ANXA11 D40G protein. G38R and D40G mutations reduce the stability of ANXA11 protein.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab106261"
+            },
+            {
+                "object": "We showed that Rheumatoid was more likely with the AA genotype compared with the AG genotype of SNP rs2977537, and with the TT genotype, or the GG genotype compared with the GT genotype of rs2929973, and with the AA genotype or GG genotype vs the AG genotype of rs2977530",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab1013556"
+            },
+            {
+                "object": "mRNA and protein expression levels of DNMT3b were upregulated in genotype 1b and 3a HCV-infected hepatocellular carcinoma patients as compared to control. DNMT3b mRNA levels did not change in genotypes 2a, 3, and 4, but were upregulated at the protein level by genotype 1b, 2a, and 3a. No differences were seen for genotypes 5 and 7.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab503048"
+            },
+            {
+                "object": "The genotype GG group had higher consumption of Remifentanil than the genotype AA group P<0.05, but the genotype AG group was not different from the genotype AA and GG groups P>0.05. The analepsia time, autonomous respiratory recovery time, and orientation recovery time in the genotype GG group were longer than in the genotype AA group P<0.05, but the genotype AG group was not different from the genotype AA and GG.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab818259"
+            },
+            {
+                "object": "plasma exposure resulted in expression of unfolded protein response UPR proteins such as glucoserelated protein 78 GRP78, protein kinase R PKRlike ER kinase PERK, and inositolrequiring enzyme 1 IRE1. Elevated expression of spliced Xbox binding protein 1 XBP1 and CCAAT/enhancerbinding protein homologous protein CHOP further confirmed that ROS generatedby NTGP induces apoptosis through the ER stress",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab599086"
+            },
+            {
+                "object": "MST3 protein coats lipid droplets in mouse liver cells from mice fed a high-fat diet. MST3 fully colocalized with ADRP, the main LD-coating protein in mouse liver. No MST3 protein was detected in the cytosolic fraction.  High mRNA and protein expression of MST3 was also found in organs that do not accumulate significant amounts of intracellular LDs.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab504219"
+            },
+            {
+                "object": "ID1 protein and mRNA expression decreased during myoblast differentiation. Lactacystin reversed the decrease in ID1 protein but not in ID1 mRNA expression, but cycloheximide prevented this reversal. Direct incubation of ID1 protein with proteasomes from myoblasts did not show differentiation stage-associated degradation of ID1 protein. Ubiquitinated ID1 protein was not detected in lactacystin-treated myoblasts",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab369968"
+            },
+            {
+                "object": "plasma exposure resulted in expression of unfolded protein response UPR proteins such as glucoserelated protein 78 GRP78, protein kinase R PKRlike ER kinase PERK, and inositolrequiring enzyme 1 IRE1. Elevated expression of spliced Xbox binding protein 1 XBP1 and CCAAT/enhancerbinding protein homologous protein CHOP further confirmed that ROS generatedby NTGP induces apoptosis through the ER stress",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab599087"
+            },
+            {
+                "object": "For the MYF5 gene, the C5084T and T5127A SNP genotypes were significantly associated with carcass traits of pigeons. Within those two SNPs, the BB genotype showed relatively higher trait association values than those of AA or AB genotypes. No significant association was observed between the KLF15 SNP genotypes and carcass traits.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab300762"
+            },
+            {
+                "object": "For the MYF5 gene, the C5084T and T5127A SNP genotypes were significantly associated with carcass traits of pigeons. Within those two SNPs, the BB genotype showed relatively higher trait association values than those of AA or AB genotypes. No significant association was observed between the KLF15 SNP genotypes and carcass traits.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab300761"
+            }
+        ],
+        "question": "How can I add a new species to the GeneNetwork database?",
+        "subquestions": null,
+        "task_id": "FA1E32391509D1EEAEBB70D3014C444A",
+        "usage": {
+            "chatgpt": 5344,
+            "gpt-4": 3726,
+            "gpt-4-turbo-preview": 2725
+        },
+        "user_id": 2
+    },
+    "document_id": "FA1E32391509D1EEAEBB70D3014C444A",
+    "task_id": "FA1E32391509D1EEAEBB70D3014C444A"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/09.json b/gnqa/paper1_eval/src/data/responses/general/experts/09.json
new file mode 100644
index 0000000..966d755
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/09.json
@@ -0,0 +1,394 @@
+{
+    "created_at": "2024-06-01T14:33:22.252190Z",
+    "data": {
+        "amplify": false,
+        "answer": "Mitochondrial DNA (mtDNA) is inherited solely from the maternal lineage, unlike nuclear DNA which requires both paternal and maternal contributions. This uniparental transmission of mtDNA is ensured by complex mechanisms that eliminate paternal mitochondria from sperm during fertilization. mtDNA also exhibits a higher mutation rate than nuclear DNA, leading to significant population-level mtDNA polymorphisms. These polymorphisms can be clustered into distinct haplogroups that represent major branch points on the mitochondrial phylogenetic tree. In contrast, nuclear DNA undergoes bi-parental recombination.",
+        "context": {
+            "0381d0d4-717f-470b-a8d4-562475cf58bb": [
+                {
+                    "document_id": "0381d0d4-717f-470b-a8d4-562475cf58bb",
+                    "text": "Oxidative stress and mitochondrial DNA\n\nNot long after it was discovered that mitochondria have their own genetic apparatus, Harman proposed that mitochondria play a central role in the free radical theory of aging [16].This idea was developed further by Miquel et al. [330], and the notion that mtDNA mutagenesis played a role in aging took hold.The phenotypical importance of mutations in mtDNA was demonstrated by Wallace et al. [331] and Holt et al. [332], who first showed that Leber's hereditary optic neuropathy and mitochondrial myopathies were caused by mtDNA mutations (reviewed in [333]).Because mtDNA is so close to the site of mitochondrial ROS production, it is exposed to considerably higher oxidative stress, resulting in 3-fold higher levels of DNA oxidative damage (the previously quoted 20-fold figure is apparently due to an isolation artifact [334,335]).In the 1990s a series of papers reported that the frequency of mitochondrial DNA deletions increases dramatically with age, being essentially undetectable in young individuals and reaching levels as high as 2% of mtDNA in old individuals.This age-related increase in mtDNA deletions was found in organisms as diverse as worms, mice, and humans (reviewed in [24,336]).The same is also true with mtDNA point mutations [337,338].Certain mtDNA polymorphisms have been found in increased frequency in centenarians, implying a protective effect during aging [339][340][341].Similar protective effects of mtDNA polymorphisms have been reported for the age-related neurodegenerative condition, Parkinson's disease [342]."
+                }
+            ],
+            "21d2cb60-92ab-4fbb-a3a1-85d3424881c1": [
+                {
+                    "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                    "text": "\n\nVariation in the structure and function of mitochondria underlies variation in organismal energetics broadly (Seebacher et al., 2010) and evidence for the importance of mitochondrial function in the evolution of natural populations continues to accumulate (Ballard and Melvin, 2010;Glanville et al., 2012;Hicks et al., 2012;Kurbalija Novičić et al., 2015).For example, variation in mitochondrial DNA sequences (mtDNA) can determine whole-organism metabolism, i.e., the rate at which organisms process energy from their environment, a phenomenon widespread across animal taxa (Arnqvist et al., 2010;Ballard et al., 2007;Ballard and Pichaud, 2014;Havird et al., 2019;Hood et al., 2018;James et al., 2016;Wolff et al., 2014).Specifically, mtDNA sequence variants are linked to functional metabolic differences in fish (Chapdelaine et al., 2020;Flight et al., 2011;Healy et al., 2019), birds (Scott et al., 2011), and mammals (Fontanillas et al., 2005), including humans (Amo and Brand, 2007;Dato et al., 2004;Niemi et al., 2003;Tranah et al., 2011).These mtDNA variants are often correlated with environmental factors such as temperature and altitude (Storz et al., 2010).However, other studies attempting to link mitochondrial function to mitochondrial DNA (mtDNA) sequence variation or environmental factors have offered mixed reports (Amo and Brand, 2007;Flight et al., 2011;Fontanillas et al., 2005;Hicks et al., 2012)."
+                },
+                {
+                    "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                    "text": "\n\nThe results here point to several potentially fruitful research directions.We have identified how nonsynonymous mutations in the mitochondrial genome associate with variation in whole-organism metabolism (including CytB, ND1, ND5 and ND6).A next step will be to characterize the molecular details of how these changes affect molecular function.It would also be beneficial to describe how variation in cellular oxygen consumption rate scales up to determine whole-organism metabolic rate across a range of temperatures, thus identifying potential mismatches across levels of organization that may impact organismal performance (Gangloff and Telemeco, 2018).While the interconnected processes that shape organismal and population-level responses to environmental variation do not lend themselves to simple narratives, and many molecular processes interact to produce the emergent ecotypic divergences at the phenotypic level, it is clear that the mitochondria play a central role even as that role may change across populations and ecological contexts (Fig. 1).Research within well-characterized natural systems, such as these garter snake populations, can offer illustrative case studies of how mitochondria respond to their environments, and thus impact physiological pathways and evolutionary patterns, creating variation in life histories and aging."
+                },
+                {
+                    "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                    "text": "\n\nDespite the complexities underlying observed variation in mitochondrial function, recent work has demonstrated examples of how evolution and plasticity in mitochondrial function across populations within a species can shape life histories.For example, evidence from Drosophila has demonstrated the effect of temperature on components of the ETC and has linked mtDNA variants to metabolic thermosensitivity (Pichaud et al., 2012), to differences in whole-organism metabolic rates (Kurbalija Novičić et al., 2015), and to fitness-related traits (Ballard et al., 2007;Pichaud et al., 2011;Pichaud et al., 2010).In general, studies in birds and mammals demonstrate that mitochondria of longer-lived species are more efficient in ATP production, produce less reactive oxygen species, and demonstrate increased antioxidant capacities (Barja and Herrero, 2000;Ku et al., 1993;Lambert et al., 2007).While some studies in lizards and snakes demonstrate a similar pattern (Olsson et al., 2008;Robert et al., 2007), the extent to which these results are generalizable across vertebrate taxa is not yet known.The diversity of life-history traits and immense variation in longevity demonstrated by reptiles, both within and among species, make these taxa ideal candidates for understanding how variation in mitochondrial physiology drives this variation in whole-organism traits (reviewed in Hoekstra et al., 2019).Such work has moved to the forefront with a recent focus on the ecological and evolutionary significance of aging processes in wild populations (reviewed in Nussey et al., 2013;Fletcher and Selman, 2015;Gaillard and Lemaître, 2020)."
+                },
+                {
+                    "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                    "text": "\n\nOver evolutionary time, differential mortality rates are a selective force in shaping genetic structure.This results in divergence of a variety of physiological networks that shape, ultimately, patterns of aging and longevity in different habitats (Monaghan et al., 2008;Stojković et al., 2017).Such selective pressures can have differential effects on the nuclear and mitochondrial genomes (McKenzie et al., 2019;Wolff et al., 2014).Genetic variation in the mitochondrial genome is known to drive mitochondrial function in many species (Ballard and Melvin, 2010;McKenzie et al., 2019;Novelletto et al., 2016) and we find this in our system as well.Whole organism metabolic rate varies with the mitochondrial genome haplogroups we identified in this study.T. elegans individuals with the introgressed T. sirtalis mitochondrial genome had the lowest metabolic rate and had 68 amino acid changes in the ETC genes relative to the T. elegans mitochondrial genomes.As species divergence are a continuation of population divergence, this introgression provides additional insight into how genetic variation can alter mitochondrial function.Whether the lower metabolic rate in our snakes with the introgressed mitochondrial genome is due to the fixed amino acid changes between the species or a mismatch between the coadapted nuclear and mitochondrially-encoded ETC proteins that could alter function of the mitochondria (Burton et al., 2013;Haenel, 2017;Rawson and Burton, 2002;Toews et al., 2014;Wolff et al., 2014) will require further comparisons to T. sirtalis individuals."
+                },
+                {
+                    "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                    "text": "\n\nBuilding on previous work in this system, the current study tests three primary hypotheses about how variation in mtDNA and mitochondrial function relate to variation in life-history traits and aging within this system (Fig. 1): (1) First, we test whether rates of cellular oxygen consumption in isolated immune cells exhibit patterns that are consistent with the hypothesis that cellular processes drive whole-organism senescence and aging, and if these patterns differ between the SA and FA ecotypes and between sexes.By measuring basal, ATP-production associated, and maximal rates of cellular oxygen consumption, we further test for evidence that phenotypic divergence is dependent on a specific aspect of oxidative phosphorylation within immune cells.The energetics of these cells are particularly important given their essential role in modulating disease and infection, important factors contributing to senescence (Metcalf et al., 2019).We predict that SA snakes will maintain levels of cellular oxygen consumption across age, whereas the FA snakes will show a decline with age, especially in ATP-associated rates, possibly due to continual degradation of electron transport chain functionality from accumulating oxidative damage and reduced DNA repair mechanisms (Robert and Bronikowski, 2010;Schwartz and Bronikowski, 2013). ( 2) Second, we expand our mitochondrial genomics dataset to quantify mtDNA genetic structure across the landscape and test whether mtDNA haplotypes, and alleles at a nonsynonymous SNP in the Cytochrome B (CytB) gene correlate with aging ecotypes. (3) Third, we test the hypothesis that variation in mtDNA correlates with whole-organism variation in metabolic rates, suggesting a pathway linking mitochondrial genetic variation in mtDNA to whole-organism energetics.We first test whether different haplotypes differ in resting metabolic rate.Then, we test the effects of the nonsynonymous SNP in CytB on resting metabolic rate.The CytB gene encodes a component of complex III of the ETC, and was previously found to segregate between these life-history ecotypes (Schwartz et al., 2015).This SNP results in an amino acid substitution from isoleucine (aliphatic, hydrophobic) to threonine (hydrophilic) on a region that comes into close contact with a nuclear-encoded subunit (Schwartz et al., 2015).We combine previously published and new data on whole-organism resting metabolic rates (oxygen consumption) to test for the effects of this nonsynonymous mutation in three populations where we find heterogeneity at this nucleotide, thus allowing us to disentangle the effects of shared environment (population) from sequence variation (SNP).We predict that this SNP will correlate with variation in whole-organism metabolic rate, demonstrating a putatively adaptive difference between the derived and ancestral sequence.By utilizing this integrative data setfrom genes to organelles to whole organisms to populationsin a known life-history context, we are able to test hypotheses across levels of organization to provide a more complete picture of the complicated story of mitochondria and life history (Havird et al., 2019)."
+                }
+            ],
+            "253fad94-3be6-4362-b56f-f00c9c5705e6": [
+                {
+                    "document_id": "253fad94-3be6-4362-b56f-f00c9c5705e6",
+                    "text": "mtDNA Diversity\n\nUnlike the nuclear genome, which requires both paternal and maternal contributions, mtDNA is inherited solely from the maternal lineage.It is unclear what advantage a uniparental mtDNA transmission confers, but one possibility is to minimize the number of distinct genomes to maximize the efficiency of a multi-genomic system (Hill et al. 2019).In fact, humans have developed complex, redundant mechanisms to ensure uniparental inheritance of mtDNA (DeLuca and O'Farrell 2012; Rojansky et al. 2016).Paternal mitochondria from sperms that enter into the egg during fertilization are actively and selectively eliminated via mitophagy through two E3 ligases, PARKIN, and MUL1 (Rojansky et al. 2016).PARKIN and MUL1 serve redundant purposes, and mitophagy becomes insufficient to eliminate paternal mtDNA only in the absence of both (Rojansky et al. 2016).Even though oocytes have  at least a thousand-fold more mitochondria than a sperm cell (Rojansky et al. 2016) and heteroplasmy levels would be very low if paternal mtDNA were to contaminate the embryo, the results can still be non-trivial.However, challenging this notion, a recent study provides evidence of potential paternal transmission (Luo et al. 2018), but awaits further corroborating studies (Lutz-Bonengel and Parson 2019)."
+                },
+                {
+                    "document_id": "253fad94-3be6-4362-b56f-f00c9c5705e6",
+                    "text": "\n\nMtDNA exhibit a higher mutation rate than nuclear DNA, leading to significant population-level mtDNA polymorphisms (van Oven and Kayser 2009; Wallace 1999; Wallace and Chalkia 2013).In fact, the co-evolution of the mitonuclear genomes has been proposed to be driven by mtDNA mutations that select for compensatory changes in the nuclear genome (Havird and Sloan 2016).Populations that share similar mtDNA polymorphisms can be clustered into distinct haplogroups that are designated using all letters of the alphabet (i.e., A through Z).The mtDNA haplogroups represent major branch points on the mitochondrial phylogenetic tree that have strong regional ties around the globe, thus supporting the concept of a 'mitochondrial eve' (Wallace 1999).Haplogroups present inherently different mitonuclear interactions (Zaidi and Makova 2019), which eventually affect the aging process (Wolff et al. 2016).For example, one haplogroup commonly found in Ashkenazi Jews can interact with a specific enrichment of an amino acid sequence in complex I, and result in altered susceptibility to type 2 diabetes mellitus (Gershoni et al. 2014).The effect of mitonuclear compatibility on lifespan is influenced by environmental cues in flies (Drummond et al. 2019).It is unclear if mitonuclear compatibility is invariable throughout an organism's life, or antagonistically pleiotropic during aging, making it a difficult moving target to understand."
+                }
+            ],
+            "2f39f55f-2604-49d4-9589-0e1403b84d7a": [
+                {
+                    "document_id": "2f39f55f-2604-49d4-9589-0e1403b84d7a",
+                    "text": "\n\nBackground: The accumulation of mitochondrial DNA (mtDNA) mutations, and the reduction of mtDNA copy number, both disrupt mitochondrial energetics, and may contribute to aging and age-associated phenotypes.However, there are few genetic and epidemiological studies on the spectra of blood mtDNA heteroplasmies, and the distribution of mtDNA copy numbers in different age groups and their impact on age-related phenotypes.In this work, we used whole-genome sequencing data of isolated peripheral blood mononuclear cells (PBMCs) from the UK10K project to investigate in parallel mtDNA heteroplasmy and copy number in 1511 women, between 17 and 85 years old, recruited in the TwinsUK cohorts."
+                }
+            ],
+            "4a17ce5c-55df-4aa0-a664-f6a03238d332": [
+                {
+                    "document_id": "4a17ce5c-55df-4aa0-a664-f6a03238d332",
+                    "text": "Discussion\n\nTwo significant questions are raised by the findings that mitochondrial DNA can integrate into the nucleus.Firstly, is this an extraordinarily rare event or is it occurring continually and at high frequency?Secondly, can such an event have pathological consequences to the organism?"
+                }
+            ],
+            "4f010a74-a9b4-4538-94f7-ae8f35c8b96e": [
+                {
+                    "document_id": "4f010a74-a9b4-4538-94f7-ae8f35c8b96e",
+                    "text": "Phylogeny\n\nThe mtDNA is maternally inherited (120) by offspring through the oocyte cytoplasm; namely, the mother transmits her mtDNAs to all of her offspring, and her daughters transmit their mtDNAs to the next generation.This is the consequence of the fact that the mature oocyte such as mouse (304) or bovine (144) contains lOO-1,000 times more mtDNA than is found in somatic cells.Hence, the few sperm mtDNAs that enter the egg (130) have little effect on the genotype.The maternal inheritance results in sequentially diverged mtDNA polymorphism of modern human, as shown in Figure 2. The polymorphism derives from the combinations of small deletions and additions of <14 bp in noncoding region and base substitutions including some point mutations in coding region."
+                },
+                {
+                    "document_id": "4f010a74-a9b4-4538-94f7-ae8f35c8b96e",
+                    "text": "\n\nThere have been few reports on distinct correlation between mitochondrial morphology and human aging, except changes in number and size of mitochondria associated with age.Concerning the gross structure of mitochondria, the overwhelming importance of the cell nucleus in mitochondrial biogenesis should be noted, because the major parts of mitochondrial proteins are encoded by nuclear genes that are stable during life with the efficient repair mechanism for nDNA."
+                },
+                {
+                    "document_id": "4f010a74-a9b4-4538-94f7-ae8f35c8b96e",
+                    "text": "\n\nEarly data on DNA polymorphism detected by restriction endonuclease (263) have suggested that the evolutionary change of mtDNA in higher animals occurs mainly by nucleotide substitution rather than by deletion and insertion.The mtDNA nucleotide sequence evolves 6-17 times faster than comparable nuclear DNA gene sequences (51,52,405).Rapid evolution of mtDNA of higher primates including human, 0.02 base substitutions per site per million years, was calculated from the restriction map of mtDNA (51).Because orthodox recombination mechanism appears to be absent in mtDNA (128), germline mutation seems to go down to posterity as maternal inheritance from our common ancestor (57)."
+                }
+            ],
+            "612a70c6-2f42-492f-9f23-0d5e9296919e": [
+                {
+                    "document_id": "612a70c6-2f42-492f-9f23-0d5e9296919e",
+                    "text": "\n\nA number of conclusions may be drawn from these results.Firstly, the data begin to answer the question of how closely mtDNA replication is kept in synchrony with nuclear DNA replication: it would appear to be regulated not by direct coupling to the nuclear DNA replication, but rather by the cell mass to be serviced by mitochondria."
+                }
+            ],
+            "65c8287b-eb19-437a-b9ca-5aaa8664d429": [
+                {
+                    "document_id": "65c8287b-eb19-437a-b9ca-5aaa8664d429",
+                    "text": "\n\nIt may be that high mtDNA levels are indeed indicative of compromised mitochondria, but that the underlying defects are unrelated to alterations in the DNA sequence.Alternatively, elevated quantities of mtDNA might be associated with increased metabolic requirements of the embryo, rather than organelles of suboptimal function.It is possible that embryos produced by older oocytes are under some form of stress and therefore have larger energy requirements.Functional experiments will be required to address these questions.Whatever the underlying basis, the current study has unequivocally demonstrated that female reproductive aging is associated with changes in the mtDNA content at the blastocyst stage."
+                }
+            ],
+            "67ec2631-aa17-436e-800b-1bc046fb5b19": [
+                {
+                    "document_id": "67ec2631-aa17-436e-800b-1bc046fb5b19",
+                    "text": "\n\nAge-associated alterations of the mitochondrial genome occur in several different species; however, their physiological relevance remains unclear.The age-associated changes of mitochondrial DNA (mtDNA) include nucleotide point mutations and modifications, as well as deletions.In this review, we summarize the current literature on age-associated mtDNA mutations and deletions and comment on their abundance.A clear need exists for a more thorough evaluation of the total damage to the mitochondrial genome that accumulates in aged tissues.᭧ 1997 Elsevier Science Inc."
+                }
+            ],
+            "8a9fe1bc-7fa3-40ee-ade0-9a498bcf9def": [
+                {
+                    "document_id": "8a9fe1bc-7fa3-40ee-ade0-9a498bcf9def",
+                    "text": "Mitochondrial genetics\n\nOne underexplored avenue for determining maternal risk for preterm birth involves the influence of the mitochondrial genome.The high mutation rate of mito chondrial DNA (mtDNA), together with the fact that most of its encoded proteins are evolutionarily con served, allowing for the selection of neutral or beneficial variants, has generated interest in defining human mtDNA variations and their roles in human biology [58]."
+                }
+            ],
+            "aa942230-9a43-4b5f-90d9-96d364861a57": [
+                {
+                    "document_id": "aa942230-9a43-4b5f-90d9-96d364861a57",
+                    "text": "\n\nClearly, as mitochondrial metabolic and genetic therapies advance for treating mitochondrial disease, they will also be available to enhance the personal lives of others.However, mitochondrial genetic variation appears to have been one of the primary factors that permitted our ancestors to adapt to new environments, survive adverse conditions, and multiple throughout the globe.Is it possible that by taking over control of individual mtDNA variation, we might also be setting our species on the road to functional decline and ultimately extinction?"
+                },
+                {
+                    "document_id": "aa942230-9a43-4b5f-90d9-96d364861a57",
+                    "text": "Mitochondrial therapeutics and performance enhancement\n\nIt is now clear that not all mtDNA variation is deleterious.Indeed, about 25% of all ancient mtDNA variation appears to have caused functional mitochondrial changes and thus been adaptive.Those mtDNA variants that are adapted to warm climates have mtDNA variants that result in tightly coupled OXPHOS, thus maximizing ATP output and minimizing heat production.The presence of these mtDNAs permits maximum muscle performance but also predispose sedentary individuals that consume excess calories to multiple problems.They would be prone to be overweight and their mitochondria would generate excessive ROS, thus making them susceptible to a variety of degenerative diseases, cancer and premature aging.Partially uncoupled mitochondria generate more heat, but at the expense of ATP production.Individual's with these variants are better able to tolerate the cold, and are less prone to obesity.They also generate less ROS making then resistant to degenerative diseases and aging.Finally, the mitochondria are why we breathe.Hence, mitochondrial variation might be an important factor in individual predisposition to altitude sickness."
+                }
+            ],
+            "b0af29ac-0997-416d-907a-6caba940536d": [
+                {
+                    "document_id": "b0af29ac-0997-416d-907a-6caba940536d",
+                    "text": "\n\nHuman mtDNA codes for 13 essential polypeptide components of the mitochondrial oxidative phosphorylation (OXPHOS) system.mtDNA undergoes strict maternal inheritance, resulting in the absence of bi-parental recombination (Elson et al., 2001) and has a high mutation rate (Tuppen et al., 2010).As such, the evolution of mtDNA is characterised by the emergence of distinct lineages (or haplogroups) (Hernstadt et al., 2002).This results in high levels of mtDNA variation at the population level despite its rather small size, which is also illustrated by the large number of sub-haplogroups (van Oven and Kayser, 2009).Africa"
+                }
+            ]
+        },
+        "data_source": [
+            {
+                "document_id": "253fad94-3be6-4362-b56f-f00c9c5705e6",
+                "section_type": "main",
+                "text": "mtDNA Diversity\n\nUnlike the nuclear genome, which requires both paternal and maternal contributions, mtDNA is inherited solely from the maternal lineage.It is unclear what advantage a uniparental mtDNA transmission confers, but one possibility is to minimize the number of distinct genomes to maximize the efficiency of a multi-genomic system (Hill et al. 2019).In fact, humans have developed complex, redundant mechanisms to ensure uniparental inheritance of mtDNA (DeLuca and O'Farrell 2012; Rojansky et al. 2016).Paternal mitochondria from sperms that enter into the egg during fertilization are actively and selectively eliminated via mitophagy through two E3 ligases, PARKIN, and MUL1 (Rojansky et al. 2016).PARKIN and MUL1 serve redundant purposes, and mitophagy becomes insufficient to eliminate paternal mtDNA only in the absence of both (Rojansky et al. 2016).Even though oocytes have  at least a thousand-fold more mitochondria than a sperm cell (Rojansky et al. 2016) and heteroplasmy levels would be very low if paternal mtDNA were to contaminate the embryo, the results can still be non-trivial.However, challenging this notion, a recent study provides evidence of potential paternal transmission (Luo et al. 2018), but awaits further corroborating studies (Lutz-Bonengel and Parson 2019)."
+            },
+            {
+                "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                "section_type": "main",
+                "text": "\n\nVariation in the structure and function of mitochondria underlies variation in organismal energetics broadly (Seebacher et al., 2010) and evidence for the importance of mitochondrial function in the evolution of natural populations continues to accumulate (Ballard and Melvin, 2010;Glanville et al., 2012;Hicks et al., 2012;Kurbalija Novičić et al., 2015).For example, variation in mitochondrial DNA sequences (mtDNA) can determine whole-organism metabolism, i.e., the rate at which organisms process energy from their environment, a phenomenon widespread across animal taxa (Arnqvist et al., 2010;Ballard et al., 2007;Ballard and Pichaud, 2014;Havird et al., 2019;Hood et al., 2018;James et al., 2016;Wolff et al., 2014).Specifically, mtDNA sequence variants are linked to functional metabolic differences in fish (Chapdelaine et al., 2020;Flight et al., 2011;Healy et al., 2019), birds (Scott et al., 2011), and mammals (Fontanillas et al., 2005), including humans (Amo and Brand, 2007;Dato et al., 2004;Niemi et al., 2003;Tranah et al., 2011).These mtDNA variants are often correlated with environmental factors such as temperature and altitude (Storz et al., 2010).However, other studies attempting to link mitochondrial function to mitochondrial DNA (mtDNA) sequence variation or environmental factors have offered mixed reports (Amo and Brand, 2007;Flight et al., 2011;Fontanillas et al., 2005;Hicks et al., 2012)."
+            },
+            {
+                "document_id": "253fad94-3be6-4362-b56f-f00c9c5705e6",
+                "section_type": "main",
+                "text": "\n\nMtDNA exhibit a higher mutation rate than nuclear DNA, leading to significant population-level mtDNA polymorphisms (van Oven and Kayser 2009; Wallace 1999; Wallace and Chalkia 2013).In fact, the co-evolution of the mitonuclear genomes has been proposed to be driven by mtDNA mutations that select for compensatory changes in the nuclear genome (Havird and Sloan 2016).Populations that share similar mtDNA polymorphisms can be clustered into distinct haplogroups that are designated using all letters of the alphabet (i.e., A through Z).The mtDNA haplogroups represent major branch points on the mitochondrial phylogenetic tree that have strong regional ties around the globe, thus supporting the concept of a 'mitochondrial eve' (Wallace 1999).Haplogroups present inherently different mitonuclear interactions (Zaidi and Makova 2019), which eventually affect the aging process (Wolff et al. 2016).For example, one haplogroup commonly found in Ashkenazi Jews can interact with a specific enrichment of an amino acid sequence in complex I, and result in altered susceptibility to type 2 diabetes mellitus (Gershoni et al. 2014).The effect of mitonuclear compatibility on lifespan is influenced by environmental cues in flies (Drummond et al. 2019).It is unclear if mitonuclear compatibility is invariable throughout an organism's life, or antagonistically pleiotropic during aging, making it a difficult moving target to understand."
+            },
+            {
+                "document_id": "4f010a74-a9b4-4538-94f7-ae8f35c8b96e",
+                "section_type": "main",
+                "text": "Phylogeny\n\nThe mtDNA is maternally inherited (120) by offspring through the oocyte cytoplasm; namely, the mother transmits her mtDNAs to all of her offspring, and her daughters transmit their mtDNAs to the next generation.This is the consequence of the fact that the mature oocyte such as mouse (304) or bovine (144) contains lOO-1,000 times more mtDNA than is found in somatic cells.Hence, the few sperm mtDNAs that enter the egg (130) have little effect on the genotype.The maternal inheritance results in sequentially diverged mtDNA polymorphism of modern human, as shown in Figure 2. The polymorphism derives from the combinations of small deletions and additions of <14 bp in noncoding region and base substitutions including some point mutations in coding region."
+            },
+            {
+                "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                "section_type": "main",
+                "text": "\n\nThe results here point to several potentially fruitful research directions.We have identified how nonsynonymous mutations in the mitochondrial genome associate with variation in whole-organism metabolism (including CytB, ND1, ND5 and ND6).A next step will be to characterize the molecular details of how these changes affect molecular function.It would also be beneficial to describe how variation in cellular oxygen consumption rate scales up to determine whole-organism metabolic rate across a range of temperatures, thus identifying potential mismatches across levels of organization that may impact organismal performance (Gangloff and Telemeco, 2018).While the interconnected processes that shape organismal and population-level responses to environmental variation do not lend themselves to simple narratives, and many molecular processes interact to produce the emergent ecotypic divergences at the phenotypic level, it is clear that the mitochondria play a central role even as that role may change across populations and ecological contexts (Fig. 1).Research within well-characterized natural systems, such as these garter snake populations, can offer illustrative case studies of how mitochondria respond to their environments, and thus impact physiological pathways and evolutionary patterns, creating variation in life histories and aging."
+            },
+            {
+                "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                "section_type": "main",
+                "text": "\n\nDespite the complexities underlying observed variation in mitochondrial function, recent work has demonstrated examples of how evolution and plasticity in mitochondrial function across populations within a species can shape life histories.For example, evidence from Drosophila has demonstrated the effect of temperature on components of the ETC and has linked mtDNA variants to metabolic thermosensitivity (Pichaud et al., 2012), to differences in whole-organism metabolic rates (Kurbalija Novičić et al., 2015), and to fitness-related traits (Ballard et al., 2007;Pichaud et al., 2011;Pichaud et al., 2010).In general, studies in birds and mammals demonstrate that mitochondria of longer-lived species are more efficient in ATP production, produce less reactive oxygen species, and demonstrate increased antioxidant capacities (Barja and Herrero, 2000;Ku et al., 1993;Lambert et al., 2007).While some studies in lizards and snakes demonstrate a similar pattern (Olsson et al., 2008;Robert et al., 2007), the extent to which these results are generalizable across vertebrate taxa is not yet known.The diversity of life-history traits and immense variation in longevity demonstrated by reptiles, both within and among species, make these taxa ideal candidates for understanding how variation in mitochondrial physiology drives this variation in whole-organism traits (reviewed in Hoekstra et al., 2019).Such work has moved to the forefront with a recent focus on the ecological and evolutionary significance of aging processes in wild populations (reviewed in Nussey et al., 2013;Fletcher and Selman, 2015;Gaillard and Lemaître, 2020)."
+            },
+            {
+                "document_id": "4a17ce5c-55df-4aa0-a664-f6a03238d332",
+                "section_type": "main",
+                "text": "Discussion\n\nTwo significant questions are raised by the findings that mitochondrial DNA can integrate into the nucleus.Firstly, is this an extraordinarily rare event or is it occurring continually and at high frequency?Secondly, can such an event have pathological consequences to the organism?"
+            },
+            {
+                "document_id": "612a70c6-2f42-492f-9f23-0d5e9296919e",
+                "section_type": "main",
+                "text": "\n\nA number of conclusions may be drawn from these results.Firstly, the data begin to answer the question of how closely mtDNA replication is kept in synchrony with nuclear DNA replication: it would appear to be regulated not by direct coupling to the nuclear DNA replication, but rather by the cell mass to be serviced by mitochondria."
+            },
+            {
+                "document_id": "b0af29ac-0997-416d-907a-6caba940536d",
+                "section_type": "main",
+                "text": "\n\nHuman mtDNA codes for 13 essential polypeptide components of the mitochondrial oxidative phosphorylation (OXPHOS) system.mtDNA undergoes strict maternal inheritance, resulting in the absence of bi-parental recombination (Elson et al., 2001) and has a high mutation rate (Tuppen et al., 2010).As such, the evolution of mtDNA is characterised by the emergence of distinct lineages (or haplogroups) (Hernstadt et al., 2002).This results in high levels of mtDNA variation at the population level despite its rather small size, which is also illustrated by the large number of sub-haplogroups (van Oven and Kayser, 2009).Africa"
+            },
+            {
+                "document_id": "2f39f55f-2604-49d4-9589-0e1403b84d7a",
+                "section_type": "main",
+                "text": "\n\nBackground: The accumulation of mitochondrial DNA (mtDNA) mutations, and the reduction of mtDNA copy number, both disrupt mitochondrial energetics, and may contribute to aging and age-associated phenotypes.However, there are few genetic and epidemiological studies on the spectra of blood mtDNA heteroplasmies, and the distribution of mtDNA copy numbers in different age groups and their impact on age-related phenotypes.In this work, we used whole-genome sequencing data of isolated peripheral blood mononuclear cells (PBMCs) from the UK10K project to investigate in parallel mtDNA heteroplasmy and copy number in 1511 women, between 17 and 85 years old, recruited in the TwinsUK cohorts."
+            },
+            {
+                "document_id": "0381d0d4-717f-470b-a8d4-562475cf58bb",
+                "section_type": "main",
+                "text": "Oxidative stress and mitochondrial DNA\n\nNot long after it was discovered that mitochondria have their own genetic apparatus, Harman proposed that mitochondria play a central role in the free radical theory of aging [16].This idea was developed further by Miquel et al. [330], and the notion that mtDNA mutagenesis played a role in aging took hold.The phenotypical importance of mutations in mtDNA was demonstrated by Wallace et al. [331] and Holt et al. [332], who first showed that Leber's hereditary optic neuropathy and mitochondrial myopathies were caused by mtDNA mutations (reviewed in [333]).Because mtDNA is so close to the site of mitochondrial ROS production, it is exposed to considerably higher oxidative stress, resulting in 3-fold higher levels of DNA oxidative damage (the previously quoted 20-fold figure is apparently due to an isolation artifact [334,335]).In the 1990s a series of papers reported that the frequency of mitochondrial DNA deletions increases dramatically with age, being essentially undetectable in young individuals and reaching levels as high as 2% of mtDNA in old individuals.This age-related increase in mtDNA deletions was found in organisms as diverse as worms, mice, and humans (reviewed in [24,336]).The same is also true with mtDNA point mutations [337,338].Certain mtDNA polymorphisms have been found in increased frequency in centenarians, implying a protective effect during aging [339][340][341].Similar protective effects of mtDNA polymorphisms have been reported for the age-related neurodegenerative condition, Parkinson's disease [342]."
+            },
+            {
+                "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                "section_type": "main",
+                "text": "\n\nOver evolutionary time, differential mortality rates are a selective force in shaping genetic structure.This results in divergence of a variety of physiological networks that shape, ultimately, patterns of aging and longevity in different habitats (Monaghan et al., 2008;Stojković et al., 2017).Such selective pressures can have differential effects on the nuclear and mitochondrial genomes (McKenzie et al., 2019;Wolff et al., 2014).Genetic variation in the mitochondrial genome is known to drive mitochondrial function in many species (Ballard and Melvin, 2010;McKenzie et al., 2019;Novelletto et al., 2016) and we find this in our system as well.Whole organism metabolic rate varies with the mitochondrial genome haplogroups we identified in this study.T. elegans individuals with the introgressed T. sirtalis mitochondrial genome had the lowest metabolic rate and had 68 amino acid changes in the ETC genes relative to the T. elegans mitochondrial genomes.As species divergence are a continuation of population divergence, this introgression provides additional insight into how genetic variation can alter mitochondrial function.Whether the lower metabolic rate in our snakes with the introgressed mitochondrial genome is due to the fixed amino acid changes between the species or a mismatch between the coadapted nuclear and mitochondrially-encoded ETC proteins that could alter function of the mitochondria (Burton et al., 2013;Haenel, 2017;Rawson and Burton, 2002;Toews et al., 2014;Wolff et al., 2014) will require further comparisons to T. sirtalis individuals."
+            },
+            {
+                "document_id": "4f010a74-a9b4-4538-94f7-ae8f35c8b96e",
+                "section_type": "main",
+                "text": "\n\nThere have been few reports on distinct correlation between mitochondrial morphology and human aging, except changes in number and size of mitochondria associated with age.Concerning the gross structure of mitochondria, the overwhelming importance of the cell nucleus in mitochondrial biogenesis should be noted, because the major parts of mitochondrial proteins are encoded by nuclear genes that are stable during life with the efficient repair mechanism for nDNA."
+            },
+            {
+                "document_id": "4f010a74-a9b4-4538-94f7-ae8f35c8b96e",
+                "section_type": "main",
+                "text": "\n\nEarly data on DNA polymorphism detected by restriction endonuclease (263) have suggested that the evolutionary change of mtDNA in higher animals occurs mainly by nucleotide substitution rather than by deletion and insertion.The mtDNA nucleotide sequence evolves 6-17 times faster than comparable nuclear DNA gene sequences (51,52,405).Rapid evolution of mtDNA of higher primates including human, 0.02 base substitutions per site per million years, was calculated from the restriction map of mtDNA (51).Because orthodox recombination mechanism appears to be absent in mtDNA (128), germline mutation seems to go down to posterity as maternal inheritance from our common ancestor (57)."
+            },
+            {
+                "document_id": "65c8287b-eb19-437a-b9ca-5aaa8664d429",
+                "section_type": "main",
+                "text": "\n\nIt may be that high mtDNA levels are indeed indicative of compromised mitochondria, but that the underlying defects are unrelated to alterations in the DNA sequence.Alternatively, elevated quantities of mtDNA might be associated with increased metabolic requirements of the embryo, rather than organelles of suboptimal function.It is possible that embryos produced by older oocytes are under some form of stress and therefore have larger energy requirements.Functional experiments will be required to address these questions.Whatever the underlying basis, the current study has unequivocally demonstrated that female reproductive aging is associated with changes in the mtDNA content at the blastocyst stage."
+            },
+            {
+                "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                "section_type": "main",
+                "text": "\n\nBuilding on previous work in this system, the current study tests three primary hypotheses about how variation in mtDNA and mitochondrial function relate to variation in life-history traits and aging within this system (Fig. 1): (1) First, we test whether rates of cellular oxygen consumption in isolated immune cells exhibit patterns that are consistent with the hypothesis that cellular processes drive whole-organism senescence and aging, and if these patterns differ between the SA and FA ecotypes and between sexes.By measuring basal, ATP-production associated, and maximal rates of cellular oxygen consumption, we further test for evidence that phenotypic divergence is dependent on a specific aspect of oxidative phosphorylation within immune cells.The energetics of these cells are particularly important given their essential role in modulating disease and infection, important factors contributing to senescence (Metcalf et al., 2019).We predict that SA snakes will maintain levels of cellular oxygen consumption across age, whereas the FA snakes will show a decline with age, especially in ATP-associated rates, possibly due to continual degradation of electron transport chain functionality from accumulating oxidative damage and reduced DNA repair mechanisms (Robert and Bronikowski, 2010;Schwartz and Bronikowski, 2013). ( 2) Second, we expand our mitochondrial genomics dataset to quantify mtDNA genetic structure across the landscape and test whether mtDNA haplotypes, and alleles at a nonsynonymous SNP in the Cytochrome B (CytB) gene correlate with aging ecotypes. (3) Third, we test the hypothesis that variation in mtDNA correlates with whole-organism variation in metabolic rates, suggesting a pathway linking mitochondrial genetic variation in mtDNA to whole-organism energetics.We first test whether different haplotypes differ in resting metabolic rate.Then, we test the effects of the nonsynonymous SNP in CytB on resting metabolic rate.The CytB gene encodes a component of complex III of the ETC, and was previously found to segregate between these life-history ecotypes (Schwartz et al., 2015).This SNP results in an amino acid substitution from isoleucine (aliphatic, hydrophobic) to threonine (hydrophilic) on a region that comes into close contact with a nuclear-encoded subunit (Schwartz et al., 2015).We combine previously published and new data on whole-organism resting metabolic rates (oxygen consumption) to test for the effects of this nonsynonymous mutation in three populations where we find heterogeneity at this nucleotide, thus allowing us to disentangle the effects of shared environment (population) from sequence variation (SNP).We predict that this SNP will correlate with variation in whole-organism metabolic rate, demonstrating a putatively adaptive difference between the derived and ancestral sequence.By utilizing this integrative data setfrom genes to organelles to whole organisms to populationsin a known life-history context, we are able to test hypotheses across levels of organization to provide a more complete picture of the complicated story of mitochondria and life history (Havird et al., 2019)."
+            },
+            {
+                "document_id": "aa942230-9a43-4b5f-90d9-96d364861a57",
+                "section_type": "main",
+                "text": "\n\nClearly, as mitochondrial metabolic and genetic therapies advance for treating mitochondrial disease, they will also be available to enhance the personal lives of others.However, mitochondrial genetic variation appears to have been one of the primary factors that permitted our ancestors to adapt to new environments, survive adverse conditions, and multiple throughout the globe.Is it possible that by taking over control of individual mtDNA variation, we might also be setting our species on the road to functional decline and ultimately extinction?"
+            },
+            {
+                "document_id": "aa942230-9a43-4b5f-90d9-96d364861a57",
+                "section_type": "main",
+                "text": "Mitochondrial therapeutics and performance enhancement\n\nIt is now clear that not all mtDNA variation is deleterious.Indeed, about 25% of all ancient mtDNA variation appears to have caused functional mitochondrial changes and thus been adaptive.Those mtDNA variants that are adapted to warm climates have mtDNA variants that result in tightly coupled OXPHOS, thus maximizing ATP output and minimizing heat production.The presence of these mtDNAs permits maximum muscle performance but also predispose sedentary individuals that consume excess calories to multiple problems.They would be prone to be overweight and their mitochondria would generate excessive ROS, thus making them susceptible to a variety of degenerative diseases, cancer and premature aging.Partially uncoupled mitochondria generate more heat, but at the expense of ATP production.Individual's with these variants are better able to tolerate the cold, and are less prone to obesity.They also generate less ROS making then resistant to degenerative diseases and aging.Finally, the mitochondria are why we breathe.Hence, mitochondrial variation might be an important factor in individual predisposition to altitude sickness."
+            },
+            {
+                "document_id": "67ec2631-aa17-436e-800b-1bc046fb5b19",
+                "section_type": "main",
+                "text": "\n\nAge-associated alterations of the mitochondrial genome occur in several different species; however, their physiological relevance remains unclear.The age-associated changes of mitochondrial DNA (mtDNA) include nucleotide point mutations and modifications, as well as deletions.In this review, we summarize the current literature on age-associated mtDNA mutations and deletions and comment on their abundance.A clear need exists for a more thorough evaluation of the total damage to the mitochondrial genome that accumulates in aged tissues.᭧ 1997 Elsevier Science Inc."
+            },
+            {
+                "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                "section_type": "main",
+                "text": "\n\nWorking within a generalized framework that integrates the environmental pressures driving the evolution of metabolic rates and lifehistories can provide insight into how these traits are integrated.In Fig. 1A we present such a framework.Central to this framework, and the best place to start our investigation of these complex interactions across scales and across lifespans, is the mitochondrion.In the cells of eukaryotes, the overwhelming majority of energy substrate (adenosine triphosphate; ATP) to sustain life's functions is produced in mitochondria via oxidative phosphorylation in the electron transport chain (reviewed in Hood et al., 2018;Solaini et al., 2010).Yet these mitochondria must carefully balance their energetic and oxygen demands, their capacity to meet cellular need for ATP, and their production of potentially toxic and harmful byproducts (Barja, 2002;Barja, 2004;Harmon, 1956;Lee and Wei, 2012;Muller et al., 2007).On one hand, energy flow through mitochondria can determine the pace of life of an individual, with implications for lifespan and 'rate of living'.On the other hand, the production of damaging reactive oxygen species (ROS) molecules is implicated in reduced performance and decline during old age, leading to the free radical theory of aging (or oxidative stress theory of aging; Balaban et al., 2005;Barja, 2002;Lyons and Kozak, 2019;Robert et al., 2007;Speakman, 2005).In addition, mitochondria possess a genome that encodes core peptides to electron transport chain (ETC) protein complexes along with nuclear-encoded mitochondrial proteins (Rand et al., 2004;Sunnucks et al., 2017;Wolff et al., 2014).This maternally inherited mitochondrial genome is subject to extensive replication across its lifetime and is linked to aging phenotypes independent of the production of damage-causing reactive oxygen species (Pinto and Moraes, 2015;Seo and Leeuwenburgh, 2015).For these reasons, any variation in mitochondrial function, especially if it is sexor age-dependent, will have ramifications for the evolution of life histories (Dowling and Simmons, 2009;Finkel and Holbrook, 2000;Fletcher et al., 2013;Wikelski and Ricklefs, 2001;Wolff et al., 2016)."
+            },
+            {
+                "document_id": "67ec2631-aa17-436e-800b-1bc046fb5b19",
+                "section_type": "abstract",
+                "text": "\nAge-associated alterations of the mitochondrial genome occur in several different species; however, their physiological relevance remains unclear.The age-associated changes of mitochondrial DNA (mtDNA) include nucleotide point mutations and modifications, as well as deletions.In this review, we summarize the current literature on age-associated mtDNA mutations and deletions and comment on their abundance.A clear need exists for a more thorough evaluation of the total damage to the mitochondrial genome that accumulates in aged tissues.᭧ 1997 Elsevier Science Inc."
+            },
+            {
+                "document_id": "8a9fe1bc-7fa3-40ee-ade0-9a498bcf9def",
+                "section_type": "main",
+                "text": "Mitochondrial genetics\n\nOne underexplored avenue for determining maternal risk for preterm birth involves the influence of the mitochondrial genome.The high mutation rate of mito chondrial DNA (mtDNA), together with the fact that most of its encoded proteins are evolutionarily con served, allowing for the selection of neutral or beneficial variants, has generated interest in defining human mtDNA variations and their roles in human biology [58]."
+            },
+            {
+                "document_id": "fd5edd5b-25d5-41ef-b9ad-7599905b844f",
+                "section_type": "main",
+                "text": "\n\nMitochondrial DNA (mtDNA) rearrangements have been shown to accumulate with age in the post-mitotic tissues of a variety of animals and have been hypothesized to result in the age-related decline of mitochondrial bioenergetics leading to tissue and organ failure.Caloric restriction in rodents has been shown to extend life span supporting an association between bioenergetics and senescence.In the present study, we use full length mtDNA amplification by long-extension polymerase chain reaction (LX-PCR) to demonstrate that mice accumulate a wide variety of mtDNA rearrangements with age in post mitotic tissues.Similarly, using an alternative PCR strategy, we have found that 2-4 kb minicircles containing the origin of heavy-strand replication accumulate with age in heart but not brain.Analysis of mtDNA structure and conformation by Southern blots of unrestricted DNA resolved by field inversion gel electrophoresis have revealed that the brain mtDNAs of young animals contain the traditional linear, nicked, and supercoiled mtDNAs while old animals accumulate substantial levels of a slower migrating species we designate age-specific mtDNAs.In old caloric restricted animals, a wide variety of rearranged mtDNAs can be detected by LX-PCR in post mitotic tissues, but Southern blots of unrestricted DNA reveals a marked reduction in the levels of the agespecific mtDNA species.These observations confirm that mtDNA mutations accumulate with age in mice and suggest that caloric restriction impedes this progress."
+            },
+            {
+                "document_id": "2f39f55f-2604-49d4-9589-0e1403b84d7a",
+                "section_type": "main",
+                "text": "\n\nHowever, no studies have investigated whether the effects of age on the two mitochondrial characteristics are independent, as it is possible that age can affect mtDNA copy number through age-related heteroplasmy changes or vice versa.In this study, we demonstrated that age was independently associated with mtDNA copy number and heteroplasmy.Furthermore, compared to previous studies, we also included WBC count and platelet count as covariates in the regression model to adjust for potential bias caused by blood cell contaminations.Mitochondrial biogenesis has been proposed as a marker of many age-related health outcomes or even the aging process itself [58].Our results suggested that both mtDNA heteroplasmy and copy number should be included to establish this relationship.Mitochondrial mutations that occur early in life can clonally expand to cause mitochondrial dysfunction and further contribute to aging through a number of potential mechanisms including decreased oxidative capacity and energy production capacity, but also nuclear signaling and transcriptional dysregulation [59][60][61][62][63].In addition, decreased mtDNA copy number may also lead to decreased energy production and/or decreased mitochondrial gene expression [57,64].Maintaining both mtDNA quality and quantity together may help to counteract or slow down the aging process."
+            },
+            {
+                "document_id": "1152aa3c-a9df-4745-b262-97c03ccf0e1a",
+                "section_type": "main",
+                "text": "\n\nWe next examined whether aging influenced behavior of the mice and added 6-month-old and 12-month-old mice to the experiments.The interaction between nDNA and mtDNA seemed to be more pronounced in older mice, as the difference in the slopes of the learning curves of H and H mtDNA N mice was amplified with age (Fig. 1c).Mitochondrial decay has been associated with memory loss and particularly with age-dependent cognitive impairment 4,7 . ).All effects were significant, including the double interaction of nDNA, mtDNA and age (P < .01).For all age groups, the transfer of mtDNA to the parental strains resulted in fewer steps taken. (c) Number of holes explored.All effects were significant including the double interaction (P < 0.0007), with congenic strains exploring fewer holes."
+            },
+            {
+                "document_id": "fd5edd5b-25d5-41ef-b9ad-7599905b844f",
+                "section_type": "abstract",
+                "text": "\nMitochondrial DNA (mtDNA) rearrangements have been shown to accumulate with age in the post-mitotic tissues of a variety of animals and have been hypothesized to result in the age-related decline of mitochondrial bioenergetics leading to tissue and organ failure.Caloric restriction in rodents has been shown to extend life span supporting an association between bioenergetics and senescence.In the present study, we use full length mtDNA amplification by long-extension polymerase chain reaction (LX-PCR) to demonstrate that mice accumulate a wide variety of mtDNA rearrangements with age in post mitotic tissues.Similarly, using an alternative PCR strategy, we have found that 2-4 kb minicircles containing the origin of heavy-strand replication accumulate with age in heart but not brain.Analysis of mtDNA structure and conformation by Southern blots of unrestricted DNA resolved by field inversion gel electrophoresis have revealed that the brain mtDNAs of young animals contain the traditional linear, nicked, and supercoiled mtDNAs while old animals accumulate substantial levels of a slower migrating species we designate age-specific mtDNAs.In old caloric restricted animals, a wide variety of rearranged mtDNAs can be detected by LX-PCR in post mitotic tissues, but Southern blots of unrestricted DNA reveals a marked reduction in the levels of the agespecific mtDNA species.These observations confirm that mtDNA mutations accumulate with age in mice and suggest that caloric restriction impedes this progress."
+            },
+            {
+                "document_id": "5d133558-fc58-42c7-8407-b3e734e8db9c",
+                "section_type": "abstract",
+                "text": "\nQuantitative information on the cell-to-cell distribution of all possible mitochondrial DNA (mtDNA) mutations in young and aged tissues is needed to assess the relevance of these mutations to the aging process.In the present study, we used PCR amplification of full-length mitochondrial genomes from single cells to scan human cardiomyocytes for all possible large deletions in mtDNA.Analysis of more than 350 individual cells that were derived from three middleaged and four centenarian donors demonstrates that while most of the cells contain no deletions, in certain cardiomyocytes a significant portion of the mtDNA molecules carried one particular deletion.Different affected cells contained different deletions.Although similar numbers of cells were screened for each donor, these deletion-rich cells were found only in the hearts of old donors, where they occurred at a frequency of up to one in seven cells.These initial observations demonstrate the efficiency of the method and indicate that mitochondrial mutations have the potential to play an important role in human myocardial aging."
+            },
+            {
+                "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                "section_type": "main",
+                "text": "\n\nAs a pacesetter for physiological processes, variation in metabolic rate can determine the shape of energetic trade-offs and thereby drive variation in life-history traits.In turn, such variation in metabolic performance and life-histories can have profound consequences for lifespan and lifetime fitness.Thus, the extent to which metabolic rate variation is due to phenotypic plasticity or fixed genetic differences among individuals or populations is likely to be shaped by natural selection.Here, we first present a generalized framework describing the central role of mitochondria in processes linking environmental, genomic, physiological, and aging variation.We then present a test of these relationships in an exemplary system: populations of garter snakes (Thamnophis elegans) exhibiting contrasting life-history strategiesfast-growing, early-reproducing, and fast-aging (FA) versus slow-growing, late-reproducing, and slow-aging (SA).Previous work has characterized divergences in mitochondrial function, reactive oxygen species processing, and whole-organism metabolic rate between these contrasting life-history ecotypes.Here, we report new data on cellular respiration and mitochondrial genomics and synthesize these results with previous work.We test hypotheses about the causes and implications of mitochondrial genome variation within this generalized framework.First, we demonstrate that snakes of the FA ecotype increase cellular metabolic rate across their lifespan, while the opposite pattern holds for SA snakes, implying that reduced energetic throughput is associated with a longer life.Second, we show that variants in mitochondrial genomes are segregating across the landscape in a manner suggesting selection on the physiological consequences of this variation in habitats varying in temperature, food availability, and rates of predation.Third, we demonstrate functional variation in whole-organism metabolic rate related to these mitochondrial genome sequence variants.With this synthesis of numerous datasets, we are able to further characterize how variation across levels of biological organization interact within this generalized framework and how this has resulted in the emergence of distinct life-history ecotypes that vary in their rates of aging and lifespan."
+            },
+            {
+                "document_id": "fd5edd5b-25d5-41ef-b9ad-7599905b844f",
+                "section_type": "main",
+                "text": "\n\nIt was previously reported that no substantive changes accumulate in the structure of the mitochondrial genome with age in either fibroblasts or Drosophila melanogaster (17,18).This was determined through analysis by Southern blot of uniquely restricted mitochondrial DNA.However, recent studies have shown that complex mtDNA rearrangements associated with human disease (19)(20)(21) can be 'masked' through restriction digestion (22).In addition, Southern analysis of unrestricted mtDNAs from senescent human skeletal muscle has revealed the accumulation of additional mtDNA species not found in young tissues which migrate with the same mobility as deleted mtDNAs (10).Hence, detection of age-specific mtDNA rearrangements requires application of appropriate methodologies."
+            },
+            {
+                "document_id": "2f39f55f-2604-49d4-9589-0e1403b84d7a",
+                "section_type": "main",
+                "text": "\n\nAging is commonly characterized as a time-dependent progressive loss of physiological integrity, leading to impaired function and increased vulnerability to death [14].One important factor in aging is the accumulation of DNA damage over time [15].mtDNA has been considered a major target of aging-associated mutation accumulation, possibly because it experiences higher oxidative damages, more turnover, and has lower replication fidelity compared to nuclear DNA (nDNA) [16][17][18].Mice carrying elevated mtDNA mutation burden present premature signs of aging including hair loss, kyphosis, and premature death (lifespan shortened by up to 50%) [19,20].In human studies, mtDNA heteroplasmy incidence increases with age [21][22][23], while lower mtDNA copy number has been reported in aged populations [12,24].Ding et al. reported an trend of increased heteroplasmies and decreased mtDNA copy number with age in their study population [25].However, previous studies were limited in one or more ways: i) limited power in detecting low-to-medium frequency heteroplasmies in blood due to low sequencing depth; ii) relatively small sample sizes, limiting statistical power; iii) small age range; iv) whole blood as the source of DNA, which contains several sources of contaminants for mtDNA analysis; and/or v) assessing either mtDNA mutation or copy number, but not both in the same biological samples.Thus, it is largely unknown whether the impacts of age on mtDNA mutation burden and on copy number are independent from each other."
+            },
+            {
+                "document_id": "b547b680-8602-4a15-8d91-6a6d3ffa19d2",
+                "section_type": "main",
+                "text": "\n\nIn the present study, myocardium was found to contain approximately twice the number of mtDNA genomes per diploid nucleus as skeletal muscle (6970 versus 3650, P = 0.006).This is in keeping with an earlier study (10) that used Southern hybridisation.This ®nding accords with a greater reliance on aerobic ATP production by the myocardium than by skeletal muscle.The mtDNA copy number in myocardium and skeletal muscle was found to remain unchanged over a 10 decade timespan in the tissues we studied (Figs 3 and 4), similar to the previous ®ndings on rat heart (12)."
+            },
+            {
+                "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                "section_type": "main",
+                "text": "\n\nAging is a complex process as a time-dependent progressive loss of physiological integrity, leading to impaired function and increased vulnerability to death [74], and as we described above, aging is highly associated with mtDNA mutations; in fact heteroplasmy incidence increases with age, while lower mtDNA copy number has been reported in aged populations as well as mitochondria morphology, abundance, and oxidative phosphorylation activity [75,76].Interestingly, in aging the significant amount of these mutations converges in sites that encode structural subunits of the ETC such as complexes I and III [77], leading to OxPhos uncoupling and mitochondrial dysfunction in aged population.Since there are several limitations to study mitochondrial metabolism in human samples, in this section we briefly described the implications of mitochondrial metabolism for aging in the most studied and high energy demand human tissues, such as skeletal muscle, heart, and brain."
+            },
+            {
+                "document_id": "ddc57e64-2b93-41e5-baac-6bdb52e7b6e6",
+                "section_type": "main",
+                "text": "\n\nIt is not known how mtDNA deletions accumulate during aging.Although the smaller size of partially-deleted molecules suggested early on that they could have a replicative advantage (5,6), direct evidence of this phenomenon has been lacking.In most cases, partially-deleted mtDNAs (DmtDNAs) contain the same number of replication origins as the wildtype genome but they can be up to 50% shorter (7).We have previously shown that cells harboring homoplasmic levels of DmtDNA repopulated their organelles with mtDNA faster than cells containing wild-type mitochondrial genomes (8).In these cells, however, there was no competition between mutated and wild-type genomes, as they were present in a homoplasmic state.Therefore, we could not rule out that differences in mtDNA repopulation were due to different metabolic states of these cells.In the present study, we addressed this issue by studying heteroplasmic cells.Our results showed that mtDNA with large deletions, but not with pathogenic point mutations, repopulates organelles signi®cantly faster than wild-type genomes in the same cell, particularly during relaxed copy number control."
+            },
+            {
+                "document_id": "ddc57e64-2b93-41e5-baac-6bdb52e7b6e6",
+                "section_type": "main",
+                "text": "\n\nAlthough there may be important differences between postmitotic tissues and our culture cell system, the observation of heteroplasmy ¯uctuations during rapid mtDNA repopulation allows us to draw some conclusions regarding the molecular aspect of differential repopulation rates.Our results are in agreement with previous in situ hybridization experiments that showed that most age-related mtDNA deletions in muscle are caused by clonal expansion of deletions (36,37).In muscle, mitochondria with defective function are stimulated to proliferate, and that may increase mtDNA replication, mimicking a relaxed copy number control situation.It also strengthened the view that age-related mtDNA deletions are probably generated at random but their levels gradually increase with time.Our results also raise the possibility that the accumulation of DmtDNAs may be accelerated by metabolic or environmental changes leading to either a transient reduction in mtDNA levels or a relaxation in copy number control."
+            },
+            {
+                "document_id": "2f39f55f-2604-49d4-9589-0e1403b84d7a",
+                "section_type": "abstract",
+                "text": "\nBackground: The accumulation of mitochondrial DNA (mtDNA) mutations, and the reduction of mtDNA copy number, both disrupt mitochondrial energetics, and may contribute to aging and age-associated phenotypes.However, there are few genetic and epidemiological studies on the spectra of blood mtDNA heteroplasmies, and the distribution of mtDNA copy numbers in different age groups and their impact on age-related phenotypes.In this work, we used whole-genome sequencing data of isolated peripheral blood mononuclear cells (PBMCs) from the UK10K project to investigate in parallel mtDNA heteroplasmy and copy number in 1511 women, between 17 and 85 years old, recruited in the TwinsUK cohorts.Results: We report a high prevalence of pathogenic mtDNA heteroplasmies in this population.We also find an increase in mtDNA heteroplasmies with age (β = 0.011, P = 5.77e-6), and showed that, on average, individuals aged 70-years or older had 58.5% more mtDNA heteroplasmies than those under 40-years old.Conversely, mtDNA copy number decreased by an average of 0.4 copies per year (β = −0.395,P = 0.0097).Multiple regression analyses also showed that age had independent effects on mtDNA copy number decrease and heteroplasmy accumulation.Finally, mtDNA copy number was positively associated with serum bicarbonate level (P = 4.46e-5), and inversely correlated with white blood cell count (P = 0.0006).Moreover, the aggregated heteroplasmy load was associated with blood apolipoprotein B level (P = 1.33e-5), linking the accumulation of mtDNA mutations to age-related physiological markers.Conclusions: Our population-based study indicates that both mtDNA quality and quantity are influenced by age.An open question for the future is whether interventions that would contribute to maintain optimal mtDNA copy number and prevent the expansion of heteroplasmy could promote healthy aging."
+            },
+            {
+                "document_id": "4f010a74-a9b4-4538-94f7-ae8f35c8b96e",
+                "section_type": "main",
+                "text": "DNA genotype during development\n\nRelatively rapid turnover of mtDNA in cells was documented (129).The half-life of mtDNA was 6.7 days in heart, 9.4 days in liver, 10.4 days in kidney, and 31 days in brain in adult rats, while a half-life of heart nDNA was -30 days.Accompanying mtDNA turnover, replicative advantage either to mutant or to wild-type mitochondrial genome has been reported on the germline point mutations."
+            },
+            {
+                "document_id": "63308275-a453-415d-8814-6f2932148ecd",
+                "section_type": "main",
+                "text": "\n\nIn this study, we have taken advantage of recent developments in high-throughput DNA sequencing to assemble one of the largest ancient mitochondrial DNA (mtDNA) datasets to date, consisting of a total of nearly 300,000 nucleotides of unique sequence data from 18 individual samples.By exploiting permafrost-preserved hair shaft material as a source of ancient DNA (3), we present five newly sequenced Siberian woolly mammoth mtDNA genomes (Fig. 1).In combination with the 13 previously published (3-7), these make it possible to scan for signs of natural selection along the mitochondrial genome and allow further investigation of the population structure discovered in past studies (1,8), including the inference of a more precise evolutionary time scale.Analysis of the combined dataset indicates a deep temporal split between the two clades (I and II).This observation, coupled with statistical analysis of the temporal distribution of the 14 C ages of these and previously identified members of the two mammoth clades (1), suggests that, although they are apparently sympatric, clade II vanished from Siberia long before clade I."
+            },
+            {
+                "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                "section_type": "abstract",
+                "text": "\nAs a pacesetter for physiological processes, variation in metabolic rate can determine the shape of energetic trade-offs and thereby drive variation in life-history traits.In turn, such variation in metabolic performance and life-histories can have profound consequences for lifespan and lifetime fitness.Thus, the extent to which metabolic rate variation is due to phenotypic plasticity or fixed genetic differences among individuals or populations is likely to be shaped by natural selection.Here, we first present a generalized framework describing the central role of mitochondria in processes linking environmental, genomic, physiological, and aging variation.We then present a test of these relationships in an exemplary system: populations of garter snakes (Thamnophis elegans) exhibiting contrasting life-history strategiesfast-growing, early-reproducing, and fast-aging (FA) versus slow-growing, late-reproducing, and slow-aging (SA).Previous work has characterized divergences in mitochondrial function, reactive oxygen species processing, and whole-organism metabolic rate between these contrasting life-history ecotypes.Here, we report new data on cellular respiration and mitochondrial genomics and synthesize these results with previous work.We test hypotheses about the causes and implications of mitochondrial genome variation within this generalized framework.First, we demonstrate that snakes of the FA ecotype increase cellular metabolic rate across their lifespan, while the opposite pattern holds for SA snakes, implying that reduced energetic throughput is associated with a longer life.Second, we show that variants in mitochondrial genomes are segregating across the landscape in a manner suggesting selection on the physiological consequences of this variation in habitats varying in temperature, food availability, and rates of predation.Third, we demonstrate functional variation in whole-organism metabolic rate related to these mitochondrial genome sequence variants.With this synthesis of numerous datasets, we are able to further characterize how variation across levels of biological organization interact within this generalized framework and how this has resulted in the emergence of distinct life-history ecotypes that vary in their rates of aging and lifespan. \"Sometimes reality is too complex.Stories give it form.\""
+            },
+            {
+                "document_id": "aa942230-9a43-4b5f-90d9-96d364861a57",
+                "section_type": "main",
+                "text": "\n\nAll of these factors and numerous others are areas that influence our daily lives.Consequently, some individuals may wish to change their energetic phenotype by changing their mtDNA genotype.If some people will undergo surgery to change their appearance, there will certainly be some who will submit to mtDNA alterations to change their life style, appearance, and physical performance.For example, changing a single mtDNA nucleotide of a high performance athlete to increase mitochondrial ATP production through altered OXPHOS coupling could increase performance by several percent and mean the difference between Olympic immortality versus obscurity.Since such a change would be undetectable by any reasonable standard screening procedure.Why wouldn't a competitive athlete take advantage of such an opportunity?"
+            },
+            {
+                "document_id": "4f010a74-a9b4-4538-94f7-ae8f35c8b96e",
+                "section_type": "main",
+                "text": "\n\nThese results strongly urged the researchers' attention on mtDNA mutations and, as a result, bridged over the distance between the biochemical findings and the molecular biology of mtDNA."
+            }
+        ],
+        "document_id": "8CC70421A233A4B1F89A6701731F7017",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "mtDNA",
+            "mitochondrial&DNA",
+            "nuclear&DNA",
+            "heredity",
+            "haplogroups",
+            "mitochondrial&genome",
+            "oxidative&phosphorylation",
+            "OXPHOS",
+            "mutation&rate",
+            "mitophagy"
+        ],
+        "metadata": [
+            {
+                "object": "Carriers of hemochromatosis gene HFE 845A and 187G alleles have significantly higher mitochondrial DNA mtDNA levels than noncarriers, but mtDNA declines among all individuals on study during 48 weeks on uninterrupted antiretroviral therapy ART. Increased cellular mtDNA content may represent a compensatory response to mitochondrial stress that is influenced by iron-loading HFE variants.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab120751"
+            },
+            {
+                "object": "We also assessed mitochondrial DNA mtDNA content, citrate synthase activity, oxidative lesions to protein and mtDNA i.e., carbonyls and the abundance of mtDNA4834 deletion, and the mitochondrial transcription factor A TFAM binding to specific mtDNA regions.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab998500"
+            },
+            {
+                "object": "Mitochondrial mtDNA haplogroups show an influence on serum levels of catalase among osteoarthritis patients. Carriers of mtDNA haplogroup J show higher serum levels than non-J carriers.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab494822"
+            },
+            {
+                "object": "We determined mitochondrial DNA mtDNA and ACTN3 genotypes in Finnish elite endurance n = 52 and sprint n = 89 athletes, and found that the frequencies of mtDNA haplogroups differed significantly between the two groups",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab1002772"
+            },
+            {
+                "object": "In mutated HMI1 the wild-type mitochondrial DNA is fragmented and loss of the wild-type mitochondrial genome is caused by this fragmentation of the mitochondrial DNA.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab396367"
+            },
+            {
+                "object": "The T790M mutation rate was 8.4% in overall patients. The T790M mutation was more frequent in patients with brain metastasis 30.0% . We found that post-TKI tyrosine kinase inhibitors samples 42.8% were associated with a higher T790M mutation rate. Subgroup analysis showed that the duration of TKI therapy for 6 to 10 months 66.6% and >10 months 75.0% were also associated with higher T790M mutation rate.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab878154"
+            },
+            {
+                "object": "Study revealed that Irc3 - a dsDNA dependent ATPase of the Superfamily II- is essential for yeast mtDNA maintenance. irc3Delta mutant yeast cells accumulated double-stranded breaks in mtDNA and lose the wild-type mitochondrial genome in the course of a few generations of growth on glucose-containing media. These results demonstrate that Irc3 is a mitochondrial branch migration enzyme.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab748584"
+            },
+            {
+                "object": "human ClpX, a novel mtDNA regulator, maintains mtDNA nucleoid distribution through TFAM function as a chaperone rather than as a protease and its involvement in mtDNA segregation.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab364328"
+            },
+            {
+                "object": "Here, we identified the E3 ubiquitin ligase HUWE1 as a key inducing factor in AMBRA1-mediated mitophagy, a process that takes place independently of the main mitophagy receptors. Furthermore, we show that mitophagy function of AMBRA1 is post-translationally controlled, upon HUWE1 activity, by a positive phosphorylation on its serine 1014.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab339502"
+            },
+            {
+                "object": "MGME1-mediated mtDNA processing is essential for faithful mitochondrial genome replication and might be required for intramolecular recombination of mtDNA.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab480937"
+            }
+        ],
+        "question": "Describe the role of mitochondrial DNA in heredity and how it differs from nuclear DNA.",
+        "subquestions": null,
+        "task_id": "8CC70421A233A4B1F89A6701731F7017",
+        "usage": {
+            "chatgpt": 9175,
+            "gpt-4": 5434,
+            "gpt-4-turbo-preview": 4489
+        },
+        "user_id": 2
+    },
+    "document_id": "8CC70421A233A4B1F89A6701731F7017",
+    "task_id": "8CC70421A233A4B1F89A6701731F7017"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/10.json b/gnqa/paper1_eval/src/data/responses/general/experts/10.json
new file mode 100644
index 0000000..5ce6b0a
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/10.json
@@ -0,0 +1,384 @@
+{
+    "created_at": "2024-06-01T14:34:54.821428Z",
+    "data": {
+        "amplify": false,
+        "answer": "Ensembl is a joint project between the EBI and the Wellcome Trust Sanger Institute. It is a publicly available web resource that contains automatically annotated genomes and integrates data from a wide range of biological research sources. Launched in 1999, the Ensembl database was the first to provide a window on the draft genome, curating the results of a series of computational analyses. It provides comprehensive information about the human genome including variants like SNPs, insertions, deletions, and somatic mutations for several species. Ensembl also offers tools for data retrieval and analysis.",
+        "context": {
+            "1a93e25f-2a43-49e9-8450-03a57c93e613": [
+                {
+                    "document_id": "1a93e25f-2a43-49e9-8450-03a57c93e613",
+                    "text": "Annotation, preprocessing and categorization of data\n\nWe used Ensembl (version 39) as the annotation reference database.Homology between human and mouse genes was derived via BioMart.The total number of genes under study comprises 15,277 Ensembl mouse genes representing the union of the homologue genes from all data sources.An overview about the T2DM specific datasets is given in Table 1."
+                }
+            ],
+            "5edf84d0-c2d9-45eb-91b9-c35743b6a463": [
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text": "But the four sites are not equivalent; there are important distinctions between them in terms of the data analysed, the analyses carried\nout and the way the results are displayed. 4.4.1 Ensembl\nEnsembl is a joint project between the EBI (http://www.ebi.ac.uk/) and the Wellcome\nTrust Sanger Institute (http://www.sanger.ac.uk/). The Ensembl database (Hubbard\net al. , 2002; http://www.ensembl.org/), launched in 1999, was the first to provide a\nwindow on the draft genome, curating the results of a series of computational analyses."
+                },
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text": "Until January 2002 (Release 3.26.1), Ensembl used the UCSC draft sequence\nassemblies as its starting point, but it is now based upon NCBI assemblies. The\nEnsembl analysis pipeline consists of a rule-based system designed to mimic decisions made by a human annotator. The idea is to identify ‘confirmed’ genes that are\ncomputationally predicted (by the GENSCAN gene prediction program) and also\nsupported by a significant BLAST match to one or more expressed sequences or\nproteins. Ensembl also identifies the positions of known human genes from public\nsequence database entries, usually using GENEWISE to predict their exon structures."
+                },
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text": "Data retrieval is extremely well catered for in Ensembl, with text searches of all\ndatabase entries, BLAST searches of all sequences archived, and the availability of bulk\ndownloads of all Ensembl data and even software source code. Ensembl annotation\ncan also be viewed interactively on one’s local machine with the Apollo viewer (Lewis\net al. , 2002; http://www.fruitfly.org/annot/apollo/). 4.4.2 The UCSC Human Genome Browser\nThe UCSC Human Genome Browser (UCSC) bears many similarities to Ensembl;\nit, too, provides annotation of the NCBI assemblies, and it displays a similar array of\nfeatures, including confirmed genes from Ensembl."
+                }
+            ],
+            "c12e853e-4f0d-48f9-93af-15db9ad2dfae": [
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "But the four sites are not equivalent; there are important distinctions between them in terms of the data analysed, the analyses carried\nout and the way the results are displayed. 4.4.1 Ensembl\nEnsembl is a joint project between the EBI (http://www.ebi.ac.uk/) and the Wellcome\nTrust Sanger Institute (http://www.sanger.ac.uk/). The Ensembl database (Hubbard\net al. , 2002; http://www.ensembl.org/), launched in 1999, was the first to provide a\nwindow on the draft genome, curating the results of a series of computational analyses."
+                },
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "Until January 2002 (Release 3.26.1), Ensembl used the UCSC draft sequence\nassemblies as its starting point, but it is now based upon NCBI assemblies. The\nEnsembl analysis pipeline consists of a rule-based system designed to mimic decisions made by a human annotator. The idea is to identify ‘confirmed’ genes that are\ncomputationally predicted (by the GENSCAN gene prediction program) and also\nsupported by a significant BLAST match to one or more expressed sequences or\nproteins. Ensembl also identifies the positions of known human genes from public\nsequence database entries, usually using GENEWISE to predict their exon structures."
+                },
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "Data retrieval is extremely well catered for in Ensembl, with text searches of all\ndatabase entries, BLAST searches of all sequences archived, and the availability of bulk\ndownloads of all Ensembl data and even software source code. Ensembl annotation\ncan also be viewed interactively on one’s local machine with the Apollo viewer (Lewis\net al. , 2002; http://www.fruitfly.org/annot/apollo/). 4.4.2 The UCSC Human Genome Browser\nThe UCSC Human Genome Browser (UCSC) bears many similarities to Ensembl;\nit, too, provides annotation of the NCBI assemblies, and it displays a similar array of\nfeatures, including confirmed genes from Ensembl."
+                },
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "Ensembl provides a DAS reference\nserver giving access to a wide range of specialist annotations of the human\ngenome (for more detail, see http://www.ensembl.org/das/). Data mining The ability to query very large databases in order to satisfy a\nhypothesis (‘top-down’ data mining), or to interrogate a database in order to\ngenerate new hypotheses based on rigorous statistical correlations (‘bottom-up’\ndata mining). Domain (protein) A region of special biological interest within a single protein\nsequence."
+                }
+            ],
+            "f35e02a1-3314-4663-913f-38a3fc072aa8": [
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text": "But the four sites are not equivalent; there are important distinctions between them in terms of the data analysed, the analyses carried\nout and the way the results are displayed. 4.4.1 Ensembl\nEnsembl is a joint project between the EBI (http://www.ebi.ac.uk/) and the Wellcome\nTrust Sanger Institute (http://www.sanger.ac.uk/). The Ensembl database (Hubbard\net al. , 2002; http://www.ensembl.org/), launched in 1999, was the first to provide a\nwindow on the draft genome, curating the results of a series of computational analyses."
+                },
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text": "Until January 2002 (Release 3.26.1), Ensembl used the UCSC draft sequence\nassemblies as its starting point, but it is now based upon NCBI assemblies. The\nEnsembl analysis pipeline consists of a rule-based system designed to mimic decisions made by a human annotator. The idea is to identify ‘confirmed’ genes that are\ncomputationally predicted (by the GENSCAN gene prediction program) and also\nsupported by a significant BLAST match to one or more expressed sequences or\nproteins. Ensembl also identifies the positions of known human genes from public\nsequence database entries, usually using GENEWISE to predict their exon structures."
+                },
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text": "Data retrieval is extremely well catered for in Ensembl, with text searches of all\ndatabase entries, BLAST searches of all sequences archived, and the availability of bulk\ndownloads of all Ensembl data and even software source code. Ensembl annotation\ncan also be viewed interactively on one’s local machine with the Apollo viewer (Lewis\net al. , 2002; http://www.fruitfly.org/annot/apollo/). 4.4.2 The UCSC Human Genome Browser\nThe UCSC Human Genome Browser (UCSC) bears many similarities to Ensembl;\nit, too, provides annotation of the NCBI assemblies, and it displays a similar array of\nfeatures, including confirmed genes from Ensembl."
+                },
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text": "Ensembl provides a DAS reference\nserver giving access to a wide range of specialist annotations of the human\ngenome (for more detail, see http://www.ensembl.org/das/). Data mining The ability to query very large databases in order to satisfy a\nhypothesis (‘top-down’ data mining), or to interrogate a database in order to\ngenerate new hypotheses based on rigorous statistical correlations (‘bottom-up’\ndata mining). Domain (protein) A region of special biological interest within a single protein\nsequence."
+                }
+            ],
+            "f7072d9b-4e07-4541-bac7-13a25761f460": [
+                {
+                    "document_id": "f7072d9b-4e07-4541-bac7-13a25761f460",
+                    "text": "Ensembl\n\nEnsembl is a publicly available web resource that contains automatically annotated genomes.It is integrated with other available biological databases like Jasper for binding motifs.It is a much larger web resource than T1Dbase, and contains general information about the human genome including variants.These include SNPs, insertions, deletions and somatic mutations (Alterations in DNA that occur after conception, meaning that they are not inherited) for several species.Data from Ensembl can be accessed in a number of ways.The names of all the SNPs that occur in the T1D susceptibility regions can be collected from Ensembl using the Biomart tool (Kinsella et al., 2011).To achieve this, the coordinates of the T1D regions obtained from T1Dbase are uploaded to the biomart query page which allows one to search the genome browser and retrieve data like the names, chromosomal positions, and genic positions (referred to as \"consequence to transcript\", in Ensembl) of the SNPs.The SNP genic positions tell if a SNP is located within a gene, adjacent to a gene or whether they occur in inter-genic positions between gene coding regions, as well as the particular genes in which they are located."
+                },
+                {
+                    "document_id": "f7072d9b-4e07-4541-bac7-13a25761f460",
+                    "text": "Advantages of Ensembl:\n\nThere is a number of advantages to using Ensembl. (i) It is a larger web resource than T1Dbase and integrates data from a wide range of biological research sources into its database.Therefore, available information is quite comprehensive. (ii) Genic positions for 99% of the variants obtained from T1Dbase could be retrieved. (iii) Ensembl contains quality checks for genetic variants in its variation pipeline.A variant is flagged as failed if certain quality criteria are not met, for instance if none of the variant alleles match the reference allele of the variant.Generally, Ensembl was found to give more detailed information regarding the genic positions of variants compared to T1Dbase."
+                },
+                {
+                    "document_id": "f7072d9b-4e07-4541-bac7-13a25761f460",
+                    "text": "\n\nInformation about genes, including gene names, chromosomal coordinates, biotype (coding or non-coding), and number of splice variants, can also be retrieved from Ensembl."
+                }
+            ],
+            "fa8bba46-ce94-439a-a676-35187a3abcbf": [
+                {
+                    "document_id": "fa8bba46-ce94-439a-a676-35187a3abcbf",
+                    "text": "doi:10.1093/nar/gkp858\nCunningham F, Amode MR, Barrell D, Beal K,\nBillis K, Brent S, Carvalho-Silva D, Clapham\nP, Coates G, Fitzgerald S, Gil L, Giron CG,\nGordon L, Hourlier T, Hunt SE, Janacek SH,\nJohnson N, Juettemann T, Kahari AK, Keenan\nS, Martin FJ, Maurel T, McLaren W, Murphy\nDN, Nag R, Overduin B, Parker A, Patricio\nM, Perry E, Pignatelli M, Riat HS, Sheppard\nD, Taylor K, Thormann A, Vullo A, Wilder\nSP, Zadissa A, Aken BL, Birney E, Harrow J,\nKinsella R, Muffato M, Ruffier M, Searle SM,\nSpudich G, Trevanion SJ, Yates A, Zerbino\nDR, Flicek P (2015) Ensembl 2015."
+                }
+            ],
+            "fca531d0-d45b-495f-a02c-fbd437617b20": [
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "But the four sites are not equivalent; there are important distinctions between them in terms of the data analysed, the analyses carried\nout and the way the results are displayed. 4.4.1 Ensembl\nEnsembl is a joint project between the EBI (http://www.ebi.ac.uk/) and the Wellcome\nTrust Sanger Institute (http://www.sanger.ac.uk/). The Ensembl database (Hubbard\net al. , 2002; http://www.ensembl.org/), launched in 1999, was the first to provide a\nwindow on the draft genome, curating the results of a series of computational analyses."
+                },
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "Until January 2002 (Release 3.26.1), Ensembl used the UCSC draft sequence\nassemblies as its starting point, but it is now based upon NCBI assemblies. The\nEnsembl analysis pipeline consists of a rule-based system designed to mimic decisions made by a human annotator. The idea is to identify ‘confirmed’ genes that are\ncomputationally predicted (by the GENSCAN gene prediction program) and also\nsupported by a significant BLAST match to one or more expressed sequences or\nproteins. Ensembl also identifies the positions of known human genes from public\nsequence database entries, usually using GENEWISE to predict their exon structures."
+                },
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "Data retrieval is extremely well catered for in Ensembl, with text searches of all\ndatabase entries, BLAST searches of all sequences archived, and the availability of bulk\ndownloads of all Ensembl data and even software source code. Ensembl annotation\ncan also be viewed interactively on one’s local machine with the Apollo viewer (Lewis\net al. , 2002; http://www.fruitfly.org/annot/apollo/). 4.4.2 The UCSC Human Genome Browser\nThe UCSC Human Genome Browser (UCSC) bears many similarities to Ensembl;\nit, too, provides annotation of the NCBI assemblies, and it displays a similar array of\nfeatures, including confirmed genes from Ensembl."
+                },
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "Ensembl provides a DAS reference\nserver giving access to a wide range of specialist annotations of the human\ngenome (for more detail, see http://www.ensembl.org/das/). Data mining The ability to query very large databases in order to satisfy a\nhypothesis (‘top-down’ data mining), or to interrogate a database in order to\ngenerate new hypotheses based on rigorous statistical correlations (‘bottom-up’\ndata mining). Domain (protein) A region of special biological interest within a single protein\nsequence."
+                }
+            ]
+        },
+        "data_source": [
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "But the four sites are not equivalent; there are important distinctions between them in terms of the data analysed, the analyses carried\nout and the way the results are displayed.\n\n 4.4.1 Ensembl\nEnsembl is a joint project between the EBI (http://www.ebi.ac.uk/) and the Wellcome\nTrust Sanger Institute (http://www.sanger.ac.uk/).  The Ensembl database (Hubbard\net al. , 2002; http://www.ensembl.org/), launched in 1999, was the first to provide a\nwindow on the draft genome, curating the results of a series of computational analyses."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "But the four sites are not equivalent; there are important distinctions between them in terms of the data analysed, the analyses carried\nout and the way the results are displayed.\n\n 4.4.1 Ensembl\nEnsembl is a joint project between the EBI (http://www.ebi.ac.uk/) and the Wellcome\nTrust Sanger Institute (http://www.sanger.ac.uk/).  The Ensembl database (Hubbard\net al. , 2002; http://www.ensembl.org/), launched in 1999, was the first to provide a\nwindow on the draft genome, curating the results of a series of computational analyses."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "But the four sites are not equivalent; there are important distinctions between them in terms of the data analysed, the analyses carried\nout and the way the results are displayed.\n\n 4.4.1 Ensembl\nEnsembl is a joint project between the EBI (http://www.ebi.ac.uk/) and the Wellcome\nTrust Sanger Institute (http://www.sanger.ac.uk/).  The Ensembl database (Hubbard\net al. , 2002; http://www.ensembl.org/), launched in 1999, was the first to provide a\nwindow on the draft genome, curating the results of a series of computational analyses."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "But the four sites are not equivalent; there are important distinctions between them in terms of the data analysed, the analyses carried\nout and the way the results are displayed.\n\n 4.4.1 Ensembl\nEnsembl is a joint project between the EBI (http://www.ebi.ac.uk/) and the Wellcome\nTrust Sanger Institute (http://www.sanger.ac.uk/).  The Ensembl database (Hubbard\net al. , 2002; http://www.ensembl.org/), launched in 1999, was the first to provide a\nwindow on the draft genome, curating the results of a series of computational analyses."
+            },
+            {
+                "document_id": "f7072d9b-4e07-4541-bac7-13a25761f460",
+                "section_type": "main",
+                "text": "Ensembl\n\nEnsembl is a publicly available web resource that contains automatically annotated genomes.It is integrated with other available biological databases like Jasper for binding motifs.It is a much larger web resource than T1Dbase, and contains general information about the human genome including variants.These include SNPs, insertions, deletions and somatic mutations (Alterations in DNA that occur after conception, meaning that they are not inherited) for several species.Data from Ensembl can be accessed in a number of ways.The names of all the SNPs that occur in the T1D susceptibility regions can be collected from Ensembl using the Biomart tool (Kinsella et al., 2011).To achieve this, the coordinates of the T1D regions obtained from T1Dbase are uploaded to the biomart query page which allows one to search the genome browser and retrieve data like the names, chromosomal positions, and genic positions (referred to as \"consequence to transcript\", in Ensembl) of the SNPs.The SNP genic positions tell if a SNP is located within a gene, adjacent to a gene or whether they occur in inter-genic positions between gene coding regions, as well as the particular genes in which they are located."
+            },
+            {
+                "document_id": "fa8bba46-ce94-439a-a676-35187a3abcbf",
+                "section_type": "main",
+                "text": "doi:10.1093/nar/gkp858\nCunningham F, Amode MR, Barrell D, Beal K,\nBillis K, Brent S, Carvalho-Silva D, Clapham\nP, Coates G, Fitzgerald S, Gil L, Giron CG,\nGordon L, Hourlier T, Hunt SE, Janacek SH,\nJohnson N, Juettemann T, Kahari AK, Keenan\nS, Martin FJ, Maurel T, McLaren W, Murphy\nDN, Nag R, Overduin B, Parker A, Patricio\nM, Perry E, Pignatelli M, Riat HS, Sheppard\nD, Taylor K, Thormann A, Vullo A, Wilder\nSP, Zadissa A, Aken BL, Birney E, Harrow J,\nKinsella R, Muffato M, Ruffier M, Searle SM,\nSpudich G, Trevanion SJ, Yates A, Zerbino\nDR, Flicek P (2015) Ensembl 2015."
+            },
+            {
+                "document_id": "f7072d9b-4e07-4541-bac7-13a25761f460",
+                "section_type": "main",
+                "text": "Advantages of Ensembl:\n\nThere is a number of advantages to using Ensembl. (i) It is a larger web resource than T1Dbase and integrates data from a wide range of biological research sources into its database.Therefore, available information is quite comprehensive. (ii) Genic positions for 99% of the variants obtained from T1Dbase could be retrieved. (iii) Ensembl contains quality checks for genetic variants in its variation pipeline.A variant is flagged as failed if certain quality criteria are not met, for instance if none of the variant alleles match the reference allele of the variant.Generally, Ensembl was found to give more detailed information regarding the genic positions of variants compared to T1Dbase."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "Until January 2002 (Release 3.26.1), Ensembl used the UCSC draft sequence\nassemblies as its starting point, but it is now based upon NCBI assemblies.  The\nEnsembl analysis pipeline consists of a rule-based system designed to mimic decisions made by a human annotator.  The idea is to identify ‘confirmed’ genes that are\ncomputationally predicted (by the GENSCAN gene prediction program) and also\nsupported by a significant BLAST match to one or more expressed sequences or\nproteins.  Ensembl also identifies the positions of known human genes from public\nsequence database entries, usually using GENEWISE to predict their exon structures."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "Until January 2002 (Release 3.26.1), Ensembl used the UCSC draft sequence\nassemblies as its starting point, but it is now based upon NCBI assemblies.  The\nEnsembl analysis pipeline consists of a rule-based system designed to mimic decisions made by a human annotator.  The idea is to identify ‘confirmed’ genes that are\ncomputationally predicted (by the GENSCAN gene prediction program) and also\nsupported by a significant BLAST match to one or more expressed sequences or\nproteins.  Ensembl also identifies the positions of known human genes from public\nsequence database entries, usually using GENEWISE to predict their exon structures."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "Until January 2002 (Release 3.26.1), Ensembl used the UCSC draft sequence\nassemblies as its starting point, but it is now based upon NCBI assemblies.  The\nEnsembl analysis pipeline consists of a rule-based system designed to mimic decisions made by a human annotator.  The idea is to identify ‘confirmed’ genes that are\ncomputationally predicted (by the GENSCAN gene prediction program) and also\nsupported by a significant BLAST match to one or more expressed sequences or\nproteins.  Ensembl also identifies the positions of known human genes from public\nsequence database entries, usually using GENEWISE to predict their exon structures."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "Until January 2002 (Release 3.26.1), Ensembl used the UCSC draft sequence\nassemblies as its starting point, but it is now based upon NCBI assemblies.  The\nEnsembl analysis pipeline consists of a rule-based system designed to mimic decisions made by a human annotator.  The idea is to identify ‘confirmed’ genes that are\ncomputationally predicted (by the GENSCAN gene prediction program) and also\nsupported by a significant BLAST match to one or more expressed sequences or\nproteins.  Ensembl also identifies the positions of known human genes from public\nsequence database entries, usually using GENEWISE to predict their exon structures."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "Another\ngrowing area of activity is in cataloguing the genetic variation present in human\npopulations as Ensembl reflects the progress of the International Haplotype Map\nProject (Thorisson et al. , 2005).\n More speculative data, such as GENSCAN-predicted exons that have not been\nincorporated into Ensembl-confirmed genes, may also be viewed.  This means that\nthe display can be used as a workbench for the user to develop personalized annotation."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "Another\ngrowing area of activity is in cataloguing the genetic variation present in human\npopulations as Ensembl reflects the progress of the International Haplotype Map\nProject (Thorisson et al. , 2005).\n More speculative data, such as GENSCAN-predicted exons that have not been\nincorporated into Ensembl-confirmed genes, may also be viewed.  This means that\nthe display can be used as a workbench for the user to develop personalized annotation."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "Another\ngrowing area of activity is in cataloguing the genetic variation present in human\npopulations as Ensembl reflects the progress of the International Haplotype Map\nProject (Thorisson et al. , 2005).\n More speculative data, such as GENSCAN-predicted exons that have not been\nincorporated into Ensembl-confirmed genes, may also be viewed.  This means that\nthe display can be used as a workbench for the user to develop personalized annotation."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "Another\ngrowing area of activity is in cataloguing the genetic variation present in human\npopulations as Ensembl reflects the progress of the International Haplotype Map\nProject (Thorisson et al. , 2005).\n More speculative data, such as GENSCAN-predicted exons that have not been\nincorporated into Ensembl-confirmed genes, may also be viewed.  This means that\nthe display can be used as a workbench for the user to develop personalized annotation."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "Data retrieval is extremely well catered for in Ensembl, with text searches of all\ndatabase entries, BLAST searches of all sequences archived, and the availability of bulk\ndownloads of all Ensembl data and even software source code.  Ensembl annotation\ncan also be viewed interactively on one’s local machine with the Apollo viewer (Lewis\net al. , 2002; http://www.fruitfly.org/annot/apollo/).\n\n 4.4.2 The UCSC Human Genome Browser\nThe UCSC Human Genome Browser (UCSC) bears many similarities to Ensembl;\nit, too, provides annotation of the NCBI assemblies, and it displays a similar array of\nfeatures, including confirmed genes from Ensembl."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "Data retrieval is extremely well catered for in Ensembl, with text searches of all\ndatabase entries, BLAST searches of all sequences archived, and the availability of bulk\ndownloads of all Ensembl data and even software source code.  Ensembl annotation\ncan also be viewed interactively on one’s local machine with the Apollo viewer (Lewis\net al. , 2002; http://www.fruitfly.org/annot/apollo/).\n\n 4.4.2 The UCSC Human Genome Browser\nThe UCSC Human Genome Browser (UCSC) bears many similarities to Ensembl;\nit, too, provides annotation of the NCBI assemblies, and it displays a similar array of\nfeatures, including confirmed genes from Ensembl."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "Data retrieval is extremely well catered for in Ensembl, with text searches of all\ndatabase entries, BLAST searches of all sequences archived, and the availability of bulk\ndownloads of all Ensembl data and even software source code.  Ensembl annotation\ncan also be viewed interactively on one’s local machine with the Apollo viewer (Lewis\net al. , 2002; http://www.fruitfly.org/annot/apollo/).\n\n 4.4.2 The UCSC Human Genome Browser\nThe UCSC Human Genome Browser (UCSC) bears many similarities to Ensembl;\nit, too, provides annotation of the NCBI assemblies, and it displays a similar array of\nfeatures, including confirmed genes from Ensembl."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "Data retrieval is extremely well catered for in Ensembl, with text searches of all\ndatabase entries, BLAST searches of all sequences archived, and the availability of bulk\ndownloads of all Ensembl data and even software source code.  Ensembl annotation\ncan also be viewed interactively on one’s local machine with the Apollo viewer (Lewis\net al. , 2002; http://www.fruitfly.org/annot/apollo/).\n\n 4.4.2 The UCSC Human Genome Browser\nThe UCSC Human Genome Browser (UCSC) bears many similarities to Ensembl;\nit, too, provides annotation of the NCBI assemblies, and it displays a similar array of\nfeatures, including confirmed genes from Ensembl."
+            },
+            {
+                "document_id": "429abfc1-f628-48ff-bfe8-f7be6d1419a8",
+                "section_type": "main",
+                "text": "Zerbino, D. R., Achuthan, P., Akanni, W., Amode, M. R., Barrell,\nD., Bhai, J., Billis, K., Cummins, C., Gall, A., Girón, C. G., Gil,\nL., Gordon, L., Haggerty, L., Haskell, E., Hourlier, T., Izuogu, O.\nG., Janacek, S. H., Juettemann, T., To, J. K., Laird, M. R., Lavidas, I., Liu, Z., Loveland, J. E., Maurel, T., McLaren, W., Moore,\nB., Mudge, J., Murphy, D. N., Newman, V., Nuhn, M., Ogeh, D.,\nOng, C. K., Parker, A., Patricio, M., Riat, H. S., Schuilenburg,\nH., Sheppard, D., Sparrow, H., Taylor, K., Thormann, A., Vullo,\nA., Walts, B., Zadissa, A., Frankish, A., Hunt, S. E., Kostadima,\nM., Langridge, N., Martin, F. J., Muffato, M., Perry, E., Ruffier,\nM., Staines, D. M., Trevanion, S. J., Aken, B. L., Cunningham,\nF., Yates, A., and Flicek, P.: Ensembl 2018, Nucl."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "gov/mapview/) evolved to allow graphical depictions of, and comparisons between,\na wide range of genetic and physical maps in parallel with NCBI draft and finished sequence contigs.  The locations of genes, markers, and SNPs are indicated\non the assembled sequences.  As with Ensembl, there is a NCBI analysis protocol\nwhich aims to predict gene structures based upon EST and mRNA alignments with\nthe draft genome.  This is carried out by a program called Acembly (unpublished;\nhttp://www.ncbi.nlm.nih.gov/IEB/Research/Acembly/index.html), which aims to\nderive gene structure from these alignments alone."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "gov/mapview/) evolved to allow graphical depictions of, and comparisons between,\na wide range of genetic and physical maps in parallel with NCBI draft and finished sequence contigs.  The locations of genes, markers, and SNPs are indicated\non the assembled sequences.  As with Ensembl, there is a NCBI analysis protocol\nwhich aims to predict gene structures based upon EST and mRNA alignments with\nthe draft genome.  This is carried out by a program called Acembly (unpublished;\nhttp://www.ncbi.nlm.nih.gov/IEB/Research/Acembly/index.html), which aims to\nderive gene structure from these alignments alone."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "gov/mapview/) evolved to allow graphical depictions of, and comparisons between,\na wide range of genetic and physical maps in parallel with NCBI draft and finished sequence contigs.  The locations of genes, markers, and SNPs are indicated\non the assembled sequences.  As with Ensembl, there is a NCBI analysis protocol\nwhich aims to predict gene structures based upon EST and mRNA alignments with\nthe draft genome.  This is carried out by a program called Acembly (unpublished;\nhttp://www.ncbi.nlm.nih.gov/IEB/Research/Acembly/index.html), which aims to\nderive gene structure from these alignments alone."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "gov/mapview/) evolved to allow graphical depictions of, and comparisons between,\na wide range of genetic and physical maps in parallel with NCBI draft and finished sequence contigs.  The locations of genes, markers, and SNPs are indicated\non the assembled sequences.  As with Ensembl, there is a NCBI analysis protocol\nwhich aims to predict gene structures based upon EST and mRNA alignments with\nthe draft genome.  This is carried out by a program called Acembly (unpublished;\nhttp://www.ncbi.nlm.nih.gov/IEB/Research/Acembly/index.html), which aims to\nderive gene structure from these alignments alone."
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "B., Ching, K. A., Batalov, S. et al.  (2001).  A comparison of the Celera and\nEnsembl predicted gene sets reveals little overlap in novel genes.  Cell 106, 413–415.\n Hubbard, T., Barker, D., Birney, E. et al.  (2002).  The Ensembl genome database project.  Nucleic\nAcids Res 30, 38–41.\n Huson, D. H., Reinert, K., Kravitz, S. A. et al.  (2001).  Design of a compartmentalized shotgun\nassembler for the human genome.  Bioinformatics 17 Suppl 1, S132–139.\n Huynen, M. A. and Bork, P. (1998).  Measuring genome evolution.  Proc Natl Acad Sci U S A\n95, 5849–5856.\n Ideker, T., Galitski, T. and Hood, L. (2001)."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "B., Ching, K. A., Batalov, S. et al.  (2001).  A comparison of the Celera and\nEnsembl predicted gene sets reveals little overlap in novel genes.  Cell 106, 413–415.\n Hubbard, T., Barker, D., Birney, E. et al.  (2002).  The Ensembl genome database project.  Nucleic\nAcids Res 30, 38–41.\n Huson, D. H., Reinert, K., Kravitz, S. A. et al.  (2001).  Design of a compartmentalized shotgun\nassembler for the human genome.  Bioinformatics 17 Suppl 1, S132–139.\n Huynen, M. A. and Bork, P. (1998).  Measuring genome evolution.  Proc Natl Acad Sci U S A\n95, 5849–5856.\n Ideker, T., Galitski, T. and Hood, L. (2001)."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "B., Ching, K. A., Batalov, S. et al.  (2001).  A comparison of the Celera and\nEnsembl predicted gene sets reveals little overlap in novel genes.  Cell 106, 413–415.\n Hubbard, T., Barker, D., Birney, E. et al.  (2002).  The Ensembl genome database project.  Nucleic\nAcids Res 30, 38–41.\n Huson, D. H., Reinert, K., Kravitz, S. A. et al.  (2001).  Design of a compartmentalized shotgun\nassembler for the human genome.  Bioinformatics 17 Suppl 1, S132–139.\n Huynen, M. A. and Bork, P. (1998).  Measuring genome evolution.  Proc Natl Acad Sci U S A\n95, 5849–5856.\n Ideker, T., Galitski, T. and Hood, L. (2001)."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "B., Ching, K. A., Batalov, S. et al.  (2001).  A comparison of the Celera and\nEnsembl predicted gene sets reveals little overlap in novel genes.  Cell 106, 413–415.\n Hubbard, T., Barker, D., Birney, E. et al.  (2002).  The Ensembl genome database project.  Nucleic\nAcids Res 30, 38–41.\n Huson, D. H., Reinert, K., Kravitz, S. A. et al.  (2001).  Design of a compartmentalized shotgun\nassembler for the human genome.  Bioinformatics 17 Suppl 1, S132–139.\n Huynen, M. A. and Bork, P. (1998).  Measuring genome evolution.  Proc Natl Acad Sci U S A\n95, 5849–5856.\n Ideker, T., Galitski, T. and Hood, L. (2001)."
+            },
+            {
+                "document_id": "1a93e25f-2a43-49e9-8450-03a57c93e613",
+                "section_type": "main",
+                "text": "Annotation, preprocessing and categorization of data\n\nWe used Ensembl (version 39) as the annotation reference database.Homology between human and mouse genes was derived via BioMart.The total number of genes under study comprises 15,277 Ensembl mouse genes representing the union of the homologue genes from all data sources.An overview about the T2DM specific datasets is given in Table 1."
+            },
+            {
+                "document_id": "f7072d9b-4e07-4541-bac7-13a25761f460",
+                "section_type": "main",
+                "text": "\n\nInformation about genes, including gene names, chromosomal coordinates, biotype (coding or non-coding), and number of splice variants, can also be retrieved from Ensembl."
+            },
+            {
+                "document_id": "046184a9-f062-4da2-9900-641aab9468e1",
+                "section_type": "main",
+                "text": "Electronic-Database Information\n\nURLs for data presented herein are as follows: Center for Medical Genetics, http://research.marshfieldclinic.org/genetics/Ensembl Genome Browser, http://www.ensembl.org/Harvard Partners Genome Center, http://www.hpcgg.org/Sequence/human.htmlOnline Mendelian Inheritance in Man (OMIM), http://www .ncbi.nlm.nih.gov/Omim/(forcandidate genes related to the chromosome 12 region of interest) Unified Database for Human Genome Mapping, The, http:// genecards.weizmann.ac.il/udb/"
+            },
+            {
+                "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                "section_type": "main",
+                "text": "Ensembl provides a DAS reference\nserver giving access to a wide range of specialist annotations of the human\ngenome (for more detail, see http://www.ensembl.org/das/).\n Data mining The ability to query very large databases in order to satisfy a\nhypothesis (‘top-down’ data mining), or to interrogate a database in order to\ngenerate new hypotheses based on rigorous statistical correlations (‘bottom-up’\ndata mining).\n Domain (protein) A region of special biological interest within a single protein\nsequence."
+            },
+            {
+                "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                "section_type": "main",
+                "text": "Ensembl provides a DAS reference\nserver giving access to a wide range of specialist annotations of the human\ngenome (for more detail, see http://www.ensembl.org/das/).\n Data mining The ability to query very large databases in order to satisfy a\nhypothesis (‘top-down’ data mining), or to interrogate a database in order to\ngenerate new hypotheses based on rigorous statistical correlations (‘bottom-up’\ndata mining).\n Domain (protein) A region of special biological interest within a single protein\nsequence."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "Ensembl provides a DAS reference\nserver giving access to a wide range of specialist annotations of the human\ngenome (for more detail, see http://www.ensembl.org/das/).\n Data mining The ability to query very large databases in order to satisfy a\nhypothesis (‘top-down’ data mining), or to interrogate a database in order to\ngenerate new hypotheses based on rigorous statistical correlations (‘bottom-up’\ndata mining).\n Domain (protein) A region of special biological interest within a single protein\nsequence."
+            },
+            {
+                "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                "section_type": "main",
+                "text": "Ensembl provides a DAS reference\nserver giving access to a wide range of specialist annotations of the human\ngenome (for more detail, see http://www.ensembl.org/das/).\n Data mining The ability to query very large databases in order to satisfy a\nhypothesis (‘top-down’ data mining), or to interrogate a database in order to\ngenerate new hypotheses based on rigorous statistical correlations (‘bottom-up’\ndata mining).\n Domain (protein) A region of special biological interest within a single protein\nsequence."
+            },
+            {
+                "document_id": "f2f55df4-7e90-4600-90a4-fa30a4c91c5f",
+                "section_type": "main",
+                "text": "\n\n*The number of Ensembl genes per megabases.Genome Biology 2003, 4:R74"
+            },
+            {
+                "document_id": "82fcaf77-adf7-47f4-8ebd-6b7a9df8d73e",
+                "section_type": "main",
+                "text": "\n\nURLs.Ensembl: http://www.ensembl.org;British 1958 Birth Cohort: http:// www.b58cgene.sgul.ac.uk/;T1DBase: http://t1dbase.org(and UK mirror site, http://dil.t1dbase.org);Stata: http://www.stata.com/;R: http://www.r-project.org/; rpart: http://cran.r-project.org/;D. Clayton's software: http://www-gene.cimr.cam.ac.uk/clayton/software/;Haploview: http://www.broad.mit.edu/mpg/haploview/; gbrowse: http://www.gmod.org/;T1DBase PosterPages: https:// dil.t1dbase.org/page/PosterAdhocAccession codes.All genes are referred to by their HUGO symbol, except for Tenr on 4q27 (Entrez GeneID 132612, alias FLJ32741) and DEXI on 16p13 (Entrez GeneID 28955, alias MYLE)."
+            },
+            {
+                "document_id": "e2a02184-d59a-4884-b67e-67209b9b9ae2",
+                "section_type": "main",
+                "text": "\n\n. ENIGMA Consortium, http://enigma.loni.ucla.edu;eqtl.uchicago.edu,http://eqtl.uchicago.edu/cgi-bin/gbrowse/eqtl/;SNAP, http://www.broadinstitute.org/mpg/snap/;GeneCruiser, http:// genecruiser.broadinstitute.org/genecruiser3/. : Supplementary information is available on the Nature Genetics website.Research was funded by the US National Institute on Aging (NIA; N01-AG-12100), with contributions from the National Eye Institute (NEI), the National Institute on Deafness and Other Communication Disorders (NIDCD), the US National Heart, Lung, and Blood Institute (NHLBI), the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association) and the Althingi (the Icelandic Parliament)."
+            },
+            {
+                "document_id": "a4e9db98-b007-49f5-bcbd-ce0f78cbff1f",
+                "section_type": "main",
+                "text": "Thierry-Mieg D, Thierry-Mieg J: AceView: a comprehensive cDNAsupported gene and transcripts annotation.  Genome Biol 2006,\n7(Suppl 1):S12.\n 28.  Kuhn RM, Karolchik D, Zweig AS, Wang T, Smith KE, Rosenbloom KR, Rhead\nB, Raney BJ, Pohl A, Pheasant M, et al: The UCSC genome browser\ndatabase: update 2009.  Nucleic Acids Res 2009, 37(suppl 1):D755–D761.\n 29.  The EPC: A User’s guide to the encyclopedia of DNA elements (ENCODE).\n PLoS Biol 2011, 9(4):e1001046.\n 30.  Frazer KA, Pachter L, Poliakov A, Rubin EM, Dubchak I: VISTA:\ncomputational tools for comparative genomics.  Nucleic Acids Res 2004,\n32(suppl 2):W273–W279.\n 31."
+            },
+            {
+                "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                "section_type": "main",
+                "text": "The Ensembl and UCSC sites now display at least 16 vertebrate genome\nassemblies; these can either be viewed directly or aligned against the human genome.\n Cross-species data can be assessed at several levels.  Comparison of DNA similarity between (vertebrate) genomes is termed ‘phylogenetic footprinting’ (Susens and\nBorgmeyer, 2001; see Chapter 6 for a detailed review of this approach)."
+            }
+        ],
+        "document_id": "FB39925222D82C39F4BBAA833135ACA5",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "Ensembl",
+            "EBI",
+            "Wellcome&Trust&Sanger&Institute",
+            "genome",
+            "computational&analyses",
+            "T1Dbase",
+            "SNPs",
+            "Biomart",
+            "NCBI",
+            "GENSCAN"
+        ],
+        "metadata": [
+            {
+                "object": "1443823_s_at: short probe set - potential SNPs could affect mapping result; 1427465_at: 3 SNPs in target area affect the hybridization of 5 probes; 1434893_at: 6 SNPs in target area could affect the hybridization of 7 probes; 1455136_at generate true cisQTL even 3 SNPs in target area affect mapping accuracy of 4 probes - BUT probes without any SNPs reveal the presence of an eQTL.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab43"
+            },
+            {
+                "object": "We discovered two genome-wide significant SNPs. The first was novel and near ISG20. The second was in TRIOBP, a gene previously associated with prelingual nonsyndromic hearing loss. Motivated by our TRIOBP results, we also looked at exons in known hearing loss genes, and identified two additional SNPs, rs2877561 in ILDR1 and rs9493672 in EYA4 at a significance threshold adjusted for number of SNPs in those regions.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab1003104"
+            },
+            {
+                "object": "We here reviewed published data on single nucleotide polymorphisms SNPs in HIF1A in various diseases; in total, 34 SNPs were tested for an association with 49 phenotypes, and the results were visualized using the Cytoscape software. Among all collected polymorphisms 16 SNPs showed significant associations with 40 different phenotypes, including six SNPs associated with 14 cancer types",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab1006971"
+            },
+            {
+                "object": "Genome-wide association analyses in 22,981 participants 2280 shingles cases from the electronic Medical Records and Genomics Network identified a genomic region in the combined and European ancestry groups that has an age of onset effect reaching genome-wide significance region tags the non-coding gene HCP5 HLA Complex P5.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab319975"
+            },
+            {
+                "object": "We identified 89 single nucleotide polymorphisms SNPs and 11 DNA insertion-deletions InDels, of which 70 SNPs and 8 InDels were found in rhg1, 9 SNPs were found in Rhg4, and 10 SNPs and 3 InDels were found in SHMT.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab1007215"
+            },
+            {
+                "object": "PNPLA3 is associated with liver enzymes in populations of Mexican American ancestry. In the PNPLA3 gene, single-nucleotide polymorphisms SNPs rs4823173 rs2896019 and rs2281135 were significantly associated with aspartate aminotransferase Although not genome-wide significant, the same SNPs were the top hits for alanine aminotransferase. The strong correlation for these SNPs indicated a single hit in the PNPLA3 gene.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab602807"
+            },
+            {
+                "object": "TH2B is a unique histone variant that plays a key role in the histone-to-protamine packing of the male genome and guides genome-wide chromatin transitions that both precede and follow transmission of the male genome to the egg.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab771863"
+            },
+            {
+                "object": "variation in GGTA1 of 8 commercial pig populations; 17 SNPs were detected: 11 in intronic regions & 6 in the 3' untranslated region; no SNPs change the encoded protein; but 8 of the SNPs may alter GGTA1 transcriptional regulation & pre-mRNA splicing",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab992182"
+            },
+            {
+                "object": "Study surveyed the non-synonymous SNPs of DNASE1L2: 19 SNPs originating from frameshift/nonsense mutations found in DNASE1L2 resulted in loss of function of the enzyme. Thus, the present findings suggest that each of the minor alleles for these SNPs may serve as one of genetic risk factors for parakeratotic skin diseases such as psoriasis, even though they lack a worldwide genetic distribution.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab752673"
+            },
+            {
+                "object": "Our results show the significance of ABCB1 SNPs on GO response in AML and warrants the need to investigate this in other cohorts. Once validated, ABCB1-SNPs in conjunction with CD33-SNPs can open up opportunities to personalize GO-therapy.",
+                "predicate": "http://www.w3.org/2000/01/rdf-schema#comment",
+                "subject": "ndd791caee50643ad90a986f563d2a0dab562151"
+            }
+        ],
+        "question": "what is ensembl?",
+        "subquestions": null,
+        "task_id": "FB39925222D82C39F4BBAA833135ACA5",
+        "usage": {
+            "chatgpt": 5858,
+            "gpt-4": 3829,
+            "gpt-4-turbo-preview": 2871
+        },
+        "user_id": 2
+    },
+    "document_id": "FB39925222D82C39F4BBAA833135ACA5",
+    "task_id": "FB39925222D82C39F4BBAA833135ACA5"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_01.json b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_01.json
new file mode 100644
index 0000000..523fff5
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_01.json
@@ -0,0 +1,156 @@
+{
+    "created_at": "2024-05-31T13:08:08.864950Z",
+    "data": {
+        "amplify": false,
+        "answer": "To determine which gene in your QTL is causal for the trait, you can follow several steps. First, narrow down the QTL interval to a reasonable size. Then, sort through the genes within the interval to identify potential Quantitative Trait Genes (QTGs). This can be challenging as more than one gene may be involved and the function of some genes may be unknown. You can use techniques like LCMS to establish causal relationships between DNA loci and transcripts. Once potential QTGs are identified, you need to prove that a particular gene is involved in the quantitative trait under study. This can be done by complementation of a QTL, which can be achieved in several ways. You can also use mediation analysis to identify the causal gene between the genetic variant and the trait-of-interest. Finally, investigate whether the expression of these genes correlates with the phenotype(s) of interest. If the gene expression strongly correlates with the QTL phenotype, this further strengthens the assumption that this gene might be causal.",
+        "context": {
+            "07d409f4-91f9-4701-bb39-1421845a6321": [
+                {
+                    "document_id": "07d409f4-91f9-4701-bb39-1421845a6321",
+                    "text": "Prior belief or knowledge about the number of true causal and true\nindependent links that might be expected in a typical QTL, depending on the study\ndesign, should be considered to safeguard against high false-positive rates (low\npositive predictive values). In studies that involve mapping gene expression (eQTL),\nprotein (pQTL) or metabolite (mQTL) traits, information about co-localization of\nQTL and genes that are functionally linked to the trait provides information about\nthe likelihood of causal links."
+                }
+            ],
+            "1a041a89-4da8-4ad5-b241-da36df917930": [
+                {
+                    "document_id": "1a041a89-4da8-4ad5-b241-da36df917930",
+                    "text": "\n\nThe next step is to investigate whether the expression of these genes correlates with the phenotype(s) of interest.This would suggest a chain of causality: a variant within a gene causes a change in its expression, and the expression of that gene correlates with expression of a phenotypic trait of interest.To do this, we created a correlation matrix between all genes within a QTL with a cis-eQTL in any brain tissue as well as the phenotypes that contributed to the QTL (Supplementary Table S6).Any gene with a cis-eQTL and a significantly correlated expression was considered a good candidate.If the gene only had a cis-eQTL and correlation in a single brain region, then it suggested that this brain region might also be of interest for the phenotype (adding another link to this chain)."
+                }
+            ],
+            "33814fad-d831-46f5-b41f-ff31626a82ca": [
+                {
+                    "document_id": "33814fad-d831-46f5-b41f-ff31626a82ca",
+                    "text": "One possible approach to facilitate this endeavor is to identify quantitative trait loci\n(QTL) that contribute to the phenotype and consequently unravel the candidate\ngenes within these loci. Each proposed candidate locus contains multiple genes and,\ntherefore, further analysis is required to choose plausible candidate genes. One of\nsuch methods is to use comparative genomics in order to narrow down the QTL to a\nregion containing only a few genes. We illustrate this strategy by applying it to\ngenetic findings regarding physical activity (PA) in mice and human."
+                }
+            ],
+            "4049da4d-c7cf-4e30-9a21-c77609fad23d": [
+                {
+                    "document_id": "4049da4d-c7cf-4e30-9a21-c77609fad23d",
+                    "text": "Network analyses\nWe now have two QTL, and we have picked potentially interesting genes within each, but now\nwe want to build up more evidence for which gene in our QTL interval is causal. The first, and\nmost obvious way, is to see what genes our trait of interest correlates with, in tissues that we\nexpect to be related to the trait. We calculated the Spearman’s correlation between the trait\nBXD_17850 and all probes with expression data in T helper cells (GN319)."
+                }
+            ],
+            "47c12133-5a30-45b9-bcb8-b96f00737f31": [
+                {
+                    "document_id": "47c12133-5a30-45b9-bcb8-b96f00737f31",
+                    "text": "Another\napproach to help to determine if a gene located near the mapped QTL would\nhave effects to influence the quantitative trait will be to use genetically engineered mice to determine if altering the expression of a candidate gene will alter\nthe phenotype of interest (38). However, it is possible that a quantitative trait is\na combined effect of multiple genes located near the QTL (39)."
+                }
+            ],
+            "547ce63b-5178-45cb-ae07-12ae66aa2967": [
+                {
+                    "document_id": "547ce63b-5178-45cb-ae07-12ae66aa2967",
+                    "text": "With a known QTL and a\nbody of evidence suggesting possible roles for the affected gene,\nphenotypes can be predicted that may be modulated as a result\nof this sequence variation. If this phenotype is of interest, it\ncan be directly measured and a traditional ‘forward’ QTL analysis carried out to confirm the prediction. Such an approach is\nextremely attractive when the enormous cost and time required\nfor phenotyping a large panel is considered."
+                }
+            ],
+            "581f83bc-3521-4cb3-ad3c-d905a90ecc29": [
+                {
+                    "document_id": "581f83bc-3521-4cb3-ad3c-d905a90ecc29",
+                    "text": "The first\nstep is to narrow down the list of\ncandidate causal genes within a\nFig\n1. Interval\nmapping\nof\noviduct\ngross\npathology\nacross\nthe\nBXD\nstrains\n\nQuantitative Trait Locus (QTL)—a\nreveals\na\nQTL\non\ndistal\nChr\n3. The\nL RS\nvalues\nare\nplotted\nin\nblue\nacross\nthe\n\nchromosomal region containing\ngenome\nand\nmeasure\nthe\nstrength\nof\nthe\nassociation\nbetween\n\nsequence variants strongly\nchromosome\nand\nMb\nposition\n(top\nand\nbottom\nX-‐axis,\nrespectively)\nand\n\nassociated with phenotypic\nphenotype\nexpression. Allele\ncontribution\nis\nshown\nby\nthe\nred\n(C57BL/6J)\n\nand\ngreen\n(DBA/2J)\nlines. Red\nand\ngrey\nhorizontal\nlines\nindicate\ngenome-‐\nvariation."
+                }
+            ],
+            "5a56fa6d-9e77-4b95-a836-04d0fa31ee2c": [
+                {
+                    "document_id": "5a56fa6d-9e77-4b95-a836-04d0fa31ee2c",
+                    "text": "A special case is the\ncorrelation of the target phenotype with the expression of the\npriorized gene(s) (RNA or protein amounts). This refers to\ncolocalization of the QTL of the target phenotype with the\neQTL position. Correlation can also be examined between the\ntarget QTL phenotype and expression of all genes in the QTL\ninterval. If the gene expression strongly correlates with the\nQTL phenotype, this further strengthens the assumption that\nthis gene might be causal (see Note 12). For performing a correlation analysis:\n–\n\nGo to the Trait Overview Page, as described in step 3, point\n1."
+                }
+            ],
+            "64886b4e-8599-4f61-84e6-9add7663a1b3": [
+                {
+                    "document_id": "64886b4e-8599-4f61-84e6-9add7663a1b3",
+                    "text": "QTL mapping of traits in mouse cohorts often ends up with a genetic locus, composed of a list of candidate\ngenes. Several studies proposed the use of mediation analysis to identify the causal gene (mediator) between\nthe genetic variant (independent variable) and the trait-of-interest (dependent variable) (Figure 1.4B) [7, 47,\n61, 77]. Mediation analysis can be used either on gene expression levels to identify the regulatory mechanisms\n[7, 47, 61], or on phenotypic traits to discover the potential causal drivers contributing to the phenotypic\nvariances [77] (Figure 1.4C upper)."
+                }
+            ],
+            "7a451204-390c-4ff2-8a1d-b4de62b73503": [
+                {
+                    "document_id": "7a451204-390c-4ff2-8a1d-b4de62b73503",
+                    "text": "1a). Second-generation offspring are then\nphenotyped and genotyped, and linkage analysis is carried out to identify a region that is\nassociated with the trait1. This approach has led to the identification of thousands of quantitative trait loci (QTLs) for\nvarious phenotypes and diseases. However, each QTL region is large, often tens of\nmegabases, and contains hundreds of genes. The process of identifying the causal variant\nand the gene involved is therefore difficult and costly. Of the thousands of QTLs identified,\nonly a small fraction of genes has been identified. NIH-PA Author Manuscript\n\n© 2012 Macmillan Publishers Limited."
+                }
+            ],
+            "7b1cecf5-a2b9-4bd9-b92b-9bd6b96ed93d": [
+                {
+                    "document_id": "7b1cecf5-a2b9-4bd9-b92b-9bd6b96ed93d",
+                    "text": "Network analyses\nWe now have two QTL, and we have picked potentially interesting genes within each, but now\nwe want to build up more evidence for which gene in our QTL interval is causal. The first, and\nmost obvious way, is to see what genes our trait of interest correlates with, in tissues that we\nexpect to be related to the trait. We calculated the Spearman’s correlation between the trait\nBXD_17850 and all probes with expression data in T helper cells (GN319)."
+                }
+            ],
+            "7d866915-9d92-4401-8340-ffdef457debe": [
+                {
+                    "document_id": "7d866915-9d92-4401-8340-ffdef457debe",
+                    "text": "10 JUNE 2016 • VOL 352 ISSUE 6291\n\naad0189-5\nR ES E A RC H | R E S EA R C H A R T I C LE\n\nSolving QTLs: Finding the quantitative\ntrait gene\nFor cis-QTLs, the causal factors can be quickly\nidentified: With few exceptions, they will be driven by variants within the gene itself or immediately adjacent. For trans-QTLs, mQTLs, and\ncQTLs, the identification of the causal quantitative trait gene (QTG) is challenging due to the\nwidth of the QTLs."
+                }
+            ],
+            "95b99c09-c336-44fd-b378-f41991edb3aa": [
+                {
+                    "document_id": "95b99c09-c336-44fd-b378-f41991edb3aa",
+                    "text": "Once the QTL interval is reduced to a reasonable size,\nthe next step in the process involves sorting through the\ngenes within the interval and attempting to determine\nwhich is the QTG. This step is daunting because more than\none gene may be involved and the function of some genes\nwithin the interval may be unknown. Until recently, this\nstep emphasized the detection of polymorphisms within\ncoding sequence (reviewed in Korstanje and Paigen, 2002\nand Glazier et al. 2002); for a polymorphism that produces\nan amino acid substitution, one can often infer and then\ntest for a functional consequence."
+                }
+            ],
+            "abea3dd4-9492-4a2b-8904-b8052e384785": [
+                {
+                    "document_id": "abea3dd4-9492-4a2b-8904-b8052e384785",
+                    "text": "To understand the genetic networks that underlie\nquantitative variation in the trait, it is also very important to\ndiscover genes whose expression is correlated with the trait\nafter accounting for the known effects of the QTL on the\ntrait. Many of these genes may have expression that is\nassociated with QTL genotype, and would therefore be\nidentified as important via the tests described above. Other\n\ngenes, however, may have expression values that are correlated with the trait but unassociated with genotype at the\nQTL."
+                },
+                {
+                    "document_id": "abea3dd4-9492-4a2b-8904-b8052e384785",
+                    "text": "The\napproach is motivated by the fact that a research project is\noften focused on a specific classical quantitative trait. If a\nmajor QTL for this classical trait has been identified, it is\noften desirable to test whether this QTL is also associated\nwith the transcription level of any genes, which will provide clues as to which genes belong to the pathway that the\nQTL uses to modulate the classical trait."
+                }
+            ],
+            "d1f04d58-2589-4183-aee4-569820dae052": [
+                {
+                    "document_id": "d1f04d58-2589-4183-aee4-569820dae052",
+                    "text": "Confirmation of Candidate Genes\nThe next step is to prove that a particular gene is involved in the quantitative trait\nunder study. This is done by complementation of a QTL, which can be achieved in\nseveral ways (9–11,40). In principle, transgenic complementation is the most straightforward. This approach has been used successfully to demonstrate that Pla2g2a was\nthe correct candidate gene for Mom1, a modifier of the apcmin allele that causes\nadenomatous polyposis coli (41)."
+                }
+            ],
+            "da485354-fcdc-49b8-9a41-0f673610156a": [
+                {
+                    "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                    "text": "So, how do you go about planning and performing a QTL study, and how\ndo you identify the responsible gene within a QTL that you have identified? Generally, one starts by performing a strain survey to find two parental inbred\nstrains that have a markedly different trait. One can now look up many different\ntraits of inbred mice online at the Mouse Phenome Database (http://phenome. jax.org/pub-cgi/phenome/mpdcgi?rtn=docs/home). However, the trait you may\nwant to study may not be present in wild type mice, so you may want to cross\na mutant (or genetically engineered) strain onto several inbred strains."
+                }
+            ],
+            "f041550e-5f2d-430e-8f46-15ebea6ca496": [
+                {
+                    "document_id": "f041550e-5f2d-430e-8f46-15ebea6ca496",
+                    "text": "Along with correlations, this tool also derives new traits representing the\nprincipal components (Figure 2d). The user can add these principal components to their Trait\nCollection and proceed to perform QTL mapping, as in the case of a single trait QTL\nmapping. The R/QTL (Broman et al. 2003) and R/CAPE (Tyler et al. 2013) packages can be\nused for deeper analysis of epistasis and pleiotropy for multiple traits and multiple\nregulatory loci. Prioritizing Candidate Genes\n7\n\nAuthor Manuscript\n\nFollowing the identification of a significant QTL, focus shifts to identifying the\nparticular gene(s) that cause the QTL."
+                }
+            ],
+            "f4e26cf0-d214-41bf-b392-9c63a903b0b8": [
+                {
+                    "document_id": "f4e26cf0-d214-41bf-b392-9c63a903b0b8",
+                    "text": "The investigators\nfirst identified all QTLs associated with\na classical phenotype and then winnowed the list of potentially associated\ngene-expression traits on the basis of\ntheir correlation or eQTL overlap with\nthe phenotype of interest. Candidate\ngenes then were ranked by applying\n\nthe LCMS technique, which uses the\neQTL data to establish causal relationships between DNA loci and transcripts as well as between transcripts\nand phenotypes and finally identifies\na model that best fits the data."
+                }
+            ],
+            "ff35f4c8-b78b-4dad-9aa8-1bb16479872d": [
+                {
+                    "document_id": "ff35f4c8-b78b-4dad-9aa8-1bb16479872d",
+                    "text": "The goal of QTL mapping is clearly the\nidentification and eventual confirmation of candidate genes\n(QTGs) underlying the phenotype. The evidence required for\nsuch confirmation has engendered much discussion (Complex\nTrait Consortium 2003; Glazier et al. 2002) and is likely to vary\ndepending on the nature of the trait and specific resources\navailable to pin down underlying genes (e.g. availability of\nknock-in or knock-outs, specific antibodies, siRNA, etc.). The\npaucity of QTGs meeting such multifaceted standards is testament to the difficulty of narrowing the confidence interval\nsufficiently to identify and test suitable candidate genes (Flint\net al."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "EFB8B9EF07428DA8D36EFCB6B06F9161",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "QTL",
+            "gene",
+            "trait",
+            "phenotype",
+            "eQTL",
+            "expression",
+            "cis-eQTL",
+            "quantitative&trait&locus",
+            "QTG",
+            "correlation"
+        ],
+        "metadata": [],
+        "question": "How do I determine which gene in my QTL is causal for the trait?",
+        "subquestions": null,
+        "task_id": "EFB8B9EF07428DA8D36EFCB6B06F9161",
+        "usage": {
+            "chatgpt": 4765,
+            "gpt-4": 3573,
+            "gpt-4-turbo-preview": 2599
+        },
+        "user_id": 2
+    },
+    "document_id": "EFB8B9EF07428DA8D36EFCB6B06F9161",
+    "task_id": "EFB8B9EF07428DA8D36EFCB6B06F9161"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_02.json b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_02.json
new file mode 100644
index 0000000..c9ab451
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_02.json
@@ -0,0 +1,144 @@
+{
+    "created_at": "2024-06-01T14:20:28.998327Z",
+    "data": {
+        "amplify": false,
+        "answer": "Actually, males have one Y chromosome and one X chromosome, while females have two X chromosomes. This combination determines the sex of an individual.",
+        "context": {
+            "1ac23aae-2a51-4846-81ec-6db70ab6e5a4": [
+                {
+                    "document_id": "1ac23aae-2a51-4846-81ec-6db70ab6e5a4",
+                    "text": "\n\nY chromosome in peripheral blood cells increases with age in men (6) and is correlated with increased risk of cancer mortality and Alzheimer's disease (6,7).X chromosome mosaicism in women also increases with age (8), as does autosomal mosaicism in both sexes (9,10).Recent studies have shown that the prevalence of age-related mosaic abnormalities is greater in men than women (9,10); however, mechanisms underlying the sex differences observed in chromosomal mosaicism in humans are unknown."
+                }
+            ],
+            "20b466c6-004b-484f-96a1-c1b4651bc856": [
+                {
+                    "document_id": "20b466c6-004b-484f-96a1-c1b4651bc856",
+                    "text": "\n\nRecent reports suggested a role of Y chromosome loss in risk for all-cause mortality and common age-related disease such as cancer, Alzheimer disease as well as severe atherosclerosis [12][13][14][15][16][17][18][19][20].Building on such reports, we aimed to evaluate the contribution of male Y chromosome mosaicism to the risk for late-stage AMD."
+                }
+            ],
+            "3f72832b-fad9-4d38-aed8-d22e5bd12a22": [
+                {
+                    "document_id": "3f72832b-fad9-4d38-aed8-d22e5bd12a22",
+                    "text": "Box 1. Sex-specific cytonuclear interactions\n\nSeveral predictions about the nature of cytonuclear conflicts follow from the patterns of chromosomal inheritance (Table I).In a mated pair of animals, mtDNA is co-transmitted with half of the autosomal genes, two-thirds of the X-linked genes and none of the Y-linked genes [76].This predicts that, relative to the autosomal case, positive nuclear-mitochondrial interactions are more likely to evolve for X-linked loci whereas deleterious interactions between Y-linked genes and mtDNA should accumulate (or cannot be purged efficiently)."
+                }
+            ],
+            "4ad6da14-56a3-48ab-a587-42761ceac238": [
+                {
+                    "document_id": "4ad6da14-56a3-48ab-a587-42761ceac238",
+                    "text": "\n\nIn addition to genetic data, the 9p Network Cohort dataset also lists the gender for all 719 individuals.Of these individuals, 406 individuals are female and 313 are male, indicating a female bias (Binomial test p ¼ 0.0006).This result was surprising considering that no female bias has been previously reported in 9p deletion and duplication syndromes.A possible explanation for the significant bias in the 9p Network Cohort dataset is the XY sex reversal phenotype, which is commonly observed in individuals with 9p deletion syndrome.This phenotype could lead to individuals with XY sex chromosomes being listed in the dataset as having a female gender.To further examine this hypothesis, we subset our dataset to include only the 236 individuals whose sex chromosomes are listed in their genetic information.For this much smaller subset, 125 individuals had female sex chromosomes and 111 had male sex chromosomes, indicating no significant sex bias (Binomial test p ¼ 0.4).We also found no significant gender bias in this group (Binomial test p ¼ 0.2), although we did confirm that four of the individuals with XY sex chromosomes had a gender of female.This comparison suggests that the XY sex reversal phenotype may be responsible for a female gender bias, but not a sex bias, in 9p deletion and duplication syndrome cohorts."
+                }
+            ],
+            "6910b508-6d25-4804-9e47-3590b57aa061": [
+                {
+                    "document_id": "6910b508-6d25-4804-9e47-3590b57aa061",
+                    "text": "\n\nDuplicated variants with multiple alternative alleles and variants in sex chromosomes X and Y"
+                }
+            ],
+            "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa": [
+                {
+                    "document_id": "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa",
+                    "text": "\n\nAutosome-One of the numbered, or nonsex, chromosomes (1 through 22).X and Y are the sex chromosomes."
+                }
+            ],
+            "7d451e79-b698-4744-aeb2-ff319f430d96": [
+                {
+                    "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                    "text": "\n\nGiven such a high abundance of young male-biased genes, we asked whether their parental genes are also male-biased.We found that fewer parental genes of X-linked male-biased duplicates were also male-biased (20%, 2/10) compared to the parental genes of autosomal young male-biased duplicates (32%, 12/37).These data, despite the small sample sizes and being statistically not significant, may suggest that compared to autosomal young genes, X-linked young genes more often evolved novel male-biased expression.However, as the majority of young genes are the result of intrachromosomal duplication events, the pattern might also reflect the fact that X-linked old genes are less likely to be male-biased."
+                },
+                {
+                    "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                    "text": "\n\nA slight excess of X-linked female-biased genes was also detected (Fig. 2).Although most of them are old, a few recently arose on the X chromosome over 4 to 6 Myr in the common ancestor of the D. melanogaster and D. simulans clade (branch 5).This can be interpreted in the context of the dominance model of the sexual antagonism hypothesis.In this case, a dominant, X-linked gene that is favorable to females but disadvantageous for males can become fixed.The slow accumulation of female-biased genes in the X reflects an overall low rate of female gene origination, either due to a small dominance effect (the degree of dominance h!1/2), or a minor disadvantageous effect on males (the ratio of fitness effects of male relative to female k!0) along with a favorable effect on females (Vicoso and Charlesworth 2006, Equation 10)."
+                },
+                {
+                    "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                    "text": "\n\nRegarding the second step in the evolution of male-biased genes, namely X!A transposition, sexual antagonism favorable for autosomal fixation (Vicoso and Charlesworth 2006) and/or MSCI (Lifschytz and Lindsley 1972;Betran et al. 2002) may play a role in this process.On the other hand, the within-chromosomal duplication rate is higher than the between-chromosomal duplication rate (Emerson et al. 2008), which may contribute to the slow pace of X!A transposition."
+                },
+                {
+                    "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                    "text": "\n\nIt has been observed that male-biased genes in Drosophila are overrepresented on autosomes (Parisi et al. 2003;Ranz et al. 2003).Consistent with this result, a dynamic process that can explain the nonrandom autosomal distribution has also been observed, in which autosomal new genes with X-linked parental genes are often male-biased.Specifically, a significant excess of autosomal testisexpressed retrogenes were identified as RNA-duplicates of X-linked parental genes (Betran et al. 2002).Recently, similar X!A gene traffic was observed in the DNA-level duplication and relocation data set of the Drosophila genus (Vibranovski et al. 2009b), and was further confirmed for DNA-level duplications in the D. pseudoobscura neo-X chromosome (Meisel et al. 2009).In addition, selective extinction of neo-X linked male-biased genes also occurred in D. pseudoobscura (Sturgill et al. 2007).These three lines of genome-wide investigation support a common pattern of outof-X traffic for male-biased genes, resulting in an enrichment of these genes on autosomes in the long term."
+                },
+                {
+                    "document_id": "7d451e79-b698-4744-aeb2-ff319f430d96",
+                    "text": "\n\nIt has been reported that the initial manifestations of new gene emergence, namely polymorphic duplicates, occur at a lower frequency on the X chromosome, thus indicating that these duplicates are subject to stronger purifying selection (Emerson et al. 2008).Therefore, the excessive fixation of X-linked duplicates might not occur via neutral processes.Positive selection could have facilitated the fixation of X-linked young genes in addition to driving their subsequent sequence evolution."
+                }
+            ],
+            "96cb840e-747f-4849-8354-e8764aa0a1ce": [
+                {
+                    "document_id": "96cb840e-747f-4849-8354-e8764aa0a1ce",
+                    "text": "\n\nOccasionally, Y chromosome DNA is detected in the maternal plasma, and the fetus appears to have female genitalia on sonographic examination.The underlying mechanisms for this include a twin demise, a maternal disorder of sexual differentiation, such as Swyer syndrome, or that the mother has undergone a bone marrow or solid organ transplant from a male donor (Bianchi, 2018;Hartwig, Ambye, Sorensen, & Jorgensen, 2017)."
+                }
+            ],
+            "9a5c3e73-8270-400f-8a2d-4f36b757188c": [
+                {
+                    "document_id": "9a5c3e73-8270-400f-8a2d-4f36b757188c",
+                    "text": "Because\nof the differences in sex chromosome number, the sexunmatched comparison contains internal controls, i.e. ,\nin this comparison, genes on the X-chromosome and\nY-chromosome (but not those on the autosomes) should\nshow copy number imbalances reﬂective of a single copy\nchange. We showed that the sample that is not sexmatched had readily detectable differences in aCGH\nsignals for genes on the X and Y chromosomes. No such\npatterns were evident for the autosomes of the sex\nunmatched individuals or for the sex chromosomes of the\nsex matched samples."
+                }
+            ],
+            "af3d7cd3-40ec-4a86-a473-89f83da250e4": [
+                {
+                    "document_id": "af3d7cd3-40ec-4a86-a473-89f83da250e4",
+                    "text": "Sex chromosome:\n\nThe X or Y chromosome in human beings that determines the sex of an individual.Females have two X chromosomes in diploid cells; males have an X and a Y chromosome.The sex chromosomes comprise the 23rd chromosome pair in a karyotype.See also: autosome Sex-linked: Traits or diseases associated with the X or Y chromosome; generally seen in males."
+                },
+                {
+                    "document_id": "af3d7cd3-40ec-4a86-a473-89f83da250e4",
+                    "text": "\n\nX chromosome: One of the two sex chromosomes, X and Y. See also: Y chromosome, sex chromosome Y chromosome: One of the two sex chromosomes, X and Y. See also; X chromosome, sex chromosome"
+                }
+            ],
+            "b04f2221-de28-4c4b-893e-9da982ff864c": [
+                {
+                    "document_id": "b04f2221-de28-4c4b-893e-9da982ff864c",
+                    "text": "The male heterogamety (XY) is the most\ncommon reported system, but many species\nhave female heterogamety (ZW), and more\noccasionally, multiple chromosome systems\n\n(Almeida-Toledo and Foresti, 2001; Devlin\nand Nagahama, 2002; Penman and Piferrer,\n2008). Given the low resolution of optical microscopy to differentiate sex chromosomes in\nﬁsh, researchers have looked for an alternative\nin the tenfold longer meiotic chromosomes to\ndetect mispairing tracts at the synaptonemal\ncomplex as an indication of the sex differentiated region with variable success."
+                },
+                {
+                    "document_id": "b04f2221-de28-4c4b-893e-9da982ff864c",
+                    "text": "The exclusive female\nconstitution of gynogenetic genomes provides\ninformation on the SD system, especially in a\nXX/XY system, where all female progenies are\nexpected. If ZZ/ZW is the underlying system,\nmale offspring always will be present, but the\ninterpretation is more complex and will depend\non the distance of the SD region to centromere\nand on the viability of WW offspring (Devlin\nand Nagahama, 2002; Penman and Piferrer,\n2008). Induced triploids, on the other hand, are\nconstituted by the combination of two female\nand one male genomes (Piferrer et al."
+                }
+            ],
+            "ef2c8463-5169-46aa-938b-7d04ea8da6b7": [
+                {
+                    "document_id": "ef2c8463-5169-46aa-938b-7d04ea8da6b7",
+                    "text": "\n\nThe existence of a maternally silenced X-linked imprinted locus playing a role in social cognition could explain why males (X m Y) are more vulnerable to disorders of social cognition such as autism spectrum disorders than are females (X m X p ).The absence of the expression of this gene would not lead to autism itself, but would eliminate a putative protective factor, making an individual more susceptible to the effects of other ASD-predisposing genetic mutations or environmental factors."
+                }
+            ],
+            "f051ad23-572d-4302-8dda-4d992aeaeb1a": [
+                {
+                    "document_id": "f051ad23-572d-4302-8dda-4d992aeaeb1a",
+                    "text": "\n\nWhen meiosis takes place, a pair of chromosomes may fail to separate properly, creating a sperm or egg that has either two copies or no copy of a specific chromosome.This is a sporadic event and it is called nondisjunction.Nondisjunction can lead to an extra chromosome, called trisomy, or a missing chromosome, called monosomy (GHR, 2008l).Down syndrome is an example of trisomy.Individuals who have Down syndrome have an extra chromosome number 21. Turner syndrome is an example of monosomy.Girls who have Turner syndrome have only one X chromosome.This causes them to have short stature and be infertile (NHGRI, 2008l)."
+                },
+                {
+                    "document_id": "f051ad23-572d-4302-8dda-4d992aeaeb1a",
+                    "text": "X-Linked Inheritance\n\nX-linked genetic disorders (also called sex-linked) are caused by gene mutations on the X chromosome.Most often X-linked genetic disorders are seen in males.Males inherit the X chromosome from their mother and the Y chromosome from their father.Because males have only one X chromosome, if they inherit a gene mutation on the X chromosome from their mother, they will have the disorder.Examples of X-linked genetic disorders occurring in males include hemophilia and Duchenne muscular dystrophy (GHR, 2008o)."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "34A6BD721632631DF6D97BCA1D315B0A",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "X&chromosome",
+            "Y&chromosome",
+            "male",
+            "female",
+            "sex&chromosomes",
+            "autosome",
+            "nondisjunction",
+            "trisomy",
+            "monosomy",
+            "X-linked&inheritance"
+        ],
+        "metadata": [],
+        "question": "Why do males have two Y chromosomes and females only one?",
+        "subquestions": null,
+        "task_id": "34A6BD721632631DF6D97BCA1D315B0A",
+        "usage": {
+            "chatgpt": 6105,
+            "gpt-4": 3430,
+            "gpt-4-turbo-preview": 2504
+        },
+        "user_id": 2
+    },
+    "document_id": "34A6BD721632631DF6D97BCA1D315B0A",
+    "task_id": "34A6BD721632631DF6D97BCA1D315B0A"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_03.json b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_03.json
new file mode 100644
index 0000000..494fe08
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_03.json
@@ -0,0 +1,154 @@
+{
+    "created_at": "2024-06-01T14:22:47.136754Z",
+    "data": {
+        "amplify": false,
+        "answer": "GeneNetwork utilizes datasets containing phenotypes and genotypes for QTL mapping analysis. These datasets may include genetic, genomic, and phenotypic data. The data are often formatted and normalized, and come with metadata. The database also includes data on complex phenotypes ranging from gene expression to behavior in standard inbred strains, and panels of mouse recombinant inbred strains. Rat and Arabidopsis populations are also represented in the database.",
+        "context": {
+            "071b4686-f5c4-4759-a038-14d79a45dac7": [
+                {
+                    "document_id": "071b4686-f5c4-4759-a038-14d79a45dac7",
+                    "text": "The project also provides online analysis tools to allow\nidentification of correlations within its data set. GeneNetwork (http://www.genenetwork.org), encompassing WebQTL, is a database of\ngenotypes and complex phenotypes ranging from gene expression to behaviour in standard\ninbred strains, and six panels of mouse recombinant inbred strains including the two largest\nsets (BXD and LXS) of approximately 80 strains each. Rat and Arabidopsis populations are\nalso represented. Approximately 1500 phenotypes spanning the 25 year history of these\nstrains are incorporated in this public resource, many of which were retrieved from the\nliterature."
+                }
+            ],
+            "0e6c370f-b514-4551-b6ed-9cc72e6f6b75": [
+                {
+                    "document_id": "0e6c370f-b514-4551-b6ed-9cc72e6f6b75",
+                    "text": "GN spares the\nuser most of these problem. Data are formatted and normalized, and usually come with good\nmetadata (often in the form of links to more information). This greatly simplifies QTL and\neQTL analysis, candidate gene discovery, coexpression analysis, and hypothesis testing [3,\n10]."
+                },
+                {
+                    "document_id": "0e6c370f-b514-4551-b6ed-9cc72e6f6b75",
+                    "text": "Suitable for quantitative\ngenetics (QTL mapping) and systems genetics, including correlation and\nnetwork analysis to compare associations between tissues and between\nother rodent or human data sets\n\nDescription and usage\n\n[32]\n\n[31]\n\n[30]\n\n[11]\n\nReferences\n\nMany of the Data Sets are amenable to systems genetics mapping and other methods and are accessible at GeneNetwork. The Description and Usage column provides details about the data set and potential\nusage."
+                }
+            ],
+            "2a92d7b5-946c-4a22-a4b9-26e950b0f757": [
+                {
+                    "document_id": "2a92d7b5-946c-4a22-a4b9-26e950b0f757",
+                    "text": "Bioinformatics\nAll of the genetic analyses were carried out in GeneNetwork, which\nis an open source bioinformatics resource for systems genetics that\nexists as both a repository for genetic, genomic and phenotypic\ndata together with a suite of statistical programs for data analysis that includes mapping and evaluating QTLs, examining phenotype/genotype correlations and building interaction networks. QTL mapping\nThe QTL mapping module of GeneNetwork was used to identify\nQTLs for hippocampal morphometry and radial maze trait data. This\nmodule enables interval mapping, composite interval mapping and\na pairwise scan option to identify epistatic effects."
+                }
+            ],
+            "389bdbf3-0224-4edb-a4fb-71a54971ba66": [
+                {
+                    "document_id": "389bdbf3-0224-4edb-a4fb-71a54971ba66",
+                    "text": "There\nare four options for QTL mapping on the GeneNetwork website: interval\nmapping, marker regression analysis, composite interval mapping, and pairscan analysis. In this case, interval mapping was used to compute linkage\nmaps for the entire genome. The log of odds (LOD) score was used to\nassert that a causal relation exists between a chromosomal location and a\nphenotypic variant, such as Gsto1 expression variation."
+                }
+            ],
+            "3df1bffa-3d23-4b6b-9d59-6ef8b0001f48": [
+                {
+                    "document_id": "3df1bffa-3d23-4b6b-9d59-6ef8b0001f48",
+                    "text": "Webqtl is an online database [110] of linked datasets, including genotype and expression\ndata, covering multiple species including mouse, macaque monkey, rat, drosophila,\narabidopsis, plants and humans [60]. While this tool cannot be used to calculate eQTLs, it\ncan be used to find and visualize eQTLs in different species, strains and tissues. It can\nperform single- and multiple-interval QTL mapping of up to 100 selected traits. Users can\nalso upload their own trait data for populations included in the database. It can also calculate\nand display trait-correlation matrices and network graphs (also for up to 100 traits)."
+                }
+            ],
+            "43407486-b9c2-487b-b19c-b605c4d201c6": [
+                {
+                    "document_id": "43407486-b9c2-487b-b19c-b605c4d201c6",
+                    "text": "GN spares the\nuser most of these problem. Data are formatted and normalized, and usually come with good\nmetadata (often in the form of links to more information). This greatly simplifies QTL and\neQTL analysis, candidate gene discovery, coexpression analysis, and hypothesis testing [3,\n10]."
+                },
+                {
+                    "document_id": "43407486-b9c2-487b-b19c-b605c4d201c6",
+                    "text": "Suitable for quantitative\ngenetics (QTL mapping) and systems genetics, including correlation and\nnetwork analysis to compare associations between tissues and between\nother rodent or human data sets\n\nDescription and usage\n\n[32]\n\n[31]\n\n[30]\n\n[11]\n\nReferences\n\nMany of the Data Sets are amenable to systems genetics mapping and other methods and are accessible at GeneNetwork. The Description and Usage column provides details about the data set and potential\nusage."
+                }
+            ],
+            "516cc395-4e7c-4371-9444-24edb56a7233": [
+                {
+                    "document_id": "516cc395-4e7c-4371-9444-24edb56a7233",
+                    "text": "QTL MAPPING AND QTG DISCOVERY IN THE RCC\nA variety of statistical methods and tools have been developed for QTL mapping and\nimplemented in free software for public use. These methods are well suited for simple\nbackcross and F2 RCC populations. R/qtl9,39 was developed for identiﬁcation of\nQTLs and higher order modeling. Another Web-based tool, GeneNetwork or\nWebQTL (GeneNetwork.org),40 was developed for QTL mapping and to explore\nassociations between variants, molecular traits (e.g. , gene expression), and higher order\nphenotypes (e.g. , behavior) and facilitate QTG identiﬁcation."
+                }
+            ],
+            "550c099f-88d0-483f-865a-01ef7362e2be": [
+                {
+                    "document_id": "550c099f-88d0-483f-865a-01ef7362e2be",
+                    "text": "This enables gene expression\ncorrelation and interval mapping, candidate gene searches and multitrait analyses. Each exported dataset was subject to an interval mapping analysis,\nwhich uses GeneNetwork’s embedded MapManager software\n(Manly et al . 2001) to perform Haley–Knott regression. Empirical P values were derived using 1000 permutations using the incorporated\npermutation feature of WebQTL. The peak of each statistically\nsignificant (P -value <0.05) or suggestive (P -value <0.63) (Lander\n& Kruglyak 1995) QTL was determined based on empirical P values (Doerge & Churchill 1996). A one-LOD drop-off was used\nto determine the QTL confidence interval about each peak."
+                }
+            ],
+            "581f83bc-3521-4cb3-ad3c-d905a90ecc29": [
+                {
+                    "document_id": "581f83bc-3521-4cb3-ad3c-d905a90ecc29",
+                    "text": "The peak linkage value\nand position was databased in GeneNetwork and users\ncan rapidly retrieve and view these mapping results for\nany probe set. Any of the QTL maps can also be rapidly\nregenerated using the same Haley-Knott methods, again\nusing functions imbedded in GeneNetwork. GeneNetwork also enable a search for epistatic interactions (pair\nscanning function) and composite interval mapping with\ncontrol for a single marker. Data quality control\n\nWe used two simple but effective methods to confirm\ncorrect sample identification of all data entered into\nGeneNetwork."
+                }
+            ],
+            "5bd8262b-b2cd-4098-a494-ede168941a9a": [
+                {
+                    "document_id": "5bd8262b-b2cd-4098-a494-ede168941a9a",
+                    "text": "QTL analysis\nAll QTL mapping for phenotypes was performed using the WebQTL software module of the\n\n170\n\nGeneNetwork (www.genenetwork.org) [34]. Interval mapping to evaluate potential QTLs was\ncalculated from the likelihood ratio statistics (LRS) as the software’s default measurement of\nthe association between differences in traits and differences in particular genotype markers. Another common measure score, the log of the odds (LOD) ratio, can be converted from the\nLRS (LRS/4.61). Suggestive and significant LRS values were determined by applying 1000\n\n175\n\npermutations."
+                }
+            ],
+            "80eb54fe-0d83-4300-9fba-e17ce5d1e5b4": [
+                {
+                    "document_id": "80eb54fe-0d83-4300-9fba-e17ce5d1e5b4",
+                    "text": "Unlike interval-specific haplotype analysis, which is most useful for narrowing a QTL shared by\nmultiple crosses, genome-wide haplotype analysis\nrequires only phenotype information from many inbred\nstrains and can effectively narrow a QTL identified in\nonly one experimental cross [36]. After narrowing the QTL to an interval that is !5 Mb\nusing these bioinformatics techniques or classical experimental methods, strain-specific sequence and gene\nexpression comparisons are effective for focusing on a\nfew strong candidate genes (Figure 7)."
+                }
+            ],
+            "86b86235-b7a8-4dfc-be13-d119dc31b377": [
+                {
+                    "document_id": "86b86235-b7a8-4dfc-be13-d119dc31b377",
+                    "text": "We considered QTL intervals that achieved genome-wide\nsignificance for one phenotype, and genome-wide suggestive for\nothers, as highest priority for candidate gene analysis. The January 2017 BXD genotype file was used4 . Updated linear mixed model mapping algorithms are now\navailable on GeneNetwork 25 (Sloan et al. , 2016), that account for\nkinship among strains. These new algorithms include GEMMA\n(Zhou and Stephens, 2012), pyLMM6 (Sul et al. , 2016), and\nR/qtl27 ."
+                }
+            ],
+            "9b2a48a0-f85e-4104-944f-0c47a3b03a9b": [
+                {
+                    "document_id": "9b2a48a0-f85e-4104-944f-0c47a3b03a9b",
+                    "text": "The peak linkage value\nand position was databased in GeneNetwork and users\ncan rapidly retrieve and view these mapping results for\nany probe set. Any of the QTL maps can also be rapidly\nregenerated using the same Haley-Knott methods, again\nusing functions imbedded in GeneNetwork. GeneNetwork also enable a search for epistatic interactions (pair\nscanning function) and composite interval mapping with\ncontrol for a single marker. Data quality control\n\nWe used two simple but effective methods to confirm\ncorrect sample identification of all data entered into\nGeneNetwork."
+                }
+            ],
+            "a4508fb3-c66b-4526-b2a2-a327505d085a": [
+                {
+                    "document_id": "a4508fb3-c66b-4526-b2a2-a327505d085a",
+                    "text": "There\nare four options for QTL mapping on the GeneNetwork website: interval\nmapping, marker regression analysis, composite interval mapping, and pairscan analysis. In this case, interval mapping was used to compute linkage\nmaps for the entire genome. The log of odds (LOD) score was used to\nassert that a causal relation exists between a chromosomal location and a\nphenotypic variant, such as Gsto1 expression variation."
+                }
+            ],
+            "b5c36c1e-458e-4009-818e-9c0c2ee23e45": [
+                {
+                    "document_id": "b5c36c1e-458e-4009-818e-9c0c2ee23e45",
+                    "text": "eQTL mapping\n\nQTL mapping was performed with GeneNetwork, an online bioinformatics resource\nfeaturing tools for systems genetic and complex trait analysis [9, 35]. QTL mapping\ninvolves entering VMB and CP iron data (strain means and SEM) as quantitative traits; the\nsoftware generates whole-genome interval maps for each trait. The interval maps graphically\nillustrate phenotype–genotype associations as peaks (QTL) indicating the strength of\nassociation between genomic polymorphisms and the quantitative trait throughout the\ngenome."
+                }
+            ],
+            "baacd740-efc8-42f2-af22-6f5ac9710900": [
+                {
+                    "document_id": "baacd740-efc8-42f2-af22-6f5ac9710900",
+                    "text": "Genetic Mapping\nIn this study we utilize GeneNetwork, a database containing phenotypes and genotypes,\nand also serves as an analysis engine for quantitative trait locus (QTL) mapping, genetic\ncorrelations, and phenome-wide association studies (PheWAS) (Sloan et al. , 2016; Mulligan et\nal. , 2017; Watson and Ashbrook, 2020). QTL analysis involves connecting phenotype data with\ngenotype data to examine genetic variation in traits controlled by multiple genes and their\ninteraction with the environment (also called complex traits)(Lynch et al. , 1998; Myles and\nWayne, 2008; Goddard et al. , 2016)."
+                }
+            ],
+            "beb7a242-21fe-4a66-8b44-7f228c0d3640": [
+                {
+                    "document_id": "beb7a242-21fe-4a66-8b44-7f228c0d3640",
+                    "text": "Once the resulting record set of the\nquery is returned, it can be further restricted by selecting\nrelevant records based on attached annotations before forwarding it for further analysis. To map genetic loci associated with mRNA abundance or\ntrait phenotypes, any one of the three QTL mapping functions currently employed by GeneNetwork's WebQTL\nmodule can be used. These are 1. interval mapping, 2. single-marker regression, or 3. composite mapping [29,30]."
+                }
+            ],
+            "e70f7c61-1734-4048-8a79-382e9b381686": [
+                {
+                    "document_id": "e70f7c61-1734-4048-8a79-382e9b381686",
+                    "text": "genenetwork.org/) a set of 3795 markers. Linkage is reported with\ngenome-wide significance levels based on 2000 permutation tests. Two types of QTL mapping analyses–simple mapping using the Haley–\nKnott regression equation, and composite interval mapping–were\nutilized in this study. Simple interval mapping was performed to\nillustrate the significance of any QTLs that regulate the TID. As a\nsecondary analysis, composite interval mapping which controlled for\nthe influence of Tyrp1 was also performed with the goal of identifying\nany secondary QTLs that may have been masked by the major QTL on\nChr 4."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "39076B38EDAF24ECEEB91924D370F4AD",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "GeneNetwork",
+            "QTL",
+            "mapping",
+            "genotype",
+            "phenotype",
+            "interval&mapping",
+            "composite&interval&mapping",
+            "marker&regression",
+            "eQTL",
+            "haplotype"
+        ],
+        "metadata": [],
+        "question": "what type of dataset is useful for qtl mapping analysis in genenetwork2?",
+        "subquestions": null,
+        "task_id": "39076B38EDAF24ECEEB91924D370F4AD",
+        "usage": {
+            "chatgpt": 5013,
+            "gpt-4": 3398,
+            "gpt-4-turbo-preview": 2412
+        },
+        "user_id": 2
+    },
+    "document_id": "39076B38EDAF24ECEEB91924D370F4AD",
+    "task_id": "39076B38EDAF24ECEEB91924D370F4AD"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_04.json b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_04.json
new file mode 100644
index 0000000..6fe6d7f
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_04.json
@@ -0,0 +1,140 @@
+{
+    "created_at": "2024-06-01T14:24:19.558227Z",
+    "data": {
+        "amplify": false,
+        "answer": "The ethical considerations surrounding prenatal genetic testing and selective termination of pregnancies based on genetic factors include the potential for implicit pressure on individuals to violate personal ethics to reduce financial burden on society, the risk of routinization of testing leading to social or medical expectations of testing in all eligible individuals, and the potential compromise of values of informed consent and individual autonomy. There are also cultural and religious beliefs to consider, as well as the potential psychological impact on parents who may feel guilt if they are carriers of genetic conditions. Furthermore, the decision to terminate a pregnancy based on genetic factors is a joint decision between parents, and the involvement of extended family members in this process varies greatly across different cultures.",
+        "context": {
+            "30eabd29-2f48-459a-b162-bd90d99f1411": [
+                {
+                    "document_id": "30eabd29-2f48-459a-b162-bd90d99f1411",
+                    "text": "\n\nA number of additional ethical implications must be considered.Associating financial investments with the prevention of disease, especially where reproductive decisions are involved, requires sensitivity, caution, and ethical rigor.Funding decisions based on imputed cost-savings must not result in implicit pressure on individuals to violate personal ethics to reduce financial burden on society.As discussions regarding prenatal testing have demonstrated, 35 is risk that \"routinization\" of testing may lead to social or medical expectations of testing in all eligible individuals.These expectations, if linked with financial incentives for the health system, could risk applying implicit pressure on serious, and potentially irreversible, personal decisions.Such expectations, if applied at the population level, could risk becoming normalized, compromising the values of informed consent and individual autonomy."
+                },
+                {
+                    "document_id": "30eabd29-2f48-459a-b162-bd90d99f1411",
+                    "text": "\n\nWith regard to pregnancies affected by a genetic condition identified through population carrier screening, we modeled the decision to terminate affected pregnancies conservatively (0.50).This is despite the literature suggesting rates above 0.90 for elective TOP for conditions such as Down syndrome 33 and SMA. 34We recognize this issue is controversial, and that laws and ethical positions vary considerably between countries/ jurisdictions.Variations in population attitudes based on age, religion, and other factors, as well as the criticality of preserving individual choice, were acknowledged in adopting this highly conservative estimate."
+                }
+            ],
+            "56cf7be3-8c73-498d-b48f-8d99592b0213": [
+                {
+                    "document_id": "56cf7be3-8c73-498d-b48f-8d99592b0213",
+                    "text": "\n\nThe use of genetic testing from pre-conception through adulthood is expanding rapidly.As a result of this expansion, new ethical issues are emerging related to genetic testing and informed consent.These new issues create ethical challenges for nurses and all healthcare providers.Currently expanding areas include newborn screening and genetic testing of children.These new ethical challenges will be described below."
+                },
+                {
+                    "document_id": "56cf7be3-8c73-498d-b48f-8d99592b0213",
+                    "text": "The use of genetic testing from pre-conception through adulthood is expanding rapidly. Psychological risks for parents who are carriers may include parental guilt."
+                }
+            ],
+            "64d87c52-1185-4080-8d06-134c32dae5fd": [
+                {
+                    "document_id": "64d87c52-1185-4080-8d06-134c32dae5fd",
+                    "text": "\n\nEthnic and cultural backgrounds may also play a role in the decisions that families make regarding prenatal testing.Moyer et al. (1999) concluded that Caucasian women more often undergo prenatal diagnoses than African American or Asian women, or Latinas.Furthermore, Awwad et al. (2008) found American couples less inclined to involve extended relatives in the prenatal decision-making process than Native Palestinian couples.Both of these examples clearly indicate that cultural differences can impact the ways in which families negotiate prenatal decisions.Further research needs to investigate how different families engage in such discussions and decision-making processes, especially as prenatal testing becomes more common and better able to predict or prevent a wider range of genetic conditions.Tightly closed ethnic groups remain at high risk of serving as carriers for genetic mutations, but the management of this possibility varies greatly.For example, some Ashkenazi Jewish groups use screening for mutations for Tay-Sachs disease (TSD) as the basis for rabbinical marriage advice; whereas, children born to Amish families in Pennsylvania more often present with glutaric aciduria type 1 (GA1) but, given their beliefs, parents tend not to accept prenatal testing because of the implication of abortion (McKusick, 2000)."
+                },
+                {
+                    "document_id": "64d87c52-1185-4080-8d06-134c32dae5fd",
+                    "text": "\n\nResearchers studying factors that contribute toward a couple's choice to undergo prenatal testing have determined that partners base their decision upon several factors, including, but not limited to: parental beliefs about abortion, attitudes regarding disability and their \"perceptions of the usefulness of having the information revealed by genetic tests\" (Moyer et al., 1999, p. 522).Abortion beliefs constitute a key issue in the decision-making process.Even though a majority of parents receiving abnormal prenatal test results terminate their pregnancies (Redlinger-Grosse, Bernhardt, Berg, Muenke, & Biesecker, 2002), Moyer et al. noted that, when asked, more families reported that they would make use of prenatal testing than would be willing to terminate a pregnancy.The decision to continue or terminate a pregnancy after prenatal testing Downloaded by [University of the Sunshine Coast] at 10:32 05 August 2017 comprises a joint decision between both parents (e.g., Awwad et al., 2008;Beeson & Golbus, 1985); however, the nature of the conversations leading to the decision and the involvement of extended family members in the decisionmaking process remains highly understudied."
+                },
+                {
+                    "document_id": "64d87c52-1185-4080-8d06-134c32dae5fd",
+                    "text": "The Genetic Divide(s) and Communication\n\nThe ability of scientists to \"map\" disease through several generations (Collins, 1999) raises practical and ethical issues of access to resulting opportunities and creates family communication challenges.Currently, prenatal testing for chromosomal diseases has become increasingly common (Moyer et al., 1999).Options such as pre-implantation genetic diagnosis (PGD) can identify over 1,250 disease-related mutations creating an opportunity for parents to select unaffected embryos for implantation in the womb (R. M. Green, 2008).Test results provide potential parents with information that may lead to decisions involving intervention in the genetic makeup of future children.Although some families welcome such options, others may be unable or unwilling to consider such procedures, due to fi nancial concerns or moral/ethical/religious beliefs."
+                }
+            ],
+            "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa": [
+                {
+                    "document_id": "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa",
+                    "text": "Privacy Issues\n\nFinally, privacy issues should be seriously considered when the use of genetic testing is contemplated, especially with respect to whole-genome sequencing of healthy people.It is an unanswered question under what circumstances, to what extent, and by what means genetic data should be incorporated into the medical record.Although easy access to such data could be helpful to providers in improving patient care, it remains to be seen how other parties (eg, insurance companies) might act on the data in ways that do not benefit patients.The US Congress acted to prohibit discrimination by employers and health insurers on the basis of genetic testing with the Genetic Information Nondiscrimination Act in 2008, but further safeguards will undoubtedly be needed as the health implications of genetic data become clearer."
+                }
+            ],
+            "782103fd-2cb6-44c8-9b39-d82430d335c9": [
+                {
+                    "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                    "text": "\n\nThe ethical evaluation of genetic testing in children is traditionally based on the balance of clinical benefits and risks (American Society of Human Genetics Board of Directors and the American College of Medical Genetics All correspondence concerning this article should be addressed to Benjamin Wilfond, MD, Treuman Katz Center for Pediatric Bioethics, Seattle Children's Hospital, Metropolitan Park West M/S: MPW 8-2, 1100 Olive Way, Room 876, Seattle WA 98101, USA.E-mail: benjamin.wilfond@seattlechildrens.org Board of Directors, 1995;Andrews, Fullerton, Holtzman, & Motolsky, 1994;Clarke, 1994;Wertz, Fanos, & Reilly, 1994).In the early 1990s, when there were only scant data about children who had received genetic tests results, the presumption was to give greater weight to the potential risks and to restrict testing.However, this criterion is not necessarily consistent with the general practice of respecting broad parental discretion in health care decisionmaking for and on behalf of their children.In general, parents are the presumed decision makers for their children and their decisions are respected unless they are abusive or neglectful (Buchanan & Brock, 1989;Goldstein, Freud, & Solnit, 1979;Ross, 1998).The tension between assessments of benefits and risks made by health care providers and policy makers, and the procedural respect owed to parental authority will be clearly tested as the ability to conduct and interpret whole-genome sequencing and related technologies gain in momentum."
+                },
+                {
+                    "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                    "text": "Ethical Considerations in Developing Policy for ''Comprehensive'' Genomic Testing\n\nIn the near future, genomic testing is likely to become more accessible and will provide both information about the risks of common conditions such as heart disease, diabetes, and hypertension as well as predictions about individual responses to specific pharmaceuticals and other medical therapies (Aspinall & Hamermesh, 2007).Over time, the number and range of conditions for which such testing is available is likely to expand to include more behavioral traits, ranging from information about anxiety and depression, to attention and addiction (Rothstein, 2005)."
+                },
+                {
+                    "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                    "text": "\nObjective Ethical evaluation of genetic testing in children is traditionally based on balancing clinical benefits and risks.However, this focus can be inconsistent with the general practice of respecting parental decision-making about their children's health care.We argue that respect for parental decision-making should play a larger role in shaping pediatric genetic testing practices, and play a similar role regarding decisions to use emerging genomic technologies.Methods Genomic testing involves the examination of thousands of DNA markers spanning genes throughout the genome and their interrelationships, yielding virtually limitless interpretations.We presume that parents and providers should proceed cautiously in applying genomic testing in children, as we explore how genomic testing will stress the fault lines of the traditional ethical analysis.Results Empirical data about the psychosocial risks and benefits of genetic testing of children do not reveal serious harms, yet virtually no such data exist yet about genomic testing.Unless empirical social and behavioral data indicate that genomic testing is highly likely to cause serious harms to the children, parental decisions to obtain comprehensive genomic testing in their children should be respected.Once comprehensive genomic testing of children becomes routine, resultant information may be more easily integrated by families than anticipated.Conclusions Research on the social and behavioral impact of comprehensive genomic testing on children and their families is needed to further inform parents, clinicians, and policy makers."
+                },
+                {
+                    "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                    "text": "\n\nObjective Ethical evaluation of genetic testing in children is traditionally based on balancing clinical benefits and risks.However, this focus can be inconsistent with the general practice of respecting parental decision-making about their children's health care.We argue that respect for parental decision-making should play a larger role in shaping pediatric genetic testing practices, and play a similar role regarding decisions to use emerging genomic technologies.Methods Genomic testing involves the examination of thousands of DNA markers spanning genes throughout the genome and their interrelationships, yielding virtually limitless interpretations.We presume that parents and providers should proceed cautiously in applying genomic testing in children, as we explore how genomic testing will stress the fault lines of the traditional ethical analysis.Results Empirical data about the psychosocial risks and benefits of genetic testing of children do not reveal serious harms, yet virtually no such data exist yet about genomic testing.Unless empirical social and behavioral data indicate that genomic testing is highly likely to cause serious harms to the children, parental decisions to obtain comprehensive genomic testing in their children should be respected.Once comprehensive genomic testing of children becomes routine, resultant information may be more easily integrated by families than anticipated.Conclusions Research on the social and behavioral impact of comprehensive genomic testing on children and their families is needed to further inform parents, clinicians, and policy makers."
+                },
+                {
+                    "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                    "text": "\n\nTo the extent that ''personal meaning'' gains wider acceptance as a legitimate criterion for expanding the availability of new tests and applications of genomic technology, the current policies and practices of restricting some genetic testing of children and mandating other tests will need to be reevaluated.There will be some parents who will find the information that becomes available through new technologies and data useful in shaping their parenting practices, while others will be more skeptical of their value.These disparate parental judgments may be independent of professional assessments of clinical validity and utility.Extrapolating from the empirical data about predictive genetic testing of children in at-risk families discussed earlier, we speculate that once comprehensive genomic testing of children becomes routine, the information may be more easily integrated by families than might be predicted.This is not meant to imply that whatever information parents want about their children should be provided carte blanche.Clearly, education and counseling will be crucial to ensure that families understand the limitations of the information.However, restrictions and mandates should be based on a criterion of risk of serious harm (Diekema, 2004).Given the lack of data confirming harm and the related data that indicate children may fare better than anticipated, such restrictions and mandates cannot be justified.Policies and practices will also need to clarify the role of the older adolescent in the decision-making process, although the issues related to balancing and assessing parental and adolescent interests and preferences goes beyond the focus of this article.This is also not meant to ignore the professional and moral obligation to educate parents and to help parents make good decisions on behalf of their children.It is morally appropriate for providers to strongly recommend particular tests in infancy and young childhood (i.e., PKU testing), and to strongly discourage other tests (e.g., ApoE testing of children for adult onset Alzheimer disease and heart disease because ApoE is not predictive but only provides an increased relative risk and has limited sensitivity and specificity) (Roberts, Cupples, Relkin, Whitehouse, & Green, 2005).Selective and directive recommendations are a routine aspect of pediatric practice.However, it will become increasingly important for professional organizations to begin to reconcile their support for mandatory genetic testing for some conditions and their support for restrictions for other conditions with the broad discretion that parents have and need in the health care arena in order to promote their children's well-being."
+                },
+                {
+                    "document_id": "782103fd-2cb6-44c8-9b39-d82430d335c9",
+                    "text": "\n\nWhat limits should be imposed, if any, need to be determined prior to commercial feasibility.In this article, we consider how genetic testing decisions for children have been made traditionally and how the anticipation of comprehensive genomic testing in the near future will stress the fault lines of traditional approaches.The potential for comprehensive genomic testing in children could shift the equilibrium towards expanding or reducing parental discretion, and forces us to reexamine the evidence for our genetic testing policies and practices.We will highlight specific domains where further empirical social and behavioral research is necessary to inform policy and practice."
+                }
+            ],
+            "93dc581e-5e45-48b4-b82f-35e32d7bd58e": [
+                {
+                    "document_id": "93dc581e-5e45-48b4-b82f-35e32d7bd58e",
+                    "text": "\n\nPrenatal genetics is largely practiced by maternal-fetal medicine specialists due to severe deficiency in the number of qualified clinical geneticists.Recent years have witnessed a tremendous growth in the demand for chorionic villous sampling and amniocentesis for the diagnosis of single gene disorders.At KFSHRC alone, the number of prenatal samples that are tested for single gene disorders has increased from 5 in 2004 to 250 in 2013.Therapeutic abortion is permitted by law if performed within 120 days from the time of fertilization in order to comply with the Islamic view of the timing of ensoulment (Alkuraya and Kilani 2001).However, the approved indication for the procedure, which is \"severe malformation\", must be authorized by three attending-level physicians.The definition of \"severe\" is left to the discretion of the medical team after consulting with the family.For example, intellectual disability is a common indication for many therapeutic abortion procedures.Contrary to commonly held views, we have shown that early prenatal diagnosis is the method of choice for couples who had one or more children with single gene disorders, as long as they are provided with a culturally sensitive genetic counseling that addresses their religious and cultural concerns (Alkuraya and Kilani 2001).Nearly 45% of these couples opt for early prenatal diagnosis compared to 35% who choose preimplantation genetic diagnosis (PGD) (Alkuraya 2013a).PGD is available freely at KFSHRC but is also provided by the private sector.Noninvasive prenatal screening using cell-free fetal DNA in maternal blood is quickly becoming integrated in prenatal care.KFSHRC offers this test routinely to all pregnant women regardless of their perceived risk and the MOH is considering making this test available throughout its vast network of hospitals and medical centers."
+                }
+            ],
+            "9f21007a-1487-46d8-8e9e-cde8df4af6d5": [
+                {
+                    "document_id": "9f21007a-1487-46d8-8e9e-cde8df4af6d5",
+                    "text": "\n\nSocial and psychological implications of accessing genetic services and information."
+                }
+            ],
+            "a4b0655d-895c-4368-9401-ee2903b15d42": [
+                {
+                    "document_id": "a4b0655d-895c-4368-9401-ee2903b15d42",
+                    "text": "\n\nA corollary of the predictive power of genetic information is the limited ability to prevent or treat many conditions with significant genetic factors involved.Indeed, virtually all of the complex ethical and legal issues relevant to genetic testing would disappear if there were effective preventions or treatments available for genetic conditions.The ability to predict future disease in conjunction with a limited ability to do much about it has important social and psychological implications that must be addressed in conducting genetic research."
+                }
+            ],
+            "b0b60080-2338-411b-bc44-1f5626a3c442": [
+                {
+                    "document_id": "b0b60080-2338-411b-bc44-1f5626a3c442",
+                    "text": "\n\nInterpretations of the literature will likely mirror the priorities and evaluative tendencies of the reader.Are you willing to accept the overall trends in genetic and genomic testing evaluation and to trust that the existing clinical approaches will apply informed consent appropriately while identifying and supporting the rare individual who has a serious adverse response to the testing?If so, you might advocate that attention be turned more toward other issues relevant to the effective implementation of genetic and genomic testing.Or do you feel a strong need to understand in more detail the possible psychosocial harms of the testing, particularly the subtler impacts or responses of individuals who do not fit the norm?In that case, you would likely encourage renewed and innovative efforts to study the psychosocial consequences of the receipt of risk information from genetic and genomic testing."
+                }
+            ],
+            "f7fe5d02-ee7c-4ec2-b6c4-ca9aa5efb41f": [
+                {
+                    "document_id": "f7fe5d02-ee7c-4ec2-b6c4-ca9aa5efb41f",
+                    "text": "\n\nOther social issues require our attention if genomic medicine is to benefit our patients.How should genetic tests be regulated?What, if any, are the appropriate uses of direct-to-consumer marketing of genetic tests?The Internet has recently had a proliferation of genetic-testing sites that feature claims grounded in greed and pseudoscience, rather than in data or reality.How will health care providers and the public distinguish between these and responsible testing services, whether they are available through the Internet or in the hospital?"
+                }
+            ],
+            "f97246cb-7a71-409b-bb1a-dd01a5ef5c5e": [
+                {
+                    "document_id": "f97246cb-7a71-409b-bb1a-dd01a5ef5c5e",
+                    "text": "Environmental Factors\n\nAs widespread use of genetic testing increases, it is the responsibility of the medical community to ensure its equitable use across socioeconomic and cultural spectrums."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "F7FF28704C5239FB329F508530F982CC",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "Tay-Sachs&disease",
+            "glutaric&aciduria&type&1",
+            "Ashkenazi&Jewish",
+            "Amish",
+            "Down&syndrome",
+            "SMA",
+            "PGD",
+            "KFSHRC",
+            "Genetic&Information&Nondiscrimination&Act",
+            "Islamic"
+        ],
+        "metadata": [],
+        "question": "What are the ethical considerations surrounding prenatal genetic testing and the selective termination of pregnancies based on genetic factors?",
+        "subquestions": null,
+        "task_id": "F7FF28704C5239FB329F508530F982CC",
+        "usage": {
+            "chatgpt": 6791,
+            "gpt-4": 4502,
+            "gpt-4-turbo-preview": 3567
+        },
+        "user_id": 2
+    },
+    "document_id": "F7FF28704C5239FB329F508530F982CC",
+    "task_id": "F7FF28704C5239FB329F508530F982CC"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_05.json b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_05.json
new file mode 100644
index 0000000..8273f71
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_05.json
@@ -0,0 +1,144 @@
+{
+    "created_at": "2024-06-01T14:26:03.986157Z",
+    "data": {
+        "amplify": false,
+        "answer": "The potential benefits of gene editing technologies like CRISPR-Cas9 include the ability to modify genes for the treatment of diseases, improvement of crop species, and the development of personalized drug or cell therapies. It can also be used for functional screening in the development of therapies and for the study of molecular causes of ageing. However, there are risks associated with these technologies. These include off-target effects, which can lead to unwanted mutations, and the potential for wide-ranging deletions or recombination events. There's also a risk of triggering a P53 response leading to apoptosis in cycling cells, and the potential for subjects to generate antibodies to Cas9, which could limit gene therapies. Furthermore, the long-term safety of CRISPR genome editing in humans is yet to be determined.",
+        "context": {
+            "03110c8a-1232-40c2-8380-c9feb8b6468c": [
+                {
+                    "document_id": "03110c8a-1232-40c2-8380-c9feb8b6468c",
+                    "text": "\n\nGene editing has gained considerable interest with the identification of the CRISPR-Cas9 system, 27 which allows for a targeted modification in the DNA sequence of an organism.Researchers can utilize their knowledge of the basic biology of the gene and its protein function to precisely change the DNA sequence, thus altering the protein function of the gene and allowing for edits to stay within the species.Researchers at the University of Missouri used the CRISPR-Cas9 system to modify the CD163 gene such that the PRRS virus is not able to replicate inside the pig. 28This slight modification of the swine genome through gene editing keeps the pigs from succumbing to PRRS which has an annual estimated loss to the United States swine industry of over $660 million per year.Despite this benefit, given the public's concerns over food safety, it is likely that approval for such technology is years away in the US, Canada and Europe.However, in some cultures, there is a wide range of non-livestock species that are consumed.Therefore, it is conceivable that these countries and cultures may be open to transgenic/gene edited livestock.They may see the importance of useful gene editing which may lead to approval and consumption of reasonable genetically edited animal products such as those with modifications that are already found in nature or those that offer a substantial welfare benefit to society."
+                }
+            ],
+            "1942712a-a39d-44f7-9b2d-609926374cbd": [
+                {
+                    "document_id": "1942712a-a39d-44f7-9b2d-609926374cbd",
+                    "text": "\n\nAs a researcher who has devoted an entire career since 1994 to the development of genome editing tools and methods, I have been amazed by the rapid progress in the field over the last few years.Considering the widespread use of the tools, I am sure that the pace will continue to accelerate.Indeed, programmable nucleases, may eventually enable humans-products of evolution-to become masters of evolution.delivered preassembled recombinant Cas9-guide RNA ribonucleoproteins (RNPs) into animal embryos 6,9 and plant 11 and mammalian cells [73][74][75] .Indeed, Cas9 RNPs were rapidly turned over in cells 73 , reducing off-target effects and mosaicism in gene-edited organisms 11 .Cas9 RNPs can be delivered into cells by various methods, including microinjection 6,9 , electroporation 73 , lipofection 74 and protein transduction 75 .Importantly-and unlike in conventional gene therapy, where therapeutic genes are delivered via plasmids or viral vectors-Cas9 RNP delivery does not involve the use of exogenous DNA; host innate immune responses against foreign DNA are not elicited, and undesired integration of foreign DNA into the host genome is avoided."
+                }
+            ],
+            "33f1abde-a821-483b-b8b4-785f499db09d": [
+                {
+                    "document_id": "33f1abde-a821-483b-b8b4-785f499db09d",
+                    "text": "\n\nIn comparison to a transgenic approach, a gene editing technique such as CRISPR-Cas9 offers the advantage that gene-edited crops are not considered genetically modified organism (GMO) in some countries, such as the US, where the demand for natural food colorants such as anthocyanins is high.Indeed, the use of GMO crops as a source of natural pigments may be inconsistent with consumer interests.However, carrot cultivars engineered with either the transgenic or gene editing approach have not been reported so far, but their development is possible."
+                }
+            ],
+            "4f709611-ea0b-4bcc-a634-df5d518ccb54": [
+                {
+                    "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                    "text": "\n\nThe notable accuracy and versatility of CRISPR-Cas for genome editing also opened the door to its use in preclinical and translational settings.In the latter case, CRISPR in vivo gene editing has led to several proof-of-concept studies that would have been unachievable without it, as in the first ever correction of inherited pathogenic mutations linked to degenerative disease in a living organism [22] and even shown to be possible in human embryos [23,24].It also has great potential in the field of precision medicine as large-scale population DNA sequencing studies have provided vast amounts of information linking particular diseases with specific genetic mutations which could, in theory, be targeted through CRISPR [25,26].This could be used during the identification and validation of potential DNA targets during the development of personalised drug or cell therapies, which will require the generation of engineered cell lines and/or animal models.Techniques such as HDR-mediated gene targeting are too labour intensive, with low targeting efficiencies and long times necessary for their establishment, and consequently are not ideally suited for drug discovery purposes.Conversely, CRISPR-Cas has been proven to be efficient for editing virtually any kind of cell line, from primary immune cells to induced pluripotent stem cells (iPSCs) [27,28].Additionally, CRISPR can also be used for functional screening in the development of combined inhibitory therapy aimed at strengthening the efficiency of targeted therapeutics.An example of the latter is shown in a study where a variation of the technology known as CRISPR interference (CRISPRi) was used in genome-wide scale to identify different survival pathways used by cancer cells after oncogene inactivation and allowing the identification of successful combination therapies [29].In terms of translational applications, the overall safety of CRISPR genome editing in humans will require long-term scrutiny before its adoption in the clinic.Nonetheless, a number of CRISPR-based clinical trials are currently in progress, including studies focused on targeting patients' own T cells in order to improve the immune response towards some forms of malignant cancer [30,31], and others aimed at correcting pathogenic mutations in the hematopoietic cells of patients with beta-thalassemia and sickle cell disease [32]."
+                },
+                {
+                    "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                    "text": "Caveats and Ethical Concerns of CRISPR-Cas Applications\n\nDespite the presence of both a PAM sequence and a specific gRNA, the CRISPR-Cas9 system is not infallible.In fact, DSBs can occur at different sites in the genome, potentially causing so-called \"off-target\" effects.This eventuality remains to date the biggest concern in the field, as possible undesirable modifications must be properly identified and followed in order to guarantee safety for medical purposes.Nevertheless, there is still little evidence of the biological consequence of Cas9 off-target effects.Two recent studies describe new methods to investigate potential off-target effects in both mammals and plants [33,34].In both cases, whole-genome sequencing revealed that selective nucleotide changes, such as conversion of an adenine to a guanine, caused off-target occurrence very rarely, with a frequency comparable to the one of spontaneous mutations.However, substitution of a cytosine with a thymidine was linked to a sizable number of off-target mutations.This newly acquired information adds to the plethora of studies conducted on the safety of CRISPR, which altogether highlight the need for the establishment of clinical standards for the future use of genome-editing techniques in the clinic.Despite this and other technical challenges still ahead for CRISPR genome editing, the pace at which this technology has developed in recent years suggests many of these concerns could be addressed soon, as long as proper ethical guidelines and regulatory mechanisms are established."
+                },
+                {
+                    "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                    "text": "Conclusions\n\nThere is no reason to doubt that the development of CRISPR-Cas genome editing represents an unprecedented breakthrough in modern science, as it has potential applications in a wide array of disciplines ranging from agriculture, zoology and renewable energy to biomedicine and synthetic biology.This powerful tool holds promise for further elucidating the molecular causes of ageing by allowing scientists to probe genetic and epigenetic pathways with a level of sophistication that was unattainable just a few years ago.It will allow so in traditional animal and cell models of ageing, but it will also drastically accelerate the generation of refined versions of those models or even allow the development of new research approaches in non-model organisms.Moreover, CRISPR-based genome editing is already having a significant impact in research aiming to understand the cellular and molecular origins of age-related diseases, as well as developing potential treatments against them.The application of CRISPR-Cas gene editing for the treatment of age-related diseases is not over the horizon yet, as it will require the identification of causative genes and their role under a variety of contexts that could be as diverse as the ageing process is across individuals.However, CRISPR-Cas might also hold the key for solving such conundrum, as it has opened the way for achieving true personalised medicine by providing both the precision and scalability required for conducting genome-wide functional screens during the refinement of drug-and cell-based therapies for age-related diseases."
+                },
+                {
+                    "document_id": "4f709611-ea0b-4bcc-a634-df5d518ccb54",
+                    "text": "\n\nSince its discovery, CRISPR-Cas technology has ignited a biological revolution by providing a highly versatile platform that allows fast and efficient genome editing in an ever-growing list of organisms.In this chapter we will first describe the most recent advances in the development and application of the CRISPR-Cas platform in biomedical research.Then we will discuss the most recent and notable basic research applications of this technology in the study of the molecular causes of ageing.Finally, we will review how CRISPR-Cas has been used for creating new models for the study of age-related diseases, as well as for manipulating diseaseassociated gene pathways."
+                }
+            ],
+            "50c72e55-b5fe-42a6-b837-64c28620a4c0": [
+                {
+                    "document_id": "50c72e55-b5fe-42a6-b837-64c28620a4c0",
+                    "text": "Caveats of advanced genome editing tools\n\nOff-target effects.The DNA-binding domains of ZFNs and TALENs need to be very specific for the target site to avoid off-target cleavage, which results in unwanted mutations and potentially cytotoxic effects [27].CRISPR/Cas9 is also known to generate off-target alterations, albeit apparently at low incidence [28,29], since mispairing is allowed between the guide RNA and the genomic DNA.Nonetheless, caution is required in their design and use.Some strategies involving the optimization of the guide RNA/Cas9 include using of software tools to predict potential off-target sites (http://omictools.com/crispr-cas9-Figure1: Genome editing methodologies which can be applied to human pluripotent stem cells.Homologous recombination (HR), or the more advanced tools such as zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) or clustered regularly interspaced short palindromic repeat (CRISPR)/Cas system can be applied to human pluripotent stem cells (hPSCs) either to 1) create naturally occurring mutations or 2) repair a mutation to generate isogenic controls in hPSCs, to understand the function of a gene of interest.c1268-p1.html),truncating the guide RNA (<20 nucleotides) to decrease off-target mutagenesis [30], lowering the dosage of guide RNA and Cas9 plasmids, and decreasing the number of mismatches between the guide RNA and the genomic DNA.A \"double nick\" system with Cas9 nickase, which contains a single inactive catalytic domain, may also be used [31e33]."
+                }
+            ],
+            "52480703-5353-4e55-a06b-110fd59db3a6": [
+                {
+                    "document_id": "52480703-5353-4e55-a06b-110fd59db3a6",
+                    "text": "CRISPR screening technologies\n\nThe discovery of CRISPR-Cas9 as a sequence-specific programmable nuclease democratized gene editing and fueled progress in forward genetic screening [20 , 66] .Genetic screens using Cas9 with a pooled singleguide RNA (sgRNA) library allow the interrogation of seemingly all genes in a genome in a single experiment [96 , 97] [null] .Engineered Cas9 variants further extend the versatility of forward genetic screening.Catalytically inactive Cas9 (dCas9) fused with chromatin effector domains permit specific activation (CRISPRa) or inhibition (CRISPRi) of gene expression [37 , 54] .Recently developed and emerging technologies -base editors, prime editors, and Cas transposases -are beginning to enable new types of genetic screens with directed, controlled, and on demand mutations by allowing the creation of user specified modifications, such as single base conversion, deletions, and insertions [4 , 42 , 58] ."
+                }
+            ],
+            "801c9288-70c9-4d14-b8bc-13ee6708803a": [
+                {
+                    "document_id": "801c9288-70c9-4d14-b8bc-13ee6708803a",
+                    "text": "\n\nComing on the heels of engineered nucleases, CRISPR-Cas9 tools have accelerated the pace of genomic research by permitting highly efficient knockouts or edits of virtually any gene in cells or model organisms.Multiple CRISPR-Cas9-based clinical trials are in progress or are expected to begin soon.Although Cas9engineered cells haven't yet demonstrated efficacy at scale, early trial results suggest that such cells are stable and don't cause acute adverse reactions in humans.Long-term safety is yet to be determined.Current applications largely focus on single-gene disorders for which gene editing can be carried out ex vivo on appropriate cells, such as bone marrow hematopoietic stem cells in the case of sickle cell anemia.Exploration is under way to develop delivery systems that can target the gene-editing apparatus to the appropriate tissue in vivo."
+                },
+                {
+                    "document_id": "801c9288-70c9-4d14-b8bc-13ee6708803a",
+                    "text": "\n\nOver the past 8 years, CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 (CRISPR-associated protein 9) technologies have emerged as accessible and adaptable tools for studying and altering genomes. 5RISPR-Cas9 can be used to induce genome edits by creating targeted DNA breaks that trigger site-specific DNA repair.In nextgeneration formats, it can also control the transcriptional output of genes or alter genome sequences using a process of nucleotide base editing that does not require repair of DNA breaks.As these technologies continue to mature, it will become increasingly possible to alter cellular genomes efficiently and accurately."
+                }
+            ],
+            "a7f21808-dce3-4110-8e7c-ceb2437e72ff": [
+                {
+                    "document_id": "a7f21808-dce3-4110-8e7c-ceb2437e72ff",
+                    "text": "\n\nThe type II CRISPR-Cas9 systems, repurposed from prokaryotic adaptive immune responses, are now widely used for targeted genome modifications in plants, animals, and human cells (Kim et al. 2014;Woo et al. 2015;Zuris et al. 2015).In particular, Cas9 nucleases have shown promise for gene and cell therapy (Maeder and Gersbach 2016).Typically, these nucleases are expressed or delivered in vivo using plasmid DNA or viruses (Yin et al. 2014;Ran et al. 2015).However, plasmid DNA delivery is often inefficient, especially in vivo, and can cause integration of small plasmid fragments degraded by endogenous nucleases at on-target and offtarget sites in the genome (Kim et al. 2014).Viral delivery of Cas9 can be highly efficient in vivo (Ran et al. 2015;Long et al. 2016;Nelson et al. 2016;Tabebordbar et al. 2016), but may be hampered by antibodies or T cells induced against the protein (Shankar et al. 2007;Calcedo et al. 2015;Chew et al. 2016).We and others have shown that preassembled Cas9 ribonucleoproteins (RNPs) can be delivered to human primary and stem cells and mice to modify target genes (Kim et al. 2014;Schumann et al. 2015;Zuris et al. 2015).Cas9 RNPs are rapidly turned over in cells, reducing off-target effects.Furthermore, Cas9 RNPs are unlikely to be limited by host immune systems because they function and disappear before the generation of antibodies and T cells directed against them.Currently, despite these advantages of RNPs, the difficult delivery of Cas9 RNPs in vivo limits its utility for therapeutic applications (Zuris et al. 2015).Here, we show that in vivo genome editing of an wild-type gene, whose up-regulation is responsible for pathogenesis, could be a new therapeutic modality for the treatment of nongenetic degenerative diseases.Our ultimate goal is to harness Cas9 RNPs for a clinical application of therapeutic genome surgery in patients with AMD."
+                }
+            ],
+            "ac00c552-7514-49d4-9e90-ab01c22472ae": [
+                {
+                    "document_id": "ac00c552-7514-49d4-9e90-ab01c22472ae",
+                    "text": "\n\nClustered regularly interspaced short palindromic repeat (CRISPR)-Cas nucleases have revolutionized the field of gene editing and have tremendous application in the field of molecular medicine [98][99][100][101][102].Despite a significant surge in CRISPR/Cas9mediated genome editing in various disease models, the progress in the field of AD has lagged behind substantially.We believe that genome editing can significantly improve the development of AD models and also create novel opportunities for the development of the next generation precision targeted AD gene and stem cell therapies.Since there are several excellent review articles on CRISPR/Cas9-mediated genome editing, here we will limit our focus on select recent articles that are noteworthy.CRISPR/Cas9 system can be engineered to either activate transcription (gain-of-function) or achieve gene silencing (Loss-of-function).Dahlman et al. have developed a CRISPR-based system that uses catalytically active Cas9 and distinct single guide (sgRNA) constructs to activate and knockout different genes in the same cell [103].Konermann et al. have used structure-guided engineering of a CRISPR-Cas9 complex to mediate efficient transcriptional activation at endogenous genomic loci [104].Using crystallographic studies, they have engineered a combination of sgRNA2.0,NLS-dCas9-VP64 and MS2-p65-HSF1 to develop one of the most effective transcription activation system."
+                }
+            ],
+            "b72eb0d1-50e3-4def-94bc-abf77891f519": [
+                {
+                    "document_id": "b72eb0d1-50e3-4def-94bc-abf77891f519",
+                    "text": "Limitations of CRISPR-Cas9\n\nCRISPR provides a simple and easy tool not only for in vitro use but potentially also for in vivo genome editing.However, there are limitations and downsides to this approach.First, and despite considerable improvements in the technology, the risk of the offtarget effect remains and must be considered carefully.Second, DSB may lead to wide-ranging deletions or recombination events involving the on-target site (204).Third, in cycling cells, DNA double strand breaks caused by Cas9 cleavage may trigger a P53 response leading to apoptosis and enrichment for potentially oncogenic P53-deficient cells (205,206).Fourth, subjects may generate antibodies to Cas9, potentially limiting gene therapies (207,208)."
+                },
+                {
+                    "document_id": "b72eb0d1-50e3-4def-94bc-abf77891f519",
+                    "text": "\n\nGenome editing tools that target the desired genomic region and allow for variants to be altered (e.g. from risk to protective), or for more substantial changes to be made (e.g. the deletion of a longer stretch of DNA harbouring a number of variants) and can help to answer each of these questions.These technologies are evolving rapidly (Figure 1 and Table 2).The most recently developed of these, Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) technology, originally developed by Doudna, Charpentier and their colleagues (72,73) and Zhang and his colleagues (50) has become a widely used tool for this purpose.Engineered CRISPR/Cas9 technology uses a guide RNA (gRNA) to direct CRISPR-associated endonuclease (Cas) to the target DNA and generate a double strand DNA break.Correction of a mutation or variant in the target DNA sequence can then be carried out by homology-directed DNA repair (HDR) with a donor template.Since its discovery eight years ago, CRISPR technology has evolved quickly to be a critical part of the molecular biologist's toolbox."
+                }
+            ],
+            "c3ae2186-ef48-46a5-b214-dc944366df8f": [
+                {
+                    "document_id": "c3ae2186-ef48-46a5-b214-dc944366df8f",
+                    "text": "INTRODUCTION\n\nGenome editing technologies based on the clustered regularly interspaced short palindromic repeats (CRISPR)-associated endonuclease Cas9 enable rapid and efficient modification of endogenous genes in a variety of cell types, allowing for analysis of gene function in many organs in vivo.CRISPR-Cas9 induces DNA double strand breaks (DSBs) at single-guide RNA (sgRNA)-specific loci in the genome, which are repaired through either non-homologous end-joining (NHEJ) or homology-directed repair (HDR) pathways.While NHEJ introduces unpredictable pattern of insertion or deletion (indel) mutations, HDR directs a precise recombination event between a homologous DNA donor template and the damaged DNA site (Cong et al., 2013;Cox et al., 2015;Doudna and Charpentier, 2014;Heidenreich and Zhang, 2016;Jinek et al., 2012;Mali et al., 2013;Sander and Joung, 2014;Wang et al., 2013;Yang et al., 2013).Thus, HDR can be used to precisely introduce sequence insertions, deletions or mutations by encoding the desired changes in the donor template DNA."
+                }
+            ],
+            "d14e93b5-01de-4208-8255-baae7898a7bb": [
+                {
+                    "document_id": "d14e93b5-01de-4208-8255-baae7898a7bb",
+                    "text": "\nCRISPR technology has rapidly changed the face of biological research, such that precise genome editing has now become routine for many labs within several years of its initial development.What makes CRISPR/Cas9 so revolutionary is the ability to target a protein (Cas9) to an exact genomic locus, through designing a specific short complementary nucleotide sequence, that together with a common scaffold sequence, constitute the guide RNA bridging the protein and the DNA.Wild-type Cas9 cleaves both DNA strands at its target sequence, but this protein can also be modified to exert many other functions.For instance, by attaching an activation domain to catalytically inactive Cas9 and targeting a promoter region, it is possible to stimulate the expression of a specific endogenous gene.In principle, any genomic region can be targeted, and recent efforts have successfully generated pooled guide RNA libraries for coding and regulatory regions of human, mouse and Drosophila genomes with high coverage, thus facilitating functional phenotypic screening.In this review, we will highlight recent developments in the area of CRISPR-based functional genomics and discuss potential future directions, with a special focus on mammalian cell systems and arrayed library screening."
+                },
+                {
+                    "document_id": "d14e93b5-01de-4208-8255-baae7898a7bb",
+                    "text": "\n\nCRISPR technology has rapidly changed the face of biological research, such that precise genome editing has now become routine for many labs within several years of its initial development.What makes CRISPR/Cas9 so revolutionary is the ability to target a protein (Cas9) to an exact genomic locus, through designing a specific short complementary nucleotide sequence, that together with a common scaffold sequence, constitute the guide RNA bridging the protein and the DNA.Wild-type Cas9 cleaves both DNA strands at its target sequence, but this protein can also be modified to exert many other functions.For instance, by attaching an activation domain to catalytically inactive Cas9 and targeting a promoter region, it is possible to stimulate the expression of a specific endogenous gene.In principle, any genomic region can be targeted, and recent efforts have successfully generated pooled guide RNA libraries for coding and regulatory regions of human, mouse and Drosophila genomes with high coverage, thus facilitating functional phenotypic screening.In this review, we will highlight recent developments in the area of CRISPR-based functional genomics and discuss potential future directions, with a special focus on mammalian cell systems and arrayed library screening."
+                },
+                {
+                    "document_id": "d14e93b5-01de-4208-8255-baae7898a7bb",
+                    "text": "\n\nThe recent development of clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 for experimental purposes has dismantled the perception that genome editing technology is off-limits for screening in mammalian systems (Heintze et al., 2013).Since this system employs the basic principle of Watson-Crick base pairing for gene targeting, generation of libraries with whole-genome target coverage is relatively easy and cost-effective.For instance, simple protocols are available to synthesize pooled lentiviral libraries by in silico design of oligonucleotides, which can then be cloned, packaged and delivered to cells by viral transduction (Paddison et al., 2004;LeProust et al., 2010).Similarly, the generation of arrayed libraries can be achieved by following protocols originally developed for arrayed shRNA library production that have been in use for a number of years (Moffat et al., 2006).All in all, the stage is set for CRISPR to make an enormous impact on genomic screening and thus scientific discovery in the coming years, and recent demonstrations of this system have shown great promise (Shalem et al., 2015).However, a number of technical challenges must be addressed in order to maximize the benefit of this technology.In this review, we will discuss current applications of CRISPR in functional genomics and provide a perspective on future developments in this area."
+                }
+            ],
+            "e5cf067c-8be0-4b0a-b376-7882cdc9d96c": [
+                {
+                    "document_id": "e5cf067c-8be0-4b0a-b376-7882cdc9d96c",
+                    "text": "Genome editing for crop improvement\n\nReports of CRISPR-Cas9-based genome editing first appeared in 2013 (Cong et al., 2013;Feng et al., 2013;Mao et al., 2013).Since then, genome editing technologies have proven to be powerful and efficient tools for the improvement of many crop species.At present, genome editing has been widely used to introduce/modify agronomically important traits, such as increased yield, improved nutritional quality, and resistance to biotic and abiotic stresses, in multiple crops, including rice, wheat, maize, tomato, and potato (Lu et al., 2017;Soyk et al., 2017;Tang et al., 2017;D'Ambrosio et al., 2018;Ye et al., 2018;Miao et al., 2019;Zhang et al., 2019;Zhong et al., 2019;Butt et al., 2020;Zhang et al., 2020c;Li et al., 2021b;Zhan et al., 2021).CRISPR-Cas-based genome editing has been extended to targeted mutagenesis, base editing, and precisely targeted gene/allele replacement or tagging in plants.mportantly, using CRISPR-Cas9 technology, transgenes present in the genomes of genome-edited plants can be removed by chromosomal segregation via a simple self-pollination or hybridization step.Gene editing technologies continue to be developed and utilized (Mao et al., 2013;Lu and Zhu, 2017;Lu et al., 2020)."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "38E097866214E3EEFE346FB836ABF345",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "CRISPR-Cas9",
+            "gene&editing",
+            "off-target&effects",
+            "genome",
+            "clinical&trials",
+            "agriculture",
+            "biomedicine",
+            "precision&medicine",
+            "transgenic",
+            "ethical&concerns"
+        ],
+        "metadata": [],
+        "question": "What are the potential benefits and risks associated with gene editing technologies like CRISPR-Cas9?",
+        "subquestions": null,
+        "task_id": "38E097866214E3EEFE346FB836ABF345",
+        "usage": {
+            "chatgpt": 9104,
+            "gpt-4": 6248,
+            "gpt-4-turbo-preview": 5340
+        },
+        "user_id": 2
+    },
+    "document_id": "38E097866214E3EEFE346FB836ABF345",
+    "task_id": "38E097866214E3EEFE346FB836ABF345"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_06.json b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_06.json
new file mode 100644
index 0000000..01f3600
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_06.json
@@ -0,0 +1,146 @@
+{
+    "created_at": "2024-06-01T14:27:38.978700Z",
+    "data": {
+        "amplify": false,
+        "answer": "Human centromeres contain the CENP-B box, a 17-bp motif that is bound by the centromere protein CENP-B. This motif is present on every chromosome except for the Y chromosome. It is necessary for the formation of de novo centromeres on artificial chromosomes, but it is not essential for the formation of neocentromeres. Mice lacking CENP-B are viable and fertile.",
+        "context": {
+            "395a51ba-bd2a-4160-8396-b13a3bf762ff": [
+                {
+                    "document_id": "395a51ba-bd2a-4160-8396-b13a3bf762ff",
+                    "text": "\n\nPrimate and mouse centromeric DNA contain the CENP-B box, a 17-bp motif that is bound by the centromere protein CENP-B.In humans, the CENP-B box is present on every chromosome except for the Y chromosome [20].It is paradoxically necessary for formation of de novo centromeres on artificial chromosomes, but it is not essential for the formation of neocentromeres, and mice lacking CENP-B are viable and fertile [21,22]."
+                }
+            ],
+            "3dfe0ec3-b3a6-4a08-8929-e54cab3ec262": [
+                {
+                    "document_id": "3dfe0ec3-b3a6-4a08-8929-e54cab3ec262",
+                    "text": "Box 3 Mechanism of homologous recombination and end joining\n\nThe severe phenotype of the mouse mutants and the highly cancer-prone human syndromes highlight the importance of homologous recombination.Mouse KU mutants display sensitivity to agents that lead to breaks in DNA, and have immunological problems because the KU proteins are involved in V(D)J recombination of antibody gene sequences.In addition, these mutants display poor development, several features of premature ageing and increased apoptosis of postmitotic neurons in the developing brain.Mice with defects in DNA-PK cs (SCID mice) display a similar but generally milder phenotype.In contrast, XRCC4-and ligase IV-knockout mice seem more severe, with late embryonic lethality resulting from massive ATM-and p53-dependent neuronal apoptosis 33,38 ."
+                },
+                {
+                    "document_id": "3dfe0ec3-b3a6-4a08-8929-e54cab3ec262",
+                    "text": "\n\nCells in G1 have only the homologous chromosome for recombination repair.However, this may be difficult to find in the complex genome.Moreover, it is potentially dangerous as a template for repair as it may lead to homozygosity for recessive mutations.As an alternative, the end-joining reaction simply links ends of a DSB together, without any template, using the end-binding KU70/80 complex and DNA-PK cs , followed by ligation by XRCC4-ligase4 (reviewed by 27,33; see the right panel of the figure, stages V-VII).The function of KU70/80 might involve end protection and approximating the ends, in addition to a signalling function by DNA-PK cs .End joining may be further facilitated when the ends are still held together through nucleosomes or other structures.End joining is sometimes associated with gain or loss of a few nucleotides if internal microhomologies are used for annealing before sealing.This implies the involvement of DNA polymerases and/or nucleases.Note that the KU complex is also involved in telomere metabolism 27,62 .found to be lethal 34 .Inactivation of ATR by itself is inviable already at the blastocyst stage.Inactivation of BRCA1 and BRCA2 in mice is also embryonically lethal; cell lines display defects in homologous recombination [35][36][37] ."
+                },
+                {
+                    "document_id": "3dfe0ec3-b3a6-4a08-8929-e54cab3ec262",
+                    "text": "371\n\nA tentative scenario for the homologousrecombination reaction is depicted in the left panel of the figure.To promote strand invasion into homologous sequences, the 5፱-3፱ exonuclease activity of the RAD50/MRE11/NBS1 complex (also a substrate for ATM phosphorylation) exposes both 3፱ ends 30 (I).RPA facilitates assembly of a RAD51 nucleoprotein filament that probably includes RAD51-related proteins XRCC2, XRCC3, RAD51B, C and D. RAD52 stimulates filament assembly (II).RAD51 has, like its Escherichia coli RecA counterpart, the ability to exchange the single strand with the same sequence from a double-stranded DNA molecule.Correct positioning of the sister chromatids by cohesins probably facilitates the identification of a homologous sequence.A candidate for the complex chromatin transactions associated with these DNA gymnastics is RAD54, a member of the SWI/SNF family of DNA-dependent ATPases.After identification of the identical sister chromatid sequence, the intact double-stranded copy is used as a template to properly heal the broken ends by DNA synthesis (III).Finally, the so-called Hollidayjunctions are resolved by resolvases 27,33,60 (IV).Homologous recombination involves the simultaneous action of large numbers of the same molecules, which are found to be concentrated in radiation-induced nuclear foci.These depend on, and also include, the BRCA1 and BRCA2 proteins 36 .Recent evidence implicates BRCA2 directly or indirectly in nuclear translocation of RAD51 (ref.61)."
+                }
+            ],
+            "748cfe7e-e4f2-453f-8575-50dfe84e2538": [
+                {
+                    "document_id": "748cfe7e-e4f2-453f-8575-50dfe84e2538",
+                    "text": "\n\nThis picture poses more questions than it seeks to answer.Is the grouping of the regions by product rather than by type of region correct?Given that the recombina- tion fraction between HLA-A and HLA-B is of the order of .08%,and that this is likely to represent a distance of at least hundreds of thousands of nucleotides, how are the pieces put together over such relatively long distances?Is it possible that regions of the DNA loop out, so that transcripts can be made directly from noncon- tiguous DNA sequences, the loops being held in place by small RNAs as suggested for the control of splicing by Steitz, and her colleagues [24] and by others [25]?If these small RNAs are coded for well outside the HLA region, does this provide a mechanism for control of expression of products by unlinked genes, as may be the case for one of the constituent polypeptides of the HLA-DR product?What might be the nature of the signals that control which of a multiple set of alternative regions is expressed by any given chromosome?"
+                }
+            ],
+            "7a451204-390c-4ff2-8a1d-b4de62b73503": [
+                {
+                    "document_id": "7a451204-390c-4ff2-8a1d-b4de62b73503",
+                    "text": "Mamm Genome. 2006; 17:220–229. [PubMed: 16518689]\n72. Romanoski CE, et al. Systems genetics analysis of gene-by-environment interactions in human\ncells. Am J Hum Genet. 2010; 86:399–410. [PubMed: 20170901]\n73. Myers S, Freeman C, Auton A, Donnelly P, McVean G. A common sequence motif associated\nwith recombination hot spots and genome instability in humans. Nature Genet. 2008; 40:1124–\n1129. [PubMed: 19165926]\n74. Myers S, et al. Drive against hotspot motifs in primates implicates the PRDM9 gene in meiotic\nrecombination. Science. 2010; 327:876–879. [PubMed: 20044541]\n75. Cordell HJ. Detecting gene-gene interactions that underlie human diseases. Nature Rev Genet. 2009; 10:392–404."
+                }
+            ],
+            "8604652e-2477-4552-8f43-f5f19e421df2": [
+                {
+                    "document_id": "8604652e-2477-4552-8f43-f5f19e421df2",
+                    "text": "Classification of common conserved sequences in mammalian\nintergenic regions. Hum. Mol. Genet. 2002, 11, 669–674. 25. Zhu, L.; Swergold, G.D.; Seldin, M.F. Examination of sequence homology between human\nchromosome 20 and the mouse genome: Intense conservation of many genomic elements. Hum. Genet. 2003, 113, 60–70. 26. Pevzner, P.; Tesler, G. Human and mouse genomic sequences reveal extensive breakpoint reuse in\nmammalian evolution. Proc. Natl. Acad. Sci. USA 2003, 100, 7672–7677. 27. Christmann, R.B. ; Sampaio-Barros, P.; Stifano, G.; Borges, C.L. ; de Carvalho, C.R. ; Kairalla, R.;\nParra, E.R. ; Spira, A.; Simms, R.; Capellozzi, V.L. ; et al."
+                }
+            ],
+            "9d82958a-45b0-4f1d-b765-38d018e4b140": [
+                {
+                    "document_id": "9d82958a-45b0-4f1d-b765-38d018e4b140",
+                    "text": "\n\na The table lists proteins in which mutations have been shown to increase homologous recombination (HR), gross chromosomal rearrangements (GCRs), chromosomal instability (CIN), sister chromatid exchanges (SCEs), tri-nucleotide repeat expansions and contractions (TNR), telomere fusions (Tel fusion), or fragile telomeres (Tel fragility).A phenotype inside brackets ([ ]) indicates that it is caused by overexpression of the protein.For further details and references see Supplementary Table1.Abbreviations: DSB, double-strand break; PCNA, proliferating cell nuclear antigen; RFC, replication factor C complex; SCF, Skp1-Cdc53/Cullin-F-box."
+                },
+                {
+                    "document_id": "9d82958a-45b0-4f1d-b765-38d018e4b140",
+                    "text": "\n\nFigure 3 Intermediates and chromosome structural alterations, as observed by different techniques. (a) Replication fork stalling, as monitored by 2D-gel electrophoresis and Southern analysis in yeast (for details about the technique, see Reference 161). (b) Slower human replication forks covering shorter DNA synthesis tracks, as determined by incorporation of IdU and CldU via DNA combing (52), which permits visualization of the process of replication on DNA fibers. (c) Accumulation of double-strand breaks (DSBs) or replicative stress, as inferred by γH2AX foci or by γH2AX pan staining, respectively, in human cells. (d ) DSBs or ssDNA (single-stranded DNA) gaps as seen directly by nuclear \"comet tails\" via single-cell electrophoresis assays in human cells (52). (e) Sister-chromatid exchanges (SCEs), as determined by Giemsa staining in human cells (207). ( f ) Hyper-recombination, as determined by colony sectoring in yeast (5). ( g) Gross chromosomal rearrangements (GCRs), as determined by spectral karyotyping in mouse cells (118). (h) Translocations, as visualized by pulse-field gel electrophoresis in yeast (168). (i ) Fragile sites, as detected by mitotic spreads in human cells (109). ( j) Telomere fusions, as determined by CO-FISH (chromosome-orientation fluorescent in situ hybridization) in mouse cells (124). (k) Anaphase bridges, presumably resulting from unfinished replication, dicentric chromosomes, and sister-chromatid nondisjunction, as detected by fluorescence microscopy in mouse cells.Arrows indicate the specific structural alterations referred to in each panel; in panel h, closed and open arrows indicate the position where the translocated or missing parental chromosome migrate or should migrate, respectively.When necessary, a normal control is shown on top of the panel, with the exception of panel a, which is shown on the left.Detailed description of each technique can be found in the references provided.Photos are from the laboratories of A. Nussenzweig ( g), A. Losada (k), M. Blasco ( j), L. Tora (i ), and ours (all others).Abbreviations: HR, homologous recombination; NHEJ, nonhomologous end-joining."
+                }
+            ],
+            "9ee491f4-5f16-4cb2-b803-54f2fdee1dba": [
+                {
+                    "document_id": "9ee491f4-5f16-4cb2-b803-54f2fdee1dba",
+                    "text": "\n\nIn humans, the pericentromeric region of chromosome 9 is densely packed with segmental genomic duplications (segdups) and is prone to microdeletions and microduplications. 5In order to evaluate this region for microdeletions and microduplications in family T, we screened genomic DNA from affected individual II-7 by arrayCGH with the Nimblegen HD2 platform with the previously described CHP-SKN sample 6 as the reference.Data were normalized and CNVs were called by identifying regions where Z-scores consistently deviated from the diploid mean.At 9q21.11, a genomic duplication of ~270 kb was apparent in the genomic DNA of II-7 (Figure 1D).The Genomic duplications may or may not be in tandem with their parent segment and may be either in the same or inverted orientation. 7We developed primers that would uniquely amplify genomic DNA with the duplication under each of these conditions.Forward (5 0 -CCCAGCAGA AGCAATGGTGGTAGCC-3 0 ) and reverse (5 0 -GGTGGTGAA TCCAAAAACACAAGAACAAAGTC-3 0 ) primers diagnostic for a tandem inverted duplication (Figure 2A) yielded products of expected size in family T relatives with hearing loss, but yielded no product in unaffected family T relatives (Figure 2B).Genotypes of all 58 participating relatives in family T indicated that the tandem inverted duplication was coinherited with hearing loss.The duplication spans approximately positions 71,705,804 to 71,974,823 (hg19) on chromosome 9 for a size of ~269,023 bp.The duplication includes the entire locus for the tight junction protein TJP2, which spans positions 71,788,971 to 71,870,124 (hg19)."
+                }
+            ],
+            "ab0a3234-c3b3-46be-8954-01eda9bc962e": [
+                {
+                    "document_id": "ab0a3234-c3b3-46be-8954-01eda9bc962e",
+                    "text": "Chromosomal context of human NORs\n\nHuman NORs are positioned on the short arms of the acrocentric chromosomes that still remain unsequenced and thus missing from the current human genome draft, GRCh38.p7.Seeking an understanding of the chromosomal context of human NORs and to identify potential NOR regulatory elements, my laboratory has begun to characterize the sequences on both proximal (centromeric) and distal (telomeric) sides of the rDNA arrays (Fig. 3A; Floutsakou et al. 2013).Building on earlier reports of sequences distal and proximal to the rDNA array on HSA21 and HSA22, respectively (Worton et al. 1988;Sakai et al. 1995;Gonzalez and Sylvester 1997), 207 kb of sequence immediately proximal and 379 kb distal to rDNA arrays have been reported recently (Floutsakou et al. 2013).Consensus proximal junction (PJ) and distal junction (DJ) sequences were constructed mostly from chromosome 21 BACs (bacterial artificial chromosomes).Comparison of these sequences with BACs and cosmids derived from the other acrocentrics revealed that the PJ and DJ sequences are, respectively, ∼95% and 99% identical between all five acrocentric chromosomes.Conservation of DJ sequences among the acrocentrics is consistent with frequent recombination between the rDNA arrays on each of the acrocentric chromosomes (Worton et al. 1988).However, conservation of PJ sequences suggests that there must also be frequent recombination events in the interval between the centromere and rDNA arrays.Proximal sequences are almost entirely segmentally duplicated, similar to the regions bordering centromeres.Consequently, they are unlikely to contain any specific elements that would regulate the activity of the linked NOR.In contrast, the distal sequence is predominantly unique to the acrocentric short arms and is dominated by a very large inverted repeat.Each arm of the inverted repeat is >100 kb, and they share an average sequence identity of 80%.There is a large (∼40-kb) block of a 48base-pair (bp) satellite repeat, CER, at the distal end of the DJ (Fig. 3A).CER blocks are found distal to the rDNA on all acrocentric chromosomes, with additional pericentromeric blocks on chromosomes 14 and 22. Finally, there are two blocks of a novel 138-bp tandem repeat, ACRO138, present within the DJ."
+                },
+                {
+                    "document_id": "ab0a3234-c3b3-46be-8954-01eda9bc962e",
+                    "text": "\n\nThe conservation of DJ sequence between the five human acrocentric chromosomes provides a unique opportunity to visualize NORs by FISH.Whereas the rDNA content of NORs can vary greatly, probing of human metaphase chromosome spreads with a DJ BAC results in signal that is consistent between NORs (Floutsakou et al. 2013).Using this probing scheme, it was observed that in most human cell lines analyzed, including multiple primary lines, at least one and sometimes as many as four of the NORs present have very little or no detectable rDNA (C van Vuuren and B McStay, unpubl. ).Many studies have used silver staining of metaphase spreads prepared from stimulated human peripheral blood lymphocytes to determine how many NORs are active in normal human cells.The number of active NORs ranges from seven to 10, with an average of eight (Heliot et al. 2000).Possibly, NORs with low rDNA content are active but fall below a detection threshold in silver staining.At this point, it is worth considering the distribution of active versus silent rDNA repeats in humans and other mammals.If 50% of rDNA repeats are truly repressed, there are insufficient \"silent\" NORs to house them.We must conclude that active NORs are a mosaic of active and silent repeats."
+                }
+            ],
+            "b04f2221-de28-4c4b-893e-9da982ff864c": [
+                {
+                    "document_id": "b04f2221-de28-4c4b-893e-9da982ff864c",
+                    "text": "However, excluding some cases, recombination\nsuppression occurs in a small genomic tract\nwhere these genes are located, and it does\nnot extend over most of the sex chromosome\npair, as occurs in mammals and birds (Bergero\nand Charlesworth, 2009). It is not clear if this\nsuppression occurs by the presence of inversions or as a modulation of the recombination\nmechanism itself, but both could be involved\n(Bergero and Charlesworth, 2009). Evidence of\nrecombination in the SD region in sex reversal\nindividuals supports the second hypothesis."
+                }
+            ],
+            "d4fb56e4-06ab-4c01-b7a0-a193c4a40800": [
+                {
+                    "document_id": "d4fb56e4-06ab-4c01-b7a0-a193c4a40800",
+                    "text": "\n\nOrthologous chromosomes between baboon and human"
+                }
+            ],
+            "da485354-fcdc-49b8-9a41-0f673610156a": [
+                {
+                    "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                    "text": "Lichter P, Cremer T, Borden J, Manuelidis L, Ward DC (1988) Delineation of\nindividual human chromosomes in metaphase and interphase cells by in situ suppression hybridization using recombinant DNA libraries. Hum Genet 80:224–234\n3. Jang W, Yonescu R, Knutsen T, Brown T, Reppert T, Sirotkin K, Schuler GD, Ried\nT, Kirsch IR (2006) Linking the human cytogenetic map with nucleotide sequence:\nthe CCAP clone set. Cancer Genet Cytogenet 168:89–97\n4."
+                },
+                {
+                    "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                    "text": "Nature\nGenet 1:222–225\n55. Foote S, Vollrath D, Hilton A, Page DC (1992) The human Y chromosome: overlapping DNA clones spanning the euchromatic region. Science 258:60–66\n56. Chumakov IM, Rigault P, Le Gall I et al (1995) A YAC contig map of the human\ngenome. Nature 377:175–297\n57. Hudson TJ, Stein LD, Gerety SS et al (1995) An STS-based map of the human\ngenome. Science 270:1945–1954\n58. Coffey AJ, Roberts RG, Green ED et al (1992) Construction of a 2.6-Mb contig in\nyeast artificial chromosomes spanning the human dystrophin gene using an STSbased approach. Genomics 12:474–484\n59."
+                }
+            ],
+            "e4541c0c-53fb-4c2c-b550-40728c356549": [
+                {
+                    "document_id": "e4541c0c-53fb-4c2c-b550-40728c356549",
+                    "text": "\n\nFigure 4 Schematic depiction of proposed mechanisms for observed intrachromosomal rearrangements.The blue and red arrows indicate the orientation of the integrated plasmid loci and the recovered mouse sequences, respectively, on the original non-rearranged chromosome (left column).All four combinations are given for an arbitrarily orientated chromosome (green line).The middle column shows how two breakpoints (lightning signs) could lead to the inversion or deletion of the encompassed chromosomal sequence (yellow-orange dual tone line) and result in a recoverable mutation in the right column.The last row indicates the two options for a transposition, in which either the transgene locus or the recovered mouse sequence is copied or excised (as indicated by the pink and light blue arrows) and integrates in the breakpoint at the other location."
+                },
+                {
+                    "document_id": "e4541c0c-53fb-4c2c-b550-40728c356549",
+                    "text": "\n\nAs mentioned above, by taking into account that for a genome rearrangement to be detected, the 5Ј plasmid sequence of the breakpoint in lacZ must remain intact and end immediately in front of the recovered mouse sequence, the simplest intrachromosomal mutation that could have taken place was inferred (Fig. 4).Rearrangements with breakpoints in the mouse genome on either site of the integrated plasmid concatamer, but with reversely orientated sequences, could be inversions (Fig. 4).Rearrangements in the direction of the integrated plasmids, proximal for chromosome 3 and distal for chromosome 4 (Fig. 3), with similarly orientated breakpoints in the mouse genome, could be deletions (Fig. 4).Rearrangements in the reverse direction of the integrated plasmids, with reversely orientated mouse sequences, are more complicated and might be owing to transpositions (Fig. 4).According to these schemes, half of the intrachromosomal rearrangements would have been inversions, whereas deletions and transpositions each made up one fourth (Fig. 3).Alternatively, these rearrangements could be explained by translocations involving the transgene clusters integrated on either the homolog or the other chromosome."
+                }
+            ],
+            "f08c0391-2d72-491c-a472-5db71bf11ac8": [
+                {
+                    "document_id": "f08c0391-2d72-491c-a472-5db71bf11ac8",
+                    "text": "\n\nFIGURE 3. Telomere arrays of chicken and human chromosomes: the chicken genome contains more telomere sequence than the human genome.Chicken (a) and human (b) metaphase chromosomes and interphase cells hybridized with a telomeric sequence-peptide nucleic acid (PNA)-fluorescein probe.Human and chicken slide preparations were processed, and images were captured using the same parameters.Qualitatively, the telomere-positive fluorescent signals (white spots) from chicken cells and chromosomes have greater intensity than those of human (4′,6 diamidino-2-phenylindole, DAPI counterstain)."
+                }
+            ],
+            "f4762690-64e9-4f6d-9031-c249dc4a6d85": [
+                {
+                    "document_id": "f4762690-64e9-4f6d-9031-c249dc4a6d85",
+                    "text": "\n\nIn a previous study on the accumulation of spontaneous genome rearrangements in normal mice with aging, we discovered that 50% of the events were intrachromosomal, i.e., large deletions or inversions [22].In contrast, in this present study most of the rearrangements resulted from inter-chromosomal recombination, in both the Ercc1-mutant and control animals (Table 3).Previously, we used lacZ-plasmid line 60 mice with integration sites on Chromosomes 3 and 4, while in the present study line 30 mice were used with a single integration site on Chromosome 11.This indicates that the relative frequency of translocations is founder line specific and could be due to the position of the lacZ-plasmid cluster on the chromosome.Indeed, the chromosomal integration sites in line 60 mice are in the E1 region of Chromosome 3 (half way along the chromosome) and the C5 region of Chromosome 4 (two-thirds of the way along the chromosome) [22], while the integration site of founder line 30 (used in this study) is on the centromeric tip of Chromosome 11 (region A1-A2; not shown).The proximal location on Chromosome 11 prevents the detection of all but relatively small intra-chromosomal recombinations; larger events would lead to loss of the centromere and, therefore, the entire chromosome.If the orientation of the integration site in line 30, which is currently unknown, is towards the centromere, transpositions and inversions towards the distal end are the only detectable large intra-chromosomal rearrangements (for a detailed explanation of the different chromosomal events that can occur at the lacZ locus, see [22])."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "575BE8FB36E8D520760A31B2CAE92034",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "CENP-B&box",
+            "human&centromeres",
+            "recombination",
+            "chromosome&11",
+            "Ercc1-mutant",
+            "lacZ-plasmid",
+            "inversions",
+            "translocations",
+            "NORs",
+            "rDNA"
+        ],
+        "metadata": [],
+        "question": "What about recombination in human centromeres?",
+        "subquestions": null,
+        "task_id": "575BE8FB36E8D520760A31B2CAE92034",
+        "usage": {
+            "chatgpt": 8855,
+            "gpt-4": 5918,
+            "gpt-4-turbo-preview": 4935
+        },
+        "user_id": 2
+    },
+    "document_id": "575BE8FB36E8D520760A31B2CAE92034",
+    "task_id": "575BE8FB36E8D520760A31B2CAE92034"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_07.json b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_07.json
new file mode 100644
index 0000000..ad4369d
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_07.json
@@ -0,0 +1,142 @@
+{
+    "created_at": "2024-06-01T14:29:54.405039Z",
+    "data": {
+        "amplify": false,
+        "answer": "The text mentions the application of site-specific recombinase technology, which allows investigators to engineer genes in the mouse that will allow for the deletion, insertion, inversion, or exchange of chromosomal DNA with high fidelity. However, it does not provide specific details about recombination in the human genome.",
+        "context": {
+            "081924f4-cdcc-4fce-9223-744c6ecffe4e": [
+                {
+                    "document_id": "081924f4-cdcc-4fce-9223-744c6ecffe4e",
+                    "text": "Genome Res, 2011, 21: 1769–1776\nMattick JS, Dinger ME. The extent of functionality in the human\ngenome. HUGO J, 2013, 7, doi:10.1186/1877-6566-1187-1182\nENCODE Project Consortium, Bernstein BE, Birney E, Dunham I,\nGreen ED, Gunter C, Snyder M. An integrated encyclopedia of DNA\nelements in the human genome. Nature, 2012, 489: 57–74\nPheasant M, Mattick JS. Raising the estimate of functional human\nsequences. Genome Res, 2007, 17: 1245–1253\nHu T, Long M, Yuan D, Zhu Z, Huang Y, Huang S. The genetic\nequidistance result, misreading by the molecular clock and neutral\ntheory and reinterpretation nearly half of a century later."
+                }
+            ],
+            "33814fad-d831-46f5-b41f-ff31626a82ca": [
+                {
+                    "document_id": "33814fad-d831-46f5-b41f-ff31626a82ca",
+                    "text": "This approach enables, on the one hand, studying the process of\nmammalian evolution and, on the other hand, translational studies using model\norganisms of complex human phenotypes. Detection of regions conserved between\ndistant species points to high functional importance of these fragments of the DNA\nsequence. Human and mouse developmental lines diverged about 75 million years ago, and\never since evolutionary forces shaped the two genotypes in a different manner\n(Waterston et al. , 2002). Nevertheless, the extent of the changes is, however, small\nenough for conservation of local gene order (Waterston et al. , 2002)."
+                }
+            ],
+            "3cafb9e7-b3d9-4e8e-a727-da79282d2b14": [
+                {
+                    "document_id": "3cafb9e7-b3d9-4e8e-a727-da79282d2b14",
+                    "text": "First, the human and mouse genome projects\nelucidated the sequences of over 20,000 genes [Lander et al. ,\n2001; Venter et al. , 2001], and most are expressed in the CNS. The availability of gene sequences has allowed rapid analysis of\ncandidate human disease and disorder genes and the isolation of\nthe mouse homologues. Second, the application of site-speciﬁc\nrecombinase technology provides investigators with the opportunity to engineer genes in the mouse that will allow for the\ndeletion, insertion, inversion, or exchange of chromosomal\nDNA with high ﬁdelity (for review see Branda and Dymechi,\n2004]."
+                }
+            ],
+            "5edf84d0-c2d9-45eb-91b9-c35743b6a463": [
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text": "In some cases, structural variations, such as copy number polymorphisms,\nexist (Feuk et al. , 2006); however, because of the nature of the genome assembly\nprocess, these will invariably be collapsed into a single contig that does not reflect\nthe natural sequence. To address the technical challenges of whole-genome assembly,\nthe human genome is released as defined ‘builds’ on a quarterly basis (Lander et al. ,\n2001; reviewed in Chapter 4). The increasing complexity of processes that map\ndata to the genome implicitly involves some lag in availability of the most current\nsequence assembly."
+                },
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text": "In\npractical terms, this has meant that we acquire many fragments, from a few hundred\nbases to a few hundred kilobases in length, of a genome that must then be assembled computationally to produce a continuous sequence. In the case of the human\ngenome, two unfinished ‘draft’ sequences were produced by different methods, one\nby the International Human Genome Sequencing Consortium (IHGSC) and one by\nCelera Genomics (CG). The IHGSC began with a BAC (bacterial artificial chromosome) clone-based physical map of the genome (IHGSC, 2001)."
+                },
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text": "4\nAssembling a View of the\nHuman Genome\nColin A. M. Semple\nBioinformatics, MRC Human Genetics Unit, Edinburgh EH4 2XU, UK\n\n4.1 Introduction\nThe miraculous birth of the draft human genome sequence took place against\nthe odds. It was only made possible by parallel revolutions in the technologies\nused to produce, store and analyse the sequence data, and by the development of\nnew, large-scale consortia to organize and obtain funding for the work (Watson,\n1990). The initial flood of human sequence has subsided as the sequencing centres have sequenced genomes from other mammalian orders and beyond."
+                }
+            ],
+            "74f148ef-696c-4e25-80e5-1d44ae70540e": [
+                {
+                    "document_id": "74f148ef-696c-4e25-80e5-1d44ae70540e",
+                    "text": "\nTHE HUMAN GENOME PROJECT IS generating vast amounts of new information at breakneck speed and causing a fundamental shift in disease research.Now with the availability of a nearly complete, high-accuracy sequence of the mouse genome (7), a new and powerful paradigm for biomedical research is established.The remarkable similarity of mouse and human genomes, in both synteny and sequence, unconditionally validates the mouse as an exceptional model organism for understanding human biology.The discovery among inbred mouse strains of defined regions of high and low genomic variation inherited primarily from two ancestral Mus subspecies (6) holds great promise to make mapping and positional cloning more rapid and feasible.Haplotype maps of inbred mouse strains combined with sophisticated delineation of their phenotypic variation and gene expression patterns will enable complex trait analysis on an unprecedented scale.This issue of Journal of Applied Physiology highlights inbred strain surveys exploring phenotypic variation in drug responses [see Crabbe et al. (1) and Watters et al. (8)  in this issue].These mouse initiatives demonstrate a viable, cost-effective alternative to human research requiring family studies, population linkage analysis, or genome-wide genotyping on a multitude of individuals for association mapping."
+                }
+            ],
+            "81c3edc4-f625-45f2-bf78-e49faf118c88": [
+                {
+                    "document_id": "81c3edc4-f625-45f2-bf78-e49faf118c88",
+                    "text": "\n\nHow Many Genes are There in the Human Genome?"
+                }
+            ],
+            "b1656249-5f62-428f-8b71-7549cc2886ff": [
+                {
+                    "document_id": "b1656249-5f62-428f-8b71-7549cc2886ff",
+                    "text": "\n\nThe Landscape of Human Genome Variation"
+                }
+            ],
+            "c12e853e-4f0d-48f9-93af-15db9ad2dfae": [
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "In some cases, structural variations, such as copy number polymorphisms,\nexist (Feuk et al. , 2006); however, because of the nature of the genome assembly\nprocess, these will invariably be collapsed into a single contig that does not reflect\nthe natural sequence. To address the technical challenges of whole-genome assembly,\nthe human genome is released as defined ‘builds’ on a quarterly basis (Lander et al. ,\n2001; reviewed in Chapter 4). The increasing complexity of processes that map\ndata to the genome implicitly involves some lag in availability of the most current\nsequence assembly."
+                },
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "In\npractical terms, this has meant that we acquire many fragments, from a few hundred\nbases to a few hundred kilobases in length, of a genome that must then be assembled computationally to produce a continuous sequence. In the case of the human\ngenome, two unfinished ‘draft’ sequences were produced by different methods, one\nby the International Human Genome Sequencing Consortium (IHGSC) and one by\nCelera Genomics (CG). The IHGSC began with a BAC (bacterial artificial chromosome) clone-based physical map of the genome (IHGSC, 2001)."
+                },
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "4\nAssembling a View of the\nHuman Genome\nColin A. M. Semple\nBioinformatics, MRC Human Genetics Unit, Edinburgh EH4 2XU, UK\n\n4.1 Introduction\nThe miraculous birth of the draft human genome sequence took place against\nthe odds. It was only made possible by parallel revolutions in the technologies\nused to produce, store and analyse the sequence data, and by the development of\nnew, large-scale consortia to organize and obtain funding for the work (Watson,\n1990). The initial flood of human sequence has subsided as the sequencing centres have sequenced genomes from other mammalian orders and beyond."
+                }
+            ],
+            "da485354-fcdc-49b8-9a41-0f673610156a": [
+                {
+                    "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                    "text": "Science 291:1304–\n1351\n3. Lander ES et al (2001) Initial sequencing and analysis of the human genome. Nature 409:860–921\n4. Engle LJ, Simpson CL, Landers JE (2006) Using high-throughput SNP technologies to study cancer. Oncogene 25:1594–1601\n5. Elston RC, Anne Spence M (2006) Advances in statistical human genetics over the\nlast 25 years. Stat Med 25:3049–3080\n6. Larson GP et al (2005) Genetic linkage of prostate cancer risk to the chromosome\n3 region bearing FHIT. Cancer Res 65:805–814\n7. Botstein D, Risch N (2003) Discovering genotypes underlying human phenotypes:\npast successes for mendelian disease, future approaches for complex disease."
+                },
+                {
+                    "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                    "text": "McPherson JD, Marra M, Hillier L et al (2001) A physical map of the human\ngenome. Nature 409:934–941\n13. Burke DT, Carle GF, Olson MV. (1987) Cloning of large segments of exogenous\nDNA into yeast by means of artificial chromosome vectors. Science 236:806–812\n14. Fleischmann RD, Adams MD, White O et al (1995) Whole-genome random\nsequencing and assembly of Haemophilus influenzae Rd Science 269:496–512\n15. Arabidopsis Genome Initiative (2000) Analysis of the genome sequence of the\nflowering plant Arabidopsis thaliana. Nature 408:796–815\n16."
+                }
+            ],
+            "e17ef791-e77a-486b-a3c1-c7f037fa530c": [
+                {
+                    "document_id": "e17ef791-e77a-486b-a3c1-c7f037fa530c",
+                    "text": "\n\nT he human genome has been cracked wide open in recent years and is spilling many of its secrets.More than 100 genome wide association studies have been conducted for scores of hu man diseases, identifying hun dreds of polymorphisms that are widely seen to influence disease risk.After many years in which the study of complex human traits was mired in false claims and methodologic inconsistencies, ge nomics has brought not only com prehensive representation of com mon variation but also welcome rigor in the interpretation of sta tistical evidence.Researchers now know how to properly account for most of the multiple hypothesis testing involved in mining the ge nome for associations, and most reported associations reflect real biologic causation.But do they matter?"
+                }
+            ],
+            "f35e02a1-3314-4663-913f-38a3fc072aa8": [
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text": "In some cases, structural variations, such as copy number polymorphisms,\nexist (Feuk et al. , 2006); however, because of the nature of the genome assembly\nprocess, these will invariably be collapsed into a single contig that does not reflect\nthe natural sequence. To address the technical challenges of whole-genome assembly,\nthe human genome is released as defined ‘builds’ on a quarterly basis (Lander et al. ,\n2001; reviewed in Chapter 4). The increasing complexity of processes that map\ndata to the genome implicitly involves some lag in availability of the most current\nsequence assembly."
+                },
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text": "In\npractical terms, this has meant that we acquire many fragments, from a few hundred\nbases to a few hundred kilobases in length, of a genome that must then be assembled computationally to produce a continuous sequence. In the case of the human\ngenome, two unfinished ‘draft’ sequences were produced by different methods, one\nby the International Human Genome Sequencing Consortium (IHGSC) and one by\nCelera Genomics (CG). The IHGSC began with a BAC (bacterial artificial chromosome) clone-based physical map of the genome (IHGSC, 2001)."
+                }
+            ],
+            "fca531d0-d45b-495f-a02c-fbd437617b20": [
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "In some cases, structural variations, such as copy number polymorphisms,\nexist (Feuk et al. , 2006); however, because of the nature of the genome assembly\nprocess, these will invariably be collapsed into a single contig that does not reflect\nthe natural sequence. To address the technical challenges of whole-genome assembly,\nthe human genome is released as defined ‘builds’ on a quarterly basis (Lander et al. ,\n2001; reviewed in Chapter 4). The increasing complexity of processes that map\ndata to the genome implicitly involves some lag in availability of the most current\nsequence assembly."
+                },
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "In\npractical terms, this has meant that we acquire many fragments, from a few hundred\nbases to a few hundred kilobases in length, of a genome that must then be assembled computationally to produce a continuous sequence. In the case of the human\ngenome, two unfinished ‘draft’ sequences were produced by different methods, one\nby the International Human Genome Sequencing Consortium (IHGSC) and one by\nCelera Genomics (CG). The IHGSC began with a BAC (bacterial artificial chromosome) clone-based physical map of the genome (IHGSC, 2001)."
+                },
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "4\nAssembling a View of the\nHuman Genome\nColin A. M. Semple\nBioinformatics, MRC Human Genetics Unit, Edinburgh EH4 2XU, UK\n\n4.1 Introduction\nThe miraculous birth of the draft human genome sequence took place against\nthe odds. It was only made possible by parallel revolutions in the technologies\nused to produce, store and analyse the sequence data, and by the development of\nnew, large-scale consortia to organize and obtain funding for the work (Watson,\n1990). The initial flood of human sequence has subsided as the sequencing centres have sequenced genomes from other mammalian orders and beyond."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "1A879F7DD77C0462CC12FB20F7D14486",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "human&genome",
+            "recombination",
+            "genes",
+            "CNS",
+            "site-specific&recombinase",
+            "structural&variations",
+            "copy&number&polymorphisms",
+            "genome&assembly",
+            "genome&wide&association&studies",
+            "polymorphisms"
+        ],
+        "metadata": [],
+        "question": "What about recombination in the human genome?",
+        "subquestions": null,
+        "task_id": "1A879F7DD77C0462CC12FB20F7D14486",
+        "usage": {
+            "chatgpt": 4864,
+            "gpt-4": 3728,
+            "gpt-4-turbo-preview": 2745
+        },
+        "user_id": 2
+    },
+    "document_id": "1A879F7DD77C0462CC12FB20F7D14486",
+    "task_id": "1A879F7DD77C0462CC12FB20F7D14486"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_08.json b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_08.json
new file mode 100644
index 0000000..10a7cd2
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_08.json
@@ -0,0 +1,163 @@
+{
+    "created_at": "2024-06-01T14:31:40.882988Z",
+    "data": {
+        "amplify": false,
+        "answer": "The text does not provide specific instructions on how to add a new species to the GeneNetwork database. It is recommended to contact the administrators or operators of the GeneNetwork database for guidance on this process.",
+        "context": {
+            "0e6c370f-b514-4551-b6ed-9cc72e6f6b75": [
+                {
+                    "document_id": "0e6c370f-b514-4551-b6ed-9cc72e6f6b75",
+                    "text": "The hierarchical organization of GN’s main Select and Search menu is\nsimple and makes it relatively easy to find relevant data sets (Fig. 1). To get data, after\nopening the browser, select the most appropriate Species from the dropdown menu. For an\nopen-ended search of phenotypes you can also select All Species at the bottom of the menu. The next steps are to select the Group, Type, and Data Set from the drop-down menus. For\nmany groups, a combination of phenotypes, genotypes, and molecular data are available."
+                }
+            ],
+            "4049da4d-c7cf-4e30-9a21-c77609fad23d": [
+                {
+                    "document_id": "4049da4d-c7cf-4e30-9a21-c77609fad23d",
+                    "text": "GeneNetwork contains data from a\nwide range of species, from humans to soybeans, but most of the available phenotypic data is\nfrom mice. Within the mouse dataset there are groups of families, crosses, non-genetic\ngroupings, and individual data. The type of dataset must be selected after defining the species\nand sample population. While genotypes, mRNA, methylated DNA, protein, metagenomic, and\n2\nbioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424047; this version posted December 24, 2020. The copyright holder for this preprint\n(which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. metabolome datasets are available (i.e."
+                }
+            ],
+            "43407486-b9c2-487b-b19c-b605c4d201c6": [
+                {
+                    "document_id": "43407486-b9c2-487b-b19c-b605c4d201c6",
+                    "text": "The hierarchical organization of GN’s main Select and Search menu is\nsimple and makes it relatively easy to find relevant data sets (Fig. 1). To get data, after\nopening the browser, select the most appropriate Species from the dropdown menu. For an\nopen-ended search of phenotypes you can also select All Species at the bottom of the menu. The next steps are to select the Group, Type, and Data Set from the drop-down menus. For\nmany groups, a combination of phenotypes, genotypes, and molecular data are available."
+                }
+            ],
+            "47a15e69-dc83-452e-95d8-c605e61f43c0": [
+                {
+                    "document_id": "47a15e69-dc83-452e-95d8-c605e61f43c0",
+                    "text": "Search and Data Retrieval\nPoint your browser to www.genenetwork.org. This brings you by default to\nthe Search page, from which you can retrieve data from many GN data sets. We will focus on the default data set, defined by Species: Mouse, Group: BXD,\nType: Whole Brain, Database: INIA Brain mRNA M430 (Apr05) PDNN\nEnter “Kcnj*” into the ALL or ANY field and click the Search button. Note\nthe location and annotation of available potassium channel genes in the Search\nResults page that opens. Use the browser Back button to return to previous page."
+                }
+            ],
+            "638b3811-7054-4788-a42d-2ccc7bfce1c7": [
+                {
+                    "document_id": "638b3811-7054-4788-a42d-2ccc7bfce1c7",
+                    "text": "Add\ninformation on data provenance by giving details in Investigation, Protocols and ProtocolApplications\n\nCustomize Customize ‘my’ XGAP database with extended variants of Trait and Subject. In the online XGAP demonstrator, Probe traits have a\nsequence and genome location and Strain subjects have parent strains and (in)breeding method. Describe extensions using MOLGENIS\nlanguage and the generator automatically changes XGAP database software to your research\nUpload\n\nUpload data from measurement devices, public databases, collaborating XGAP databases, or a public XGAP repository with community\ndata."
+                },
+                {
+                    "document_id": "638b3811-7054-4788-a42d-2ccc7bfce1c7",
+                    "text": "However, a suitable and customizable integration of\nthese elements to support high throughput genotype-tophenotype experiments is still needed [34]: dbGaP, GeneNetwork and the model organism databases are\ndesigned as international repositories and not to serve\nas general data infrastructure for individual projects;\nmany of the existing bespoke data models are too complicated and specialized, hard to integrate between profiling technologies, or lack software support to easily\nconnect to new analysis tools; and customization of the\nexisting infrastructures dbGaP, GeneNetwork or other\ninternational repositories [35,36] or assembly of Bioconductor and generic model organism database components to suit particular experimental designs, organisms\nand biotechnologies still requires many minor and\nsometimes major manual changes in the software code\nthat go beyond what individual lab bioinformaticians\ncan or should do, and result in duplicated efforts\nbetween labs if attempted."
+                }
+            ],
+            "75813bc2-f0b5-400c-92d7-0958df97a04f": [
+                {
+                    "document_id": "75813bc2-f0b5-400c-92d7-0958df97a04f",
+                    "text": ", 2014; see Section 9). GeneNetwork is a database that enables searching for ∼4000 phenotypes from multiple studies in the BXD, HXB, and in other recombinant inbred rodent families, as well as in other model organisms\nand even humans (Mulligan et al. , 2017). GeneNetwork employed a\nsomewhat diﬀerent strategy than MPD in that it did not rely solely on\nresearchers submitting their data. Instead the database operators extracted the data from the scientiﬁc literature and integrated them into a\nuniform format (Chesler et al. , 2003)."
+                }
+            ],
+            "7b1cecf5-a2b9-4bd9-b92b-9bd6b96ed93d": [
+                {
+                    "document_id": "7b1cecf5-a2b9-4bd9-b92b-9bd6b96ed93d",
+                    "text": "GeneNetwork contains data from a\nwide range of species, from humans to soybeans, but most of the available phenotypic data is\nfrom mice. Within the mouse dataset there are groups of families, crosses, non-genetic\ngroupings, and individual data. The type of dataset must be selected after defining the species\nand sample population. While genotypes, mRNA, methylated DNA, protein, metagenomic, and\n2\nbioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424047; this version posted December 24, 2020. The copyright holder for this preprint\n(which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. metabolome datasets are available (i.e."
+                }
+            ],
+            "85ee9743-b34d-4d49-9017-d7d2e5d4b996": [
+                {
+                    "document_id": "85ee9743-b34d-4d49-9017-d7d2e5d4b996",
+                    "text": "However, a suitable and customizable integration of these elements\nto support high throughput genotype-to-phenotype experiments is still\nneeded[340]: dbGaP, GeneNetwork and the model organism databases\nare designed as international repositories and not to serve as general\ndata infrastructure for individual projects; many of the existing bespoke\ndata models are too complicated and specialized, hard to integrate between proﬁling technologies, or lack software support to easily connect\nto new analysis tools; and customization of the existing infrastructures\ndbGaP, GeneNetwork or other international repositories[384, 154] or\nassembly of Bioconductor and generic model organism database components to suit particular experimental designs, organisms and biotechnologies still requires many minor and sometimes major manual changes\n38\n2.1."
+                }
+            ],
+            "92fa8f50-2923-41a1-812b-32d931c71684": [
+                {
+                    "document_id": "92fa8f50-2923-41a1-812b-32d931c71684",
+                    "text": "All data presented in this paper were deposited in the online database\nGeneNetwork (www.genenetwork.org), an open web resource that contains\ngenotypic, gene expression, and phenotypic data from several genetic reference\npopulations of multiple species (e.g. mouse, rat and human) and various cell\ntypes and tissues.35;36 It provides a valuable tool to integrate gene networks and\nphenotypic traits, and also allows cross-cell type and cross-species comparative\ngene expression and eQTL analyses."
+                }
+            ],
+            "d2f9c5cf-835c-450a-bb42-a2454a99e058": [
+                {
+                    "document_id": "d2f9c5cf-835c-450a-bb42-a2454a99e058",
+                    "text": "There is a good chance that you will be able to apply these new\ntechniques to specific problems, even while you read. If you have a computer with an\nInternet connection—so much the better, and you can read and work along at the same time. This short review and primer will take you on a tour of a web site called GeneNetwork that\nembeds many large data sets that are relevant to studies of behavioral variation. GeneNetwork is an unusual site because it contains a coherent \"universe\" of data, as well as\nmany powerful analytic tools."
+                }
+            ],
+            "dbe5a781-3561-48cb-9f63-cfb4f3246434": [
+                {
+                    "document_id": "dbe5a781-3561-48cb-9f63-cfb4f3246434",
+                    "text": "The GeneNetwork database provides open access\nto BXD and other RI strain derived microarray data, single nucleotide polymorphism (SNP) data,\nand phenotypic data for quantitative trait loci analysis and gene expression correlation analyses. Gene expression data were exported for manually selected probes in the PDNN hippocampus\ndatabase (Hippocampus Consortium M430v2), and the PDNN whole brain database (INIA Brain\nmRNA M430). The Hippocampus database was chosen as one of the most elaborate brain databases,\nas well as most highly recommended dataset on GeneNetwork itself (http://www.genenetwork.org/\nwebqtl/main.py?FormID=sharinginfo&GN_AccessionId=112)."
+                }
+            ],
+            "f041550e-5f2d-430e-8f46-15ebea6ca496": [
+                {
+                    "document_id": "f041550e-5f2d-430e-8f46-15ebea6ca496",
+                    "text": "2016) and can\nalso be accessed in GeneNetwork by entering Record ID 18494 in the Get Any\nspace on the Search page and clicking on the Search button. Alternatively, enter\ndata by hand into the designated boxes provided by GeneNetwork. These latter\noptions also allow for the inclusion of trait variance. It is a good idea to name\nthe trait in the box provided. Then click Next, and manually enter the data for\neach RI strain, F1, and founder strain. 3\n\nAuthor Manuscript\n\nAfter entering the data, click on the blue plus sign button called Add."
+                },
+                {
+                    "document_id": "f041550e-5f2d-430e-8f46-15ebea6ca496",
+                    "text": "To submit multiple phenotypes at the same\ntime, select the option for Batch Submission under the Home tab. This allows\nusers to submit up to 100 traits for analysis by GeneNetwork. Here, select BXD\nas the cross or RI set to analyze from the first pull-down menu. The phenotype\nfile should follow the format described in the Sample text (http://\ngenenetwork.org/sample.txt). After uploading the appropriate file using the\nBrowse button, enter a name for the file in the Dataset space. The data will be\nstored in the GeneNetwork server for 24 hours. Click Next."
+                },
+                {
+                    "document_id": "f041550e-5f2d-430e-8f46-15ebea6ca496",
+                    "text": "Author Manuscript\n\nMaterials\nHere we will provide detailed instructions for using GeneNetwork along with some\n“worked” examples taken from the recent study of intravenous cocaine self-administration\nby Dickson et al. (2016) in BXD RI mice. A complete overview of GeneNetwork is beyond\nthe scope of this protocol, but is extensively covered in elsewhere (see Mulligan et al. 2016;\nWilliams & Mulligan 2012 for excellent reviews on GeneNetwork). A computer with an internet connection and current web browser. See the GeneNetwork.org\nsite for information on supported browser versions. Author Manuscript\n\nMethod\nEntering Data\n\nAuthor Manuscript\n\n1\n\nLink to http://www.genenetwork.org."
+                }
+            ],
+            "f2b8524b-501d-4ec7-a3d7-048aab67ce05": [
+                {
+                    "document_id": "f2b8524b-501d-4ec7-a3d7-048aab67ce05",
+                    "text": "\n\nSpecies in GenAge model organisms"
+                }
+            ],
+            "f9b2eeba-5f93-49c1-8828-311f0797d9e3": [
+                {
+                    "document_id": "f9b2eeba-5f93-49c1-8828-311f0797d9e3",
+                    "text": "Data are reviewed before entry in\nGeneNetwork by the senior author. Phenotypes are currently split into 15 broad\nphenotypic categories (Supplementary Data 1). Phenome curation and description\nwas initiated by R.W.W. and Dr Elissa Chesler in 2002 by literature review and data\nextraction. The early work is described brieﬂy in Chesler et al.51,52. Most work over\nthe past 5 years has been performed by two of the coauthors (R.W.W. and\nM.K.M.). We have used a controlled vocabulary and set of rules described here\n(http://www.genenetwork.org/faq.html#Q-22)."
+                }
+            ],
+            "fa8bba46-ce94-439a-a676-35187a3abcbf": [
+                {
+                    "document_id": "fa8bba46-ce94-439a-a676-35187a3abcbf",
+                    "text": "9) To bring your data to GeneWeaver,\nclick on the GeneWeaver icon, making sure to be previously\nlogin to your GeneWeaver account. You will be brought to the\nGeneSet upload page with the Genes Uploaded and the\nGeneweaver Analysis Platform\n\n139\n\nFig. 5 Default settings at GeneNetwork.org are set to search “Mouse”, “Phenotypes”, from among the “BXD\nPublished Phenotypes” data set. Here the term nociception was searched for\n\nFig. 6 The search results page in GeneNetwork showing the 33 records retrieved from the phenotype search\nfor nociception."
+                },
+                {
+                    "document_id": "fa8bba46-ce94-439a-a676-35187a3abcbf",
+                    "text": "Users may also share their data with other users selectively,\nmake it public, or keep it restricted to a private account. Data can be\nimported by users, uploading their gene set data directly or exporting to GeneWeaver from within another online resource such as\nNeuro Informatics Framework (NIF) [8], Grappa [9], Mouse\nPhenome Database (MPD) [10] or GeneNetwork [11]. These datasets can then be added to your collection to be analyzed together\nwith other gene sets retrieved from the GeneWeaver database. To begin a GeneWeaver analysis a user must collect “GeneSets”\ntogether in a “Project”."
+                },
+                {
+                    "document_id": "fa8bba46-ce94-439a-a676-35187a3abcbf",
+                    "text": "Alternatively the spreadsheet can be saved as a .txt file\nand uploaded by clicking on “Switch to file upload.” Once\ncomplete click on upload GeneSet. 7. Once completed you are taken to the GeneSet detail page. If\nthere are errors in your uploaded data you can correct them by\nclicking on “Edit”. 8. Use the Add Selected to Project, and create a new project, e.g. “Chronic Cocaine”. 9. Now using the Search function populate this project with additional gene sets related to this study trying Queries such as\n“Cocaine Addiction”, “Chronic Cocaine”."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "FA1E32391509D1EEAEBB70D3014C444A",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "GeneNetwork",
+            "Record&ID&18494",
+            "Search&page",
+            "Add",
+            "Trait",
+            "RI&strain",
+            "F1",
+            "founder&strain",
+            "Batch&Submission",
+            "GeneWeaver",
+            "GeneSet",
+            "Project",
+            "Cocaine&Addiction",
+            "Chronic&Cocaine",
+            "Species",
+            "Mouse",
+            "BXD",
+            "HXB",
+            "Phenotypes",
+            "genotypes",
+            "mRNA",
+            "methylated&DNA",
+            "protein",
+            "metagenomic",
+            "metabolome"
+        ],
+        "metadata": [],
+        "question": "How can I add a new species to the GeneNetwork database?",
+        "subquestions": null,
+        "task_id": "FA1E32391509D1EEAEBB70D3014C444A",
+        "usage": {
+            "chatgpt": 5344,
+            "gpt-4": 3726,
+            "gpt-4-turbo-preview": 2725
+        },
+        "user_id": 2
+    },
+    "document_id": "FA1E32391509D1EEAEBB70D3014C444A",
+    "task_id": "FA1E32391509D1EEAEBB70D3014C444A"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_09.json b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_09.json
new file mode 100644
index 0000000..fc81f81
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_09.json
@@ -0,0 +1,142 @@
+{
+    "created_at": "2024-06-01T14:33:22.252190Z",
+    "data": {
+        "amplify": false,
+        "answer": "Mitochondrial DNA (mtDNA) is inherited solely from the maternal lineage, unlike nuclear DNA which requires both paternal and maternal contributions. This uniparental transmission of mtDNA is ensured by complex mechanisms that eliminate paternal mitochondria from sperm during fertilization. mtDNA also exhibits a higher mutation rate than nuclear DNA, leading to significant population-level mtDNA polymorphisms. These polymorphisms can be clustered into distinct haplogroups that represent major branch points on the mitochondrial phylogenetic tree. In contrast, nuclear DNA undergoes bi-parental recombination.",
+        "context": {
+            "0381d0d4-717f-470b-a8d4-562475cf58bb": [
+                {
+                    "document_id": "0381d0d4-717f-470b-a8d4-562475cf58bb",
+                    "text": "Oxidative stress and mitochondrial DNA\n\nNot long after it was discovered that mitochondria have their own genetic apparatus, Harman proposed that mitochondria play a central role in the free radical theory of aging [16].This idea was developed further by Miquel et al. [330], and the notion that mtDNA mutagenesis played a role in aging took hold.The phenotypical importance of mutations in mtDNA was demonstrated by Wallace et al. [331] and Holt et al. [332], who first showed that Leber's hereditary optic neuropathy and mitochondrial myopathies were caused by mtDNA mutations (reviewed in [333]).Because mtDNA is so close to the site of mitochondrial ROS production, it is exposed to considerably higher oxidative stress, resulting in 3-fold higher levels of DNA oxidative damage (the previously quoted 20-fold figure is apparently due to an isolation artifact [334,335]).In the 1990s a series of papers reported that the frequency of mitochondrial DNA deletions increases dramatically with age, being essentially undetectable in young individuals and reaching levels as high as 2% of mtDNA in old individuals.This age-related increase in mtDNA deletions was found in organisms as diverse as worms, mice, and humans (reviewed in [24,336]).The same is also true with mtDNA point mutations [337,338].Certain mtDNA polymorphisms have been found in increased frequency in centenarians, implying a protective effect during aging [339][340][341].Similar protective effects of mtDNA polymorphisms have been reported for the age-related neurodegenerative condition, Parkinson's disease [342]."
+                }
+            ],
+            "21d2cb60-92ab-4fbb-a3a1-85d3424881c1": [
+                {
+                    "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                    "text": "\n\nVariation in the structure and function of mitochondria underlies variation in organismal energetics broadly (Seebacher et al., 2010) and evidence for the importance of mitochondrial function in the evolution of natural populations continues to accumulate (Ballard and Melvin, 2010;Glanville et al., 2012;Hicks et al., 2012;Kurbalija Novičić et al., 2015).For example, variation in mitochondrial DNA sequences (mtDNA) can determine whole-organism metabolism, i.e., the rate at which organisms process energy from their environment, a phenomenon widespread across animal taxa (Arnqvist et al., 2010;Ballard et al., 2007;Ballard and Pichaud, 2014;Havird et al., 2019;Hood et al., 2018;James et al., 2016;Wolff et al., 2014).Specifically, mtDNA sequence variants are linked to functional metabolic differences in fish (Chapdelaine et al., 2020;Flight et al., 2011;Healy et al., 2019), birds (Scott et al., 2011), and mammals (Fontanillas et al., 2005), including humans (Amo and Brand, 2007;Dato et al., 2004;Niemi et al., 2003;Tranah et al., 2011).These mtDNA variants are often correlated with environmental factors such as temperature and altitude (Storz et al., 2010).However, other studies attempting to link mitochondrial function to mitochondrial DNA (mtDNA) sequence variation or environmental factors have offered mixed reports (Amo and Brand, 2007;Flight et al., 2011;Fontanillas et al., 2005;Hicks et al., 2012)."
+                },
+                {
+                    "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                    "text": "\n\nThe results here point to several potentially fruitful research directions.We have identified how nonsynonymous mutations in the mitochondrial genome associate with variation in whole-organism metabolism (including CytB, ND1, ND5 and ND6).A next step will be to characterize the molecular details of how these changes affect molecular function.It would also be beneficial to describe how variation in cellular oxygen consumption rate scales up to determine whole-organism metabolic rate across a range of temperatures, thus identifying potential mismatches across levels of organization that may impact organismal performance (Gangloff and Telemeco, 2018).While the interconnected processes that shape organismal and population-level responses to environmental variation do not lend themselves to simple narratives, and many molecular processes interact to produce the emergent ecotypic divergences at the phenotypic level, it is clear that the mitochondria play a central role even as that role may change across populations and ecological contexts (Fig. 1).Research within well-characterized natural systems, such as these garter snake populations, can offer illustrative case studies of how mitochondria respond to their environments, and thus impact physiological pathways and evolutionary patterns, creating variation in life histories and aging."
+                },
+                {
+                    "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                    "text": "\n\nDespite the complexities underlying observed variation in mitochondrial function, recent work has demonstrated examples of how evolution and plasticity in mitochondrial function across populations within a species can shape life histories.For example, evidence from Drosophila has demonstrated the effect of temperature on components of the ETC and has linked mtDNA variants to metabolic thermosensitivity (Pichaud et al., 2012), to differences in whole-organism metabolic rates (Kurbalija Novičić et al., 2015), and to fitness-related traits (Ballard et al., 2007;Pichaud et al., 2011;Pichaud et al., 2010).In general, studies in birds and mammals demonstrate that mitochondria of longer-lived species are more efficient in ATP production, produce less reactive oxygen species, and demonstrate increased antioxidant capacities (Barja and Herrero, 2000;Ku et al., 1993;Lambert et al., 2007).While some studies in lizards and snakes demonstrate a similar pattern (Olsson et al., 2008;Robert et al., 2007), the extent to which these results are generalizable across vertebrate taxa is not yet known.The diversity of life-history traits and immense variation in longevity demonstrated by reptiles, both within and among species, make these taxa ideal candidates for understanding how variation in mitochondrial physiology drives this variation in whole-organism traits (reviewed in Hoekstra et al., 2019).Such work has moved to the forefront with a recent focus on the ecological and evolutionary significance of aging processes in wild populations (reviewed in Nussey et al., 2013;Fletcher and Selman, 2015;Gaillard and Lemaître, 2020)."
+                },
+                {
+                    "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                    "text": "\n\nOver evolutionary time, differential mortality rates are a selective force in shaping genetic structure.This results in divergence of a variety of physiological networks that shape, ultimately, patterns of aging and longevity in different habitats (Monaghan et al., 2008;Stojković et al., 2017).Such selective pressures can have differential effects on the nuclear and mitochondrial genomes (McKenzie et al., 2019;Wolff et al., 2014).Genetic variation in the mitochondrial genome is known to drive mitochondrial function in many species (Ballard and Melvin, 2010;McKenzie et al., 2019;Novelletto et al., 2016) and we find this in our system as well.Whole organism metabolic rate varies with the mitochondrial genome haplogroups we identified in this study.T. elegans individuals with the introgressed T. sirtalis mitochondrial genome had the lowest metabolic rate and had 68 amino acid changes in the ETC genes relative to the T. elegans mitochondrial genomes.As species divergence are a continuation of population divergence, this introgression provides additional insight into how genetic variation can alter mitochondrial function.Whether the lower metabolic rate in our snakes with the introgressed mitochondrial genome is due to the fixed amino acid changes between the species or a mismatch between the coadapted nuclear and mitochondrially-encoded ETC proteins that could alter function of the mitochondria (Burton et al., 2013;Haenel, 2017;Rawson and Burton, 2002;Toews et al., 2014;Wolff et al., 2014) will require further comparisons to T. sirtalis individuals."
+                },
+                {
+                    "document_id": "21d2cb60-92ab-4fbb-a3a1-85d3424881c1",
+                    "text": "\n\nBuilding on previous work in this system, the current study tests three primary hypotheses about how variation in mtDNA and mitochondrial function relate to variation in life-history traits and aging within this system (Fig. 1): (1) First, we test whether rates of cellular oxygen consumption in isolated immune cells exhibit patterns that are consistent with the hypothesis that cellular processes drive whole-organism senescence and aging, and if these patterns differ between the SA and FA ecotypes and between sexes.By measuring basal, ATP-production associated, and maximal rates of cellular oxygen consumption, we further test for evidence that phenotypic divergence is dependent on a specific aspect of oxidative phosphorylation within immune cells.The energetics of these cells are particularly important given their essential role in modulating disease and infection, important factors contributing to senescence (Metcalf et al., 2019).We predict that SA snakes will maintain levels of cellular oxygen consumption across age, whereas the FA snakes will show a decline with age, especially in ATP-associated rates, possibly due to continual degradation of electron transport chain functionality from accumulating oxidative damage and reduced DNA repair mechanisms (Robert and Bronikowski, 2010;Schwartz and Bronikowski, 2013). ( 2) Second, we expand our mitochondrial genomics dataset to quantify mtDNA genetic structure across the landscape and test whether mtDNA haplotypes, and alleles at a nonsynonymous SNP in the Cytochrome B (CytB) gene correlate with aging ecotypes. (3) Third, we test the hypothesis that variation in mtDNA correlates with whole-organism variation in metabolic rates, suggesting a pathway linking mitochondrial genetic variation in mtDNA to whole-organism energetics.We first test whether different haplotypes differ in resting metabolic rate.Then, we test the effects of the nonsynonymous SNP in CytB on resting metabolic rate.The CytB gene encodes a component of complex III of the ETC, and was previously found to segregate between these life-history ecotypes (Schwartz et al., 2015).This SNP results in an amino acid substitution from isoleucine (aliphatic, hydrophobic) to threonine (hydrophilic) on a region that comes into close contact with a nuclear-encoded subunit (Schwartz et al., 2015).We combine previously published and new data on whole-organism resting metabolic rates (oxygen consumption) to test for the effects of this nonsynonymous mutation in three populations where we find heterogeneity at this nucleotide, thus allowing us to disentangle the effects of shared environment (population) from sequence variation (SNP).We predict that this SNP will correlate with variation in whole-organism metabolic rate, demonstrating a putatively adaptive difference between the derived and ancestral sequence.By utilizing this integrative data setfrom genes to organelles to whole organisms to populationsin a known life-history context, we are able to test hypotheses across levels of organization to provide a more complete picture of the complicated story of mitochondria and life history (Havird et al., 2019)."
+                }
+            ],
+            "253fad94-3be6-4362-b56f-f00c9c5705e6": [
+                {
+                    "document_id": "253fad94-3be6-4362-b56f-f00c9c5705e6",
+                    "text": "mtDNA Diversity\n\nUnlike the nuclear genome, which requires both paternal and maternal contributions, mtDNA is inherited solely from the maternal lineage.It is unclear what advantage a uniparental mtDNA transmission confers, but one possibility is to minimize the number of distinct genomes to maximize the efficiency of a multi-genomic system (Hill et al. 2019).In fact, humans have developed complex, redundant mechanisms to ensure uniparental inheritance of mtDNA (DeLuca and O'Farrell 2012; Rojansky et al. 2016).Paternal mitochondria from sperms that enter into the egg during fertilization are actively and selectively eliminated via mitophagy through two E3 ligases, PARKIN, and MUL1 (Rojansky et al. 2016).PARKIN and MUL1 serve redundant purposes, and mitophagy becomes insufficient to eliminate paternal mtDNA only in the absence of both (Rojansky et al. 2016).Even though oocytes have  at least a thousand-fold more mitochondria than a sperm cell (Rojansky et al. 2016) and heteroplasmy levels would be very low if paternal mtDNA were to contaminate the embryo, the results can still be non-trivial.However, challenging this notion, a recent study provides evidence of potential paternal transmission (Luo et al. 2018), but awaits further corroborating studies (Lutz-Bonengel and Parson 2019)."
+                },
+                {
+                    "document_id": "253fad94-3be6-4362-b56f-f00c9c5705e6",
+                    "text": "\n\nMtDNA exhibit a higher mutation rate than nuclear DNA, leading to significant population-level mtDNA polymorphisms (van Oven and Kayser 2009; Wallace 1999; Wallace and Chalkia 2013).In fact, the co-evolution of the mitonuclear genomes has been proposed to be driven by mtDNA mutations that select for compensatory changes in the nuclear genome (Havird and Sloan 2016).Populations that share similar mtDNA polymorphisms can be clustered into distinct haplogroups that are designated using all letters of the alphabet (i.e., A through Z).The mtDNA haplogroups represent major branch points on the mitochondrial phylogenetic tree that have strong regional ties around the globe, thus supporting the concept of a 'mitochondrial eve' (Wallace 1999).Haplogroups present inherently different mitonuclear interactions (Zaidi and Makova 2019), which eventually affect the aging process (Wolff et al. 2016).For example, one haplogroup commonly found in Ashkenazi Jews can interact with a specific enrichment of an amino acid sequence in complex I, and result in altered susceptibility to type 2 diabetes mellitus (Gershoni et al. 2014).The effect of mitonuclear compatibility on lifespan is influenced by environmental cues in flies (Drummond et al. 2019).It is unclear if mitonuclear compatibility is invariable throughout an organism's life, or antagonistically pleiotropic during aging, making it a difficult moving target to understand."
+                }
+            ],
+            "2f39f55f-2604-49d4-9589-0e1403b84d7a": [
+                {
+                    "document_id": "2f39f55f-2604-49d4-9589-0e1403b84d7a",
+                    "text": "\n\nBackground: The accumulation of mitochondrial DNA (mtDNA) mutations, and the reduction of mtDNA copy number, both disrupt mitochondrial energetics, and may contribute to aging and age-associated phenotypes.However, there are few genetic and epidemiological studies on the spectra of blood mtDNA heteroplasmies, and the distribution of mtDNA copy numbers in different age groups and their impact on age-related phenotypes.In this work, we used whole-genome sequencing data of isolated peripheral blood mononuclear cells (PBMCs) from the UK10K project to investigate in parallel mtDNA heteroplasmy and copy number in 1511 women, between 17 and 85 years old, recruited in the TwinsUK cohorts."
+                }
+            ],
+            "4a17ce5c-55df-4aa0-a664-f6a03238d332": [
+                {
+                    "document_id": "4a17ce5c-55df-4aa0-a664-f6a03238d332",
+                    "text": "Discussion\n\nTwo significant questions are raised by the findings that mitochondrial DNA can integrate into the nucleus.Firstly, is this an extraordinarily rare event or is it occurring continually and at high frequency?Secondly, can such an event have pathological consequences to the organism?"
+                }
+            ],
+            "4f010a74-a9b4-4538-94f7-ae8f35c8b96e": [
+                {
+                    "document_id": "4f010a74-a9b4-4538-94f7-ae8f35c8b96e",
+                    "text": "Phylogeny\n\nThe mtDNA is maternally inherited (120) by offspring through the oocyte cytoplasm; namely, the mother transmits her mtDNAs to all of her offspring, and her daughters transmit their mtDNAs to the next generation.This is the consequence of the fact that the mature oocyte such as mouse (304) or bovine (144) contains lOO-1,000 times more mtDNA than is found in somatic cells.Hence, the few sperm mtDNAs that enter the egg (130) have little effect on the genotype.The maternal inheritance results in sequentially diverged mtDNA polymorphism of modern human, as shown in Figure 2. The polymorphism derives from the combinations of small deletions and additions of <14 bp in noncoding region and base substitutions including some point mutations in coding region."
+                },
+                {
+                    "document_id": "4f010a74-a9b4-4538-94f7-ae8f35c8b96e",
+                    "text": "\n\nThere have been few reports on distinct correlation between mitochondrial morphology and human aging, except changes in number and size of mitochondria associated with age.Concerning the gross structure of mitochondria, the overwhelming importance of the cell nucleus in mitochondrial biogenesis should be noted, because the major parts of mitochondrial proteins are encoded by nuclear genes that are stable during life with the efficient repair mechanism for nDNA."
+                },
+                {
+                    "document_id": "4f010a74-a9b4-4538-94f7-ae8f35c8b96e",
+                    "text": "\n\nEarly data on DNA polymorphism detected by restriction endonuclease (263) have suggested that the evolutionary change of mtDNA in higher animals occurs mainly by nucleotide substitution rather than by deletion and insertion.The mtDNA nucleotide sequence evolves 6-17 times faster than comparable nuclear DNA gene sequences (51,52,405).Rapid evolution of mtDNA of higher primates including human, 0.02 base substitutions per site per million years, was calculated from the restriction map of mtDNA (51).Because orthodox recombination mechanism appears to be absent in mtDNA (128), germline mutation seems to go down to posterity as maternal inheritance from our common ancestor (57)."
+                }
+            ],
+            "612a70c6-2f42-492f-9f23-0d5e9296919e": [
+                {
+                    "document_id": "612a70c6-2f42-492f-9f23-0d5e9296919e",
+                    "text": "\n\nA number of conclusions may be drawn from these results.Firstly, the data begin to answer the question of how closely mtDNA replication is kept in synchrony with nuclear DNA replication: it would appear to be regulated not by direct coupling to the nuclear DNA replication, but rather by the cell mass to be serviced by mitochondria."
+                }
+            ],
+            "65c8287b-eb19-437a-b9ca-5aaa8664d429": [
+                {
+                    "document_id": "65c8287b-eb19-437a-b9ca-5aaa8664d429",
+                    "text": "\n\nIt may be that high mtDNA levels are indeed indicative of compromised mitochondria, but that the underlying defects are unrelated to alterations in the DNA sequence.Alternatively, elevated quantities of mtDNA might be associated with increased metabolic requirements of the embryo, rather than organelles of suboptimal function.It is possible that embryos produced by older oocytes are under some form of stress and therefore have larger energy requirements.Functional experiments will be required to address these questions.Whatever the underlying basis, the current study has unequivocally demonstrated that female reproductive aging is associated with changes in the mtDNA content at the blastocyst stage."
+                }
+            ],
+            "67ec2631-aa17-436e-800b-1bc046fb5b19": [
+                {
+                    "document_id": "67ec2631-aa17-436e-800b-1bc046fb5b19",
+                    "text": "\n\nAge-associated alterations of the mitochondrial genome occur in several different species; however, their physiological relevance remains unclear.The age-associated changes of mitochondrial DNA (mtDNA) include nucleotide point mutations and modifications, as well as deletions.In this review, we summarize the current literature on age-associated mtDNA mutations and deletions and comment on their abundance.A clear need exists for a more thorough evaluation of the total damage to the mitochondrial genome that accumulates in aged tissues.᭧ 1997 Elsevier Science Inc."
+                }
+            ],
+            "8a9fe1bc-7fa3-40ee-ade0-9a498bcf9def": [
+                {
+                    "document_id": "8a9fe1bc-7fa3-40ee-ade0-9a498bcf9def",
+                    "text": "Mitochondrial genetics\n\nOne underexplored avenue for determining maternal risk for preterm birth involves the influence of the mitochondrial genome.The high mutation rate of mito chondrial DNA (mtDNA), together with the fact that most of its encoded proteins are evolutionarily con served, allowing for the selection of neutral or beneficial variants, has generated interest in defining human mtDNA variations and their roles in human biology [58]."
+                }
+            ],
+            "aa942230-9a43-4b5f-90d9-96d364861a57": [
+                {
+                    "document_id": "aa942230-9a43-4b5f-90d9-96d364861a57",
+                    "text": "\n\nClearly, as mitochondrial metabolic and genetic therapies advance for treating mitochondrial disease, they will also be available to enhance the personal lives of others.However, mitochondrial genetic variation appears to have been one of the primary factors that permitted our ancestors to adapt to new environments, survive adverse conditions, and multiple throughout the globe.Is it possible that by taking over control of individual mtDNA variation, we might also be setting our species on the road to functional decline and ultimately extinction?"
+                },
+                {
+                    "document_id": "aa942230-9a43-4b5f-90d9-96d364861a57",
+                    "text": "Mitochondrial therapeutics and performance enhancement\n\nIt is now clear that not all mtDNA variation is deleterious.Indeed, about 25% of all ancient mtDNA variation appears to have caused functional mitochondrial changes and thus been adaptive.Those mtDNA variants that are adapted to warm climates have mtDNA variants that result in tightly coupled OXPHOS, thus maximizing ATP output and minimizing heat production.The presence of these mtDNAs permits maximum muscle performance but also predispose sedentary individuals that consume excess calories to multiple problems.They would be prone to be overweight and their mitochondria would generate excessive ROS, thus making them susceptible to a variety of degenerative diseases, cancer and premature aging.Partially uncoupled mitochondria generate more heat, but at the expense of ATP production.Individual's with these variants are better able to tolerate the cold, and are less prone to obesity.They also generate less ROS making then resistant to degenerative diseases and aging.Finally, the mitochondria are why we breathe.Hence, mitochondrial variation might be an important factor in individual predisposition to altitude sickness."
+                }
+            ],
+            "b0af29ac-0997-416d-907a-6caba940536d": [
+                {
+                    "document_id": "b0af29ac-0997-416d-907a-6caba940536d",
+                    "text": "\n\nHuman mtDNA codes for 13 essential polypeptide components of the mitochondrial oxidative phosphorylation (OXPHOS) system.mtDNA undergoes strict maternal inheritance, resulting in the absence of bi-parental recombination (Elson et al., 2001) and has a high mutation rate (Tuppen et al., 2010).As such, the evolution of mtDNA is characterised by the emergence of distinct lineages (or haplogroups) (Hernstadt et al., 2002).This results in high levels of mtDNA variation at the population level despite its rather small size, which is also illustrated by the large number of sub-haplogroups (van Oven and Kayser, 2009).Africa"
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "8CC70421A233A4B1F89A6701731F7017",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "mtDNA",
+            "mitochondrial&DNA",
+            "nuclear&DNA",
+            "heredity",
+            "haplogroups",
+            "mitochondrial&genome",
+            "oxidative&phosphorylation",
+            "OXPHOS",
+            "mutation&rate",
+            "mitophagy"
+        ],
+        "metadata": [],
+        "question": "Describe the role of mitochondrial DNA in heredity and how it differs from nuclear DNA.",
+        "subquestions": null,
+        "task_id": "8CC70421A233A4B1F89A6701731F7017",
+        "usage": {
+            "chatgpt": 9175,
+            "gpt-4": 5434,
+            "gpt-4-turbo-preview": 4489
+        },
+        "user_id": 2
+    },
+    "document_id": "8CC70421A233A4B1F89A6701731F7017",
+    "task_id": "8CC70421A233A4B1F89A6701731F7017"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_10.json b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_10.json
new file mode 100644
index 0000000..72e4a7a
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/experts/expert_general_10.json
@@ -0,0 +1,132 @@
+{
+    "created_at": "2024-06-01T14:34:54.821428Z",
+    "data": {
+        "amplify": false,
+        "answer": "Ensembl is a joint project between the EBI and the Wellcome Trust Sanger Institute. It is a publicly available web resource that contains automatically annotated genomes and integrates data from a wide range of biological research sources. Launched in 1999, the Ensembl database was the first to provide a window on the draft genome, curating the results of a series of computational analyses. It provides comprehensive information about the human genome including variants like SNPs, insertions, deletions, and somatic mutations for several species. Ensembl also offers tools for data retrieval and analysis.",
+        "context": {
+            "1a93e25f-2a43-49e9-8450-03a57c93e613": [
+                {
+                    "document_id": "1a93e25f-2a43-49e9-8450-03a57c93e613",
+                    "text": "Annotation, preprocessing and categorization of data\n\nWe used Ensembl (version 39) as the annotation reference database.Homology between human and mouse genes was derived via BioMart.The total number of genes under study comprises 15,277 Ensembl mouse genes representing the union of the homologue genes from all data sources.An overview about the T2DM specific datasets is given in Table 1."
+                }
+            ],
+            "5edf84d0-c2d9-45eb-91b9-c35743b6a463": [
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text": "But the four sites are not equivalent; there are important distinctions between them in terms of the data analysed, the analyses carried\nout and the way the results are displayed. 4.4.1 Ensembl\nEnsembl is a joint project between the EBI (http://www.ebi.ac.uk/) and the Wellcome\nTrust Sanger Institute (http://www.sanger.ac.uk/). The Ensembl database (Hubbard\net al. , 2002; http://www.ensembl.org/), launched in 1999, was the first to provide a\nwindow on the draft genome, curating the results of a series of computational analyses."
+                },
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text": "Until January 2002 (Release 3.26.1), Ensembl used the UCSC draft sequence\nassemblies as its starting point, but it is now based upon NCBI assemblies. The\nEnsembl analysis pipeline consists of a rule-based system designed to mimic decisions made by a human annotator. The idea is to identify ‘confirmed’ genes that are\ncomputationally predicted (by the GENSCAN gene prediction program) and also\nsupported by a significant BLAST match to one or more expressed sequences or\nproteins. Ensembl also identifies the positions of known human genes from public\nsequence database entries, usually using GENEWISE to predict their exon structures."
+                },
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text": "Data retrieval is extremely well catered for in Ensembl, with text searches of all\ndatabase entries, BLAST searches of all sequences archived, and the availability of bulk\ndownloads of all Ensembl data and even software source code. Ensembl annotation\ncan also be viewed interactively on one’s local machine with the Apollo viewer (Lewis\net al. , 2002; http://www.fruitfly.org/annot/apollo/). 4.4.2 The UCSC Human Genome Browser\nThe UCSC Human Genome Browser (UCSC) bears many similarities to Ensembl;\nit, too, provides annotation of the NCBI assemblies, and it displays a similar array of\nfeatures, including confirmed genes from Ensembl."
+                }
+            ],
+            "c12e853e-4f0d-48f9-93af-15db9ad2dfae": [
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "But the four sites are not equivalent; there are important distinctions between them in terms of the data analysed, the analyses carried\nout and the way the results are displayed. 4.4.1 Ensembl\nEnsembl is a joint project between the EBI (http://www.ebi.ac.uk/) and the Wellcome\nTrust Sanger Institute (http://www.sanger.ac.uk/). The Ensembl database (Hubbard\net al. , 2002; http://www.ensembl.org/), launched in 1999, was the first to provide a\nwindow on the draft genome, curating the results of a series of computational analyses."
+                },
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "Until January 2002 (Release 3.26.1), Ensembl used the UCSC draft sequence\nassemblies as its starting point, but it is now based upon NCBI assemblies. The\nEnsembl analysis pipeline consists of a rule-based system designed to mimic decisions made by a human annotator. The idea is to identify ‘confirmed’ genes that are\ncomputationally predicted (by the GENSCAN gene prediction program) and also\nsupported by a significant BLAST match to one or more expressed sequences or\nproteins. Ensembl also identifies the positions of known human genes from public\nsequence database entries, usually using GENEWISE to predict their exon structures."
+                },
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "Data retrieval is extremely well catered for in Ensembl, with text searches of all\ndatabase entries, BLAST searches of all sequences archived, and the availability of bulk\ndownloads of all Ensembl data and even software source code. Ensembl annotation\ncan also be viewed interactively on one’s local machine with the Apollo viewer (Lewis\net al. , 2002; http://www.fruitfly.org/annot/apollo/). 4.4.2 The UCSC Human Genome Browser\nThe UCSC Human Genome Browser (UCSC) bears many similarities to Ensembl;\nit, too, provides annotation of the NCBI assemblies, and it displays a similar array of\nfeatures, including confirmed genes from Ensembl."
+                },
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "Ensembl provides a DAS reference\nserver giving access to a wide range of specialist annotations of the human\ngenome (for more detail, see http://www.ensembl.org/das/). Data mining The ability to query very large databases in order to satisfy a\nhypothesis (‘top-down’ data mining), or to interrogate a database in order to\ngenerate new hypotheses based on rigorous statistical correlations (‘bottom-up’\ndata mining). Domain (protein) A region of special biological interest within a single protein\nsequence."
+                }
+            ],
+            "f35e02a1-3314-4663-913f-38a3fc072aa8": [
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text": "But the four sites are not equivalent; there are important distinctions between them in terms of the data analysed, the analyses carried\nout and the way the results are displayed. 4.4.1 Ensembl\nEnsembl is a joint project between the EBI (http://www.ebi.ac.uk/) and the Wellcome\nTrust Sanger Institute (http://www.sanger.ac.uk/). The Ensembl database (Hubbard\net al. , 2002; http://www.ensembl.org/), launched in 1999, was the first to provide a\nwindow on the draft genome, curating the results of a series of computational analyses."
+                },
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text": "Until January 2002 (Release 3.26.1), Ensembl used the UCSC draft sequence\nassemblies as its starting point, but it is now based upon NCBI assemblies. The\nEnsembl analysis pipeline consists of a rule-based system designed to mimic decisions made by a human annotator. The idea is to identify ‘confirmed’ genes that are\ncomputationally predicted (by the GENSCAN gene prediction program) and also\nsupported by a significant BLAST match to one or more expressed sequences or\nproteins. Ensembl also identifies the positions of known human genes from public\nsequence database entries, usually using GENEWISE to predict their exon structures."
+                },
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text": "Data retrieval is extremely well catered for in Ensembl, with text searches of all\ndatabase entries, BLAST searches of all sequences archived, and the availability of bulk\ndownloads of all Ensembl data and even software source code. Ensembl annotation\ncan also be viewed interactively on one’s local machine with the Apollo viewer (Lewis\net al. , 2002; http://www.fruitfly.org/annot/apollo/). 4.4.2 The UCSC Human Genome Browser\nThe UCSC Human Genome Browser (UCSC) bears many similarities to Ensembl;\nit, too, provides annotation of the NCBI assemblies, and it displays a similar array of\nfeatures, including confirmed genes from Ensembl."
+                },
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text": "Ensembl provides a DAS reference\nserver giving access to a wide range of specialist annotations of the human\ngenome (for more detail, see http://www.ensembl.org/das/). Data mining The ability to query very large databases in order to satisfy a\nhypothesis (‘top-down’ data mining), or to interrogate a database in order to\ngenerate new hypotheses based on rigorous statistical correlations (‘bottom-up’\ndata mining). Domain (protein) A region of special biological interest within a single protein\nsequence."
+                }
+            ],
+            "f7072d9b-4e07-4541-bac7-13a25761f460": [
+                {
+                    "document_id": "f7072d9b-4e07-4541-bac7-13a25761f460",
+                    "text": "Ensembl\n\nEnsembl is a publicly available web resource that contains automatically annotated genomes.It is integrated with other available biological databases like Jasper for binding motifs.It is a much larger web resource than T1Dbase, and contains general information about the human genome including variants.These include SNPs, insertions, deletions and somatic mutations (Alterations in DNA that occur after conception, meaning that they are not inherited) for several species.Data from Ensembl can be accessed in a number of ways.The names of all the SNPs that occur in the T1D susceptibility regions can be collected from Ensembl using the Biomart tool (Kinsella et al., 2011).To achieve this, the coordinates of the T1D regions obtained from T1Dbase are uploaded to the biomart query page which allows one to search the genome browser and retrieve data like the names, chromosomal positions, and genic positions (referred to as \"consequence to transcript\", in Ensembl) of the SNPs.The SNP genic positions tell if a SNP is located within a gene, adjacent to a gene or whether they occur in inter-genic positions between gene coding regions, as well as the particular genes in which they are located."
+                },
+                {
+                    "document_id": "f7072d9b-4e07-4541-bac7-13a25761f460",
+                    "text": "Advantages of Ensembl:\n\nThere is a number of advantages to using Ensembl. (i) It is a larger web resource than T1Dbase and integrates data from a wide range of biological research sources into its database.Therefore, available information is quite comprehensive. (ii) Genic positions for 99% of the variants obtained from T1Dbase could be retrieved. (iii) Ensembl contains quality checks for genetic variants in its variation pipeline.A variant is flagged as failed if certain quality criteria are not met, for instance if none of the variant alleles match the reference allele of the variant.Generally, Ensembl was found to give more detailed information regarding the genic positions of variants compared to T1Dbase."
+                },
+                {
+                    "document_id": "f7072d9b-4e07-4541-bac7-13a25761f460",
+                    "text": "\n\nInformation about genes, including gene names, chromosomal coordinates, biotype (coding or non-coding), and number of splice variants, can also be retrieved from Ensembl."
+                }
+            ],
+            "fa8bba46-ce94-439a-a676-35187a3abcbf": [
+                {
+                    "document_id": "fa8bba46-ce94-439a-a676-35187a3abcbf",
+                    "text": "doi:10.1093/nar/gkp858\nCunningham F, Amode MR, Barrell D, Beal K,\nBillis K, Brent S, Carvalho-Silva D, Clapham\nP, Coates G, Fitzgerald S, Gil L, Giron CG,\nGordon L, Hourlier T, Hunt SE, Janacek SH,\nJohnson N, Juettemann T, Kahari AK, Keenan\nS, Martin FJ, Maurel T, McLaren W, Murphy\nDN, Nag R, Overduin B, Parker A, Patricio\nM, Perry E, Pignatelli M, Riat HS, Sheppard\nD, Taylor K, Thormann A, Vullo A, Wilder\nSP, Zadissa A, Aken BL, Birney E, Harrow J,\nKinsella R, Muffato M, Ruffier M, Searle SM,\nSpudich G, Trevanion SJ, Yates A, Zerbino\nDR, Flicek P (2015) Ensembl 2015."
+                }
+            ],
+            "fca531d0-d45b-495f-a02c-fbd437617b20": [
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "But the four sites are not equivalent; there are important distinctions between them in terms of the data analysed, the analyses carried\nout and the way the results are displayed. 4.4.1 Ensembl\nEnsembl is a joint project between the EBI (http://www.ebi.ac.uk/) and the Wellcome\nTrust Sanger Institute (http://www.sanger.ac.uk/). The Ensembl database (Hubbard\net al. , 2002; http://www.ensembl.org/), launched in 1999, was the first to provide a\nwindow on the draft genome, curating the results of a series of computational analyses."
+                },
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "Until January 2002 (Release 3.26.1), Ensembl used the UCSC draft sequence\nassemblies as its starting point, but it is now based upon NCBI assemblies. The\nEnsembl analysis pipeline consists of a rule-based system designed to mimic decisions made by a human annotator. The idea is to identify ‘confirmed’ genes that are\ncomputationally predicted (by the GENSCAN gene prediction program) and also\nsupported by a significant BLAST match to one or more expressed sequences or\nproteins. Ensembl also identifies the positions of known human genes from public\nsequence database entries, usually using GENEWISE to predict their exon structures."
+                },
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "Data retrieval is extremely well catered for in Ensembl, with text searches of all\ndatabase entries, BLAST searches of all sequences archived, and the availability of bulk\ndownloads of all Ensembl data and even software source code. Ensembl annotation\ncan also be viewed interactively on one’s local machine with the Apollo viewer (Lewis\net al. , 2002; http://www.fruitfly.org/annot/apollo/). 4.4.2 The UCSC Human Genome Browser\nThe UCSC Human Genome Browser (UCSC) bears many similarities to Ensembl;\nit, too, provides annotation of the NCBI assemblies, and it displays a similar array of\nfeatures, including confirmed genes from Ensembl."
+                },
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "Ensembl provides a DAS reference\nserver giving access to a wide range of specialist annotations of the human\ngenome (for more detail, see http://www.ensembl.org/das/). Data mining The ability to query very large databases in order to satisfy a\nhypothesis (‘top-down’ data mining), or to interrogate a database in order to\ngenerate new hypotheses based on rigorous statistical correlations (‘bottom-up’\ndata mining). Domain (protein) A region of special biological interest within a single protein\nsequence."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "FB39925222D82C39F4BBAA833135ACA5",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "Ensembl",
+            "EBI",
+            "Wellcome&Trust&Sanger&Institute",
+            "genome",
+            "computational&analyses",
+            "T1Dbase",
+            "SNPs",
+            "Biomart",
+            "NCBI",
+            "GENSCAN"
+        ],
+        "metadata": [],
+        "question": "what is ensembl?",
+        "subquestions": null,
+        "task_id": "FB39925222D82C39F4BBAA833135ACA5",
+        "usage": {
+            "chatgpt": 5858,
+            "gpt-4": 3829,
+            "gpt-4-turbo-preview": 2871
+        },
+        "user_id": 2
+    },
+    "document_id": "FB39925222D82C39F4BBAA833135ACA5",
+    "task_id": "FB39925222D82C39F4BBAA833135ACA5"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/gen_resp01.json b/gnqa/paper1_eval/src/data/responses/general/gen_resp01.json
new file mode 100644
index 0000000..49d5475
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/gen_resp01.json
@@ -0,0 +1,136 @@
+{
+    "created_at": "2024-04-01T11:43:32.011648Z",
+    "data": {
+        "amplify": false,
+        "answer": "Air pollution is the most cited environmental factor for the onset of asthma.",
+        "context": {
+            "0df24827-df9f-46ee-a43d-dc5465c62f0d": [
+                {
+                    "document_id": "0df24827-df9f-46ee-a43d-dc5465c62f0d",
+                    "text": "INTRODUCTION\n\nAsthma is a chronic disease of the airways defined by its symptoms, which include reversible airflow obstruction, inflammation, and bronchial hyperresponsiveness.The ancient Egyptians, Greeks, and Romans made reference to the symptoms of asthma, and today the disease is estimated to affect 235-334 million people worldwide (44,53)."
+                },
+                {
+                    "document_id": "0df24827-df9f-46ee-a43d-dc5465c62f0d",
+                    "text": "\n\nThe atopic triad.Perhaps the most widely recognized pattern of co-occurrence is the one of asthma, atopic dermatitis (eczema), and allergic rhinitis (hay fever), which together are referred to as the atopic triad and characteristically present clinically in a temporal sequence known as the atopic march.Within this sequence, atopic dermatitis is typically the first component to manifest, with approximately 20-30% of individuals with mild disease and 70% of those with severe disease going on to develop asthma.Individuals who undergo this distinctive sequence of disease progression frequently exhibit a more severe and persistent phenotype, with increased risk of allergen sensitization."
+                }
+            ],
+            "14cad5a7-e53a-4ab8-9d4f-8f0b827ae427": [
+                {
+                    "document_id": "14cad5a7-e53a-4ab8-9d4f-8f0b827ae427",
+                    "text": "\n\nClinically, asthma is characterized by episodes of coughing, chest tightness, wheezing, dyspnea, or sputum production.Often, asthma sufferers experience a combination of these symptoms, or some symptoms more than others.Pulmonary breathing tests typically demonstrate variable airway obstruction and hyperreactivity, but may be normal, even in patients with severe and uncontrolled disease [8].Thus, the diagnosis of asthma, which is based on general clinical symptoms and variable lung function testing, is non-specific and heavily dependent on clinical history.Within the \"umbrella\" diagnosis of asthma there exists a diverse array of differing clinical phenotypes [9].For example, childhood asthma is often associated with personal and parental atopic diseases (i.e., atopic dermatitis, food allergy, eosinophilic esophagitis, allergic rhinitis), viral infections, and tobacco smoke exposure [10].Alternatively, adult-onset asthma is less associated with atopic disease [11,12], but more associated with female sex [13], sinus disease [14], and preceding respiratory infections such as pneumonia [15].In addition, adult-onset disease is often of higher severity [12,16] with a faster and more persistent decline in lung function [17].Moreover, although severe patients are found in every demographic and age group, the most common phenotype is an adult female that is older and obese [18]."
+                },
+                {
+                    "document_id": "14cad5a7-e53a-4ab8-9d4f-8f0b827ae427",
+                    "text": "Introduction\n\nAn estimated 9% of children and 6% of adults in the United States have asthma [1].The total number of asthma sufferers worldwide is estimated to be over 300 million, with an additional 100 million expected to develop asthma by 2025 [2][3][4][5].Developed countries are the most affected, with some of the highest rates found in the United Kingdom, Australia, New Zealand and the Republic of Ireland [3].Asthma prevalence is rising significantly in developing countries in transition to a more Western lifestyle [3].In 2007, the cost of disease in the United States was estimated to be $56 billion in relation to medical expenses, missed days of work, and early deaths [1].The rate of asthma deaths has likely plateaued, but is still as high as 250,000 per year worldwide [6].Morbidity and mortality are particularly high in ethnic minorities living below or near the poverty line, and African American children had a death rate 10 times that of non-Hispanic white children in 2015 [7].Thus, asthma is a costly, growing health problem associated with high morbidity and mortality."
+                }
+            ],
+            "2a7da18e-3756-45c5-b18c-a2231685fefd": [
+                {
+                    "document_id": "2a7da18e-3756-45c5-b18c-a2231685fefd",
+                    "text": "Getting accurate estimates\nof exposures is difficult, whether this is air pollution or toxins in our food and\ndrink, but these are important questions. Rutter: That is an important point. From the twin study data it is clear that\nenvironmental effects account for quite a lot of the variance on all the multifactorial disorders. Yet the kinds of measures that are used aren’t terribly solid. They\ninclude broad thing such as socio-economic status (SES). Even where there are\ngood measures the care taken in testing for environmental mediation is usually\npoor."
+                },
+                {
+                    "document_id": "2a7da18e-3756-45c5-b18c-a2231685fefd",
+                    "text": "Bronchiolitis, a disease\nthat happens in the first year of life in many infants, is strongly associated with\nsubsequent asthma. We ascertained it in the first years of life and have been following these people to age 25 now. For the people who had bronchiolitis and now\nhave asthma, their parents recall much better that they had bronchiolitis than those\nwho don’t have asthma now. It is at least twice more. Extraordinarily, some of\nthese latter parents don’t recall that they took their child to the doctor in the fi rst\nyear of life."
+                },
+                {
+                    "document_id": "2a7da18e-3756-45c5-b18c-a2231685fefd",
+                    "text": "If you arrive in the USA when\nyou are young you have almost the same prevalence of asthma as an adult as those\nwho are born in the USA and who are not Mexican. But if you arrive at older ages\nyou have less asthma. If you arrive at the age of 20 you have the same asthma risk\nas those born in Mexico (Eldeirawi et al 2005). Kotb: This is extremely interesting. There is a relationship between depression\nand the immune system. This especially applies to natural killer (NK) cells, which\nare the main cells that fight cancers."
+                },
+                {
+                    "document_id": "2a7da18e-3756-45c5-b18c-a2231685fefd",
+                    "text": "A colleague of mine in\nGeorgia found this may have a protective effect against later development of\nasthma (Ownby et al 2002). Martinez: We find significantly decreased likelihood of asthma if you have a dog\nin a home, but not if you have a cat. The reason for this is not that I hate cats,\nwhich I do, but most likely because cats are stealth hunters, and they have to be\nvery clean. Dogs are collective hunters and they don’t care if they smell."
+                }
+            ],
+            "443efea1-ffe7-446e-b2fb-37d8ec3cb74a": [
+                {
+                    "document_id": "443efea1-ffe7-446e-b2fb-37d8ec3cb74a",
+                    "text": "; Guffey, S.E. Investigation into pedestrian exposure to near-vehicle exhaust emissions. Environ. Health\n2009, 8, 13. [CrossRef] [PubMed]\nOur World in Data.org. 2017. Available online: https://ourworldindata.org/data-review-air-pollution-deaths (accessed on\n10 January 2022). Pope, C.A. , III. Respiratory disease associated with community air pollution and a steel mill, Utah Valley. Am. J. Public Health\n1989, 79, 623–628. [CrossRef] [PubMed]\nPope, C.A. , III. What do epidemiologic findings tell us about the health effects of environmental aerosols? J. Aerosol. Med. 2000,\n13, 335–354. [CrossRef] [PubMed]\nPope, C.A. , III."
+                }
+            ],
+            "58714c13-954b-46b3-bd0e-69ccadd9dc6a": [
+                {
+                    "document_id": "58714c13-954b-46b3-bd0e-69ccadd9dc6a",
+                    "text": "Case for Support BBSRC Grant Application September 2005\n“Integrative Analysis of the Genetic Factors behind Asthma and Atopic Dermatitis”\n\nPart I: Research Proposal\nBackground\nA\nIntroduction of topic of research and its academic and wider context\nAsthma is the most common disease of childhood, and affects one child in seven in the United\nKingdom. Atopic Dermatitis (AD, eczema) affects similar numbers of children. About 60% of children with\nsevere AD will have concomitant asthma. Treatments for both diseases are unsatisfactory. Abandonment of\northodox medical therapy for AD is common in many families who have children with the disease."
+                }
+            ],
+            "8b4276be-c77e-4e80-a5bb-54e9ff75d2ba": [
+                {
+                    "document_id": "8b4276be-c77e-4e80-a5bb-54e9ff75d2ba",
+                    "text": "This is most common during the rainy\nseason when aerosols are created, which results in repeated inhalation of Bp [43, 44]. Environmental sampling studies reveal there is a positive association between the\nprevalence of disease and the degree of environmental contamination [7]. In addition to\nenvironmental factors, data suggests that host factors play an important role in mounting\nan immune response against infectious diseases [45] such as melioidosis. While healthy\npersons can contract melioidosis, most patients in endemic regions have an underlying\npredisposition [28], which suggests that the immunological status of the patient can\ninfluence disease initiation and progression [15]."
+                }
+            ],
+            "98d443c7-8d99-4139-a27d-e447b0f6630f": [
+                {
+                    "document_id": "98d443c7-8d99-4139-a27d-e447b0f6630f",
+                    "text": "Sensitivity analysis\n\nWe did two sets of post-hoc sensitivity analyses to assess the effects of potential poor recall of age of onset among individuals with adult-onset asthma, and the effects of misclassification of COPD as asthma among the adultonset cases, even with exclusion of cases with a reported diagnosis of COPD, emphysema, or chronic bronchitis.First, to assure that the adult-onset cases did not include a significant proportion of childhood-onset asthma in which symptoms remitted in early life but then relapsed in adulthood, we replaced adult-onset cases with increasing proportions of randomly selected childhood-onset cases, and then tested for association at the two most significant childhood onset-specific loci.This procedure was repeated 20 times for each proportion to quantify the sampling variability (appendix pp 7-8).Second, we did two analyses in which we removed either individuals with ages of asthma onset between 46 and 65 years or adult-onset cases and controls with FEV₁/FVC <0•70.For each, we compared p values and ORs with the GWAS including all adult-onset cases (appendix pp 8-9)."
+                },
+                {
+                    "document_id": "98d443c7-8d99-4139-a27d-e447b0f6630f",
+                    "text": "\n\nWe used data for British white individuals from UK Biobank data release July 19, 2017. 8We extracted disease status (asthma, allergic rhinitis, atopic dermatitis, food allergy, chronic obstructive pulmonary disease (COPD), emphysema, and chronic bronchitis), age of on set of asthma, and sex from self-reported question naires and hospital records (International Classification of Diseases 10th revision [ICD-10] codes) by querying our in-house protected UK Biobank database server. 9For our main case analysis, we included individuals who self-reported that they had doctor-diagnosed asthma.Further details of our research approach are provided in the appendix (pp 4-7)."
+                }
+            ],
+            "a1c91fbe-9f6c-45fe-af9a-46c162d340ed": [
+                {
+                    "document_id": "a1c91fbe-9f6c-45fe-af9a-46c162d340ed",
+                    "text": "; Guffey, S.E. Investigation into pedestrian exposure to near-vehicle exhaust emissions. Environ. Health\n2009, 8, 13. [CrossRef] [PubMed]\nOur World in Data.org. 2017. Available online: https://ourworldindata.org/data-review-air-pollution-deaths (accessed on\n10 January 2022). Pope, C.A. , III. Respiratory disease associated with community air pollution and a steel mill, Utah Valley. Am. J. Public Health\n1989, 79, 623–628. [CrossRef] [PubMed]\nPope, C.A. , III. What do epidemiologic findings tell us about the health effects of environmental aerosols? J. Aerosol. Med. 2000,\n13, 335–354. [CrossRef] [PubMed]\nPope, C.A. , III."
+                }
+            ],
+            "c449650e-a0ac-4023-b3c8-82cf3463b0f3": [
+                {
+                    "document_id": "c449650e-a0ac-4023-b3c8-82cf3463b0f3",
+                    "text": "8 The\nsocio-ecologic framework posits that various aspects of a child’s environment directly and indirectly impact the\nchild’s health and development.9 Drawing on this framework, Beck and colleagues10 examined several biologic,\nsocial and ecologic variables to provide a greater understanding of factors influencing asthma-related hospital\nreadmissions for black children compared to their white counterparts. The study revealed that black children\nwere over two times as likely to be readmitted for an asthma-related illness compared to white children; this\nresulted from significant differences in almost every socio-ecologic variable measured, including disease\nmanagement practices and access to primary care."
+                },
+                {
+                    "document_id": "c449650e-a0ac-4023-b3c8-82cf3463b0f3",
+                    "text": "Specific Aims\nAsthma is the most common chronic pediatric medical condition in the United States, with a prevalence\nover 9.6% in children under 18 years of age.1, 2 Low-income, urban children incur a disproportionate share of\nasthma prevalence and morbidity;2-4 13% of children living below the poverty threshold are diagnosed with\nasthma compared to 8% of non-poor (>200% poverty),3 and poverty is associated with higher rates of asthma\nattacks.1 Living in an urban area confers additional risk for asthma and increased ED utilization.4, 5\nImplementation of the National Asthma Education and Prevention Program’s (NAEPP) Guidelines has\ncontributed to reductions in asthma morbidity and mortality rates, and these guidelines emphasize establishing\na partnership between healthcare providers and patients/families to promote effective asthma management.6\nThe NAEPP expert panel states, “building a partnership requires that clinicians promote open\ncommunication and ensure that patients have a basic and accurate foundation of knowledge about asthma…”\n(p.124),6 yet care partnerships also require that the patient/parent effectively communicate issues such as\nemerging symptoms or response to medications."
+                },
+                {
+                    "document_id": "c449650e-a0ac-4023-b3c8-82cf3463b0f3",
+                    "text": "Vital & health statistics Series 3, Analytical and epidemiological studies. 2012(35):1-58. CDC. Current Asthma Prevalence. https://www.cdc.gov/asthma/most_recent_data.htm. 2015. Updated\nJune 2017. Accessed March 9, 2018. Northridge J, Ramirez OF, Stingone JA, Claudio L. The role of housing type and housing quality in\nurban children with asthma. Journal of urban health : bulletin of the New York Academy of Medicine. 2010;87(2):211-224. Flores G, Snowden-Bridon C, Torres S, et al. Urban minority children with asthma: substantial\nmorbidity, compromised quality and access to specialists, and the importance of poverty and specialty\ncare."
+                },
+                {
+                    "document_id": "c449650e-a0ac-4023-b3c8-82cf3463b0f3",
+                    "text": "Asthma Prevalence and Disparities\nAsthma is the most common chronic pediatric medical condition in the United States,1 affecting an\nestimated 6.2 million children annually.2 Poorly controlled pediatric asthma contributes to over 700,000 visits a\nyear to emergency departments (ED).1 Children living in impoverished, urban settings are disproportionately\naffected by asthma,3 and the disparate impact of asthma is even worse among black and Latino children, and\nchildren whose parents have limited English proficiency (LEP) in these urban low-income areas.4-6 A 2017\nlongitudinal study revealed that black race and Latino ethnicity are significantly associated with worse asthma\noutcomes including 1) asthma knowledge, 2) asthma-related quality of life, 3) asthma severity, and\n4) asthma control."
+                },
+                {
+                    "document_id": "c449650e-a0ac-4023-b3c8-82cf3463b0f3",
+                    "text": "The Journal of asthma : official journal of the Association for the Care of Asthma. 2017:16. Inkelas M, Garro N, McQuaid EL, Ortega AN. Race/ethnicity, language, and asthma care: findings from\na 4-state survey. Annals of allergy, asthma & immunology : official publication of the American College\nof Allergy, Asthma, & Immunology. 2008;100(2):120-127. National Asthma Education and Prevention Program. Expert Panel Report 3: Guidelines for the\nDiagnosis and Management of Asthma Bethesda, MD: National Institutes of Health, National Heart,\nLung, and Blood Institute; 2007. Publication no. 08-045.1. NIH Consensus Group. Video report: What is mHealth?"
+                },
+                {
+                    "document_id": "c449650e-a0ac-4023-b3c8-82cf3463b0f3",
+                    "text": "Contact PD/PI: Coker, Tumaini Rucker\n\nINTRODUCTION TO APPLICATION\nResearch Plan Overview\nChildhood asthma is the most common pediatric medical condition in the United States, and\ndisproportionately affects children living in low-income, urban settings. Many low-income, urban families rely on\nemergency department (ED) services as their source for sick care for their child. This is often due to not having\na primary care provider or sufficient access to their primary care provider for asthma management."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "1BB877C826E934EA87131E2F63B68EEC",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "asthma",
+            "environmental&factors",
+            "urban",
+            "poverty",
+            "air&pollution",
+            "atopic&dermatitis",
+            "allergic&rhinitis",
+            "bronchiolitis",
+            "socio-economic&status",
+            "dogs"
+        ],
+        "metadata": [],
+        "question": "What is the most cited environmental factor for the onset of asthma.",
+        "subquestions": null,
+        "task_id": "1BB877C826E934EA87131E2F63B68EEC",
+        "usage": {
+            "chatgpt": 6004,
+            "gpt-4": 4357,
+            "gpt-4-turbo-preview": 3350
+        },
+        "user_id": 2
+    },
+    "document_id": "1BB877C826E934EA87131E2F63B68EEC",
+    "task_id": "1BB877C826E934EA87131E2F63B68EEC"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/gen_resp02.json b/gnqa/paper1_eval/src/data/responses/general/gen_resp02.json
new file mode 100644
index 0000000..20982f0
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/gen_resp02.json
@@ -0,0 +1,152 @@
+{
+    "created_at": "2024-04-01T11:57:23.158088Z",
+    "data": {
+        "amplify": false,
+        "answer": "Apoptosis, also known as cell suicide or programmed cell death, is a biological process in multicellular organisms that allows specific cells to be removed during the development of complex tissues, or potentially dangerous damaged cells to be destroyed for the benefit of the whole organism. It is characterized by a sequence of well-defined events resulting in cell destruction and is necessary for normal cell turnover. It is also essential to various other biological processes.",
+        "context": {
+            "05346fc4-57eb-424f-8c9f-cc144e600cb6": [
+                {
+                    "document_id": "05346fc4-57eb-424f-8c9f-cc144e600cb6",
+                    "text": "\n\nApoptosis, or controlled cell death [62], is another major stressed-cell response, and was also represented in our results (Fig. 9e).A large body of direct evidence points to apoptosis as one of the main routes of RPE degeneration in AMD [63].Induction of apoptosis upon stress is dictated by the action of master regulator p53, and it was recently shown that aging increases the activity of p53 in RPE cells and the likelihood for apoptotic cell death [64].Consistent with this evidence, we found association with pathways in Transcriptional regulation by TP53 group (Fig. 9d).In particular, Regulation of TP53 activity through methylation was among the top pathway in our association analysis (Table 1), suggesting that p53 modification by methylation and the closely related histone modifications [Protein lysine methyltransferases (PKMTs) methylate histone lysine in Fig. 9e] play important roles in RPE apoptosis regulation.In the intrinsic apoptotic pathway induced by oxidative stress, cytochrome c is released from mitochondria into the cytosol, binding and activating caspases, the main proteases central to apoptotic action.We found association in pathways involving 'inhibitor of apoptosis' (IAP) and its negative regulator 'second mitochondrial activator of caspases' (SMAC) [65], which suggests that disruption to regulatory mechanisms preventing apoptosis in RPE cells may play roles in AMD."
+                }
+            ],
+            "2186130e-2523-4fcc-a52f-fc2bdd986230": [
+                {
+                    "document_id": "2186130e-2523-4fcc-a52f-fc2bdd986230",
+                    "text": "Apoptosis\n\nPersistent DNA damage"
+                }
+            ],
+            "2715e261-b26c-46d6-918f-c6aa47688f0c": [
+                {
+                    "document_id": "2715e261-b26c-46d6-918f-c6aa47688f0c",
+                    "text": "42\nABSTRACT 18\nA MODULARIZED MODEL OF APOPTOSIS\nHA Harrington, KHo, Sk Ghosh, KC Tung , CY Kao, and B Aguda\nImperial College London, Courant Institute of Mathematical Sciences New York\nUniversity, University of Texas at Arlington, University of Texas Southwestern\nMedical Center, Mathematical Biosciences Institute, and Department of\nMathematics, The Ohio State University Columbus, OH, USA\nBackground: One of the key physiological mechanisms employed by the cell\n(during development and for maintenance of homeostasis) in multi-cellular\norganism is apoptosis, which is characterized by a sequence of well-defined\nevents resulting in cell destruction."
+                }
+            ],
+            "2dfc2b82-b8eb-4e73-957a-0ea8a4401a84": [
+                {
+                    "document_id": "2dfc2b82-b8eb-4e73-957a-0ea8a4401a84",
+                    "text": "14\nApoptosis is caused by the activation of the caspase cascade, which is\ninitiated by two signaling routes (stress-induced death and death-domain\nreceptor-induced death) (Domen 2001). This process can be prevented by antiapoptotic molecules, such as Bcl-2 (Domen and Weissman 2000). Direct\nevidence for the involvement of apoptosis in HSC number regulation came from\nthe findings that overexpression of the anti-apoptotic gene bcl-2 led to increased\nnumbers of Thy-1.1low, Sca-1+, c-kit+, Lin- cells, a population with long-term\nmulti-lineage repopulation potential (Domen et al. 2000)."
+                },
+                {
+                    "document_id": "2dfc2b82-b8eb-4e73-957a-0ea8a4401a84",
+                    "text": "Several lines of evidence have indicated that apoptosis acts as an\nimportant regulator of stem cells. First of all, expression of some apoptosisrelated genes were detected in human and/or murine HSCs (Domen 2001). Secondly, targeted disruption of some of these genes in null and dominant\nnegative mutant mice interfered with normal apoptotic processes in HSCs. For\nexample, overexpression of Bcl-2, a negative regulator of apoptosis, increased\nnot only the numbers and competitive repopulation capabilities of HSCs, but also\nthe resistance of HSCs to apoptosis induced by ionizing radiation (Domen and\nWeissman 2003)."
+                }
+            ],
+            "3c78c2be-0bd2-4954-bb47-8b48f6125ed7": [
+                {
+                    "document_id": "3c78c2be-0bd2-4954-bb47-8b48f6125ed7",
+                    "text": "Apoptosis\n\nCell suicide, or apoptosis, is a well-studied biological phenomenon in multicellular organisms that allows specific cells to be removed during the development of complex tissues, or potentially dangerous damaged cells to be destroyed for the benefit of the whole organism.The lack of an apparent evolutionary benefit for such a process in a single-celled organism initially caused controversy about the presence of an apoptotic pathway in yeast.Today, however, a number of yeast orthologues to mammalian apoptosis genes have been discovered and apoptotic-like cell death has been linked to mating, colony formation, and aging (Buttner et al. 2006;Eisenberg et al. 2007;Frohlich et al. 2007).With respect to aging, both replicatively and chronologically aged cells that die have increased ROS and display apoptotic phenotypes (Fabrizio et al. 2004a;Herker et al. 2004;Laun et al. 2001)."
+                },
+                {
+                    "document_id": "3c78c2be-0bd2-4954-bb47-8b48f6125ed7",
+                    "text": "\n\nThe importance of apoptosis in yeast aging has yet to be fully characterized.At the very least, yeast apoptosis provides a useful pathway for studying genetic interactions for age-related diseases that affect humans, such as cancer.Readers interested in further information related to yeast apoptosis are referred to several in-depth reviews (Buttner et al. 2006;Eisenberg et al. 2007;Frohlich et al. 2007)."
+                }
+            ],
+            "489539fd-f7c5-44eb-bb58-5fc19d50a7cf": [
+                {
+                    "document_id": "489539fd-f7c5-44eb-bb58-5fc19d50a7cf",
+                    "text": "Early redistribution of plasma membrane phosphatidylserine is a general\nfeature of apoptosis regardless of the initiating stimulus: inhibition by overexpression of\nBcl-2 and Abl. J Exp Med 182: 1545-56. Mathew CG (2006). Fanconi anaemia genes and susceptibility to cancer. Oncogene 25:\n5875-84. McBride MW, Carr FJ, Graham D, Anderson NH, Clark JS, Lee WK et al (2003). Microarray analysis of rat chromosome 2 congenic strains. Hypertension 41: 847-53. Merino-Trigo A, Kerr MC, Houghton F, Lindberg A, Mitchell C, Teasdale RD et al\n(2004)."
+                }
+            ],
+            "516fb027-d7ef-481b-95b2-89c25f4e4f8d": [
+                {
+                    "document_id": "516fb027-d7ef-481b-95b2-89c25f4e4f8d",
+                    "text": "\n\nWhen a cell harbors such severe DNA damage that it is beyond repair, it is disposed of through apoptosis.Alternatively, DNA damage can induce cellular senescence, the irreversible cessation of mitosis.Both processes are critically dependent on p53, which is known as the guardian of the genome [3] .DNA damage may also trigger autophagy, a cellular catabolic process that maintains homeostasis [4] .It should be noted that under normal conditions cells are rarely exposed to very high doses of DNAdamaging agents, which may be the explanation why we do not age and die because we run out of cells.However, aging is associated with some atrophy [1] and it is conceivable that at older ages bursts of DNA damage, for example from free radical reactions associated with inflammation, do occur and give rise to an increasingly high rate of apoptosis or cellular senescence.While there is some evidence for increased apoptosis and cellular senescence at old age, it is doubtful that under normal conditions this would lead to a significant loss of functional cells."
+                }
+            ],
+            "5c814c02-7157-40db-968d-98ac062744d6": [
+                {
+                    "document_id": "5c814c02-7157-40db-968d-98ac062744d6",
+                    "text": "\n\nApoptosis, or programmed cell death, literally eliminates cells at risk for neoplastic transformation.Senescence, by contrast, permanently arrests their growth.Both processes are controlled by the p53 tumor suppressor protein (Amundson, Myers, & Fornace, 1998;Bringold & Serrano, 2000;Hickman, Moroni, & Helin, 2002;Itahana, Dimri, & Campisi, 2001).p53 is a transcriptional regulator that both transactivates and transrepresses target genes in response to stress (Prives & Hall, 1999;Ryan, Phillips, & Voudsen, 2001).These target genes, in turn, stimulate DNA repair, transient cell cycle arrest, permanent cell cycle arrest (senescence) or cell death (apoptosis), depending on cell type, degree and type of damage, and other variables.In contrast, cells that lack normal p53 regulation or function -for example, tumor cells -tend to die in response to telomere dysfunction.Some normal human cells, on the other hand, undergo a senescence growth arrest.In either case, when present, p53 is crucial for mediating the cellular response to telomere dysfunction (Yaswen & Stampfer, 2002) (Fig. 4)."
+                }
+            ],
+            "667ac3eb-7d19-4359-98b7-e76871637910": [
+                {
+                    "document_id": "667ac3eb-7d19-4359-98b7-e76871637910",
+                    "text": "Cell death, and in particular\napoptosis, can be caused by a number of mechanisms including\nloss of growth factors and excitotoxicity (e.g. , Bhutta and Anand,\n2002; Nikolić et al. , 2013). It is of interest therefore, that proximal\nto the region of the QTL there are several genes that are related\nto growth factors including the latent transforming growth factor\nprotein 2 (ltbp2), placental growth factor (pgf), and transforming\ngrowth factor beta (Tgf beta)."
+                }
+            ],
+            "6f38cfff-88f1-4333-bc97-293200855bbf": [
+                {
+                    "document_id": "6f38cfff-88f1-4333-bc97-293200855bbf",
+                    "text": "\n\nApoptosis-related gene expression profiles"
+                }
+            ],
+            "98ce73c6-a53b-486f-8326-4b0bd47ec22e": [
+                {
+                    "document_id": "98ce73c6-a53b-486f-8326-4b0bd47ec22e",
+                    "text": "\n\nApoptosis.Programmed death of cells during embryogenesis and metamorphosis or during cell turnover in adult tissues."
+                }
+            ],
+            "9c266a06-68f9-4e25-8de4-87d8ee02d929": [
+                {
+                    "document_id": "9c266a06-68f9-4e25-8de4-87d8ee02d929",
+                    "text": "14\nApoptosis is caused by the activation of the caspase cascade, which is\ninitiated by two signaling routes (stress-induced death and death-domain\nreceptor-induced death) (Domen 2001). This process can be prevented by antiapoptotic molecules, such as Bcl-2 (Domen and Weissman 2000). Direct\nevidence for the involvement of apoptosis in HSC number regulation came from\nthe findings that overexpression of the anti-apoptotic gene bcl-2 led to increased\nnumbers of Thy-1.1low, Sca-1+, c-kit+, Lin- cells, a population with long-term\nmulti-lineage repopulation potential (Domen et al. 2000)."
+                },
+                {
+                    "document_id": "9c266a06-68f9-4e25-8de4-87d8ee02d929",
+                    "text": "Several lines of evidence have indicated that apoptosis acts as an\nimportant regulator of stem cells. First of all, expression of some apoptosisrelated genes were detected in human and/or murine HSCs (Domen 2001). Secondly, targeted disruption of some of these genes in null and dominant\nnegative mutant mice interfered with normal apoptotic processes in HSCs. For\nexample, overexpression of Bcl-2, a negative regulator of apoptosis, increased\nnot only the numbers and competitive repopulation capabilities of HSCs, but also\nthe resistance of HSCs to apoptosis induced by ionizing radiation (Domen and\nWeissman 2003)."
+                }
+            ],
+            "a68762fb-d3d0-4589-80a2-24ad1fca73a9": [
+                {
+                    "document_id": "a68762fb-d3d0-4589-80a2-24ad1fca73a9",
+                    "text": "\n\nFraction of cells displaying apoptosis"
+                }
+            ],
+            "b47e2055-8573-46ac-aec5-c2697df4d4b9": [
+                {
+                    "document_id": "b47e2055-8573-46ac-aec5-c2697df4d4b9",
+                    "text": "\n\nIt has been known that mitochondria play a central role in the life and death of cells (Kroemer & Reed, 2000).Apoptosis was observed in developmentally arrested embryos by 72 h, but not at 24 h after FCCP treatment, despite considerable telomere attrition at this early stage, suggesting that telomere attrition occurs prior to apoptosis and may serve as an intermediate step between mitochondrial dysfunction and apoptosis.These results also suggest that telomere shortening may signal apoptosis (Lee et al ., 1998;Karlseder et al ., 1999)."
+                }
+            ],
+            "d05f2105-e665-426c-8a7b-1ee57c89f23d": [
+                {
+                    "document_id": "d05f2105-e665-426c-8a7b-1ee57c89f23d",
+                    "text": "Cell Death\n\nA form of programmed cell death, apoptosis is necessary for normal cell turnover and is essential to a plethora of other biological processes.Apoptosis can be executed via Bcl-2 activation of caspases, via signals from the death receptor on the plasma membrane, or via induction by granzyme B secreted from cytotoxic T cells (Tc cells) [35].Endonucleases and proteases are activated by active caspases, eventually leading to the death of the cell.With age, however, apoptotic activity changes.In heart [36], kidney [37], skeletal muscle [38], and Tc cells [39], increased apoptosis has been reported, perhaps contributing to loss of cellularity in these tissues.This escalation across various tissues may be attributed to the increased production of free radicals [40] and furthermore exacerbated by the accumulation of DNA damage in the aged cells [41].As the risk increases for cells to turn cancerous and dysfunctional with advancing age, increased apoptosis in aged cells is argued to be a defense strategy.In other tissues, such as the colon, apoptosis appears to decrease with age perhaps contributing to the accumulation of senescent cells and age-associated carcinogenesis [42]."
+                }
+            ],
+            "d54db58c-5e5f-4552-a0cb-4e27787aee00": [
+                {
+                    "document_id": "d54db58c-5e5f-4552-a0cb-4e27787aee00",
+                    "text": "\n\nThe regulation and execution of apoptosis in endothelial cells is a complex process involving paracrine factors, membrane receptors, interaction of pro-and anti-apoptotic factors and cysteinyl aspartate-specific proteases (caspases).Recent studies suggest that in aging there is an imbalance in the expression of pro-and anti-apoptotic genes resulting in an enhanced apoptosis in the myocardium (19), central nervous system (24), skeletal muscle (10), lung (33), and liver (2,33).Yet, age-related alterations in the expression of pro-and anti-apoptotic genes in coronary arteries have not been elucidated."
+                }
+            ],
+            "e4eca0fc-d0bc-45fa-87e6-4958ebdf66f0": [
+                {
+                    "document_id": "e4eca0fc-d0bc-45fa-87e6-4958ebdf66f0",
+                    "text": "Apoptosis modulating genes\n\nApopotosis or programmed cell death is associated with alterations in cell morphology, particularly the nucleus, with endonucleatytic cleavage of DNA into nucleosomal length fragments.Apoptosis may result from withdrawal of growth signals."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "80493D7D624E399B7931DC3737018190",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "apoptosis",
+            "cell",
+            "death",
+            "p53",
+            "caspases",
+            "Bcl-2",
+            "DNA",
+            "damage",
+            "senescence",
+            "aging"
+        ],
+        "metadata": [],
+        "question": "What is apoptosis?",
+        "subquestions": null,
+        "task_id": "80493D7D624E399B7931DC3737018190",
+        "usage": {
+            "chatgpt": 5468,
+            "gpt-4": 3741,
+            "gpt-4-turbo-preview": 2788
+        },
+        "user_id": 2
+    },
+    "document_id": "80493D7D624E399B7931DC3737018190",
+    "task_id": "80493D7D624E399B7931DC3737018190"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/gen_resp03.json b/gnqa/paper1_eval/src/data/responses/general/gen_resp03.json
new file mode 100644
index 0000000..3c7935f
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/gen_resp03.json
@@ -0,0 +1,156 @@
+{
+    "created_at": "2024-04-01T11:59:12.696644Z",
+    "data": {
+        "amplify": false,
+        "answer": "For mammals, DNA can be extracted using a DNA Isolation Kit for Mammalian Blood, following the manufacturer's instructions. This process typically involves mixing blood with lysis buffer and Proteinase K, followed by the addition of isopropanol and Inhibitor Removal Buffer. The DNA is then washed, centrifuged, and the supernatant discarded. The remaining pellet, which contains the purified genomic DNA, is diluted in TE buffer.\n\nFor plants, the mixed alkyl trimethyl ammonium bromide (MATAB) procedure can be used. This involves grinding plant material in liquid nitrogen, incubating it in extraction buffer, and then purifying it with chloroform:isoamylalcohol. The DNA extracts are then precipitated with isopropanol and resuspended in a buffer. The extracts are further purified on anion exchange columns.",
+        "context": {
+            "05c26b4c-cc56-49bc-914e-066ba0f05e97": [
+                {
+                    "document_id": "05c26b4c-cc56-49bc-914e-066ba0f05e97",
+                    "text": "DNA and RNA extraction of tissues\n\nGenomic DNA was extracted from frozen placentae (n ϭ 3/group) and liver (n ϭ 9/group) using a modified version of an established protocol (28,29).Total RNA was extracted from the remaining tissue using TRIzol, as per the manufacturer's instructions (Invitrogen Canada Inc).Genomic DNA and RNA purity and concentration were assessed using spectrophotometric anal-ysis, and integrity was verified using agarose gel [1% (wt/vol)] electrophoresis."
+                }
+            ],
+            "147b69a0-1397-4b1a-aa01-fa310677edb9": [
+                {
+                    "document_id": "147b69a0-1397-4b1a-aa01-fa310677edb9",
+                    "text": "Taxon Sampling and DNA Extractions\n\nWe extracted DNA from 72 pinned specimens from the National Museum of Natural History (NMNH) Entomology collection for this study.We plucked middle legs from the pinned bees using a pair of sterilized forceps and washed the tissue in 95% ethanol to remove dust, pollen, and other forms of accumulated debris on the bee legs.After evaporation of the ethanol (by drying the tissue on a clean Kimwipe ™ ), the samples were placed in a freezer for several hours.DNA was then extracted destructively by grinding the frozen tissue with a sterile pestle, using a DNeasy Blood and TissueKit (Qiagen, Valencia, CA, USA) and following the manufacturer's protocol, except the DNA was eluted in 130μL ddH 2 O instead of the supplied buffer.We ran 10μL of each extract for 60 min at 100 volt on 1.5% agarose SB (sodium borate) gels, to estimate size of the genomic DNA."
+                }
+            ],
+            "1c1f2541-c4ff-407a-b541-0e7859f5b49a": [
+                {
+                    "document_id": "1c1f2541-c4ff-407a-b541-0e7859f5b49a",
+                    "text": "DNA extraction\n\nDNA was extracted from PBMCs using the QIAamp DNA Mini kit (Qiagen, CA, USA), following the manufacturer's instructions for the spin protocol.The DNA was eluted in 60 μl of AE elution buffer and stored at -20°C.The concentration and quality of the DNA was assessed with the Qubit dsDNA HS Assay (Invitrogen, Eugene, OR, USA)."
+                }
+            ],
+            "27b471ec-acc3-4624-9050-57516328da07": [
+                {
+                    "document_id": "27b471ec-acc3-4624-9050-57516328da07",
+                    "text": "Methods\n\nLaboratory procedures.We initially screened 107 ancient samples (Supplementary Data 1) in dedicated clean facilities at the ancient DNA lab of Jilin University, China, following published protocols for DNA extraction and library preparation 36,37 .Prior to sampling, we wiped all skeletal elements with 5% bleach and irradiated with UV-light for 30 min from each side.We drilled teeth to obtain fine powder using a dental drill (Dremel, USA).We sampled the dense part of petrous bones around the cochlea by first removing the outer part using the sandblaster (Renfert, Germany), and then grinding the clean inner part into fine powder with the mixer mill (Retsch, Germany).We digested the powder (50-100 mg) in 900 μl 0.5 M EDTA (Sigma-Aldrich), 16.7 μl of Proteinase K (Sigma-Aldrich), and 83.3 μl ddH 2 O (Thermo Fisher, USA) at 37 °C for 18 h.Then we transferred the supernatant to a MinElute silica spin column (QIAGEN, Germany) after fully mixed with the 13 ml custom binding buffer [5 M guanidine hydrochloride (MW 95.53), 40% Isopropanol, 90 mM Sodium Acetate (3 M), and 0.05% Tween-20] followed by two washes with PE buffer (80% ethanol).Then we eluted the DNA with 100 μl TET buffer (QIAGEN, Germany)."
+                }
+            ],
+            "3bde9884-e31d-4719-b42f-02dca25d6c08": [
+                {
+                    "document_id": "3bde9884-e31d-4719-b42f-02dca25d6c08",
+                    "text": "DNA Extraction\n\nAfter blood was drawn into EDTA tubes, genomic DNA was extracted using a DNA Isolation Kit for Mammalian Blood Kit (Roche Applied Science, Indianapolis, IN, USA) according to the manufacturer's recommendations.Briefly, 300 μl of whole blood from each sample was mixed with 200 μl of lysis buffer (50 mM Tris pH 8.0, 100 mM EDTA, 100 mM NaCl, 1% SDS) and 40 μl of Proteinase K, followed by addition of 100 μl of isoproponal and 500 μl of Inhibitor Removal Buffer (5M guanidine-HCl, 20 mM Tris-HCl pH 6.6).The DNA was washed with a buffer (20 mM NaCl; 2 mM Tris-HCl; pH 7.5), centrifuged twice at 2000 rpm, washed using cold 70% ethanol and centrifuged at 3000 rpm.The supernatant was discarded and the pellet containing purified genomic DNA was diluted in TE buffer (1 mM EDTA; 10 mM Tris-HCl, pH 7.5) to a concentration of approximately 50 ng/μl."
+                }
+            ],
+            "58f36772-b82e-437e-a5dd-2442277089f5": [
+                {
+                    "document_id": "58f36772-b82e-437e-a5dd-2442277089f5",
+                    "text": "Genomic DNA extraction\n\nLeukocytes were isolated from 5-ml peripheral blood samples.DNA was prepared by phenol extraction and chloroform extraction followed by isopropanol precipitation, washed with ethanol, and air-dried.Tris-EDTA buffer pH 8.0 was used to dissolve the final genomic DNA product."
+                }
+            ],
+            "5b4350f1-779d-4763-a0e1-23008db25633": [
+                {
+                    "document_id": "5b4350f1-779d-4763-a0e1-23008db25633",
+                    "text": "\n\nThe pulled down DNA fragments were extracted and purified using phenolchloroform extraction/ethanol precipitation.The samples were stored at -20 °C until use."
+                }
+            ],
+            "752b2413-8c90-4af7-b65b-db429145b3bb": [
+                {
+                    "document_id": "752b2413-8c90-4af7-b65b-db429145b3bb",
+                    "text": "DNA extraction for genotyping\n\nFor the majority of samples, DNA was extracted from either spleen or the exocrine fraction of the islet isolation using the Tissue DNA Purification Kit according to manufacturer's instructions on an automated Maxwell 16 system (both Promega, USA).When no other tissue was available, DNA was extracted from human islets using the Trizol fraction remaining after extraction of RNA (see above).To precipitate the DNA, 300μl 100% ethanol was added to the thawed solution.This mixture was incubated at room temperature for a minimum of 30 minutes.DNA was then pelleted by centrifugation at 4,000 x g for 5 minutes at 4°C.After removing the supernatant, the pellet was twice washed with 0.1M trisodium citrate (Sigma Aldrich, UK) in 10% ethanol and left at room temperature for 30 minutes, followed by another wash step with 75% ethanol.After the final wash step, pellets were air-dried for 10 minutes to remove residual ethanol and re-suspended in a minimum of 100 μL 8mM NaOH (Sigma Aldrich).Extracted DNA was stored at -20°C before further use."
+                }
+            ],
+            "9292750d-3941-465c-8e2c-bb041f6bea0b": [
+                {
+                    "document_id": "9292750d-3941-465c-8e2c-bb041f6bea0b",
+                    "text": "DNA extraction\n\nTissue samples were incubated at 50°C overnight with shaking in DNA extraction buffer (100 mM NaCl, 10 mM Tris.HCl pH8, 25 mM EDTA, 0.5% (w/v) SDS), containing 200 μg/ml proteinase K. DNA was isolated by two rounds of phenol:chloroform extraction, followed by RNAse A treatment, precipitation in absolute ethanol containing 10% (v/v) sodium acetate (3 M, pH 5.2), and resuspended in 100 μl nuclease-free water (Ambion, Austin, TX, USA) or using salting out method followed by purification with Qiagen blood and tissue kit (Qiagen, Mississauga, ON, USA).DNA was stored at -20°C."
+                }
+            ],
+            "9605f23b-0620-4c0c-8f38-d9e0171e7e64": [
+                {
+                    "document_id": "9605f23b-0620-4c0c-8f38-d9e0171e7e64",
+                    "text": "Methods\n\nHuman DNA samples DNA was extracted from human patient tissue samples acquired from the University of Minnesota Tissue Procurement Facility from BioNet (IRB#0805E32181).See Supplemental Table S4 for patient data.Briefly, 2 mg of tissue was digested overnight at 55°C on a rotating platform in 710 mL of digest buffer (1 M Tris at pH 8.0, 1 mM EDTA, 13 SSC, 1% SDS, 1 Mm NaCl, 10 mg/mL Proteinase K).Following digest, DNA was purified using phenolchloroform-isoamyl alcohol (Life Sciences) isolation protocol."
+                }
+            ],
+            "9981a933-8fdf-4107-a6fd-3f9ef71f5d08": [
+                {
+                    "document_id": "9981a933-8fdf-4107-a6fd-3f9ef71f5d08",
+                    "text": "3.2.2 Isolation of genomic DNA\nGenomic DNA was isolated from frozen liver tissue. The isolation was conducted using the\nQiagen DNeasy Blood & Tissue Kit (Qiagen) according to the manufacturer’s protocol. DNA concentration was evaluated photometrically at a wavelength of 260 nm using\nthe FusionTM Universal Microplate Analyzer. For nucleic acid quantification, the Beer-Lambert\n(A = ε * b * c) equation is modified to use an extinction coefficient with units of M-1 cm-1."
+                }
+            ],
+            "a4e27158-1e54-4ee2-9cc1-049489a628bc": [
+                {
+                    "document_id": "a4e27158-1e54-4ee2-9cc1-049489a628bc",
+                    "text": "\n\nMost typically, DNA is extracted from blood samples, dried blood spots, buccal swabs, saliva, tissue and even urine and stool samples.In forensic science, other sources have been validated e.g.bone, tooth pulp, dandruff and others."
+                }
+            ],
+            "c10ff8e0-81ff-4ac2-b1cc-2fdc89640166": [
+                {
+                    "document_id": "c10ff8e0-81ff-4ac2-b1cc-2fdc89640166",
+                    "text": "DNA isolation\n\nHigh-molecular weight DNAs was isolated from the samples by organic solvent extraction method, followed by precipitation in cold ethanol [14]."
+                }
+            ],
+            "c6b165b1-a39e-4278-9615-8285c1999e7e": [
+                {
+                    "document_id": "c6b165b1-a39e-4278-9615-8285c1999e7e",
+                    "text": "Genomic DNA extraction\n\nDNA from MEF cultures or mouse liver was isolated by phenol/chloroform extraction, as described [11]."
+                }
+            ],
+            "da485354-fcdc-49b8-9a41-0f673610156a": [
+                {
+                    "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                    "text": "DNA is\nusually recovered from cells by methods that include cell rupture but that\nprevent the DNA from fragmenting by mechanical shearing. This is generally undertaken in the presence of EDTA, which chelates the magnesium ions\nneeded as cofactors for enzymes that degrade DNA, termed DNase. Ideally,\ncell walls, if present, should be digested enzymatically (e.g. , lysozyme in the\nbacteria or bacterial cell). In addition the cell membrane should be solubilized\nusing detergent."
+                },
+                {
+                    "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                    "text": "DNA solutions can be stored frozen,\nalthough repeated freezing and thawing tends to damage long DNA molecules\nby shearing. A flow diagram summarizing the extraction of DNA is given in\nFig. 1.2. The above-described procedure is suitable for total cellular DNA. If the DNA from a specific organelle or viral particle is needed, it is best to\nisolate the organelle or virus before extracting its DNA, because the recovery\nof a particular type of DNA from a mixture is usually rather difficult."
+                }
+            ],
+            "f0849937-dc25-42f4-a512-99783761674d": [
+                {
+                    "document_id": "f0849937-dc25-42f4-a512-99783761674d",
+                    "text": "Genomic DNA extraction\n\nGenomic DNA was extracted by the mixed alkyl trimethyl ammonium bromide (MATAB) procedure.Briefly, 250 mg of plant material was ground in liquid nitrogen and immediately incubated in 2 ml of pre-warmed extraction buffer (100 mM Tris-HCl, pH 8, containing 20 mM EDTA, 1.4 M NaCl, 2% (w/v) MATAB, 1% (w/v) PEG6000 (polyethylene glycol), 0.5% (w/v) sodium sulfite, 20% (w/v) Igepal CA630, 20% (w/v) lithium dodecyl sulfate, and 20% (w/v) sodium deoxycholate) at 74 °C for 20 min.After purification with 2 ml of chloroform:isoamylalcohol (24:1, v/v), DNA extracts were precipitated with 1.6 ml of isopropanol then resuspended in 1 ml of buffer (50 mM Tris-HCl, pH 8, containing 10 mM EDTA and 0.7 M NaCl).The extracts were purified on anion exchange columns (QIAGEN-tip 20) following the manufacturer's instructions (QIAGEN, Valencia, CA)."
+                }
+            ],
+            "f9002547-db31-4f9e-abc1-7aace5c8ea18": [
+                {
+                    "document_id": "f9002547-db31-4f9e-abc1-7aace5c8ea18",
+                    "text": "DNA extraction and enzymatic digestion\n\nTotal DNA was isolated from whole blood and separated blood subtypes using a Qiagen DNeasy Blood & Tissue Kit following the manufacturer instructions.After extraction, DNA was quantified by NanoDrop (Thermo Scientific NanoDrop products, Wilmington, DE).The isolated genomic DNA was enzymatically digested according to previously described method.Briefly, DNA (3 μg) was first denatured by heating at 95 °C for 5 min and then chilling on ice for 2 min.Then, 1/10 volume of S1 nuclease buffer (30 mM CH 3 COONa, pH 4.6, 280 mM NaCl, 1 mM ZnSO 4 ) and 100 units of S1 nuclease were added before the mixture (20 μL) was incubated at 37 °C for 16 h.Subsequently, after 1/10 volume of alkaline phosphatase buffer (50 mM Tris-HCl, 10 mM MgCl 2 , pH 9.0), 0.002 units of venom phosphodiesterase I, and 10 units of alkaline phosphatase were added, the solution was incubated at 37 °C for an additional 4 h followed by extraction with an equal volume of chloroform for twice.The aqueous layer was collected and lyophilized to dryness and then reconstituted in 100 μL water.About 30 μL of the obtained samples were then subjected to liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) analysis."
+                }
+            ],
+            "fabfccb1-4ba7-47b4-8415-941742ddea40": [
+                {
+                    "document_id": "fabfccb1-4ba7-47b4-8415-941742ddea40",
+                    "text": "\n\nThe conventional DNA extraction procedure involved the homogenization of single D. magna in 400 l of sperm lysis buffer (100 mM Tris-HCl, pH 8; 500 mM NaCl; 10 mM ethylenediaminetetraacetic acid [EDTA], pH 8; 1% SDS; 2% mercaptoethanol) followed by RNase treatment (40 g, 37ЊC for 1.5 h).The DNA was then extracted in phenol (pH 8) and chloroform:isoamyl alcohol (1:1).The DNA was finally precipitated by two volumes of ice-cold ethanol in the presence of 3 M sodium acetate (1/10 of the DNA volume) and was incubated at Ϫ80ЊC overnight.Precipitated DNA was harvested by centrifugation, dried in air, and the final pellet dissolved in sterile analytic grade water."
+                }
+            ],
+            "fd5edd5b-25d5-41ef-b9ad-7599905b844f": [
+                {
+                    "document_id": "fd5edd5b-25d5-41ef-b9ad-7599905b844f",
+                    "text": "DNA extraction and quantification\n\nDNA was extracted from whole organs by standard techniques (34) with emphasis on minimizing shearing or nicking of DNA as nicked DNA has been shown to be refractory to LX-PCR (35).DNA from the brain was extracted from the right hemisphere.Extracted DNA was resuspended in 10 mM Tris 1 mM EDTA (pH 8) (TE) and stored at 4_C.A number of samples were normalized for mtDNA content by dot blotting and hybridization with digoxigenin-labeled full-length mtDNA and densitometry.In cases where mtDNA quantification was not carried out, the DNAs were normalized by A 260 of total DNA."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "D5884AA974550493E54BFAD47AAEB737",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "DNA",
+            "extraction",
+            "phenol",
+            "chloroform",
+            "ethanol",
+            "precipitation",
+            "Qiagen",
+            "EDTA",
+            "Proteinase&K",
+            "isopropanol"
+        ],
+        "metadata": [],
+        "question": "How would one extract the DNA, from say, mammals or plants?",
+        "subquestions": null,
+        "task_id": "D5884AA974550493E54BFAD47AAEB737",
+        "usage": {
+            "chatgpt": 6218,
+            "gpt-4": 4090,
+            "gpt-4-turbo-preview": 3185
+        },
+        "user_id": 2
+    },
+    "document_id": "D5884AA974550493E54BFAD47AAEB737",
+    "task_id": "D5884AA974550493E54BFAD47AAEB737"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/gen_resp04.json b/gnqa/paper1_eval/src/data/responses/general/gen_resp04.json
new file mode 100644
index 0000000..8497fd1
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/gen_resp04.json
@@ -0,0 +1,150 @@
+{
+    "created_at": "2024-04-01T12:01:45.671040Z",
+    "data": {
+        "amplify": false,
+        "answer": "A genetic marker is a measurable polymorphic sequence of DNA whose chromosomal location is known. They often have no known functional significance but are used as pointers to a particular chromosomal location. They are used to track the inheritance of genes and can be a gene or some section of DNA with no known function.",
+        "context": {
+            "0a30029f-fa8f-49e3-9a68-82d1a8ae3157": [
+                {
+                    "document_id": "0a30029f-fa8f-49e3-9a68-82d1a8ae3157",
+                    "text": "Using genetic markers, the pattern of inheritance can be tracked through\nfamilies. For example, by analyzing a marker linked to the eye color gene\nin several generations, it is possible to determine from which grandparents a\nchild has inherited its eye color alleles. More importantly, ﬁnding a marker\nlinked to a disease can lead to location of the faulty gene causing the disease. Finding the gene is very valuable in the search for the cure. The distance between two loci can be expressed either as physical or genetic distance."
+                }
+            ],
+            "0c80320f-bca2-4f46-858e-bd3fba2f67a2": [
+                {
+                    "document_id": "0c80320f-bca2-4f46-858e-bd3fba2f67a2",
+                    "text": "\n\nIt is well known, however, that not all genomic markers are independent (Frazer et al., 2007).Genetic variation is often inherited in contiguous segments of DNA, such that there tends to be correlation between the inheritance of alleles at markers close to each other on the same chromosome.This genetic correlation is called linkage disequilibrium (LD), and, as a result, the effective number of independent tests (M eff ) conducted is less than the total number of markers (M).By effective number of tests, we mean the number of independent tests that would have to be conducted to lead to a null distribution for the minimum P-values that was approximately the same as that obtained when conducting tests that are necessarily correlated due to LD."
+                }
+            ],
+            "32338b01-15af-4ec9-9bc4-e9c58b53068e": [
+                {
+                    "document_id": "32338b01-15af-4ec9-9bc4-e9c58b53068e",
+                    "text": "Genetic\nmapping is a powerful strategy that exploits genomic information to dissect complex traits into Mendelian loci\n(quantitative trait loci or QTL) and identifies genetic\n* Correspondence: marioenrico.pe@sssup.it\n1\nInstitute of Life Sciences, Scuola Superiore Sant’Anna, Pisa, Italy\nFull list of author information is available at the end of the article\n\ndeterminants that may lead to crop improvement. As\nmarker density ceases to be a limiting factor [3], our\nability to discover specific genetic determinants in a\nsingle mapping study depends upon the availability of\npopulations with high genetic diversity and recombination density [4]."
+                }
+            ],
+            "7a7773ed-2548-4297-86ad-b7ce115448e0": [
+                {
+                    "document_id": "7a7773ed-2548-4297-86ad-b7ce115448e0",
+                    "text": "This capacity allows samples to be placed into\nmeaningful genetic groups that reflect evolutionary relationships (more stable, lower diversity markers), while simultaneously permitting high levels of strain resolution (high diversity\nmarkers). From a clinical perspective, markers that accurately\nreflect broad evolutionary relationships are valuable for comparing the genetic similarity of an isolate to isolates on a regional\nor global scale, whereas high-resolution markers are valuable\nfor detailed epidemiological tracking in an outbreak. Variable-number tandem repeats (VNTRs) are genetic markers that can span a range of variability and, therefore, can capture\ngenetic relationships on multiple scales (18–19)."
+                }
+            ],
+            "835a094d-9c2b-4686-8725-d3c4123175b0": [
+                {
+                    "document_id": "835a094d-9c2b-4686-8725-d3c4123175b0",
+                    "text": "Identifying the genetic loci that modulate a trait based on correlation between\nvariation in phenotype and variation in genotype is the essence of genetic mapping. This\nfirst involves systematically genotyping a genetically diverse population using\nmicrosatellite or SNP markers. The phenotype of interest is then measured and its\nvariability in the population assessed. A statistical test is then carried out to identify\nchromosomal regions that segregate with the trait and show linkage with the trait, i.e. ,\n\n3\nidentify genetic regions that have the same genotype among individuals with similar trait\nvalues but differ between individuals with dissimilar trait values."
+                }
+            ],
+            "83a4ab87-f4a5-40b9-9297-5a3596e3636f": [
+                {
+                    "document_id": "83a4ab87-f4a5-40b9-9297-5a3596e3636f",
+                    "text": "Using genetic markers, the pattern of inheritance can be tracked through\nfamilies. For example, by analyzing a marker linked to the eye color gene\nin several generations, it is possible to determine from which grandparents a\nchild has inherited its eye color alleles. More importantly, ﬁnding a marker\nlinked to a disease can lead to location of the faulty gene causing the disease. Finding the gene is very valuable in the search for the cure. The distance between two loci can be expressed either as physical or genetic distance."
+                }
+            ],
+            "8b95c7a6-0ca5-445e-8776-14d1e6550fa0": [
+                {
+                    "document_id": "8b95c7a6-0ca5-445e-8776-14d1e6550fa0",
+                    "text": "Genetic variation\n\nFor decades researchers used single markers to elucidate clinal differentiation and spatial variation in allele frequencies.This approach revealed multiple markers with variation that tracked the clines, including some with the same allele at higher frequency at the same latitude in the Northern and Southern hemispheres.Examples include alcohol dehydrogenase (Adh), a-glycerol-3-phosphate dehydrogenase (Gpdh), glucose-6-phosphate dehydrogenase (G6pd), esterase-6 (Est-6), octanol dehydrogenase (Odh), and 6-phosphogluconate dehydrogenase (Pgd) [30][31][32][33] (Table 1).Perhaps the most heavily explored locus in D. melanogaster has been Adh, the first step in the ethanol detoxification pathway.The Adh-F allele encodes high catalytic activity of ADH, but this increase in activity trades off with enzyme stability at higher temperatures [34,35].Unsurprisingly, the Adh-F allele is found at a higher frequency in cooler high-latitude populations, and differentiation has occurred in parallel along clines in"
+                }
+            ],
+            "92fa8f50-2923-41a1-812b-32d931c71684": [
+                {
+                    "document_id": "92fa8f50-2923-41a1-812b-32d931c71684",
+                    "text": "In the case of\ngenetic markers, this easily runs in the several hundreds to thousands. Moreover,\nthe optimal subset of markers is heavily dependent on how these markers are\ncombined, i.e. dependent on the optimal Boolean function . Altogether, one\nfrequently has to rely on greedy search strategies that easily get stuck in local\noptima or near exhaustive searches that are computationally too expensive,\nespecially when employed in permutation procedures required to assess statistical\nsignificance. Our solution to this problem hinges upon two observations."
+                }
+            ],
+            "98ce73c6-a53b-486f-8326-4b0bd47ec22e": [
+                {
+                    "document_id": "98ce73c6-a53b-486f-8326-4b0bd47ec22e",
+                    "text": "GENE MAPPING\n\nThe opportunity to merge advances in molecular genetic technology with advances in statistical techniques expanded in earnest with the development of DNA markers such as restriction fragment length polymorphisms (Lander and Botstein, 1989).Research exploded in the past decade with the continued refinement of molecular technology yielding a variety of DNA markers-e.g., short tandem repeats (STRs) or microsatellites; variable number of tandem repeats (VNTRs); single nucleotide polymorpohisms (SNPs), and gene expression microarrays or gene chips.A genetic marker is a measurable polymorphic sequence of DNA whose chromosomal location is known.Markers often have no known functional significance but are used as pointers to a particular chromosomal location.The logic of gene mapping technology is simple: Determine if there is a relationship between variability in a phenotype and variability in an anonymous DNA marker of known chromosomal location.If there is a relationship, it is taken as evidence that there is a gene that influences the trait at or near the marker."
+                },
+                {
+                    "document_id": "98ce73c6-a53b-486f-8326-4b0bd47ec22e",
+                    "text": "Genetic drift. Genetic changes in populations caused by random phenomena rather than by selection.Genetic marker.A segment of DNA with an identifiable physical location on a chromosome whose inheritance can be followed.A marker can be a gene, or it can be some section of DNA with no known function."
+                },
+                {
+                    "document_id": "98ce73c6-a53b-486f-8326-4b0bd47ec22e",
+                    "text": "\n\nBiological characteristics indicating initial resiliency or susceptibility of an organism include genetic profiles.As noted above, genetic markers need to have a high prevalence in the population and have a reasonably strong effect on common population health outcomes, or have an interaction effect with other health-affecting mechanisms, to be candidates for inclusion in population studies.At the moment, the only known genetic marker of clear value in a population survey is the apolipoprotein E gene (APOE), although this is likely to change in the very near future.APOE allele status is clearly related to a number of major health outcomes in older populations which are reasonably well measured in population surveys: mortality, heart disease, and cognitive functioning (Albert et al., 1995b;Corder et al., 1993;Evans et al., 1997;Ewbank, 1997;Hofman et al., 1997;Hyman et al., 1996;Luc et al., 1994;Saunders et al., 1993).Both the prevalence of alleles indicating higher risk and the size of the effect are large enough to be of importance in explaining variability in currently studied health outcomes.APOE allele status has been shown to have independent effects on health outcomes and to interact with other life circumstances such as sex and race in its effect on health outcomes (Jarvik et al., 1995;Maestre et al., 1995;Payami et al., 1992).Incorporation of information on this genetic indicator could lead to increased knowledge of the interactive mechanisms of this genetic marker and other social and behavioral variables and thus clarify some of the mechanisms leading to population differentials in cognition, heart disease, and mortality."
+                },
+                {
+                    "document_id": "98ce73c6-a53b-486f-8326-4b0bd47ec22e",
+                    "text": "\n\nAs described by Hermalin (1999), if genetic markers are modeled as part of an individual's physiological structure, they can provide controls for predisposing factors that affect more proximate mid-level markers of function as well as downstream health outcomes.This potential benefit of genetic information-i.e., its power in explicating the black box of Figure 11-1-may outweigh, or at least precede, its near-term potential for discovering genetic links to chronic disease.As discussed by Weiss (1998b), the situation with chronic disease differs from single locus disorders that are inherited following well-identified Mendelian rules.In general, we cannot expect to find relationships that are even as straightforward as the APOE links to cardiovascular and Alzheimer's disease.Variation across populations, difficulty in identifying a small enough area on the chromosome to search for disease-associated genes, and the problems inherent in identifying continuous outcomes with particular genes may limit finding the connections."
+                }
+            ],
+            "ad14b0c4-2a38-411b-9bb1-cacf9203f29d": [
+                {
+                    "document_id": "ad14b0c4-2a38-411b-9bb1-cacf9203f29d",
+                    "text": "This capacity allows samples to be placed into\nmeaningful genetic groups that reflect evolutionary relationships (more stable, lower diversity markers), while simultaneously permitting high levels of strain resolution (high diversity\nmarkers). From a clinical perspective, markers that accurately\nreflect broad evolutionary relationships are valuable for comparing the genetic similarity of an isolate to isolates on a regional\nor global scale, whereas high-resolution markers are valuable\nfor detailed epidemiological tracking in an outbreak. Variable-number tandem repeats (VNTRs) are genetic markers that can span a range of variability and, therefore, can capture\ngenetic relationships on multiple scales (18–19)."
+                }
+            ],
+            "b04f2221-de28-4c4b-893e-9da982ff864c": [
+                {
+                    "document_id": "b04f2221-de28-4c4b-893e-9da982ff864c",
+                    "text":"These variations provide a species the ability of adapting\nto the environment change (Liu and Cordes,\n2004). DNA markers are among the most powerful tools for revealing genetic variations in\norganisms. Historically, many different types of markers have been used for aquaculture studies\n\nFunctional Genomics in Aquaculture, First Edition. Edited by Marco Saroglia and Zhanjiang (John) Liu. ␂\nC 2012 John Wiley & Sons, Inc. Published 2012 by John Wiley & Sons, Inc.\n\n41\n42\n\nFunctional Genomics in Aquaculture\n\nTable 2.1\n\nA summary of characteristics of various molecular markers used in aquaculture species."
+                },
+                {
+                    "document_id": "b04f2221-de28-4c4b-893e-9da982ff864c",
+                    "text": "For instance,\nmapping of a trait or a phenotype would require polymorphic DNA markers such as microsatellites (SSRs) or single nucleotide polymorphisms (SNPs); expression proﬁling would\nrequire genome annotation information; microarray design would require sequence information of genes, etc. The objective of this chapter is to provide a general review of genomic\nresources needed, and currently present for\naquaculture species, for functional genomics\nstudies. Polymorphic DNA Markers\nThe key factor behind the signiﬁcant differences at the level of individuals, species,\nand higher order of taxonomic groups is genetic variation (polymorphism)."
+                }
+            ],
+            "cbc03a11-fe9c-4b54-b290-bd24c1447607": [
+                {
+                    "document_id": "cbc03a11-fe9c-4b54-b290-bd24c1447607",
+                    "text": "Functional genomics:\n\nThe study of genes, their resulting proteins, and the role played by the proteins in the biochemical processes of the body.Gene: A unit of inheritance; a working subunit of DNA.Each of the 20 000 to 25 000 genes in the body contains the code for a specific product, typically a protein such as an enzyme.Gene expression: The process by which the coded information of a gene is translated into the structures present and operating in the cell (either proteins or ribonucleic acids).Gene markers: Landmarks for a target gene, either detectable traits that are inherited along with the gene or distinctive segments of DNA.Gene map: A description of the relative positions of genes on a chromosome and the distance between them.Genetic counseling: A short-term educational counseling process for individuals and families who have a genetic disease or who are at risk for such a disease.Genetic counseling provides patients with information about their condition and helps them make informed decisions.Genetic linkage maps: DNA maps that assign relative chromosomal locations to genetic landmarks-either genes for known traits or distinctive sequences of DNA (ie, genetic markers)-on the basis of how frequently they are inherited together.Genetic testing: Examining a sample of blood or other body fluid or tissue for biochemical, chromosomal, or genetic markers that indicate the presence or absence of genetic disease.Genetics: The scientific study of heredity, how particular qualities or traits are transmitted from parents to offspring.Genome: All the genetic material in the chromosomes of a particular organism.Genome-wide: Descriptor that indicates that the entire breadth of the genome has been examined in a study (eg, a linkage or association study).Genome-wide studies do not resequence the entire genome but type (an increasingly large set of) markers distributed throughout the genome.Genomics: A \"scaled-up\" version of the science of genetics that investigates the structure and function of large sections of the genome simultaneously.Genotype: The actual genes carried by an individual (as distinct from phenotype-ie, the physical, bodily characteristics into which genes are translated).Haplotype: A way of denoting the collective genotype of a number of closely linked loci on a chromosome.Heritability (h 2 ): For any trait, the proportion of the phenotypic variability resulting from genetic variance.Note that heritability does not indicate the degree to which a trait is \"genetic. \"Nor does a high h 2 mean that the trait cannot be influenced by environment.A heritability significantly Ͼ0, however, can provide a rationale for further genetic and genomic study of a trait of interest.Heterozygous: Possessing 2 different sequences (ie, genotypes) of a particular gene, 1 inherited from each parent.High-throughput genotyping: In contrast to the older labor-and time-intensive genotyping methods, high-throughput genotyping makes use of robots, computers, and other evolving technologies, thus enabling laboratories to type up to hundreds of thousands of polymorphisms in many samples in a relatively short period of time.Homozygous: Possessing 2 identical sequences of a particular gene, 1 inherited from each parent.Interaction: The differing effect of 1 independent variable on the dependent variable, depending on the particular level of another independent variable.For example, there would be an interaction between the factors sex and treatment if the effect of treatment was not the same for male and female subjects in a drug trial.Linkage analysis: A gene-hunting technique that traces patterns of heredity in large, high-risk families in an attempt to locate a disease-causing gene mutation by identifying traits that are coinherited with it.Linkage disequilibrium: Two alleles at different loci that occur together on the same chromosome more often than would be predicted by chance alone.It is a measure of cosegregation of alleles in a population."
+                }
+            ],
+            "d0d6c5d6-36c6-45f1-9107-cef95df83bb3": [
+                {
+                    "document_id": "d0d6c5d6-36c6-45f1-9107-cef95df83bb3",
+                    "text": "Source: Kearsey and Pooni (1996). Genetic maps consist of a series of markers or identifiable features at known, or perhaps\nbest described as estimated, locations on the genome (see Figure 9). For some discrete traits, simple Mendelian inheritance is followed and the phenotype has\na one to one correspondence with the genes controlling it. These are so called morphological\nmarkers, which were then related to continuous or quantitative traits of interest. Examples are\nshape, colour, size or height in particular varieties of peas, as studied by Mendel. For another\nexample, see Appendix A.2."
+                }
+            ],
+            "d333b766-b7e4-4ab5-96a8-50a8a1d805f1": [
+                {
+                    "document_id": "d333b766-b7e4-4ab5-96a8-50a8a1d805f1",
+                    "text": "Genomic markers used in linkage mapping have evolved from\nrestriction fragment length polymorphisms (RFLPs) to microsatellites (simple sequence repeat\npolymorphisms; SSRPs), to single-nucleotide polymorphisms (SNPs), with the more modern\nmarkers exhibiting higher frequencies in the genome (thus ensuring fuller coverage). Linkage\nmapping of a trait is in fact the demonstration of linkage between the phenotype and a genomic\nmarker, followed by an inference of linkage between the genomic marker and the responsible\nDNA variant. Transitive logic ties the phenotype with the DNA variant, which is of course the\npoint of the exercise. See Fig."
+                }
+            ],
+            "e8397443-575a-4645-b161-59862203f7b4": [
+                {
+                    "document_id": "e8397443-575a-4645-b161-59862203f7b4",
+                    "text": "However, because of time constraints it is often more\npracticable to choose an appropriate mapping population that is already available\nthrough the current stock centers. Plant species chosen for study will depend\nlargely on the availability of suitable plant resources. Obtain appropriate mapping population information to include information on\nmarkers/genotypes (see Note 4). A marker is an identifying factor; a gene or other\nDNA of known location that is used to track the inheritance and so on of other\ngenes whose exact location is not yet known."
+                }
+            ],
+            "f9f8f648-bd40-49e9-8aee-c341faa43290": [
+                {
+                    "document_id": "f9f8f648-bd40-49e9-8aee-c341faa43290",
+                    "text":"The closer two genes are together on a chromosome, the\n\nless likely it is for a recombination event to occur between the two, causing a non-random association. This is the basis for genetic linkage. The development of genetic markers allowed the theory of linkage disequilibrium (LD) to be used\nin mapping genes. Genetic markers are speci\nc genetic di␛erences between species or cultivars, and\ngenetic linkage of these markers to particular morphological traits can allow genetic markers to be used\nto represent the gene of interest (Collard et al. , 2005)."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "90CA41EEE653DCE5B03FBDDF9E1E82BF",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "genetic&marker",
+            "DNA",
+            "chromosome",
+            "phenotype",
+            "genotype",
+            "SNP",
+            "microsatellite",
+            "linkage&disequilibrium",
+            "quantitative&trait&loci",
+            "gene&mapping"
+        ],
+        "metadata": [],
+        "question": "What is a genetic marker?",
+        "subquestions": null,
+        "task_id": "90CA41EEE653DCE5B03FBDDF9E1E82BF",
+        "usage": {
+            "chatgpt": 5874,
+            "gpt-4": 4652,
+            "gpt-4-turbo-preview": 3673
+        },
+        "user_id": 2
+    },
+    "document_id": "90CA41EEE653DCE5B03FBDDF9E1E82BF",
+    "task_id": "90CA41EEE653DCE5B03FBDDF9E1E82BF"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/gen_resp05.json b/gnqa/paper1_eval/src/data/responses/general/gen_resp05.json
new file mode 100644
index 0000000..c807f03
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/gen_resp05.json
@@ -0,0 +1,156 @@
+{
+    "created_at": "2024-04-01T12:02:57.687420Z",
+    "data": {
+        "amplify": false,
+        "answer": "The process of finding a genetic marker followed by a quantitative trait loci (QTL) involves several steps. First, a population is developed for genetic mapping. This population can be a segregating population or a permanent population. The population is then genotyped using molecular markers. Next, the population is phenotyped for an interested trait. QTL analysis is then conducted using statistical procedures to find markers linked to the QTL. This involves single-marker regression across all chromosomes, where a hypothetical QTL is evaluated at the location of each marker locus. The significance of that QTL is estimated from a likelihood ratio statistic. A permutation test is then conducted to establish genome-wide significance criteria for the trait. The result is a list of marker loci that show a significant association with the trait. These loci are most likely to be near QTLs. The goal of QTL mapping is to identify regions of the genome that harbor genes relevant to a specified trait.",
+        "context": {
+            "0265286c-7bac-4ae3-831c-5bf5a4f758c6": [
+                {
+                    "document_id": "0265286c-7bac-4ae3-831c-5bf5a4f758c6",
+                    "text": "This is an open access article distributed under the Creative Commons Attribution License,\nwhich permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1. Introduction\nThe association between a complex phenotypic trait and\ngenetic markers on the chromosomes can be detected\nthrough statistical analysis, leading to the identification of\nquantitative trait loci (QTL)—regions of the chromosomes\nthat appear to be associated with the phenotype. Quantitative\ntrait loci (QTL) are expected to be associated with the genes\ncontrolling some aspects of the phenotype."
+                }
+            ],
+            "07d409f4-91f9-4701-bb39-1421845a6321": [
+                {
+                    "document_id": "07d409f4-91f9-4701-bb39-1421845a6321",
+                    "text": "Nowadays many\ndifferent cost-efficient genotyping solutions (including sequencing and Single\nNucleotide Polymorphisms arrays) have opened the way to systematic genome-wide\nfine mapping of quantitative traits (Quantitative Trait Locus or QTL mapping). The process of QTL mapping (Figure 1) consists in searching for genome regions that influence the value of a given trait. For example, identifying a QTL for\nplant height means finding a DNA region at which the plants that carry a certain\nallele tend to be significantly higher or lower than those carrying another allele."
+                }
+            ],
+            "29f5af5f-8dc7-4e53-b0fa-66d37317a3f4": [
+                {
+                    "document_id": "29f5af5f-8dc7-4e53-b0fa-66d37317a3f4",
+                    "text": "QTLs are regions within the\ngenome whose genetic variation modulates quantitatively a phenotype characteristic of\nthe particular trait under study (Lynch and Walsh, 1998). Determining the association\nbetween variations in specific disease phenotypes or a trait, with variations in genotypes\nof a reference population can be used to locate a QTL. One of the methods used for\nmapping QTLs associated with complex traits is genetic markers-trait association. Genetic markers associated with certain loci can be inherited in linkage disequilibrium. Generating populations with linked loci in disequilibrium is achieved though either\ncrosses between inbred lines, or use of the out-bred populations."
+                }
+            ],
+            "2c6178fe-c05a-42e6-aafb-7408592dcc50": [
+                {
+                    "document_id": "2c6178fe-c05a-42e6-aafb-7408592dcc50",
+                    "text": "Often, the first step in analysis of new trait\ndata is single-marker regression across all chromosomes. A hypothetical QTL is evaluated at\nthe location of each marker locus, and the significance of that QTL is estimated from a likelihood ratio statistic (LRS) (Haley and Knott,\n1992). For this analysis, WebQTL automatically does a permutation test to establish genomewide significance criteria for the trait (Churchill\nand Doerge, 1994)."
+                }
+            ],
+            "33814fad-d831-46f5-b41f-ff31626a82ca": [
+                {
+                    "document_id": "33814fad-d831-46f5-b41f-ff31626a82ca",
+                    "text": "One possible approach to facilitate this endeavor is to identify quantitative trait loci\n(QTL) that contribute to the phenotype and consequently unravel the candidate\ngenes within these loci. Each proposed candidate locus contains multiple genes and,\ntherefore, further analysis is required to choose plausible candidate genes. One of\nsuch methods is to use comparative genomics in order to narrow down the QTL to a\nregion containing only a few genes. We illustrate this strategy by applying it to\ngenetic findings regarding physical activity (PA) in mice and human."
+                }
+            ],
+            "3c69df9d-414a-420b-a513-ca3860662d57": [
+                {
+                    "document_id": "3c69df9d-414a-420b-a513-ca3860662d57",
+                    "text": "Elucidation of the molecular basis of these traits has proven\ndifficult as they are under the control of multiple genes and\ngenetic loci. The standard approach to gene identification\ninvolves mapping by linkage analysis in experimental crosses,\nand this has led to the localization in the rat genome of\nhundreds of quantitative trait loci (QTLs) underlying trait\nvariation (68). We refer to these loci as physiological quantitative trait loci (pQTLs)."
+                }
+            ],
+            "561145bb-7fe6-4941-9f02-5e6c73839100": [
+                {
+                    "document_id": "561145bb-7fe6-4941-9f02-5e6c73839100",
+                    "text": "\n\nOften, the first step in analysis of new trait data is single-marker regression across all chromosomes.A hypothetical QTL is evaluated at the location of each marker locus, and the significance of that QTL is estimated from a likelihood ratio statistic (LRS) (Haley and Knott, 1992).For this analysis, WebQTL automatically does a permutation test to establish genomewide significance criteria for the trait (Churchill and Doerge, 1994).By default, it returns a list of marker loci that show greater than sugges-tive association with the trait according to standard criteria (Lander and Kruglyak, 1995), but it will also accept user-defined criteria.Local maxima in the LRS in this list identify loci that are most likely to be near QTLs.WebQTL provides this list within a few seconds."
+                }
+            ],
+            "8b4276be-c77e-4e80-a5bb-54e9ff75d2ba": [
+                {
+                    "document_id": "8b4276be-c77e-4e80-a5bb-54e9ff75d2ba",
+                    "text": "QTLs can be identified through their genetic\nlinkage to visible marker loci with genotypes that can be readily classified [94, 97]. As\nsuch, markers that are genetically linked quantitative trait will segregate more often with\ntrait values, whereas unlinked markers will lack an association with the phenotype [94,\n98]. The principal goal of a QTL analysis is to identify all QTLs linked to a trait and\ndiscern whether phenotypic differences are mainly due to a few loci with large effects, or\nmany loci with small effects [98]."
+                }
+            ],
+            "8ec43c84-e565-4b47-a07a-0ddd99da6728": [
+                {
+                    "document_id": "8ec43c84-e565-4b47-a07a-0ddd99da6728",
+                    "text": "This is an open access article distributed under the Creative Commons Attribution License,\nwhich permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1. Introduction\nThe association between a complex phenotypic trait and\ngenetic markers on the chromosomes can be detected\nthrough statistical analysis, leading to the identification of\nquantitative trait loci (QTL)—regions of the chromosomes\nthat appear to be associated with the phenotype. Quantitative\ntrait loci (QTL) are expected to be associated with the genes\ncontrolling some aspects of the phenotype."
+                }
+            ],
+            "8fb56fda-e1a2-4407-acb2-9a5983861202": [
+                {
+                    "document_id": "8fb56fda-e1a2-4407-acb2-9a5983861202",
+                    "text": "The basic principle of classic QTL is trait segregation along with the\nmarkers and necessitated the availability of two or more genetically different\nlines corresponding with the phenotypic trait. Markers like single nucleotide\npolymorphisms (SNPs) and microsatellites are used for genotypic distinctions\n(Vignal et al. , 2002). QTL mapping is achieved in four basic steps; the first one is the measurement\nof variation for a trait in the individuals. It is a prerequisite to have the traits\nthat show phenotypic variability among the individuals (inbred strains)."
+                }
+            ],
+            "9161eaca-9841-4097-8dcd-4ea73ae81188": [
+                {
+                    "document_id": "9161eaca-9841-4097-8dcd-4ea73ae81188",
+                    "text": "\n\nOften, the first step in analysis of new trait data is single-marker regression across all chromosomes.A hypothetical QTL is evaluated at the location of each marker locus, and the significance of that QTL is estimated from a likelihood ratio statistic (LRS) (Haley and Knott, 1992).For this analysis, WebQTL automatically does a permutation test to establish genomewide significance criteria for the trait (Churchill and Doerge, 1994).By default, it returns a list of marker loci that show greater than sugges-tive association with the trait according to standard criteria (Lander and Kruglyak, 1995), but it will also accept user-defined criteria.Local maxima in the LRS in this list identify loci that are most likely to be near QTLs.WebQTL provides this list within a few seconds."
+                }
+            ],
+            "9a882703-e0ff-4bac-b11a-d99284bf7f6c": [
+                {
+                    "document_id": "9a882703-e0ff-4bac-b11a-d99284bf7f6c",
+                    "text": "Often, the first step in analysis of new trait\ndata is single-marker regression across all chromosomes. A hypothetical QTL is evaluated at\nthe location of each marker locus, and the significance of that QTL is estimated from a likelihood ratio statistic (LRS) (Haley and Knott,\n1992). For this analysis, WebQTL automatically does a permutation test to establish genomewide significance criteria for the trait (Churchill\nand Doerge, 1994)."
+                }
+            ],
+            "ae202e58-4233-4abe-9231-c17f802e8d61": [
+                {
+                    "document_id": "ae202e58-4233-4abe-9231-c17f802e8d61",
+                    "text": "Quantitative Trait Locus (QTL) mapping\nTo map QTL, we used 934 AXB/BXA genetic informative markers obtained from http://www. genenetwork.org. For all the in vitro measurements and gene expression linkage analysis, a\ngenome-wide scan was performed using R/qtl [57]. Significance of QTL logarithm-of-odds\n(LOD) scores was assessed using 1000 permutations of the phenotype data [114] and the corresponding p-values reported. For the cellular phenotypes, QTL significance was reported at a\ngenome-wide threshold corresponding to p < 0.05."
+                }
+            ],
+            "b034070a-267b-428e-8d6b-bda2b1727b51": [
+                {
+                    "document_id": "b034070a-267b-428e-8d6b-bda2b1727b51",
+                    "text": "Typically one may obtain a location known to derive from only one of the two\nparent strains that contains a chromosomal region that correlates with a trait of interest. Since the actual gene and gene product will frequently remain unknown, the region is\nreferred to as quantitative trait locus (QTL), and is simply named for the trait itself\n(Alberts & Schughart, 2010). Growing sets of strain-dependent marker locations in\nestablished RI strains are continually updated in online repositories."
+                }
+            ],
+            "b078162f-a48d-405b-b2cf-3559fc3338c8": [
+                {
+                    "document_id": "b078162f-a48d-405b-b2cf-3559fc3338c8",
+                    "text": "By definition, a\nquantitative trait locus is a chromosomal region that contains a gene, or genes, that\nregulate a portion of the genetic variation for a particular phenotype (Wehner et al. 2001). The goal of QTL mapping is to identify regions of the genome that harbour\ngenes relevant to a specified trait. QTL map locations are commonly determined by\ninitial screening of mice with specific genetic characteristics, such as recombinant\ninbred strains, the F2 of two inbred strains, or recombinant congenic strains (Flint\n2003)."
+                }
+            ],
+            "b3e8c6d4-fc8b-4a1c-b6d8-7c0252101571": [
+                {
+                    "document_id": "b3e8c6d4-fc8b-4a1c-b6d8-7c0252101571",
+                    "text": "Often, the first step in analysis of new trait\ndata is single-marker regression across all chromosomes. A hypothetical QTL is evaluated at\nthe location of each marker locus, and the significance of that QTL is estimated from a likelihood ratio statistic (LRS) (Haley and Knott,\n1992). For this analysis, WebQTL automatically does a permutation test to establish genomewide significance criteria for the trait (Churchill\nand Doerge, 1994)."
+                }
+            ],
+            "d0d6c5d6-36c6-45f1-9107-cef95df83bb3": [
+                {
+                    "document_id": "d0d6c5d6-36c6-45f1-9107-cef95df83bb3",
+                    "text": "QTL linkage studies are conducted in order to map a region or regions of the genome which\naffect a continuous or quantitative trait. In agriculture, as soon as markers linked to QTL are\nfound for economically important traits, these markers can be used for selecting individuals\nin breeding programmes. In human studies, the aim is often to identify markers indicating\ndisease susceptibility. Current techniques for measuring markers are usually relatively slow\nand laborious. Newer DNA technology, such as SNP or single nucleotide polymorphisms\n(Kwok, 2001b; Patil et al."
+                }
+            ],
+            "eae7406a-efdd-46af-b2e2-7868ce150157": [
+                {
+                    "document_id": "eae7406a-efdd-46af-b2e2-7868ce150157",
+                    "text": "Genomic regions linked to complex traits can be identified by genetic mapping\nand quantitative trait locus (QTL) analysis (Shehzad and Okuno 2014). 7\nQTL mapping\nQTL mapping with molecular markers is the first strategy in genetic studies. In plant\nbreeding, QTL mapping is an essential step required for marker-assisted selection\n(Mohan et al. 1997; Shehzad and Okuno 2014). The fundamental idea underlying QTL\nanalysis is to associate genotype and phenotype in a population exhibiting a genetic\nvariation (Broman and Sen 2009)."
+                },
+                {
+                    "document_id": "eae7406a-efdd-46af-b2e2-7868ce150157",
+                    "text": "Four steps of QTL mapping are (1) development a\n\nW\n\npopulation, (2) genotyping the population using molecular markers, (3) phenotyping the\npopulation for an interested trait, and (4) QTL analysis using statistical procedures to find\n\nIE\n\nmarkers linked to the QTL (Bernardo 2002). PR\nEV\n\nPopulations used for genetic mapping can be a segregating population (F2 and\nbackcross) or a permanent population (double haploids or recombinant inbred lines). Recombinant inbred lines (RILs) are developed by selfing of individual progenies of the\nF2 plants until homozygosity is achieved (F7-F8)."
+                }
+            ],
+            "eb90c74a-60f0-4485-b1b9-bb6665469828": [
+                {
+                    "document_id": "eb90c74a-60f0-4485-b1b9-bb6665469828",
+                    "text": "This\ntool allows systems genetic analysis of single genes or small sets of genes using a bottom-up\napproach. relations define quantitative trait loci (QTLs). Because the marker is not typically the\nactual site of the polymorphism, interpolative methods have been developed to estimate\nthe distance of the QTL from the marker and the strength of the association. Using\nmultiple-regression and model-fitting methods, the true complexity of the phenotypic\nvariation can be modeled through the consideration of multiple loci and environmental\nfactors as predictors [13]."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "241CA981DE08EC38C6A145D452CF6615",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "QTL&mapping",
+            "molecular&markers",
+            "genetic&variation",
+            "phenotype",
+            "genotype",
+            "quantitative&trait&loci",
+            "statistical&analysis",
+            "genetic&linkage",
+            "single-marker&regression",
+            "likelihood&ratio&statistic"
+        ],
+        "metadata": [],
+        "question": "Explain the process of finding a genetic marker followed by a quantitative trait loci.",
+        "subquestions": null,
+        "task_id": "241CA981DE08EC38C6A145D452CF6615",
+        "usage": {
+            "chatgpt": 5221,
+            "gpt-4": 3525,
+            "gpt-4-turbo-preview": 2564
+        },
+        "user_id": 2
+    },
+    "document_id": "241CA981DE08EC38C6A145D452CF6615",
+    "task_id": "241CA981DE08EC38C6A145D452CF6615"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/gen_resp06.json b/gnqa/paper1_eval/src/data/responses/general/gen_resp06.json
new file mode 100644
index 0000000..88fcd65
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/gen_resp06.json
@@ -0,0 +1,140 @@
+{
+    "created_at": "2024-04-01T12:04:13.564651Z",
+    "data": {
+        "amplify": false,
+        "answer": "1. Start with an initial linkage or association: This is the first step in a genetic study where a trait or disease is linked to a specific region of the genome.\n\n2. Perform Laboratory Genotyping: This involves determining the genetic variation of an individual by examining their DNA sequence using biological assays and comparing it to a standard sequence.\n\n3. Use Genomic Sequence: The role of genomic sequence is crucial at every stage. It serves as a common thread that ties all the stages together.\n\n4. Establish True Orthology: Determine the true orthology between genes in different species. If two genes are truly orthologous, their evolution closely follows patterns of speciation.\n\n5. Apply Bioinformatics: Use bioinformatics tools and techniques to analyze the data. This can be applied to sequence data from any collection of organisms.\n\n6. Understand Genome Structure and Content: Provide an overview of genome structure and content to provide a context for subsequent discussions.\n\n7. Improve DNA Sequencing Methods: Constantly work on improving DNA sequencing methods with the ultimate goal of sequencing a human genome in a single day for a cost of about US $1,000.\n\n8. Interpret the Information: The major challenge ahead is the interpretation of this information. Understand how our genes interact with each other, and how the environment contributes to the development of health and disease.\n\n9. Consider the Implications: Understand the individual and societal implications of knowing our genome sequence.\n\n10. Keep Up with Technological Advances: With further technological advances, other previously unimaginable research approaches will become real.",
+        "context": {
+            "1f5f2923-ca25-496c-b70e-5d15825c5575": [
+                {
+                    "document_id": "1f5f2923-ca25-496c-b70e-5d15825c5575",
+                    "text": "\n\nTo overcome the lack of phenotypic information in the 1000 Genomes Project, The ClinSeq Project was developed to pilot large-scale genome sequencing for research in genomic medicine at the National Institutes of Health Clinical Research Center in Bethesda, MD. 40 The study seeks to enroll 1000 individuals who will be evaluated for personal health status and family history.The project aims to:"
+                }
+            ],
+            "58714c13-954b-46b3-bd0e-69ccadd9dc6a": [
+                {
+                    "document_id": "58714c13-954b-46b3-bd0e-69ccadd9dc6a",
+                    "text": "We (Hein, Schierup and Wiuf) have published a\n300 page book on molecular population genetics titled “Gene Genealogies, Sequence Variation and Evolution” Oxford\nUniversity Press, and are presently developing a tutorial in association mapping that we hope to publish as a booklet in\n2006 and are also involved in a very large EU collaboration (Holland, Denmark, Iceland and UK) to find susceptibility\ngenes for breast and prostate cancer. In comparative genomics, the most fundamental investigation is to find genes in a pair of aligned genomes."
+                }
+            ],
+            "5edf84d0-c2d9-45eb-91b9-c35743b6a463": [
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text": "Key bioinformatic steps to\ntake a genetic study from an initial linkage or association to laboratory genotyping are illustrated. The reader should note the role of genomic sequence as a common thread through every stage\n\nregions in man (see Chapter 5). Similar issues also exist in the establishment of\ntrue orthology between genes in different species, where one is identified to play a\nrole in a disease model. If two genes are truly orthologous, their evolution closely\nfollows patterns of speciation (Fitch, 2000)."
+                },
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text":"In general terms, the approaches we describe can be applied to sequence data from any collection of organisms, but our emphasis here is primarily on\nBioinformatics for Geneticists, Second Edition. Edited by Michael R. Barnes\n2007 John Wiley & Sons, Ltd ISBN 978-0-470-02619-9 (HB) ISBN 978-0-470-02620-5 (PB)\n\n␂\nC\n106\n\nCH 6 COMPARATIVE GENOMICS\n\nquestions of relevance to human genetics. We begin, in Section 6.2 by presenting an\noverview of genome structure and content, providing a context for the subsequent\ndiscussions."
+                },
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text": "4\nAssembling a View of the\nHuman Genome\nColin A. M. Semple\nBioinformatics, MRC Human Genetics Unit, Edinburgh EH4 2XU, UK\n\n4.1 Introduction\nThe miraculous birth of the draft human genome sequence took place against\nthe odds. It was only made possible by parallel revolutions in the technologies\nused to produce, store and analyse the sequence data, and by the development of\nnew, large-scale consortia to organize and obtain funding for the work (Watson,\n1990). The initial flood of human sequence has subsided as the sequencing centres have sequenced genomes from other mammalian orders and beyond."
+                },
+                {
+                    "document_id": "5edf84d0-c2d9-45eb-91b9-c35743b6a463",
+                    "text":"This fully indexed but semi-intelligible\n\nBioinformatics for Geneticists, Second Edition. Edited by Michael R. Barnes\n2007 John Wiley & Sons, Ltd ISBN 978-0-470-02619-9 (HB) ISBN 978-0-470-02620-5 (PB)\n\n␂\nC\n4\n\nCH 1 BIOINFORMATICS CHALLENGES FOR THE GENETICIST\n\n‘book of life’ immediately began to serve as a valuable framework for integration of\ngenetic and biological data. However, knowledge of the genome sequence did not\nimmediately clarify the nature and structure of human genetic variation."
+                }
+            ],
+            "96f13e8e-633e-4728-853f-81ffbad6c58a": [
+                {
+                    "document_id": "96f13e8e-633e-4728-853f-81ffbad6c58a",
+                    "text": "\n\nMethods for DNA sequencing are constantly being improved, with the ultimate goal of sequencing a human genome in a single day for a cost of about US $1,000, an end that appears to be in sight (Hayden, 2014).In the very near future, whole-genome sequencing will be routinely available for clinical purposes, perhaps even beginning at birth.The major challenge ahead is the interpretation of this information.How do our genes interact with each other, and how does the environment contribute to the development of health and disease?What are the individual and societal implications of knowing our genome sequence?The answers to these and other important questions will unfold in the years ahead.Thus, we are truly in an era where precision medicine may soon become a reality."
+                }
+            ],
+            "a83987ea-607c-4952-a1cc-69c6f193ba2a": [
+                {
+                    "document_id": "a83987ea-607c-4952-a1cc-69c6f193ba2a",
+                    "text": "\n\nCharacteristics of genotyping and sequencing technologies"
+                }
+            ],
+            "c12e853e-4f0d-48f9-93af-15db9ad2dfae": [
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "Key bioinformatic steps to\ntake a genetic study from an initial linkage or association to laboratory genotyping are illustrated. The reader should note the role of genomic sequence as a common thread through every stage\n\nregions in man (see Chapter 5). Similar issues also exist in the establishment of\ntrue orthology between genes in different species, where one is identified to play a\nrole in a disease model. If two genes are truly orthologous, their evolution closely\nfollows patterns of speciation (Fitch, 2000)."
+                },
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text":"In general terms, the approaches we describe can be applied to sequence data from any collection of organisms, but our emphasis here is primarily on\nBioinformatics for Geneticists, Second Edition. Edited by Michael R. Barnes\n2007 John Wiley & Sons, Ltd ISBN 978-0-470-02619-9 (HB) ISBN 978-0-470-02620-5 (PB)\n\n␂\nC\n106\n\nCH 6 COMPARATIVE GENOMICS\n\nquestions of relevance to human genetics. We begin, in Section 6.2 by presenting an\noverview of genome structure and content, providing a context for the subsequent\ndiscussions."
+                },
+                {
+                    "document_id": "c12e853e-4f0d-48f9-93af-15db9ad2dfae",
+                    "text": "4\nAssembling a View of the\nHuman Genome\nColin A. M. Semple\nBioinformatics, MRC Human Genetics Unit, Edinburgh EH4 2XU, UK\n\n4.1 Introduction\nThe miraculous birth of the draft human genome sequence took place against\nthe odds. It was only made possible by parallel revolutions in the technologies\nused to produce, store and analyse the sequence data, and by the development of\nnew, large-scale consortia to organize and obtain funding for the work (Watson,\n1990). The initial flood of human sequence has subsided as the sequencing centres have sequenced genomes from other mammalian orders and beyond."
+                }
+            ],
+            "e074ba47-cd7a-4bb2-8bcb-9a15da69cc2d": [
+                {
+                    "document_id": "e074ba47-cd7a-4bb2-8bcb-9a15da69cc2d",
+                    "text": "Introduction\n\nSince the first human genome was sequenced at an estimated cost of $150 million,\nseveral advanced high-throughput techniques – some with lower costs - have come up. At\nthe same time, this resulted in a data deluge and a critical need to connect the\nheterogeneous sequencing data and associated annotations – structural and functional with the basic tenets of biology or molecular basis of development and disease."
+                }
+            ],
+            "f35e02a1-3314-4663-913f-38a3fc072aa8": [
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text": "Key bioinformatic steps to\ntake a genetic study from an initial linkage or association to laboratory genotyping are illustrated. The reader should note the role of genomic sequence as a common thread through every stage\n\nregions in man (see Chapter 5). Similar issues also exist in the establishment of\ntrue orthology between genes in different species, where one is identified to play a\nrole in a disease model. If two genes are truly orthologous, their evolution closely\nfollows patterns of speciation (Fitch, 2000)."
+                },
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text":"In general terms, the approaches we describe can be applied to sequence data from any collection of organisms, but our emphasis here is primarily on\nBioinformatics for Geneticists, Second Edition. Edited by Michael R. Barnes\n2007 John Wiley & Sons, Ltd ISBN 978-0-470-02619-9 (HB) ISBN 978-0-470-02620-5 (PB)\n\n␂\nC\n106\n\nCH 6 COMPARATIVE GENOMICS\n\nquestions of relevance to human genetics. We begin, in Section 6.2 by presenting an\noverview of genome structure and content, providing a context for the subsequent\ndiscussions."
+                },
+                {
+                    "document_id": "f35e02a1-3314-4663-913f-38a3fc072aa8",
+                    "text": "4\nAssembling a View of the\nHuman Genome\nColin A. M. Semple\nBioinformatics, MRC Human Genetics Unit, Edinburgh EH4 2XU, UK\n\n4.1 Introduction\nThe miraculous birth of the draft human genome sequence took place against\nthe odds. It was only made possible by parallel revolutions in the technologies\nused to produce, store and analyse the sequence data, and by the development of\nnew, large-scale consortia to organize and obtain funding for the work (Watson,\n1990). The initial flood of human sequence has subsided as the sequencing centres have sequenced genomes from other mammalian orders and beyond."
+                }
+            ],
+            "f8659e89-3f2f-4c83-8069-f015862b7377": [
+                {
+                    "document_id": "f8659e89-3f2f-4c83-8069-f015862b7377",
+                    "text": "\n\nAmple time was allotted to answer questions and a copy of \"A Guide to Your Genome\" (National Human Genome Research Institute 2007) was provided to further assist participants' understanding and ability to communicate results with family members or others."
+                }
+            ],
+            "f8be7949-8fa0-4730-9143-caa6161bf463": [
+                {
+                    "document_id": "f8be7949-8fa0-4730-9143-caa6161bf463",
+                    "text": "\n\nWhether within 10 or 12 (or 8) years, such inexpensive sequencing will change both research and clinical care, and progress does not need to wait even that long.The National Human Genome Research Institute (NHGRI) plans to focus a significant portion of the sequencing capacity that it supports on medical sequencing.For instance, the NHGRI and the National Cancer Institute are actively considering a Human Cancer Genome Project, 22 which would use DNA sequencing and a host of other genome technologies to gather information about the mutations and functional abnormalities found in multiple samples from many major types of cancer.Medical sequencing should also provide important insight into many other diseases.For example, sequencing all exons in X-linked mental retardation syndromes may reveal much about their etiology.Sequencing candidate genes in the extremes of the distribution of quantitative traits should also reveal much of importance about common diseases, such as coronary atherosclerosis. 23With further technological advances, other previously unimaginable research approaches will become real."
+                }
+            ],
+            "fca531d0-d45b-495f-a02c-fbd437617b20": [
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "Key bioinformatic steps to\ntake a genetic study from an initial linkage or association to laboratory genotyping are illustrated. The reader should note the role of genomic sequence as a common thread through every stage\n\nregions in man (see Chapter 5). Similar issues also exist in the establishment of\ntrue orthology between genes in different species, where one is identified to play a\nrole in a disease model. If two genes are truly orthologous, their evolution closely\nfollows patterns of speciation (Fitch, 2000)."
+                },
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text":"In general terms, the approaches we describe can be applied to sequence data from any collection of organisms, but our emphasis here is primarily on\nBioinformatics for Geneticists, Second Edition. Edited by Michael R. Barnes\n2007 John Wiley & Sons, Ltd ISBN 978-0-470-02619-9 (HB) ISBN 978-0-470-02620-5 (PB)\n\n␂\nC\n106\n\nCH 6 COMPARATIVE GENOMICS\n\nquestions of relevance to human genetics. We begin, in Section 6.2 by presenting an\noverview of genome structure and content, providing a context for the subsequent\ndiscussions."
+                },
+                {
+                    "document_id": "fca531d0-d45b-495f-a02c-fbd437617b20",
+                    "text": "4\nAssembling a View of the\nHuman Genome\nColin A. M. Semple\nBioinformatics, MRC Human Genetics Unit, Edinburgh EH4 2XU, UK\n\n4.1 Introduction\nThe miraculous birth of the draft human genome sequence took place against\nthe odds. It was only made possible by parallel revolutions in the technologies\nused to produce, store and analyse the sequence data, and by the development of\nnew, large-scale consortia to organize and obtain funding for the work (Watson,\n1990). The initial flood of human sequence has subsided as the sequencing centres have sequenced genomes from other mammalian orders and beyond."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "B756E99E279768E5604363F2A725E6BE",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "genetic",
+            "sequencing",
+            "genome",
+            "bioinformatics",
+            "human",
+            "genes",
+            "disease",
+            "research",
+            "technology",
+            "data"
+        ],
+        "metadata": [],
+        "question": "Create a how-to guide for genetic sequencing.",
+        "subquestions": null,
+        "task_id": "B756E99E279768E5604363F2A725E6BE",
+        "usage": {
+            "chatgpt": 5646,
+            "gpt-4": 3422,
+            "gpt-4-turbo-preview": 2434
+        },
+        "user_id": 2
+    },
+    "document_id": "B756E99E279768E5604363F2A725E6BE",
+    "task_id": "B756E99E279768E5604363F2A725E6BE"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/gen_resp07.json b/gnqa/paper1_eval/src/data/responses/general/gen_resp07.json
new file mode 100644
index 0000000..01cb1c3
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/gen_resp07.json
@@ -0,0 +1,134 @@
+{
+    "created_at": "2024-04-01T12:07:20.647660Z",
+    "data": {
+        "amplify": false,
+        "answer": "The length of telomeres is significant as it is associated with aging, disease, and mortality. Longer telomeres are generally associated with better health outcomes, including protection from age-related diseases, better cognitive function, and healthier lipid profiles. Shorter telomeres, on the other hand, have been linked to higher risks of heart disease, infection-related death, and other diseases. Telomere length can also be influenced by factors such as stress, with high-stress situations potentially leading to faster telomere shortening and premature aging.",
+        "context": {
+            "1ac23aae-2a51-4846-81ec-6db70ab6e5a4": [
+                {
+                    "document_id": "1ac23aae-2a51-4846-81ec-6db70ab6e5a4",
+                    "text": "\n\nIn birds, where erythrocyte telomere length (ETL) is measured, the majority of species sampled have shown no sex difference (36).Nonetheless, bird telomere dynamics are complex and, as with humans, may be affected by environment and stress.For example, a longitudinal study of black-tailed gulls (Larus crassitostris) over 2-5 years found no correlation between ETL and age or sex.Rather, ETL attrition was correlated with reduced food availability and environmental stressors (55).In a captive zebra finch (Taeniopygia guttata) population, male and female mean telomere length decreased with increasing age of the animals, but did differ between sexes (56).As these examples illustrate, the relationship between telomere length, lifespan, and sex is likely to be complex in other vertebrates."
+                },
+                {
+                    "document_id": "1ac23aae-2a51-4846-81ec-6db70ab6e5a4",
+                    "text": "\n\nComparative studies of age-related telomere attrition in other species also reveal a variety of patterns.Barrett and Richardson (36) recently summarized the comparative data available on sex differences in telomere length.They found a strong correlation between male-biased mortality and either shorter telomeres or greater telomere attrition in males across bird and mammal taxa.However, telomere length did not differ between males and females in species where females are shorter-lived than males (36), suggesting that telomere shortening is not associated with species-specific longevity in a simple linear fashion.These studies generally suffer from relatively small sample sizes and are largely cross-sectional.Further, the use of diverse assays, different tissues (eg, leukocytes in mammals vs erythrocytes in birds), and lack of standardized benchmarks for accuracy makes comparisons between studies difficult."
+                },
+                {
+                    "document_id": "1ac23aae-2a51-4846-81ec-6db70ab6e5a4",
+                    "text": "\n\nIn some organisms, there is no clear relationship between telomere length and lifespan.Age-related telomere attrition could not be detected in Daphnia pulex (57) or sea urchin species (Strongylocentrotus franciscanus and Lytechinus variegatus) (58).Studies in C. elegans examining natural variation in telomere length and experimentally manipulated telomere length detect no correlation with lifespan (59,60), and in Drosophila, which uses a telomerase-independent mechanism for telomere maintenance, there is a similar lack of correlation between longevity and telomere length (61).Similarly, data on sex differences in age-related telomere shortening are mixed.For example, in the ant species Lasius niger, the rate of telomere shortening is more rapid in short-lived males compared to longer-lived females.But, mean telomere length does not differ between the two types of females, queens and workers, despite the fact that queens live much longer than workers (up to 28 years vs 2-3 months) (62).These findings suggest that the question of how telomere shortening affects aging across species and how sex affects telomere attrition rates are complex."
+                }
+            ],
+            "5a8540de-d034-4dc4-b08b-e96e22f47ff8": [
+                {
+                    "document_id": "5a8540de-d034-4dc4-b08b-e96e22f47ff8",
+                    "text": "\n\nWith new methodologies to assess relative telomere length by Q-PCR, studies were designed to address the impact of telomere length on aging, aging associated pathologies, and mortality.One such study has correlated shorter leukocyte telomere lengths at age 60 with a three times higher risk of heart disease and an eightfold increase in risk of infection-related death (36), thereby associating measured relative cellular aging with disease and life expectancy.In a similar way, chronic stress was shown to correlate with short leukocyte telomere length, a phenomenon attributed to higher levels of oxidative stress at the cellular level (70).More recent studies have linked telomere length in smooth muscle cells with senescence and disease severity in patients with atherosclerosis (141,150).Leukocyte telomere length was also short in a cohort of similar patients and associated with a higher risk of developing occult cardiovascular disease (71).More data are needed to understand and validate the use of leukocyte telomere length as a biomarker for cardiovascular and other diseases."
+                }
+            ],
+            "5e6ad994-9cad-4b8b-903d-2d5c350e25dc": [
+                {
+                    "document_id": "5e6ad994-9cad-4b8b-903d-2d5c350e25dc",
+                    "text": "\n\nShortening of the telomeres at the ends of chromosomes has been associated with age-related disease and mortality [16][17][18].A recent study identified a common haplotype of four SNPs in the human telomerase reverse transcriptase gene (hTERT) that is enriched in centenarians and associated with longer telomere length [19].It was also shown that centenarians and their offspring maintain longer telomeres compared with controls and that longer telomeres are associated with protection from age-related diseases, better cognitive function and lipid profiles of healthy ageing [19]."
+                }
+            ],
+            "99445b90-1950-4299-815d-e912c5ae06ac": [
+                {
+                    "document_id": "99445b90-1950-4299-815d-e912c5ae06ac",
+                    "text": "\n\nNew research has indicated how social factors, such as subordination, may translate into biological effects (epel et al. 2004;Chae et al. 2014).In a now classic study, epel et al. ( 2004) examined the telomere lengths of fifty-eight healthy premenopausal women who either had a healthy child (n = 19) or were giving care to a chronically ill child (n = 39. )They measured perceived stress, years of caregiving, telomere length, and oxidative stress.They found highly statistically significant differences in telomere length between women taking care of chronically ill children and those who had healthy children.They found highly statistically significant negative correlations between telomere length and perceived stress and years of caregiving.Telomerase activity had highly statistically significant negative correlations with perceived stress and years of caregiving.Oxidative stress was highly positively correlated with perceived stress and years of caregiving.They concluded that the telomere length shortening was equivalent to 9 to 17 years of aging in the high stress group.Telomere length is considered a biomarker of aging (Finch and Kirkwood 2000).Thus, this study showed that caregiver stress had essentially aged these women 9 to 17 years compared to women who had healthy children."
+                }
+            ],
+            "c9fda811-1e12-480c-b432-987fa1d24fce": [
+                {
+                    "document_id": "c9fda811-1e12-480c-b432-987fa1d24fce",
+                    "text": "\n\nThe single, consistent predictor of the rate of telomere attrition shown in multiple adult and the few child longitudinal studies is the baseline measurement of telomere length at the start of each study.This suggests the importance of understanding predictors of telomere length prior to adulthood, as it determines in part the rate of change (Revesz et al. 2014a, b;Nordfjall et al. 2009).Moreover, longitudinal studies in adults have had found that telomere attrition rate is dependent on baseline telomere length independent of any phenotypic predictors of shortening, such as disease or demographic variables (Nordfjall et al. 2009), attesting to the importance of studies to evaluate risk factors for shortening prior to adulthood."
+                },
+                {
+                    "document_id": "c9fda811-1e12-480c-b432-987fa1d24fce",
+                    "text": "\n\nRates of decline in childhood may be particularly relevant for later chronic disease risk as shorter telomere length has been implicated in disease progression through exposure to cellular senescence, inflammatory cytokines and adipocyte hypertrophy (Raschenberger et al. 2015;Willeit et al. 2014;Monickaraj et al. 2012;Fyhrquist et al. 2013)."
+                },
+                {
+                    "document_id": "c9fda811-1e12-480c-b432-987fa1d24fce",
+                    "text": "\n\nAdult studies have also found a negative correlation with baseline telomere length, suggesting a negative feedback regulation of leukocyte telomere length (Farzaneh-Far et al. 2010;Aviv et al. 2009;Epel et al. 2008;Nordfjall et al. 2009).It is possible that while our follow-up period was shorter than Shalev et al. 2013 and adult studies, which had a minimum of 5 year intervals with the exception of Puterman et al. (2015) who followed for a one-year time period, there may be biological regulation of telomere length at 4 and 5 years of age such that shorter telomeres are more robustly maintained, whereas longer telomeres have greater rates of decline, over a short period of one year.It is unlikely that this relationship is due to assay error or regression to the mean given the consistency of our findings across studies.We have had similar findings of longer telomeres having greater rates of decline and shorter telomeres being maintained in our different studies (Farzaneh-Far et al. 2010;Epel et al. 2008;Puterman et al. 2015)."
+                },
+                {
+                    "document_id": "c9fda811-1e12-480c-b432-987fa1d24fce",
+                    "text": "\n\nWe found primarily maintenance and lengthening from 4 to 5 years of age in children, with minimal telomere attrition, indicating that most of the telomere loss happens in the first 4 years, plateauing by age 4. Lastly, we found close to 10 % of the variance in rate of change in children shared by mothers.While some of this shared variance is genetic, there are likely environmental factors that need to be further identified that impact rate of telomere length change."
+                },
+                {
+                    "document_id": "c9fda811-1e12-480c-b432-987fa1d24fce",
+                    "text": "\n\nAbstract Telomeres are the protective complexes at the end of chromosomes, required for genomic stability.Little is known about predictors of attrition in young children or the relationship between parental and child patterns of telomere change.Telomere length was assessed twice over one year, at 4 and at 5 years of age, in Latino preschool children (n = 77) and their mothers (n = 70) in whole blood leukocytes.Maternal and child rates of attrition during the same time period were compared in 70 mother-child pairs.More children showed lengthened telomeres over one year compared to their mothers and very few children showed attrition (2.6 %).Approximately 31 % of children and 16 % of mothers displayed lengthening over one year while 66 % of children showed maintenance in contrast with 74 % of mothers.The strongest predictor for child telomere length change was child's baseline telomere length (r = −0.61,p < 0.01).Maternal rate of change was associated with child rate of change (r = 0.33, p < 0.01).After controlling for child baseline telomere length, the relationship between child and maternal rate of change trended towards significance (Coeff = 0.20, 95 % CI −0.03 to 0.43; p = 0.08)."
+                }
+            ],
+            "ca76f85d-9f72-4e15-8ba9-3bf94308c449": [
+                {
+                    "document_id": "ca76f85d-9f72-4e15-8ba9-3bf94308c449",
+                    "text": "\n\nBlackburn and Epel, a health psychologist who did original research on how specific lifestyle and psychological habits can protect telomeres, published The Telomere Effect (Blackburn & Epel, 2017), in which they suggested that individuals with shorter telomeres developed diseases earlier in life (a shorter \"disease span\").What follows is the evidence from these authors, their colleagues, and other researchers describing how length of telomeres contributes to mind-body connection and healthy longevity."
+                }
+            ],
+            "eea4020b-1e14-4af9-9d67-f75d1802fdcd": [
+                {
+                    "document_id": "eea4020b-1e14-4af9-9d67-f75d1802fdcd",
+                    "text": "\n\nAs early as at the time of birth, each of the 92 telomeres of the human genome has its own characteristic length.Additionally, each telomere shortens by its individual attrition rate.In general, longer telomeres at birth are associated with higher age-dependent attrition rates and vice versa.Overall, telomere shortening appears more dynamic in males."
+                },
+                {
+                    "document_id": "eea4020b-1e14-4af9-9d67-f75d1802fdcd",
+                    "text": "\n\nIn conclusion, a combination of overall and chromosomespecifi c shorter telomeres and more pronounced age-dependent telomere erosion could be observed in males.There is a prospective clinical study strongly suggesting that longer telomeres decrease the risk of dying (Cawthon et al., 2003).With this in mind, the telomere length discrepancies between the sexes may indeed be a factor infl uencing the differences in their life expectancy."
+                },
+                {
+                    "document_id": "eea4020b-1e14-4af9-9d67-f75d1802fdcd",
+                    "text": "\n\nIn every chromosome a linear decline of telomere length with age was observed, being more pronounced in men independent of the examined chromosome arm.This might suggest that telomere length on single chromosome arms may be infl uenced by the same factors which determine overall telomere length."
+                },
+                {
+                    "document_id": "eea4020b-1e14-4af9-9d67-f75d1802fdcd",
+                    "text": "\n\nS. Mayer a S. Brüderlein a S. Perner a I. Waibel a A. Holdenried a N. Ciloglu a C. Hasel a T. Mattfeldt a K.V. Nielsen b P. Möller a a Institute of Pathology, University of Ulm, Ulm (Germany); b DakoCytomation A/S, Glostrup (Denmark) follow uniformity.In previous studies, sex-specifi c differences in telomere length and attrition rate of men and women were found (Benetos et al., 2001;Cawthon et al., 2003;Nawrot et al., 2004), suggesting gender differences in behavior of telomeres.In individual chromosome arms, telomere length was also shown not to be homogeneous (Lansdorp et al., 1996;Benn, 1997;Martens et al., 1998;Surralles et al., 1999;Hao and Tan, 2001;Londono-Vallejo et al., 2001;Graakjaer et al., 2003), some telomeres being signifi cantly shorter, others longer than the average length."
+                },
+                {
+                    "document_id": "eea4020b-1e14-4af9-9d67-f75d1802fdcd",
+                    "text": "\n\nTo date, these characteristics in telomere lengths could not be set in a biological context, as only a few groups have provided detailed information about chromosome-specifi c patterns of telomere distribution (Lansdorp et al., 1996;Graakjaer et al., 2003).Whether accumulation of short telomeres (Martens et al., 2000;Londono-Vallejo et al., 2001) or rather the shortest telomere of one specifi c chromosome arm (Hemann et al., 2001) elicits senescence, remains an open question so far."
+                },
+                {
+                    "document_id": "eea4020b-1e14-4af9-9d67-f75d1802fdcd",
+                    "text": "\n\nIn recent literature, there are hints that the average telomere length may be higher in women and that their annual shortening rate may be somewhat lower (Vaziri et al., 1993;Rufer et al., 1998;Jeanclos et al., 2000), but these reported differences failed to reach statistical signifi cance except for one study (Jeanclos et al., 2000).Here, we provide compelling evidence that this is indeed the case."
+                },
+                {
+                    "document_id": "eea4020b-1e14-4af9-9d67-f75d1802fdcd",
+                    "text": "\n\nIt is generally accepted that telomeres shorten during DNA replication both in vitro and in vivo.In individuals, short telomeres are considered to be a sign of advanced age.Cawthon and coworkers (2003) showed that telomere shortening in humans likely contributes to mortality, supporting the hypothesis that they might act as a mitotic clock (Allsopp et al., 1992).Telomere length dynamics, however, does not seem to Abstract.During aging, telomeres are gradually shortened, eventually leading to cellular senescence.By T/C-FISH (telomere/centromere-FISH), we investigated human telomere length differences on single chromosome arms of 205 individuals in different age groups and sexes.For all chromosome arms, we found a linear correlation between telomere length and donor age.Generally, males had shorter telomeres and higher attrition rates.Every chromosome arm had its individual age-specifi c telomere length and erosion pattern, resulting in an unexpected heterogeneity in chromosomespecifi c regression lines.This differential erosion pattern, however, does not seem to be accidental, since we found a correlation between average telomere length of single chromosome arms in newborns and their annual attrition rate.Apart from the above-mentioned sex-specifi c discrepancies, chromosome arm-specifi c telomere lengths were strikingly similar in men and women.This implies a mechanism that arm specifi cally regulates the telomere length independent of gender, thus leading to interchromosomal telomere variations."
+                }
+            ],
+            "f3610ccc-2831-42f6-a3d3-1a0feeba4902": [
+                {
+                    "document_id": "f3610ccc-2831-42f6-a3d3-1a0feeba4902",
+                    "text": "\n\nShortening of the telomeres at the ends of chromosomes has been associated with age-related disease and mortality [16][17][18].A recent study identified a common haplotype of four SNPs in the human telomerase reverse transcriptase gene (hTERT) that is enriched in centenarians and associated with longer telomere length [19].It was also shown that centenarians and their offspring maintain longer telomeres compared with controls and that longer telomeres are associated with protection from age-related diseases, better cognitive function and lipid profiles of healthy ageing [19]."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "F91D61921F6212793795027C274D0E7E",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "telomeres",
+            "telomere&length",
+            "DNA",
+            "chromosomes",
+            "aging",
+            "senescence",
+            "leukocyte",
+            "telomerase",
+            "oxidative&stress",
+            "centenarians"
+        ],
+        "metadata": [],
+        "question": "What is the significance of the length of telomeres?",
+        "subquestions": null,
+        "task_id": "F91D61921F6212793795027C274D0E7E",
+        "usage": {
+            "chatgpt": 7797,
+            "gpt-4": 4400,
+            "gpt-4-turbo-preview": 3459
+        },
+        "user_id": 2
+    },
+    "document_id": "F91D61921F6212793795027C274D0E7E",
+    "task_id": "F91D61921F6212793795027C274D0E7E"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/gen_resp08.json b/gnqa/paper1_eval/src/data/responses/general/gen_resp08.json
new file mode 100644
index 0000000..6914fd7
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/gen_resp08.json
@@ -0,0 +1,142 @@
+{
+    "created_at": "2024-04-01T12:09:26.502626Z",
+    "data": {
+        "amplify": false,
+        "answer": "The traits are determined by the combination of genes from both the sperm and the egg. This process involves meiosis, where each gamete (sperm and egg) contributes one chromosome to each pair, resulting in a zygote with a full complement of 23 chromosome pairs. The process of recombination or crossing over, where similar DNA sequences from the paired chromosomes swap genetic material, also plays a crucial role in determining the traits of the offspring. This results in a shuffling of genetic material and contributes to the genetic variation seen among offspring.",
+        "context": {
+            "2e22b52d-1a13-48d8-aab8-01a1840aa749": [
+                {
+                    "document_id": "2e22b52d-1a13-48d8-aab8-01a1840aa749",
+                    "text": "\n\nSelection could occur at multiple levels, from germ cell generation and propagation to fertilization and early embryonic growth.Chromosomal abnormalities, including aneuploidy, were found in 10-20% of spermatozoa and oocytes (20) and in the cleaved embryo, with a 21% rate of abnormalities in preimplantation embryos (21).These findings led to a model for natural selection against chromosome abnormalities (21).Selection extends to the end of gestation: Only approximately 30% of all conceptions result in a live birth, with more than half of aborted fetuses containing chromosomal abnormalities (22), a number likely to be an underestimate because of technological limitations in measuring all possible mutations.But even in the very small fraction of germ cell duos that survive this withering genome attack and result in a live birth, a number of severe de novo mutations will still be found (23).The data on gross chromosomal alterations suggest that overall, mutation frequency early in life is very high.The functional consequence, however, is limited because of selection.Somewhat surprisingly, this picture points toward an initial decline in genomic alterations, allowing the adult individual to acquire a somatic genome optimally equipped to provide function."
+                }
+            ],
+            "3f8db22e-d5f9-44ba-8f78-fc77ccf024ce": [
+                {
+                    "document_id": "3f8db22e-d5f9-44ba-8f78-fc77ccf024ce",
+                    "text": "The phenotype of\nthe F1 hybrids is compared to those of the parental inbred strains to reveal\ndominance or semi-dominance relationships between the alleles that a¡ect the\nphenotype. Phenotypic di¡erences between reciprocal F1 hybrids indicate that\none or more of the following factors may a¡ect the trait: (1) sex linkage (X- or Ylinked traits), (2) genomic imprinting of QTLs that a¡ect the phenotype, (3)\nprenatal maternal e¡ects (e¡ects of intrauterine environment), and/or (4)\npostnatal maternal or paternal e¡ects (e¡ects of maternal and/or paternal\nparenting behaviour on o¡spring)."
+                }
+            ],
+            "606c59c5-5ae4-47e9-b3eb-58afa55669d1": [
+                {
+                    "document_id": "606c59c5-5ae4-47e9-b3eb-58afa55669d1",
+                    "text": "Sex brings harmful alleles together into the\nsame genetic background, allowing selection to more efficiently purge them from\nthe population and potentially producing some offspring that are fitter than either\nparent. However, the benefit of recombining deleterious mutations may depend on the\nnature of the epistatic interactions between them. The mutational deterministic hypothesis\n(Kondrashov 1988) depends partly on this epistasis."
+                },
+                {
+                    "document_id": "606c59c5-5ae4-47e9-b3eb-58afa55669d1",
+                    "text": "In most plants and animals, sex\nis a necessary component of reproduction, and the question for evolutionary biologists\nis why reproductive mechanisms have evolved that way. In one of the experiments\ndescribed next, evolutionary geneticists have nevertheless devised a way to compare\nevolution with and without recombination in the obligately sexual fruit fly."
+                },
+                {
+                    "document_id": "606c59c5-5ae4-47e9-b3eb-58afa55669d1",
+                    "text": "This disparity in investment is the basis for the twofold cost: asexual\nfemales hypothetically could transmit twice as many alleles at the same cost. In most plants and animals, mates tend to be unrelated, leading to outcrossing. But\nsex usually also involves the basic process of physical recombination: the breakage and\nreunion of two different DNA or RNA molecules. Of these two processes, recombination\nis clearly the more widespread feature of sexual reproduction. A variety of reproductive\nsystems, such as selfing and automixis, involve recombination but not outcrossing. In\ncontrast, relatively few reproductive systems have outcrossing without recombination."
+                }
+            ],
+            "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa": [
+                {
+                    "document_id": "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa",
+                    "text": "\n\nCrossing over-The swapping of genetic material that occurs in the germline.During the formation of egg and sperm cells, also known as meiosis, paired chromosomes from each parent align so that similar DNA sequences from the paired chromosomes cross over one another.Crossing over results in a shuffling of genetic material and is an important cause of the genetic variation seen among offspring.This process is also known as meiotic recombination."
+                },
+                {
+                    "document_id": "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa",
+                    "text": "\n\nThe reason for the rarity of these mutations is natural selection: If the mutations result in disorders that decrease health and reproductive fitness, they will eventually be eliminated from a population.In exceptional cases, mutations may cause both beneficial and detrimental consequences, resulting in opposing forces of positive selection and negative selection that may cause the mutations to be preserved at nonrare frequencies in a population.For example, the HbS mutation in the HBB gene (which produces the β subunit of hemoglobin) causes sickle cell disease when present in both alleles, a detrimental consequence, but protects against malaria when present in 1 allele, a beneficial consequence, ensuring that the mutation persists in populations in areas of the world where malaria is endemic.Genes are passed from parents to offspring via the process of meiosis by which gametes, the egg cells in the mother and the sperm cells in the father, are generated.Ordinarily, each cell has 23 pairs of chromosomes; the gametes have 23 unpaired chromosomes.In meiosis, the 23 pairs are split so that each gamete receives 1 chromosome from each pair (Figures 8 and 9).Two gametes (egg and sperm) ultimately join into a single cell, the zygote, which has the full complement of 23 chromosome pairs restored.If all goes well, the zygote gives rise to a live offspring."
+                },
+                {
+                    "document_id": "6c0eb981-977a-42f5-a3b1-136e1ccfc5aa",
+                    "text": "\n\nRecombination (meiotic recombination)-The swapping of genetic material that occurs in the germline.During the formation of egg and sperm cells, also known as meiosis, paired chromosomes from each parent align so that similar DNA sequences from the paired chromosomes recombine with one another.Recombination results in a shuffling of genetic material and is an important cause of the genetic variation seen among offspring.Also known as crossing over."
+                }
+            ],
+            "98ce73c6-a53b-486f-8326-4b0bd47ec22e": [
+                {
+                    "document_id": "98ce73c6-a53b-486f-8326-4b0bd47ec22e",
+                    "text": "\n\nIn the generation of gametes, crossing over regularly occurs, and genetic information is swapped between members of a chromosome pair.That doesn't matter within inbred animals, because the swapped parts are identical.In an F 1 animal, however, the chromosomes of a particular pair are genetically different, one each having come from each parent.Each gamete produced will be unique, as will be each F 2 zygote formed by uniting of the gametes from two F 1 parents.An F 2 group thus provides for expression of some genetic variability.This variability is limited to the allelic differences existing between the parent strains of the F 1 s, so that another F 2 , derived from different inbred strains, will express different genetic differences."
+                }
+            ],
+            "a440a3fa-74e7-4fd8-8a7f-d0391300d6ed": [
+                {
+                    "document_id": "a440a3fa-74e7-4fd8-8a7f-d0391300d6ed",
+                    "text": "Sex brings harmful alleles together into the\nsame genetic background, allowing selection to more efficiently purge them from\nthe population and potentially producing some offspring that are fitter than either\nparent. However, the benefit of recombining deleterious mutations may depend on the\nnature of the epistatic interactions between them. The mutational deterministic hypothesis\n(Kondrashov 1988) depends partly on this epistasis."
+                },
+                {
+                    "document_id": "a440a3fa-74e7-4fd8-8a7f-d0391300d6ed",
+                    "text": "In most plants and animals, sex\nis a necessary component of reproduction, and the question for evolutionary biologists\nis why reproductive mechanisms have evolved that way. In one of the experiments\ndescribed next, evolutionary geneticists have nevertheless devised a way to compare\nevolution with and without recombination in the obligately sexual fruit fly."
+                },
+                {
+                    "document_id": "a440a3fa-74e7-4fd8-8a7f-d0391300d6ed",
+                    "text": "This disparity in investment is the basis for the twofold cost: asexual\nfemales hypothetically could transmit twice as many alleles at the same cost. In most plants and animals, mates tend to be unrelated, leading to outcrossing. But\nsex usually also involves the basic process of physical recombination: the breakage and\nreunion of two different DNA or RNA molecules. Of these two processes, recombination\nis clearly the more widespread feature of sexual reproduction. A variety of reproductive\nsystems, such as selfing and automixis, involve recombination but not outcrossing. In\ncontrast, relatively few reproductive systems have outcrossing without recombination."
+                }
+            ],
+            "b014e368-d0d5-4eff-a9af-abd4a4ed6d29": [
+                {
+                    "document_id": "b014e368-d0d5-4eff-a9af-abd4a4ed6d29",
+                    "text": "\n\nAberrant recombination patterns on chromosomes that have missegregated have also been identified as an important factor, in both male and female gametes (Table I).This is because recombination together with cohesion of sister chromatids establish the unique 'bivalent' chromosome structure where homologous partner chromosomes are tethered together, a configuration that is critical for their accurate segregation in meiosis I (Fig. 2A).The remarkable feature is that recombination occurs in foetal oocytes whereas chromosome segregation takes place decades later (Fig. 2A).Since mammalian oocytes are arrested at the G2/M transition (or dictyate stage), this raises the intriguing question of how the bivalent is maintained until the meiotic divisions."
+                }
+            ],
+            "b04f2221-de28-4c4b-893e-9da982ff864c": [
+                {
+                    "document_id": "b04f2221-de28-4c4b-893e-9da982ff864c",
+                    "text": "Traditionally, it has been agreed that the\nﬁnal sex of an individual (phenotypic sex)\ndepends on two sequential processes: the sex\ndetermination system of the species and the\ngonad differentiation process (Valenzuela,\n2008). However, recently, these two seemingly\ndistinct processes are viewed as part of a general process leading to gonad formation and\nsex ratios (Sarre et al. , 2004; Quinn et al. , 2011;\nUller and Helanterä, 2011)."
+                },
+                {
+                    "document_id": "b04f2221-de28-4c4b-893e-9da982ff864c",
+                    "text": "However, we expect that\nonly at this level, the most signiﬁcant contributions brought by integrating epigenetics will be\nmade. Concluding Remarks and Future\nProspects\nFish sex ratios are the result of a complex interaction between genetic, biochemical, and environmental interactions. The ultimate result\nof these interactions at the individual level is\ngender: male or female. However, at the population level, the combination of sex determination and differentiation sets the sex ratio. In\nturn, sex ratios deﬁne the reproductive capacity\nof populations and, if sex growth dimorphism\nexists, also the growth characteristics, something very important in an aquaculture context."
+                }
+            ],
+            "dcc71b11-5668-4274-9f35-d9b7f01695a2": [
+                {
+                    "document_id": "dcc71b11-5668-4274-9f35-d9b7f01695a2",
+                    "text": "Obehav is, in turn, influenced by offspring genes\nand environment (Ogene and Oenvir respectively). Hence, indirect genetic effects (blue arrows)\nand direct genetic effects (red arrow) are important influencers of behaviour. B) Parentoffspring conflict theory predicts that parental resource investment and offspring solicitation\nbehaviours are influenced by the fitness benefit to a focal individual (O), cost to a social\npartner such as a sibling (S1 and S2) or parent (P), and by their coefficient of relatedness\n(black arrows). 42\nFigure 2: Genomic imprinting can result in divergent phenotypes from the same\ngenotype. A) A paternally imprinted gene, i.e. maternally expressed."
+                }
+            ],
+            "e7030862-fb3c-48cc-bbd1-e30ac5ed5864": [
+                {
+                    "document_id": "e7030862-fb3c-48cc-bbd1-e30ac5ed5864",
+                    "text": "Because of the small contribution, through the sperm, of\nthe paternal transcriptome to the fertilized zygote, and because of the stronger maternal contribution\nto child rearing in most model organisms, parental effects are typically thought of as synonymous with\nmaternal effects, although true paternal effects are known to exist (Rando, 2012). Maternal effects have been shown to be important during embryonic development, leading to\ndifferences in the birth weight of mice depending on the genotype of the mother (Cowley et al. ,\n1989; Wolf et al. , 2011)."
+                },
+                {
+                    "document_id": "e7030862-fb3c-48cc-bbd1-e30ac5ed5864",
+                    "text": "Therefore, the resulting phenotypic patterns lag a generation\nbehind the genetic transmission of the causal variants. The most well-studied parental genetic effects\nare caused by deposition of maternal transcripts into the egg prior to fertilization, resulting in\ndifferences in early embryonic development depending on the genotype of the mother. Certain genes\nhave also been shown to respond to maternal influence after birth through genetically defined\nmaternal behaviors (Weaver et al. , 2004)."
+                }
+            ],
+            "f253e087-e030-40a8-8400-3b6bf50c1fd6": [
+                {
+                    "document_id": "f253e087-e030-40a8-8400-3b6bf50c1fd6",
+                    "text": "The phenotype of\nthe F1 hybrids is compared to those of the parental inbred strains to reveal\ndominance or semi-dominance relationships between the alleles that a¡ect the\nphenotype. Phenotypic di¡erences between reciprocal F1 hybrids indicate that\none or more of the following factors may a¡ect the trait: (1) sex linkage (X- or Ylinked traits), (2) genomic imprinting of QTLs that a¡ect the phenotype, (3)\nprenatal maternal e¡ects (e¡ects of intrauterine environment), and/or (4)\npostnatal maternal or paternal e¡ects (e¡ects of maternal and/or paternal\nparenting behaviour on o¡spring)."
+                }
+            ],
+            "f9d93e23-292c-44b3-8f27-dc1b4d6b494f": [
+                {
+                    "document_id": "f9d93e23-292c-44b3-8f27-dc1b4d6b494f",
+                    "text": "It was believed by many that for each trait variant we should expect to find a\ncorresponding genetic change, or „gene for‟ that trait. Through historical happenstance the\nrelationship between genes and traits was set up and treated as if it were one-to-one. But the\nproduction of a trait involves not only genes, but also their interactions with each other and the\nenvironment, and chance."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "4FD9E20567FA6D4E536E3BA72E3CB09F",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "sperm",
+            "egg",
+            "traits",
+            "genetic",
+            "recombination",
+            "meiosis",
+            "chromosomes",
+            "mutations",
+            "selection",
+            "zygote"
+        ],
+        "metadata": [],
+        "question": "Once a sperm combines with an egg, what determines how traits are passed onto the resulting lifeform?",
+        "subquestions": null,
+        "task_id": "4FD9E20567FA6D4E536E3BA72E3CB09F",
+        "usage": {
+            "chatgpt": 5281,
+            "gpt-4": 3689,
+            "gpt-4-turbo-preview": 2717
+        },
+        "user_id": 2
+    },
+    "document_id": "4FD9E20567FA6D4E536E3BA72E3CB09F",
+    "task_id": "4FD9E20567FA6D4E536E3BA72E3CB09F"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/gen_resp09.json b/gnqa/paper1_eval/src/data/responses/general/gen_resp09.json
new file mode 100644
index 0000000..0c70fd3
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/gen_resp09.json
@@ -0,0 +1,154 @@
+{
+    "created_at": "2024-04-01T12:11:33.748564Z",
+    "data": {
+        "amplify": false,
+        "answer": "Genetic tracing is matrilineal due to the inheritance of mitochondrial DNA (mtDNA), which is passed from mother to all her children without any admixture from the father. This allows for a clear lineage tracing through the maternal line. In contrast, Y-DNA is passed from father to son, allowing for patrilineal tracing, but it does not provide information about the genetic contributions of other ancestors in a family tree.",
+        "context": {
+            "0376df42-5df7-4966-8f0d-e254b86ae743": [
+                {
+                    "document_id": "0376df42-5df7-4966-8f0d-e254b86ae743",
+                    "text": "distinguishing prenatal\nfrom postnatal maternal effects, see below). Maternal effects can\naccount for a large proportion of phenotypic variance, especially\nduring early life, and for some traits explain more variation than\ndirect genetic effects [33, 97, 99, 100, 102–115]. However, maternal and offspring genotype are correlated (i.e. half their genes are\nshared), and in inbred lines they are fully confounded, thus separating the effects of their respective genotypes is difficult. To remove\nthis confounding effect cross-fostering has been used, both in the\nlaboratory and in the field [119, 131]."
+                }
+            ],
+            "0a30029f-fa8f-49e3-9a68-82d1a8ae3157": [
+                {
+                    "document_id": "0a30029f-fa8f-49e3-9a68-82d1a8ae3157",
+                    "text": "Using genetic markers, the pattern of inheritance can be tracked through\nfamilies. For example, by analyzing a marker linked to the eye color gene\nin several generations, it is possible to determine from which grandparents a\nchild has inherited its eye color alleles. More importantly, ﬁnding a marker\nlinked to a disease can lead to location of the faulty gene causing the disease. Finding the gene is very valuable in the search for the cure. The distance between two loci can be expressed either as physical or genetic distance."
+                }
+            ],
+            "0e27d15f-e4a2-4902-b4a4-1e72c4202346": [
+                {
+                    "document_id": "0e27d15f-e4a2-4902-b4a4-1e72c4202346",
+                    "text": "\n\nAlthough autosomal SNPs are commonly used as genetic markers to infer ancestry or race/ethnicity membership, haploid such as mitochondria, Y-DNA, and X-lined markers are also important to provide separate stories of ancestry of individuals from paternal and maternal sides [42,43].Therefore, genetic structure created due to autosomal markers could be different from those of lineage markers (often influenced by political, social, and migration history of individuals/populations).mitochondrial DNA or mtDNA haploid is the maternally inherited mitochondrial genome (mtDNA) [44].All children inherit mtDNA from their mother, with no admixture from the father.Like Y-line DNA, mtDNA is passed intact from one generation to the next but through maternal line."
+                },
+                {
+                    "document_id": "0e27d15f-e4a2-4902-b4a4-1e72c4202346",
+                    "text": "\n\na) Autosomal DNA (testing both sexes) markers: autosomal DNA tests utilize DNA from the 22 pairs of autosomal chromosomes.Autosomal DNA is inherited from both parents.Autosomal testing provides percentages of ethnicity using autosomal DNA SNP test (i.e., ancestry informative markers), and it is the most commonly used test to infer ancestry across diploid genome.b) Y-DNA or Y-SNPs (paternal line testing) markers: a haploid Y-DNA is the paternally inherited non-recombining portion of the Y chromosome, and it tests only for males.The Y-DNA testing tests the Y chromosome which is passed intact from father to son with no DNA from the mother.Y-DNA testing can then be used to trace direct paternal line.Y-DNA remains the same in each generation, allowing us to compare surname from different regions to see if we are from the same family.Y-line testing does not indicate anything about the contributions of the other ancestors in a family tree.In other words, you could be 3/4th Native American, with only the direct paternal line being European, and this test would tell you nothing at all about those other three Native lines.When testing the Y-chromosome, there are two types of tests, short tandem repeat (STR) and SNP markers.STR tests are best for recent ancestry while SNP tests tell about more ancient ancestry.c) Mitochondrial DNA (maternal line testing) markers:"
+                }
+            ],
+            "14a15ff3-706d-44be-aca5-4bad24a5e4ec": [
+                {
+                    "document_id": "14a15ff3-706d-44be-aca5-4bad24a5e4ec",
+                    "text": "\n\nAdditional information about past breeding practices can be gleaned by quantifying the number of reproductive males and females in a population.This can be achieved by comparing levels of genetic diversity between sex chromosomes, autosomes and mtDNA 99 .In cattle, for example, gene flow from aurochs is evident in the autosomes but is absent in mtDNA 41 .This has been interpreted as a management strategy that may have involved allowing insemination of domesticated females by wild bulls 41,100 .In horses, a comparison of the levels of diversity of the Y chromosome and the autosomal chromosomes demonstrated that some cultures allowed fewer males to breed and instead selected specific stallion bloodlines 55 .This male-oriented breeding strategy was not practised by the Romans and only became increasingly prominent in the past 1,000 years as a result of the growing influence of Oriental stallions (Arabian, Persian and Turkmen) 101 ."
+                }
+            ],
+            "2420b221-94fa-40ac-8bfd-55e90d7c1c23": [
+                {
+                    "document_id": "2420b221-94fa-40ac-8bfd-55e90d7c1c23",
+                    "text": "\n\nDr Ring: What makes the maternal gene so peculiar compared to the paternal?Dr Cookson: If you look in the epidemiologic sense, many studies show that there is increased risk of allergic disease if the mother is affected.However, very few studies have actually set out to test that formally and most of them might suffer from some sort of selection bias because the mother is more likely to be aware of her symptoms and feel guilty, and so on.It is very difficult to explain.Is it genomic imprinting, where the gene is only active when transmitted through the mother?I do not think all of these genes would be imprinted, though it is possible.It also seems that there are effects of the maternal phenotype.The maternal phenotype, if the mother is affected or unaffected, determines the strength of the maternal effect.Again, if a gene was imprinted, you would not expect maternal phenotype to be important.So, I think that this has something to do with maternal/fetal interaction, either through the placenta or shortly after birth.There is the issue of immune conflict between mother and child.At the same time, the mother is trying to prime the infant's immune system."
+                }
+            ],
+            "25622783-ac42-479d-8698-905a7523c38a": [
+                {
+                    "document_id": "25622783-ac42-479d-8698-905a7523c38a",
+                    "text": "Genetic and Genomic Discovery Using Family Studies\n\nIngrid B. Borecki, PhD; Michael A. Province, PhD G enetic studies traditionally have been performed on sets of related individuals, that is, families.Mendel's early studies in sweet peas (Pisum sativum) on the inheritance patterns of discrete traits from parents with specific mating types to offspring has shed light on the basic mechanisms of inheritance, including the fundamental laws of segregation of discrete factors (genes) from parents to offspring and the cosegregation of genes that are closely located on a chromosome (linkage).The distribution of traits within families exhibited mathematical segregation ratios in offspring from known mating types.These expected segregation ratios have been used as an important discovery tool in the study of human diseases in pedigrees, providing evidence for a multitude of single-gene disorders.Furthermore, in some cases, trait cosegregation with genetic markers with known positions provides mapping information that enables localization and, ultimately, identification of the relevant causative gene."
+                }
+            ],
+            "46f190d1-f784-45cd-be09-d43a27ec4063": [
+                {
+                    "document_id": "46f190d1-f784-45cd-be09-d43a27ec4063",
+                    "text": "In fact, this idea has been pursued before in the\ncontext of signatures of reproductive isolation and shown to reveal\npatterns consistent with epistatic gene interactions that arise in the\nshape of Dobzhansky-Muller incompatibilities [10,11]. In contrast to the mouse data, the available human genotypes\nwere derived from outbred, ethnically distinct populations. In this\ncase pairs of functionally interacting genes can be detected\nfollowing a slightly different approach."
+                }
+            ],
+            "5c9aed30-dec7-49af-9401-3ec6fa0e1334": [
+                {
+                    "document_id": "5c9aed30-dec7-49af-9401-3ec6fa0e1334",
+                    "text": "Family Structure\n\nThe first re-identification method (FAMILY) employs genealogical data accompanying genomic data.Genealogies, rich in depth and structure, permit the construction of complex familial relationships.Consider a simple family structure of two parents and one child.Since the parental genders are guaranteed, there exist 2 variants of this structure, since the child's gender is either male or female.When disease status is taken into account, it is represented as a Boolean variable; either an individual afflicted or not afflicted.In this aspect, all three family members can be represented as three attributes {Father, Mother, Child}, and there exist (father's disease status)*(mother's disease status)*(child's disease status)*(child's gender) = 2*2*2*2 = 16 possible family-disease combinations.In reality, pedigrees are much more robust than a simple nuclear family.For example, a three-generation family of two children per family permits on the order of 10 5 distinct variants of the family-disease structure and 10 6 individuals that could be uniquely characterized.The number of combinationsk is larger when supplementary information, such as living status or medical/genetic features, is considered. 16e ability to determine unique family structures is only one part of the re-identification process.These structures must be linked to identifiable information, which, in many instances, is publicly available in the form of various genealogical databases.These databases are accessible both offline and via the World Wide Web.For example, genealogical records are available in many public databases, including ,Ancestry.com>,,Infospace.com>,,RootsWeb.com>,,GeneaNet.com>,,FamilySearch.org>, and ,Genealogy.com>. {From such data, it is not difficult to construct family structures and, with such information in hand, an adversary can link disease-labeled family structures to named individuals."
+                }
+            ],
+            "6041a1eb-5376-4e06-a4df-0563f1b8a724": [
+                {
+                    "document_id": "6041a1eb-5376-4e06-a4df-0563f1b8a724",
+                    "text": "\n\nFig. 3. Illustrations of the three CEU pedigrees (black) showing how genetic information from distant patrilineal relatives (arrow; red, patrilineal lines) can identify individuals.Filled squares represent sequenced individuals.To respect the privacy of these families, only abbreviated versions are presented.The sex of the CEU grandchildren was randomized.The numbers of grandchildren are not given."
+                }
+            ],
+            "748cfe7e-e4f2-453f-8575-50dfe84e2538": [
+                {
+                    "document_id": "748cfe7e-e4f2-453f-8575-50dfe84e2538",
+                    "text": "\n\nWhen I was in high school, I remember often trying to match my friends to their parents at various school functions and being surprised at how easy this was.As human geneticists, in spite of the enormous advances being made in our field, we still cannot answer many of the everyday questions that we are asked, such as: \"Why does he look just like his mother? \"Max Perutz [1], in a recent editorial comment in the New Scientist entitled \"The Molecular Biology of the Future,\" suggested some questions, for, as he put it, \"an examination in some future century. \"Here are two of them: (1) \"The time has come\" the Walrus said, \"To talk of many things ...And why the sea is boiling hot And whether pigs have wings. \"Calculate the amount of genetic information this would require in megacricks."
+                }
+            ],
+            "83a4ab87-f4a5-40b9-9297-5a3596e3636f": [
+                {
+                    "document_id": "83a4ab87-f4a5-40b9-9297-5a3596e3636f",
+                    "text": "Using genetic markers, the pattern of inheritance can be tracked through\nfamilies. For example, by analyzing a marker linked to the eye color gene\nin several generations, it is possible to determine from which grandparents a\nchild has inherited its eye color alleles. More importantly, ﬁnding a marker\nlinked to a disease can lead to location of the faulty gene causing the disease. Finding the gene is very valuable in the search for the cure. The distance between two loci can be expressed either as physical or genetic distance."
+                }
+            ],
+            "86b86235-b7a8-4dfc-be13-d119dc31b377": [
+                {
+                    "document_id": "86b86235-b7a8-4dfc-be13-d119dc31b377",
+                    "text": "In\ncontrast, genomic imprinting is due to epigenetic changes within\nthe individual causing differential gene expression characterized\nby either complete or partial silencing of one parental allele\n(Barlow, 2011; Abramowitz and Bartolomei, 2012; Ashbrook and\nHager, 2013). As both mothers and fathers had contact with the\npups in our study, our observed PGEs could come from either\nparent. Among quantitative USV traits only peak amplitude of call\ndisplayed a possible parent-of-origin effect. For call number, call\nduration, mean peak frequency, and all morphological traits,\nthere were no significant parent-of-origin effect in reciprocal\nF1 females. In contrast, Thornton et al."
+                }
+            ],
+            "915ee14c-df93-4482-966a-fbf3db2c11ea": [
+                {
+                    "document_id": "915ee14c-df93-4482-966a-fbf3db2c11ea",
+                    "text": "\n\nAnother way of avoiding stratification is to use family-based samples.This approach has several theoretical advantages: as well as being immune to stratification 114 , these samples can be used to determine whether an allele has different effects on disease when it is inherited maternally or paternally 115 , and DISCORDANT SIB designs [116][117][118] can control for the effects of shared environment.Furthermore, more complex family-based designs are possible 119 that might allow combined association and linkage analysis 120 , and family-based association tests have also been developed for quantitative traits [94][95][96][97][98] .However, pure sibship-based association studies are underpowered relative to case-control studies 107,116,117 , and the requirement for living parents might introduce an age-of-onset bias towards younger patients for diseases that usually arise late in life.Furthermore, family-based samples are often much more difficult to collect, particularly if larger pedigrees are sought.Finally, the most commonly used family-based design, the TRANSMISSION DISEQUILIBIRIUM TEST (TDT; see REF. 114) is susceptible to technical artefacts (see below)."
+                }
+            ],
+            "a12388bc-0a2c-4cf4-aa39-39eebabe9a7e": [
+                {
+                    "document_id": "a12388bc-0a2c-4cf4-aa39-39eebabe9a7e",
+                    "text": "\n\nBecause mtDNA is not subjected (as far as we know) to sexual recombination and crossover at the time of nuclear meiosis, nature must call on other means to ensure that inevitable germ plasm mtDNA mutations (Medvedev, 1981) are not transmitted.These mutations among primary oocytes, on the face of it, can be expected to increase with time, that is with maternal age.Empirical data on this question are incomplete and conflicting, being mostly confined so far to searches for deletions rather than point mutations (Chen et al., 1995;Keefe et al., 1995).It is inevitable, however, that there will be such mutations and that there must therefore be a reliable physiological mechanism (a) for giving an opportunity for back-mutations to occur, (b) for selecting in favor of those back-mutations (thus preserving the genome) and in favor of rare advantageous mutations, and (c) for preventing the spread of persistent harmful mutations through the population -mutations that are too slight (or too late in origin) to have escaped intraovarian culling.The sheer conservation of the mitochondrial genome over 0.5 billion years or more, despite a mutation rate estimated at 10 -20 times that of nuclear DNA, is ample reason to conclude that such a physiological purification process must exist."
+                }
+            ],
+            "ab1a324f-3c9c-4b41-bb1d-5d5ca216a001": [
+                {
+                    "document_id": "ab1a324f-3c9c-4b41-bb1d-5d5ca216a001",
+                    "text": "To scrutinize the polygenic networks underlying complex diseases, however, mouse resources\nthat are optimized to study the actions of isolated genetic loci on\na fixed background will be insufficient on their own. For example, predisposition to the metabolic syndrome is inherited in\na non-Mendelian fashion stressing genetic heterogeneity and\nmultigenetic pathogenesis (Nandi et al. , 2004). With the reawakening as to the extraordinary genetic resources and phenotypic\ndiversity archived in extant inbred strains, however, a foundation\nis in place for tracking down these complex traits and quantitative trait loci (QTL)."
+                }
+            ],
+            "b58ddaa8-9d41-4dc5-97d7-aca64de3685b": [
+                {
+                    "document_id": "b58ddaa8-9d41-4dc5-97d7-aca64de3685b",
+                    "text": "Otherwise, tens of thousands or markers will appear significant in\nthe genome-wise association studies using up to one million genetic\nmarkers. Approaches to control for stratification include using of\nself report of ancestry or genetically derived principle components\nin the analysis. For studies using inbred mouse lines, a cladogram\nwhich is a hierarchical grouping based on phylogenetic analysis of\nstrain relatedness can be created to subdivide inbred strains into\nmore genetically homogenous subgroups."
+                }
+            ],
+            "dc2f6b02-5c9a-4764-b70e-d2321135e148": [
+                {
+                    "document_id": "dc2f6b02-5c9a-4764-b70e-d2321135e148",
+                    "text": "\n\nAlthough bilateral descent is the norm in Western societies, it is not universal and there is variation with cultural practices around lineage.In certain societies, individuals place greater importance on (and have greater knowledge about) one side of the family than another (unilineal descent).Thus, individuals in patrilineal groups trace relationships through males only so that your father's brother's children are members of your family, but not your father's sisters (Kottak, 2007).They are members of their husband's group or family.Efforts to create a family pedigree may be hampered if the participant is not familiar with her mother's relatives, but her mother's brother's children (her cousins) may be able to supplement her overall family history.Knowledge about the cultural system of unilineal descent avoids assuming the universality of bilateral descent.Cultural beliefs such as these also have implications in the conduct of genetic research in terms of confidentiality and autonomy (Benkendorf et al., 1997;Wertz, 1997).One cannot assume that the named proband is in a position to speak for the extended family in agreeing to participate in any genetic research (DudokdeWit et al., 1997)."
+                }
+            ],
+            "dcc71b11-5668-4274-9f35-d9b7f01695a2": [
+                {
+                    "document_id": "dcc71b11-5668-4274-9f35-d9b7f01695a2",
+                    "text": "In particular in polygynous species, a female’s\noffspring may have different fathers and are thus more closely related through the maternal\nthan the paternal line. Therefore, any fitness cost to mothers, such as increased provisioning\nand care, affect maternally derived genes more strongly than paternally derived genes,\nleading to the silencing of the maternal copy (i.e. paternal expression) of genes that increase\nresource transfer. 5. Coadaptation between offspring and maternal traits\nThe genetics of the co-evolution of parental and offspring traits has been investigated using\nquantitative genetics models and in several empirical studies (Agrawal et al."
+                },
+                {
+                    "document_id": "dcc71b11-5668-4274-9f35-d9b7f01695a2",
+                    "text": "In this\nscenario, genes expressed in parents will be selected for their effects on parental behaviour\nwhile genes expressed in offspring will be selected for their effects on influencing parental\nbehaviour. At the genetic level the predicted conflict between paternal and maternal genomes is\nthought to have led to the evolution of genomic imprinting (monoallelic gene expression). Genomic imprinting effects are good examples of offspring genetic effects on maternal care\nbecause of the impact on the quality of maternal care and level of resource provisioning (e.g. Li et al. , 1999)."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "9520AB55F5C8D714F196867C1A9C4702",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "mtDNA",
+            "patrilineal",
+            "matrilineal",
+            "genetic&markers",
+            "autosomal&DNA",
+            "Y-DNA",
+            "mitochondrial&DNA",
+            "genomic&imprinting",
+            "ancestry",
+            "haploid"
+        ],
+        "metadata": [],
+        "question": "Why is genetic tracing matrilineal rather than patrilineal?",
+        "subquestions": null,
+        "task_id": "9520AB55F5C8D714F196867C1A9C4702",
+        "usage": {
+            "chatgpt": 7241,
+            "gpt-4": 4620,
+            "gpt-4-turbo-preview": 3661
+        },
+        "user_id": 2
+    },
+    "document_id": "9520AB55F5C8D714F196867C1A9C4702",
+    "task_id": "9520AB55F5C8D714F196867C1A9C4702"
+}
diff --git a/gnqa/paper1_eval/src/data/responses/general/gen_resp10.json b/gnqa/paper1_eval/src/data/responses/general/gen_resp10.json
new file mode 100644
index 0000000..11ff807
--- /dev/null
+++ b/gnqa/paper1_eval/src/data/responses/general/gen_resp10.json
@@ -0,0 +1,152 @@
+{
+    "created_at": "2024-04-01T12:16:23.401343Z",
+    "data": {
+        "amplify": false,
+        "answer": "The difference between X and Y DNA is not explicitly discussed in the context of determining QTLs in the provided text. However, in general, X and Y chromosomes are different in size and gene content, which can be identified through genetic sequencing. In the context of QTL studies, these differences could potentially influence the traits being studied. However, the specific process of how this is done in QTL mapping is not detailed in the provided text.",
+        "context": {
+            "13036fc5-c31c-4d21-a5f0-5ddfe11663d2": [
+                {
+                    "document_id": "13036fc5-c31c-4d21-a5f0-5ddfe11663d2",
+                    "text": "Genetic mapping in\nmouse strains enhances the power of detecting modifier genes and identifying complex\ngenetic interactions. Genomewide quantitative trait locus (QTL) analysis, as described in\nmore detail below, represents a promising approach to detect genetic variants that are\nassociated with specific phenotypes and interact with each other. 16\nACCEPTED MANUSCRIPT\nIn experimental crosses of two (inbred) strains the first generation (F1) of\noffsprings is genetically heterozygous but equal. Then in the next generation (F2) the\n\nPT\n\nstrain-specific genetic information is distributed across the genomes of their progeny and\n\nRI\n\neach offspring is genetically unique."
+                }
+            ],
+            "1fb6e4db-79c1-49c9-a358-3414f6a674da": [
+                {
+                    "document_id": "1fb6e4db-79c1-49c9-a358-3414f6a674da",
+                    "text": "Second, and perhaps more\nimportant, is the difference in the size and types of the\ngenetic reference populations. In our previous study, we\nmapped the QTL with 36 F2 mice that were genotyped at\n82 markers. In the current study, by comparison, we were\nable to map QTLs after examining 342 mice from 55 strains\nthat were genotyped at approximately 4000 markers."
+                }
+            ],
+            "27e14ff3-b5a5-4f60-80a2-eaa2ab53e991": [
+                {
+                    "document_id": "27e14ff3-b5a5-4f60-80a2-eaa2ab53e991",
+                    "text": "This contrast can be exploited to identify subregions that underlie the trans-QTLs [67]. SNPs were counted for all four pairs of parental haplotypes—B\nvs D, B vs H, B vs C, and L vs S—and SNP profiles for the four\ncrosses were compared (figure 6). Qrr1 is a highly polymorphic\nPLoS Genetics | www.plosgenetics.org\n\n8\n\nNovember 2008 | Volume 4 | Issue 11 | e1000260\nQTL Hotspot on Mouse Distal Chromosome 1\n\nFigure 5. QTL for aminoacyl-tRNA synthetases in distal Qrr1."
+                }
+            ],
+            "3485665e-4e33-481a-943e-d0fcb7c2f2ac": [
+                {
+                    "document_id": "3485665e-4e33-481a-943e-d0fcb7c2f2ac",
+                    "text": "The traditional approach to QTL mapping is to use\ntwo strains that differ maximally in the phenotype as\nparental strains for genetic crosses, with the following\ncaveats. QTL analysis based on a single cross will most\nlikely reflect only a small portion of the net genetic\nvariation, and QTL detection will be limited to regions\nwhere the two progenitor strains have functional polymorphisms. Data from multiple crosses, or from an HS,\nwill overcome this limitation and can also be used to\nreduce QTL intervals [5,30]."
+                }
+            ],
+            "3f8db22e-d5f9-44ba-8f78-fc77ccf024ce": [
+                {
+                    "document_id": "3f8db22e-d5f9-44ba-8f78-fc77ccf024ce",
+                    "text":"These candidate genes are then sequenced in the two parental inbred\nstrains looking for sequence di¡erences in coding or regulatory regions. After ¢ne mapping the QTL interval and shortening the list of plausible\ncandidate polymorphisms, the major challenge remains ␁ proving de¢nitively\nwhich nucleotide polymorphism underlies the QTL. The most direct proof\nwould be replacing one strain’s allele with another strain’s allele (creating a\nFIG. 1. Intercross breeding strategy for mapping quantitative trait loci (QTLs). On the right, the parental, F1 hybrid, and intercross (F2) mouse\ngenerations are depicted."
+                }
+            ],
+            "516cc395-4e7c-4371-9444-24edb56a7233": [
+                {
+                    "document_id": "516cc395-4e7c-4371-9444-24edb56a7233",
+                    "text": "Furthermore, splicing QTLs\n(sQTLs) rather than eQTLs could comprise the molecular mechanism linking DNA variants with YFP53; thus, sQTL analysis could uncover genes that would not normally be\ndetected at the level of differential gene expression (DGE),53 and thus, a differentially\n\n181\n182\n\nMolecular-Genetic and Statistical Techniques for Behavioral and Neural Research\n\nFigure 8.5 Schematic for immediate, rapid ﬁne mapping in select F2 recombinants of the RCC-F2\ncross. Top panel: Genome-wide signiﬁcant QTL (green trace; red dashed line ¼ signiﬁcance threshold;\nblue vertical lines ¼ Bayes credible interval)."
+                }
+            ],
+            "7dc4230d-c0a3-484b-9fb4-04d5ff09956b": [
+                {
+                    "document_id": "7dc4230d-c0a3-484b-9fb4-04d5ff09956b",
+                    "text": "Interval-specific haplotype analysis\nApproximately 97% of the genetic variation between\ninbred mouse strains is ancestral [22], so regions of\nidentity by descent (IBD) between two strains used to\ndetect a QTL are highly unlikely to contain the causal\ngenetic polymorphism underlying the QTL [28]. For\nexample, a cross between C57BL/6J and A/J mice detected\nwww.sciencedirect.com\n\na blood pressure QTL on Chr 1 [7]."
+                }
+            ],
+            "80eb54fe-0d83-4300-9fba-e17ce5d1e5b4": [
+                {
+                    "document_id": "80eb54fe-0d83-4300-9fba-e17ce5d1e5b4",
+                    "text": "Interval-specific haplotype analysis\nApproximately 97% of the genetic variation between\ninbred mouse strains is ancestral [22], so regions of\nidentity by descent (IBD) between two strains used to\ndetect a QTL are highly unlikely to contain the causal\ngenetic polymorphism underlying the QTL [28]. For\nexample, a cross between C57BL/6J and A/J mice detected\nwww.sciencedirect.com\n\na blood pressure QTL on Chr 1 [7]."
+                }
+            ],
+            "92fa8f50-2923-41a1-812b-32d931c71684": [
+                {
+                    "document_id": "92fa8f50-2923-41a1-812b-32d931c71684",
+                    "text": "At present, the BXD panel is composed of 80 different strains that all have been\nfully genotyped.26 Variation in any quantifiable trait can be associated with the\nsegregation of parental alleles, and linkage genetics can map this variation to\nquantitative trait loci (QTLs), thereby identifying the genomic region(s) affecting\nthat trait. An overview of the QTL mapping approach is depicted in Figure 2. Classical QTL analysis has permitted the identification of loci that are\nassociated with variation in HSC traits."
+                }
+            ],
+            "9981a933-8fdf-4107-a6fd-3f9ef71f5d08": [
+                {
+                    "document_id": "9981a933-8fdf-4107-a6fd-3f9ef71f5d08",
+                    "text": "In general,\nlinking genetic variation with trait variation identifies QTL and a significant linkage of\nphenotype and genotype suggest that the DNA status helps to determine trait expression. As stated above, mouse QTL studies provide distinct advantages over human studies\nin the examination of genetic causes of a quantitative trait (e.g. alcoholism), even in the\nabsence of specific hypotheses regarding its aetiology or candidate genes."
+                },
+                {
+                    "document_id": "9981a933-8fdf-4107-a6fd-3f9ef71f5d08",
+                    "text": "The progenitor mouse strains\nshould have sufficient variation for the traits of interest and they should be genetically diverse\nenough to enable genetic mapping (BENNETT et al. 2006; FLINT 2003; GRISEL 2000). The\nsample size required for the identification of QTL depends largely on the effect size that a\nQTL contributes to phenotypes on interest. Inference about QTL can be made if one or more\ngenetic markers are over- or underrepresented in the analysed individuals. Genotyping is\noften done by means of microsatellite markers, which contains mono, di-, tri-, or\ntetranucleotide tandem repeats flanked by specific sequences (Figure 4a)."
+                },
+                {
+                    "document_id": "9981a933-8fdf-4107-a6fd-3f9ef71f5d08",
+                    "text": "This comparison gives information about the reliability of the observed genotype\ninformation: The more the marker locations differ between the two maps (which signifies\nvariation in marker positions), the higher the possibility of genotyping errors. QTL mapping was done in several stages to identify loci acting individually and QTL that\ninteracted, either additively or epistatically. To determine individually-acting QTL, a singleQTL genome scan was conducted with the function scanone."
+                }
+            ],
+            "9b830769-1d42-4dce-b529-4e07902c0743": [
+                {
+                    "document_id": "9b830769-1d42-4dce-b529-4e07902c0743",
+                    "text": "Importantly, whereas\nthese studies required substantial labor, time, and resources, X-QTL is a quick and easy\napproach to achieve a comparable level of genetic dissection. The levels of complexity\nobserved here (e.g. 14 loci explaining 70% of the genetic variance for 4-NQO resistance) are\nstill dramatically lower than those seen in for some human traits in GWAS (e.g. 40 loci\nexplaining 5% of the variance for height 2,5). One obvious explanation is the difference in\nexperimental designs (line crosses vs. population association studies), but differences in\ngenetic architectures among species and traits may also contribute."
+                }
+            ],
+            "a64778cd-bff8-43dd-b5a3-d608ab8f4828": [
+                {
+                    "document_id": "a64778cd-bff8-43dd-b5a3-d608ab8f4828",
+                    "text": "The method uses two pieces of information: mapping data from crosses that\ninvolve more than two inbred strains and sequence variants in the progenitor strains within the interval\ncontaining a quantitative trait locus (QTL). By testing whether the strain distribution pattern in the progenitor strains is consistent with the observed genetic effect of the QTL we can assign a probability that any\nsequence variant is a quantitative trait nucleotide (QTN). It is not necessary to genotype the animals except\nat a skeleton of markers; the genotypes at all other polymorphisms are estimated by a multipoint analysis."
+                }
+            ],
+            "c2efeeee-f71a-4292-8240-80a4518f820d": [
+                {
+                    "document_id": "c2efeeee-f71a-4292-8240-80a4518f820d",
+                    "text": "The method uses two pieces of information: mapping data from crosses that\ninvolve more than two inbred strains and sequence variants in the progenitor strains within the interval\ncontaining a quantitative trait locus (QTL). By testing whether the strain distribution pattern in the progenitor strains is consistent with the observed genetic effect of the QTL we can assign a probability that any\nsequence variant is a quantitative trait nucleotide (QTN). It is not necessary to genotype the animals except\nat a skeleton of markers; the genotypes at all other polymorphisms are estimated by a multipoint analysis."
+                }
+            ],
+            "d1f04d58-2589-4183-aee4-569820dae052": [
+                {
+                    "document_id": "d1f04d58-2589-4183-aee4-569820dae052",
+                    "text": "Genotyping all the individual progeny for\nmarkers that show allelic variation between the parental strains (either single nucleotide polymorphisms or simple sequence repeats) will allow the detection of associations between trait values and marker genotype, and in this way demonstrate to which\nset of markers a QTL is linked. To reduce the genotyping effort, selective genotyping\nof the individuals at the extremes of the phenotypic spectrum can be performed (20,23). Although these three approaches are in general considered to be the best to detect and\nmap QTL, they have several disadvantages for quantitative traits involving HSC."
+                }
+            ],
+            "da485354-fcdc-49b8-9a41-0f673610156a": [
+                {
+                    "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                    "text": "So, how do you go about planning and performing a QTL study, and how\ndo you identify the responsible gene within a QTL that you have identified? Generally, one starts by performing a strain survey to find two parental inbred\nstrains that have a markedly different trait. One can now look up many different\ntraits of inbred mice online at the Mouse Phenome Database (http://phenome. jax.org/pub-cgi/phenome/mpdcgi?rtn=docs/home). However, the trait you may\nwant to study may not be present in wild type mice, so you may want to cross\na mutant (or genetically engineered) strain onto several inbred strains."
+                },
+                {
+                    "document_id": "da485354-fcdc-49b8-9a41-0f673610156a",
+                    "text": "QTL Theory and Planning\nThe theory behind the most basic form of QTL mapping is based upon intercrossing two inbred strains. The mouse genome consists of 19 pairs of autosomes (non sex-determining chromosome) and the X and Y chromosomes. In\nthe example shown in Fig. 18.1, we are intercrossing stain A (shown with a\nblack chromosome pair) with strain B (shown with a white chromosome pair). The initial F1 (filial generation 1) mice are true hybrids, with each individual\n\nFrom: Molecular Biomethods Handbook, 2nd Edition."
+                }
+            ],
+            "f253e087-e030-40a8-8400-3b6bf50c1fd6": [
+                {
+                    "document_id": "f253e087-e030-40a8-8400-3b6bf50c1fd6",
+                    "text":"These candidate genes are then sequenced in the two parental inbred\nstrains looking for sequence di¡erences in coding or regulatory regions. After ¢ne mapping the QTL interval and shortening the list of plausible\ncandidate polymorphisms, the major challenge remains ␁ proving de¢nitively\nwhich nucleotide polymorphism underlies the QTL. The most direct proof\nwould be replacing one strain’s allele with another strain’s allele (creating a\nFIG. 1. Intercross breeding strategy for mapping quantitative trait loci (QTLs). On the right, the parental, F1 hybrid, and intercross (F2) mouse\ngenerations are depicted."
+                }
+            ],
+            "f4e26cf0-d214-41bf-b392-9c63a903b0b8": [
+                {
+                    "document_id": "f4e26cf0-d214-41bf-b392-9c63a903b0b8",
+                    "text": "QTL mapping studies then\nseek to detect the polymorphisms underlying the complex traits of interest by\nscanning for alleles that co-vary with\nthe traits. Similar experiments also can be conducted with special derivatives of inbred\nstrains known as recombinant inbred\n(RI) mice. These animals are derived\nby cross-breeding two or more distinct\nparental strains (which often diverge\nwidely for the trait of interest), followed\nby inbreeding of the offspring for several\ngenerations (Bailey 1971). Given the\ncorrect breeding strategy, this method\n1\n\nThis is an issue faced by GWASs researchers when classifying\nsamples as cases or controls."
+                }
+            ]
+        },
+        "data_source": [],
+        "document_id": "1F8BA9562D43754B872EEE810B6D5676",
+        "engine": "gpt-4",
+        "first_load": false,
+        "focus": "api",
+        "keywords": [
+            "QTL",
+            "DNA",
+            "mapping",
+            "genotype",
+            "phenotype",
+            "inbred&strains",
+            "polymorphism",
+            "allele",
+            "genetic&variation",
+            "quantitative&trait&loci"
+        ],
+        "metadata": [],
+        "question": "How does one tell the difference between X and Y DNA, with respect to DNA tracing and determining QTLs?",
+        "subquestions": null,
+        "task_id": "1F8BA9562D43754B872EEE810B6D5676",
+        "usage": {
+            "chatgpt": 4992,
+            "gpt-4": 3589,
+            "gpt-4-turbo-preview": 2616
+        },
+        "user_id": 2
+    },
+    "document_id": "1F8BA9562D43754B872EEE810B6D5676",
+    "task_id": "1F8BA9562D43754B872EEE810B6D5676"
+}
author	SoloDShelby	2024-07-19 14:41:40 +0300
committer	SoloDShelby	2024-07-19 14:41:40 +0300
commit	3fa31b50af2861382fbe2c76406f5a04c3fefc93 (patch)
tree	34d581648b0e0d3fc8dbe6577752a4fd433a3258 /gnqa/paper1_eval/src/data/responses/general
parent	74616897e30c7daafe5e74d34073466464921316 (diff)
download	gn-ai-3fa31b50af2861382fbe2c76406f5a04c3fefc93.tar.gz