{
  "question": [
    "List genes related to asthma with their phenotype descriptions.",
    "Which types of mouse studies are popular in genenetwork, where a type an ailment, e.g. asthma, allergies, aging, heart failure, diabetes, glaucoma?",
    "Do we find significant quantitative trait loci in the studies for diabetes?",
    "What environmental factors effect mice that also influence diabetes?",
    "List mouse studies that involve insulin.",
    "What is the typical weight of a mouse liver?",
    "How are C57BL/6 and DBA/2 different?",
    "What behavioural QTLs have been found in mice?",
    "Where do I look for genes that regulate hippocampal neural stem cell proliferation?",
    "What does QTL mean?"
  ],
  "answer": [
    "The text mentions two severe asthma clusters, SC2 and SC3, but does not specify individual genes. SC2 is characterized by high T2 inflammation, high FeNO, bronchoalveolar lavage and blood eosinophilia, and up-regulated expression of T2 signature and mast cell genes. SC3 is characterized by lower levels of T2 clinical biomarkers and gene expression, a later age of onset, increased incidence of nasal polyposis, and higher levels of neutrophilic inflammation.",
    "Mouse studies popular in genenetwork often focus on ailments such as diabetes, glaucoma, obesity-associated diabetes, and metabolic diseases. These studies utilize genetically modified mouse models, inbred mouse models, and polygenic models. They also use specific strains like DBA/2J, Goto-Kakizaki (GK) rat, and KK mice.",
    "Yes, the studies identified significant quantitative trait loci associated with both type 1 and type 2 diabetes. These include loci such as TCF7L2, DNER, SRR, HNF1A, KCNQ1, CDKN2A/CDKN2B, JAZF1, CDC123, CAMK1D, TSPAN8, LGR5, THADA, ADAMTS9, NOTCH2, and others. However, the significance of some loci varied across different populations and studies.",
    "Several environmental factors can affect mice and influence diabetes. These include the stress response, which can be greater in male mice and can confound feeding behavior, the unique gut microbiota of rodents from different production facilities, cage position, single versus group housing, the skill level of the researcher, ambient room temperature, and the type of cage bedding. Diet, particularly high-fat feeding, can also induce obesity and diabetes. Additionally, the intrauterine environment can impact the subsequent development of diabetes amongst offspring.",
    "1. Diabetes incidence study where mice were tested for diabetes monthly by blood glucose and weekly by urine assessment.\n2. Studies involving transgenic/knockout animal models of type 2 diabetes to study the role of genes and their effects on peripheral insulin action.\n3. Study involving male type-2 diabetic db/db mice and genetic control non-diabetic db/ mice.\n4. Study involving young adult mice fed a high-fat or Western diet to elicit DIO and insulin resistance.\n5. Study involving Akita mouse genotyping.\n6. Study involving 12-week-old male type 2 diabetic db/db mice and contemporary control wild-type mice.\n7. Study involving transgenic mice to create specific models of type 1 and type 2 diabetes.\n8. Study involving AKITA mice derived from a C57BL/6NSlc mouse with a spontaneous mutation in the insulin 2 gene.\n9. Study monitoring mice for the development of diabetes.",
    "The typical weight of a mouse liver can vary, but in the context provided, it can weigh up to 4.5 grams in a 40 gram mouse and 1.2 grams in a 20 gram normal mouse.",
    "C57BL/6 and DBA/2 mice differ in several ways. C57BL/6 mice are more accurate in tasks with greater demands and make fewer impulsive responses. They also have larger brain weights and are more resistant to radiation-induced genomic instability. DBA/2 mice, on the other hand, make fewer omission errors, respond more vigorously to certain influenza viruses, and perform better in less spatially demanding tasks. They also have larger cortical areas when adjusted for brain weight and are more sensitive to acute nephrotoxicity. Genetic differences between the two strains affect various responses including activity, memory, learning tasks, and responses to alcohol and opioids.",
    "Several behavioral QTLs have been found in mice. These include QTLs affecting aggressive behaviors, which have been identified in strains such as the Turku aggressive (TA) and non-aggressive (TNS) strains, the NC900 and NC100 strains, and the short attack latency (SAL) and long attack latency (LAL) strains. Other QTLs have been associated with traits like anxiety-related behavior, seizure, hippocampal volume, and alcohol preference. Additionally, QTLs related to alcohol, morphine or other drugs, painful arthritis, emotionality/anxiety, and seizure susceptibility have been mapped. There are also QTLs that influence exploratory behavior in mice.",
    "You can look for genes that regulate hippocampal neural stem cell proliferation in the results of gene expression profiling studies, such as the one mentioned in the text. Specifically, the study identified LRP6 as a novel regulator of adult hippocampal neurogenesis. Other genes like Lef1, Mtdh, and Chchd8 may also be involved.",
    "QTL stands for Quantitative Trait Locus. It is a region of the genome that is linked to a trait and contains a gene or genes that regulate a portion of the genetic variation for a particular phenotype. QTLs are associated with quantitative traits, which are traits that have measurable phenotypic variation due to genetic and/or environmental influences."
  ],
  "contexts": [
    [
      "  We present an analytical technique designed to test a priori defined gene sets (for example, pathways) for association with disease phenotypes.We apply this method to gene expression profiles of human diabetic muscle, identifying a set of genes whose expression is correlated with insulin resistance and aerobic capacity.These results suggest hypotheses about pathways contributing to human metabolic disease and, more generally, show the value of incorporating information about functional relationships among genes in the analysis of microarray data.",
      "  Pathway and gene ontology analysis for select phenotypes and envionmental factors showing GxE interactions.",
      "  Next, the genes that correlated with FeNO (n = 549) were used to objectively cluster asthma subjects into subgroups.In agreement with Moore et al., most of the severe asthma patients clustered into 2 subject clusters (SCs) (SC2 and SC3).One severe asthma cluster (SC2) had high T2 inflammation, as evidence by a high FeNO, bronchoalveolar lavage and blood eosinophilia, and up-regulated expression of T2 signature and mast cell genes.The other severe asthma cluster (SC3) had lower levels of T2 clinical biomarkers and gene expression, in addition to a later age of onset, increased incidence of nasal polyposis and higher levels of neutrophilic inflammation.Roughly 1/2 of all asthma subjects had evidence of high T2 inflammatory response (by clinical biomarkers and gene expression), confirming the prior findings of Woodruff et al. in a more severe and steroid-treated patient population.In general, both severe asthma clusters (SC2 and SC3) were older and more obese than the other non-severe subclusters.Further, both of the severe SCs demonstrated suppression of genes associated with cilia function, neuronal function, cell adhesion and wound repair.These findings suggested that airway epithelial defense, repair, neuronal function are an integral part of a healthy epithelial layer and perhaps prevention of severe asthma.",
      "These genes are high priority candidates, although we acknowledge that causal variants may lie in non-coding regions. For each of these high priority candidates we then examined which GO:biological processes (Consortium, 2015) and KEGG pathways (Kanehisa et al. , 2012) the gene was annotated as being part of, and highlighted those which may relate to our phenotypes. We also reviewed known effects of mutations using the Mouse Genome Informatics (MGI) Phenotypes, Alleles and Disease Models Search (www.informatics.jax.org/allele) (Bello et al. , 2015).",
      "Results were displayed as a matrix with all phenotypes/diseases associated with  173  mouse models and human genes found for the candidate gene list. 174 175  2.6. Expression-phenotype correlations  176  For each gene discovered after filtering, an adequate probe within the well-curated INIA Amygdala  177  Cohort Affy MoGene 1.0ST (Mar11) RMA, Hippocampus Consortium M430v2 (Jun06) PDNN,  178  VCU BXD Prefrontal Cortex M430 2.0 (Dec06) RMA, INIA Hypothalamus Affy MoGene 1.0ST  179  (Nov10), and INIA Adrenal Affy MoGene 1.0ST (Jun12) RMA Databases was identified using  180  GeneNetwork (http://www.genenetwork.org; Williams and Mulligan, 2012)).",
      "  The GeneNetwork website contains extensive phenotypic datasets ranging from behavioral to morphological to pharmacological.To identify phenotypes associated with Gsto1 variation, we queried the BXD phenotype database in GeneNetwork, which contains nearly 3000 phenotypes, to look for the phenotypes that are most closely related to hippocampal expression of Gsto1 (probe set 1416531_at).",
      "  To examine known causal genes that have been reported in the literature, including related genes and pathways, a gene list was generated consisting of 6264 genes categorized by disorders, pathways, expression, AmiGO terms, and other into 26 sublists (supplemental data).This list was manually collected from different database sources covering all aspects of insulin-and glucose-related genes and disorders.This was done through an extensive literature review using PubMed, Ovid\u00ae, GeneCards\u00ae, and the National Center for Biotechnology Information (NCBI).Gene and protein expression databases such as BioGPS and The Human Protein Atlas were used.Protein interactions and gene network databases, such as AmiGO, BioGRID, GIANT, KEGG, and Reactome, were also used.Knockout mouse databases, such as MGI and IMPC, were also used.However, filtering against the gene list will not replace the manual screening for all variants called; therefore, we did not consider the results of our gene list alone.Once the raw data were obtained, they were filtered and investigated individually.As shown in Fig. 1, mutations went through serial steps ending up with a single nucleotide polymorphism mutation as a potential explanation.Pathogenicity scores were determined by SIFT, PolyPhen-2, PROVEAN, and PhD-SNP.",
      "Chesler, E. J., Wang, J., Lu, L., Qu, Y., Manly, K. F., and Williams, R. W. (2003). Genetic correlates of gene expression in recombinant inbred strains: a relational model system to explore neurobehavioral phenotypes. Neuroinformatics 1, 343\u2013357. doi:10.1385/NI:1:4:343. Denny, J. C., Ritchie, M. D., Basford, M. A., Pulley, J. M., Bastarache, L., Brown-Gentry, K., et al. (2010). PheWAS: demonstrating the feasibility of a phenome-wide scan to discover genedisease associations. Bioinformatics 26, 1205\u20131210. doi:10.1093/bioinformatics/btq126. Farrar, C. A., Zhou, W., and Sacks, S. H. (2016). Role of the lectin complement pathway in kidney transplantation. Immunobiology 221, 1068\u20131072. doi:10.1016/j.imbio.2016.05.004. Gene Ontology Consortium (2015).",
      "Exploring genes, molecules, and phenotypes is easily accomplished using GeneNetwork. In this manuscript we will outline some simple use cases, and show how a small number of plausible candidate genes can be identified for an immune phenotype. 1. Data Once you have navigated to genenetwork.org, there are two ways to search for data in GN. The first is to use the global search bar located at the top of the page (Figure 1). This is a new feature in GN that allows researchers to search for genes, mRNAs, or proteins across all of the datasets.",
      "Protein interaction data: There is a growing body of protein-interaction data and this data is a useful extension to inferences of functional interaction between disease gene candidates and co-expressed genes. Ontologies for Functional Annotation: This project will lead to a small subset of genes of interest for asthma and AD.. Ontologies are key in making automated and vocabulary controlled statements about function and it will be interesting to interface the analytical framework presented in the proposal with contemporary advances in gene ontology methodology.",
      "A network or interaction model will be generated using methods of graphical modelling with both inhouse data and public databases to propose predictive models for epithelial cells and characterise critical molecular interactions within asthma and AD biology. Finally, supporting and extending methodologies from above will contribute to (E) Future Directions of the study and include interfacing and data exchange with contemporary public databases. D(a) Disease Association and eQTL Mapping Mapping the human genome for regions and positions that are responsible for disease susceptibility and differential gene expression is central to this project.",
      "For example, time series data sets potentially capture relationships and dependencies of gene expression within and between time points which may suggest causative co-regulation. These dependencies and interactions could be better uncovered using statistical modelling approaches such as Bayesian model based methods that aim to identify co-expressed clusters of genes under a model of temporal dependence between observations, that is utilising gene expression measures in time to better judge cluster membership11,12. Secondly, the asthma and AD expression dataset of sibpairs inherently contains underlying structures of shared genetic disease risk.",
      "Genes are arranged based on their genetic positions, and genes annotated to be involved in the module are colored red. Genes with absolute GMAS over 0.268 are considered significantly associated. DDT, BOLA3, and ARID1A are labeled. B, Venn diagram of novel genes associated with respiratory electron transport module in human, mouse and rat. 707 genes were predicted to be mito-proteins by G-MAD in all three species.",
      "Chesler, E. J., Wang, J., Lu, L., Qu, Y., Manly, K. F., and Williams, R. W. (2003). Genetic correlates of gene expression in recombinant inbred strains: a relational model system to explore neurobehavioral phenotypes. Neuroinformatics 1, 343\u2013357. doi:10.1385/NI:1:4:343. Denny, J. C., Ritchie, M. D., Basford, M. A., Pulley, J. M., Bastarache, L., Brown-Gentry, K., et al. (2010). PheWAS: demonstrating the feasibility of a phenome-wide scan to discover genedisease associations. Bioinformatics 26, 1205\u20131210. doi:10.1093/bioinformatics/btq126. Farrar, C. A., Zhou, W., and Sacks, S. H. (2016). Role of the lectin complement pathway in kidney transplantation. Immunobiology 221, 1068\u20131072. doi:10.1016/j.imbio.2016.05.004. Gene Ontology Consortium (2015).",
      "Exploring genes, molecules, and phenotypes is easily accomplished using GeneNetwork. In this manuscript we will outline some simple use cases, and show how a small number of plausible candidate genes can be identified for an immune phenotype. 1. Data Once you have navigated to genenetwork.org, there are two ways to search for data in GN. The first is to use the global search bar located at the top of the page (Figure 1). This is a new feature in GN that allows researchers to search for genes, mRNAs, or proteins across all of the datasets.",
      "6  Phenotype-matched reports  7  The framework implementation we have presented uses only genomic information to generate a patient or research report. Of course, the clinical features of the sample o\ufb00er vital clues as to which gene is likely responsible for the disease. It would therefore make sense to include phenotype-based gene \ufb01ltering or prioritization to the report. To make this possible, associations of Human Phenotype Ontology (HPO) terms[292] to their known disease genes could be integrated into the system. Users can enter HPO terms that match the phenotypes observed in a patient to shorten their list of candidate genes.",
      "Predicted transcriptome association test  We used the PrediXcan 16 framework to identify genes that might mediate associations between genetic variants and asthma risk.PrediXcan is a software tool that estimates tissue-specific gene expression profiles from an individual's SNP genotype profile by use of prediction models trained in large reference databases of genotypes and tissue-specific gene expression profiles.With these genotype-imputed expression profiles, PrediXcan can perform gene-based association tests that correlate predicted expression levels with phenotypes (eg, asthma) to identify candidate causal genes from GWAS data.We used a summary version of PrediXcan, which has high concordance with the individual-level version (r\u00b2>0\u202299). 17or predictions, we downloaded elastic net models trained with reference transcriptome data from the Genotype-Tissue Expression consortium 18 for 49 tissues (appendix pp 9, 47).",
      "  Gene selection was based on searches conducted using the Genetic Association Database (geneticassociationdb.nih.gov).Only genes with multiple, independent indicators of function were included.aPhenotype available for one cohort only.",
      "The results from the phenotype-driven searches should then be linked to gene names associated with a given phenotype. These genes are presented as a list from which the user can choose the genes of interest and save them in a shopping cart. It is then possible to feed the genes into the gene-centric use-case and perform a more detailed data mining or meta-analysis. The description and further development of the phenotype-driven use-case may represent a very useful concept for scientists and clinicians outside the mouse community.",
      "  As a demonstration of the utility of the web interface, we entered the 9 genes that reached suggestive significance in a recent genome-wide association study of opioid cessation (Cox et al. 2020).The graph view of the search results are shown in Fig. 3. Genes and keywords are all shown as circles and lines connecting them show the number of abstracts containing the 2 circles they connect.Keywords under the same main category are shown with the same color in the graphic output.Clicking on the lines brings up a new page that displays all sentences containing the keywords that line connects.An alternative tabular view of the same results is also available, where genes, the keywords, and number of abstracts are shown as separate columns."
    ],
    [
      "A major advantage of the mouse as an animal model is the availability of well-characterized inbred strains that enable functional genomics on defined genetic backgrounds. Currently, however, exploiting the full utility of mice to study human diseases is hampered by the lack of gene targeting resources for multiple inbred mouse strains. DBA/2J is a common inbred mouse strain critical in studying a diverse range of human diseases. For example, it is widely used as an inherited model of glaucoma. Glaucoma is a neurodegenerative disorder that affects 70 million people worldwide.",
      "The network is driven by a common regulator, Ebi2 (also known as Gpr183), which is conserved in rats and humans, is expressed in macrophages and is associated in GWASs with human type 1 diabetes48. Such systemsgenetics studies are possible in rats because of the ready availability of ex vivo tissues and the statistical power gained from studies of inbred strains in controlled environments. Overall, these vignettes provide clear examples of the translational focus of the rat genetics community in an era of unprecedented scientific opportunity enabled by ultra-high-throughput genomics and mathematical biology.",
      "  Inbred animal models with homogeneous genetic backgrounds have been a powerful adjunct to human studies, providing a sufficiently large number of samples required for an unconstrained genetic analysis.Several polygenic NIDDM rodent models have been developed.These include the Goto-Kakizaki (GK) rat, the Otsuka Long-Evans Tokushima Fatty (OLETF) rat, the Nagoya Shibata Yasuda mouse, the New Zealand Obese mouse (reviewed in Kim et al., 1998), and the Tsumura-Suzuki Obese Diabetes mouse (Suzuki et al., 1999).The underlying genetic factors in these animal models have been studied by quantitative trait locus (QTL) mapping analysis, and several QTLs associated with glucose intolerance, defective insulin secretion, or parameters defining glucose homeostasis have been located (reviewed in Kim et al., 1998;Hirayama et al., 1999;Ueda et al., 1999).",
      "In as much as it is quite difficult to conduct certain infectious disease studies in humans, there has been a critical need for small animal models for infectious diseases. Appreciating the limitations of existing models, we developed several novel and complementary mouse models that are ideal for use in systems genetics studies of complex diseases. These models not only allow biological validation of known genetic associations, but importantly they afford an unbiased tool for discovering novel genes and pathways contributing to disease outcomes, under different environments. 2008 Genetic effects on environmental vulnerability to disease.",
      "Generalities  Mouse models have been developed to give new insights into human diseases.Mouse models can be classified into two main classes: 1) genetically modified mouse models, animals that lack (knockout) or overexpress a specific gene and the protein that is encoded for, 2) mice that acquire a disease/symptom following an experimental procedure, such as diet, chemical injections and specific surgery.",
      "However, in other contexts, B6 mice are more likely than D2 to spontaneously develop diabetic syndromes, Aging Clin Exp Res  indicating that risk factors exist on both genetic backgrounds [29]. QTL mapping studies indicate that these murine metabolic traits have a complex genetic architecture that is not dominated by any single allele [29\u201331], much like humans [32, 33]. Prior work identified candidate genes on Chr 13 that might underlie diabetes-related traits, including RASA1, Nnt, and PSK1. RASA1 show strong sequence differences between B6 and D2 strains [34]. Rasche et al.",
      "In other cases, the rat phenotypes have proved more robust and consistent, such as pristane-induced arthritis as a model for rheumatoid arthritis (Holmdahl et al. 2001) and cresentic glomerulonephritis (Aitman et al. 2006). Decades of careful phenotyping and detailed analyses in rat experimental crosses have led to the localization of hundreds of rat physiological quantitative trait loci (pQTLs) containing genes that confer susceptibility to complex disease phenotypes, including hypertension, type 2 diabetes, autoimmune disorders, and cancer (Flint et al. 2005). The availability of the rat genome sequence in June 2003 (Gibbs et al.",
      ", et al. , Harnessing Genetic Complexity to Enhance Translatability of Alzheimer's Disease Mouse Models: A Path toward Precision Medicine. Neuron, 2019. 101(3): p. 399-411 e5. Beura, L.K. , et al. , Normalizing the environment recapitulates adult human immune traits in laboratory mice. Nature, 2016. 532(7600): p. 512-6. Kleinert, M., et al. , Animal models of obesity and diabetes mellitus. Nat Rev Endocrinol, 2018. 14(3): p. 140-162. Kebede, M.A. and A.D. Attie, Insights into obesity and diabetes at the intersection of mouse and human genetics. Trends Endocrinol Metab, 2014. 25(10): p. 493-501. von Scheidt, M., et al.",
      "Researchers have access to all the tissue samples in mice, especially those highly relevant in diseases, which is impossible in most human studies because of ethical issues. 8. Mouse models can be used to capture the disease progression stages in longitudinal studies. 9. Mouse genetic populations are able to model the genetic diversity of human populations, and require fewer individuals for genetic association analyses. 10. Unlike human genetic studies where data should always be kept highly confidential, data from mouse studies can be made public available to facilitate its re-analysis to the fullest extent.",
      "Knock-out and transgenic mice in diabetes research  Transgenic mice have been used to create specific models of type 1 and type 2 diabetes, including hIAPP mice, humanized mice with aspects of the human immune system and mice allowing conditional ablation of beta cells, as outlined above.Beta cells expressing fluorescent proteins can also provide elegant methods of tracking beta cells for use in diabetes research (Hara et al., 2003).",
      "  Polygenic models of obesity.Polygenic models of obesity may provide a more accurate model of the human condition.A variety of different polygenic mouse models of obesity, glucose intolerance and diabetes exist, allowing a variety of genotypes and susceptibilities to be studied.However, unlike the monogenic models, there are no wild-type controls.In addition, the male sex bias is more extreme in these models (Leiter, 2009).These polygenic models have been used in a wide variety of studies that have aimed to reverse the symptoms of type 2 diabetes (Chen et al., 2009;Fukaya et al., 2009;Guo et al., 2010;Mochizuki et al., 2011;Yoshinari and Igarashi, 2011), understand more about the interplay of obesity and glucose homeostasis (Kluth et al., 2011) (Jurgens et al., 2007) or study diabetic complications (Cheng et al., 2007;Fang et al., 2010;Buck et al., 2011;Lee et al., 2011a).KK mice.KK mice are a mildly obese and hyperleptinaemic strain derived from wild-derived ddY mice in Japan by Kondo in 1957 (Clee and Attie, 2007).They develop severe hyperinsulinaemia and demonstrate insulin resistance in both muscle and adipose tissue.The pancreatic islets are hypertrophic and degranulated.This mouse strain also shows signs of diabetic nephropathy (Ikeda, 1994).",
      ", 2008) and specific genetic factors for predisposition to DN were recently identified in several diabetic sibling studies (Bleyer et al. , 2008; Schelling et al.,2008; Tanaka et al. , 2005). Similar to humans, inbred strains of mice exhibit differences in their susceptibility to diabetes, renal and cardiovascular diseases (Krolewski et al. , 1996). More recently, differential susceptibilities to DN have also been observed in well-defined strains of  23",
      "  The third advantage of the mouse model is that after identification of a candidate gene, direct genetic evidence for its involvement in a pathophysiology can be obtained in mice, but very rarely in humans.Thus, inbred mouse models are ideally suited for the investigation of the obesity-associated diabetes.However, the genetic homogeneity of the inbred strains is not only an advantage, it also limits their potential.Individuals of an inbred mouse line are genetically identical, and it cannot be expected that a single strain carries more than a small portion of all relevant gene variants.Currently, more than 2000 mouse QTL for different traits have been identified in crosses between inbred stains, but only about 1 % has been characterized on molecular level (Flint et al. 2005).Thus, more than one model and new resources, e.g., systems biology may be required for a complete genetic analysis of complex traits.Previous and ongoing research supports the view that the combination of individual genomes-by intercross of inbred strains and by the generation of congenic lineswill reveal effects of many more genes and gene interactions than can be observed in a single inbred strain.Because the cross-breeding experiments are time consuming and expensive, selecting the ''right'' models of the obesity-associated diabetes is of crucial importance (Leiter 2009).Another advantage of mouse studies in comparison to human studies is the ability to control the environment and to investigate effects of diets, exercise, and intestinal microbiota.",
      "Introduction Rodents, particularly mouse and rat have been widely used for biomedical research in models of human diseases since it is known that almost of all of genes in mouse and rat are similar to that of humans. However, not every genetic pathway or molecular mechanism of diseases or drugs discovered to be efficacious in these models can be extrapolated to human diseases. Thus, while much data from animal studies have been successfully applied to humans, some have not. The present study aims to explore the degrees of differences in the causal pathways for lung fibrosis between humans and mice.",
      "  These limitations support the increasing need of experimental systems to characterize the fundamental biological mechanisms responsible for diabetes inheritance and the function of risk genes.In the context of diabetes pathogenesis, in vitro systems are useful but often limited, in particular to assess glucose tolerance, insulin sensitivity, islet architecture and function and diabetes complications.The laboratory mouse provides a wide range of experimental models for diabetes gene discovery and for in vivo post-GWAS studies of diabetes that develops either spontaneously or following gene editing [5].The laboratory rat is also a powerful system to implement phenotyping methods required to record biological variables relevant to common chronic diseases.The rat is the preferred model to perform phenotyping procedures that are often technically challenging in mice or require the collection of large volumes of blood or organs.For these reasons, rat models of type 2 diabetes or hypertension have been successfully used to localise in the genome genes controlling endophenotypes relevant to these complex diseases.This review addresses strategies used to map the genetic determinants of physiological and molecular phenotypes relevant to type 2 diabetes pathogenesis and to characterize their biological function in vivo through examples derived from genetic and genomic research in the Goto-Kakizaki (GK) rat strain.",
      "However, many of the phenotypes of the homozygous null mutations were extreme and/or did not model the complexity of the metabolic syndrome. For example, IR knockout (IR2/2) mice died because of developmental effects (Accili et al. , 1996), which precluded analysis of adult mice. Likewise, GLUT42/2 mice exhibited only moderate insulin resistance and were not overtly diabetic, suggesting compensatory mechanisms (Katz et al. , 1995). Monogenic GEMMs furthermore ignore the polygenic nature of metabolic diseases, resulting from genetic and environmental factors impacting at multiple levels in signaling cascades. Oligogenic mouse models remedied some of these shortcomings.",
      "Since glucokinase2/2 mice are embryonic lethal, this collection of glucokinase mutants is useful for dissecting the pathogenesis of MODY2. Genetic reference populations (GRPs) Perhaps the most \u2018\u2018refreshing\u2019\u2019 mouse resource for investigating complex diseases is the construction of mouse crosses using inbred mice and the subsequent QTL mapping. Inbred mice have an inherent wealth of variation due to past spontaneous mutation events, which have been preserved through systematic and uninterrupted brother-sister matings (Paigen, 2003). Inbred mice are appealing since they are genetically identical within a strain but are diverse between strains.",
      "Mouse Models of Oxidative Stress and Mitochondrial  Dysfunction in Aging.Genetically engineered mouse models provide great systems to directly dissect the complex relationship between oxidative damage, mitochondrial dysfunction, and aging.Although it is difficult to manipulate mitochondrial genome, genetic engineering of nuclear genes that are involved in oxidative stress response and mitochondrial function has been utilized to study mitochondrial biology and aging.",
      "Rodent models of glaucoma have gained favor in the research community due to their ease of handling and the lower costs associated with acquisition and care. In particular, the mouse provides a number of useful genetic approaches to create models and to test specific molecular interactions associated with the disease process. Furthermore, the mouse genome is relatively conserved compared to the human genome.",
      "Better Mouse Models. A key point to bear in mind in assessing the usefulness of mouse models is the relative plasticity displayed by rodents faced with gene deletions.Thus, differences between the penetrance of mutations in human genes linked to monogenic forms of diabetes, including maturity onset diabetes of the young (MODY), between humans and mice, are usually observed [114] with the mouse equivalents showing far less marked disturbances in glycemia or changes which are seen only after deletion of both alleles.This clearly reflects the limitations of the use of mice (weight \u223c25 g, life expectancy \u223c3 years) for comparisons with human subjects.Nonetheless, and although the phenotypes of the above murine models are thus often more subtle than the human counterparts, they remain useful models for the study of diabetes, allowing single-targeted gene deletions which are impossible in man.For example, human populations with different genetic backgrounds have different susceptibility to the R235W ZnT8 polymorphism.We should not, therefore, find surprising the results that different genetic backgrounds and different diet reveal different phenotypes in ZnT8 knockout models."
    ],
    [
      "  Additional large-scale meta-analysis predicated upon increased sample size, were carried out on existing datasets from the WTCCC [18] and the Genetics of Kidneys in Diabetes (GoKinD) study [69][70][71] plus control data derived from the National Institute of Mental Health.These investigators observed significant association of previously observed loci.Importantly, they did not observe evidence of new T1D loci reaching the threshold for genome-wide significance.Instead they re-analyzed the most nominally significant associated SNP in an independent British cohort of approximately 6000 cases, 7000 controls and in 2800 families, where they uncovered four additional loci, BACH2 (previously reported [67]), 10p15 harboring protein kinase C theta (PRKCQ), 15q24 harboring nine genes including the cathepsin H (CTSH), complement 1q (C1q), tumor necrosis factor related protein 6 (C1QTNF6) and somatostatin receptor 3 (SSTR3) genes.Table 1 summarizes the 16 T1D loci reported to date.An example of a tag-SNP that captures the association with T1D in each instance is highlighted together with its relative minor allele frequency in controls and what magnitude of risk or protection it confers.Key references regarding the role of each locus in the context of the disease are included and along with the chromosomal band where each locus resides, the main candidate gene (symbol and full name) is highlighted.",
      "Detection of established loci  We explored the extent to which previously reported type 2 diabetes association signals could be detected in African-descent individuals.Based on the previously reported effect sizes and the effect allele frequency and sample size from our African meta-analysis, we had sufficient power (80%) to detect three signals (TCF7L2, DNER and SRR) at genome-wide significance (p < 2.5 \u00d7 10 \u22128 ) (ESM Table 2).Only the TCF7L2 variant reached genome-wide significance in our study, whereas both variants in DNER (rs1861612) and SRR (rs391300), originally discovered in Pima Indians and East Asians, respectively, had p > 0.1 (ESM Table 2).",
      "  On the basis of the combined stage 1-3 analyses, we found that six signals reached compelling levels of evidence (P \u00bc 5.0 \u00c2 10 -8 or better) for association with T2D (Table 2).As in all linkage disequilibrium (LD)-mapping approaches, characterization of the causal variants responsible, their effect sizes and the genes through which they act will require extensive resequencing and fine-mapping.However, on the basis of current evidence, we found that the most associated variants in each of these signals map to intron 1 of JAZF1, between CDC123 and CAMK1D, between TSPAN8 and LGR5, in exon 24 of THADA, near ADAMTS9 and in intron 5 of NOTCH2.",
      "  Replication study of newly identified type 1 diabetes risk loci",
      "  Although these are considered to be loci convincingly associated with susceptibility to type 2 diabetes in populations of European descent, other genes related to susceptibility to the disease are probably still unidentified, particularly those for populations of other ancestries.In order to uncover genetic variants that increase the risk of type 2 diabetes, we conducted a genome-wide association study in Japanese individuals with type 2 diabetes and unrelated controls.We first genotyped 268,068 SNPs, which covered approximately 56% of common SNPs in the Japanese, in 194 individuals with type 2 diabetes and diabetic retinopathy (case 1) and in 1,558 controls (control 1) collected in the BioBank Japan.We compared the allele frequencies of 207,097 successfully genotyped SNPs and selected the 8,323 SNPs showing the lowest P values.We then attempted to genotype these 8,323 SNPs in 1,367 individuals with type 2 diabetes and diabetic retinopathy (case 2) and for 1,266 controls (control 2) (stage 2), and successfully obtained data for 6,731 SNPs (the P value distribution in the second test is shown in Supplementary Fig. 1a online).The results of principal component analysis 8 in the stage 1 and 2 samples and HapMap samples revealed that there was no evidence for population stratification between the case and control groups throughout the present tests (Supplementary Fig. 1b,c).We selected the 9 SNP loci showing P values o0.0001 (additive model in stage 2, Table 1) and genotyped a third set of cases and controls comprising 3,557 Japanese individuals with type 2 diabetes (cases 3,4,5) and 1,352 controls (controls 3,4).We evaluated the differences in the population structure among these three sets of case and two sets of control groups by Wright's F test.As the results indicated that there was no difference in the population structure among these groups (Supplementary Table 1b online), we combined these populations for the third test of case-control study.The third set of analysis identified the significant associations for six SNPs (Table 1), including the CDKAL1 locus at 6p22.3 (rs4712524, rs9295475 and rs9460546), the IGF2BP2 locus at 3q27.2 (rs6769511 and rs4376068) and the KCNQ1 locus at 11p15.5 (rs2283228).The remaining three SNPs (rs13259803, rs612774 and rs10836097) had P values of 40.05 in the third test and were not further examined.CDKAL1 and IGF2BP2 were previously reported as susceptibility genes for type 2 diabetes in the Japanese population 9 .Therefore, we focused on the KCNQ1 locus, which was highly associated with type 2 diabetes.",
      "  We consider these data as an interesting preliminary result that surely requires additional independent studies including a higher number of patients in order to confirm and clarify the possible contribution of this locus to the development of T2DM complications.",
      "DISCUSSION  Taken together, our full second-stage approach and combined meta-analysis have revealed additional loci associated with type 1 diabetes.Clearly the risks are relatively modest compared with previously described associations, and it was only with this sample size at our disposal that we could we detect and establish these signals as true positives through an independent validation effort.",
      "Identification of susceptibility loci  The degree of evidence for all reported T2D loci was quantified as follows: a locus with a logarithm of odds ratio (LOD) score of 3 or more was considered significant, a LOD score between 2.2 and 3 was considered suggestive and a LOD score between 1 and 2.2 was considered nominal.For T2D, only those loci were included that were significant at least once, or were suggestive in at least one study and at least nominal in two or more studies.The inclusion of the second category of loci was based on a study by Wiltshire et al. [72], in which it was postulated that locus counting is a useful additional tool for the evaluation of genome scan data for complex trait loci.We used the same two criteria to determine the loci from the five papers published on obesity since 2004 and combined these loci with those from Bell et al. [7].As obesity phenotypes, BMI, serum leptin levels, abdominal subcutaneous and visceral fat, and percentage body fat were included.All of these phenotypes were used as continuous quantitative traits, as well as with various cut-off levels.",
      "  Today, more than 100 loci for type 2 diabetes and glycemic traits have been identified through numerous GWA studies of common and rare variation in populations of diverse ancestral origins [31]; however, to date, very few GWA studies have been published in cohorts of Mexican ancestry.The first GWA study performed in a non-European cohort was published in 2007 and comprised 561 Mexican American type 2 diabetes cases and controls drawn from the Starr County Health Studies [32].Although no loci reached genome-wide significance, several loci identified in prior GWA studies in Europeans were replicated [32].This analysis was subsequently expanded (N = 1273) and meta-analyzed with a cohort from Mexico City (N = 1310) in 2011 [33,34].The most significant variants observed in this meta-analysis included known regions near HNF1A and KCNQ1.Top association signals were then meta-analyzed with the DIAGRAM and DIAGRAM+ datasets of European ancestry individuals, resulting in two regions reaching genome-wide significance: HNF1A and CDKN2A/CDKN2B (Table 1).Top association signals in both studies were annotated to explore their roles as expression quantitative trait loci (eQTL) in both adipose and muscle tissues, revealing a marked excess of transacting eQTL in top signals in both tissue types.",
      "  75\u00b179 The main conclusion is that there is no major locus for T2D (analogous to HLA in type 1 diabetes).This is not surprising given the modest l s for T2D (approximately 3.5 in Europeans), imposing a limit on the magnitude of any single gene eect. 4Many scans have consequently been signi\u00aecantly underpowered to detect the modest gene eects anticipated.Certainly, few T2D scans have reported linkages meeting the established criteria for genomewide signi\u00aecance. 80This modest power, combined with the diversity of the pedigrees sampled and the analytical techniques used, means that the replication of positive \u00aendings between data sets has been the exception rather than the rule.",
      "Quantitative Trait Analysis  Exploration of putative T2DM variants with quantitative glycemic traits in a subset of African-American samples (n = 671 from the IRAS and IRASFS control samples, Table S5) revealed     limited insight into the biological mechanism associated with T2DM risk.In addition, the five putative African-American T2DM susceptibility loci were tested for association with quantitative measures of glucose homeostasis in the European Caucasian population, in silico, by the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC; [16]).These results did not provide further insight into the probable role these variants may have in disease susceptibility (Table S6).The most significantly associated SNP in African Americans, rs7560163, failed quality controls filters and was not included in analysis likely due to being monomorphic as seen in a representative Caucasian population from the HapMap project (Table S4).",
      "  Discovery of novel loci for T2D susceptibility.We tested for T2D association with ~27 million variants passing quality-control filters, ~21 million of which had a minor allele frequency (MAF) < 5%.Our meta-analysis identified variants at 231 loci reaching genomewide significance (P < 5 \u00d7 10 \u22128 ) in the BMI-unadjusted analysis (N eff 231,436) and 152 in the smaller (N eff 157,401) BMI-adjusted analysis.Of the 243 loci identified across these two analyses, 135 mapped outside regions previously implicated in T2D risk (Methods, Fig. 1 and Supplementary Table 2).",
      "  Genetic studies performed since 2012 have identified many additional T2D loci based on risk alleles common in one population but less common in others.Studies in African Americans identified RND3-RBM43 (28), HLA-B and INS-IGF2 (29).Studies in South Asians identified TMEM163 (30) and SGCG (31).One locus, SLC16A11-SLC16A13, was simultaneously identified in Japanese and Mexican Americans (32,33), and studies in East Asians identified ANK1 (34), GRK5 and RASGRP1 (35), LEP and GPSM1 (32), and CCDC63 and C12orf51 (36).A study of individuals from Greenland identified TBC1D4 (37), and a sequencing-based study of Danes with follow-up in other Europeans identified MACF1 (38).Finally, the largest GWAS to date in American Indians identified DNER at near genome-wide significance (P = 6.6 \u00d7 10 \u22128 ) (39).Three of these studies imputed GWAS data using the 1000 Genomes Project sequence-based reference panels, providing better genome coverage (29,32,33,40).Taken together, these studies highlight the value of diverse populations, including founder and historically isolated populations, to detect risk loci.",
      "  Finally, a recent study identified additional susceptibility loci for type 2 diabetes by performing a meta-analysis of three published GWAs. 21As acknowledged by the authors, GWAs are limited by the modest effect sizes of individual common variants and the need for stringent statistical thresholds.Thus, by combining data involving 10,128 samples, the authors found in the initial stages of the analysis highly associated variants (they followed only 69 signals out of over 2 million metaanalyzed SNPs) with P values \u03fd10 \u03ea4 in unknown loci, and 11 of these type 2 diabetes' associated SNPs were taken forward to further stages of analysis.Large stage replication testing allowed the detection of at least six previously unknown loci with robust evidence for association with type 2 diabetes.",
      "  Surprisingly, data about previous published loci associated with type 2 diabetes were not sufficiently powerful to reach a significant P value in individual scans.For example, variants at SLC30A8 and PPARG were significantly associated with type 2 diabetes only when pooling all the GWAs data, whereas in a single genome scan (DGI), no gene showed a positive signal (P value: 0.92 and 0.83, respectively).Thus, this may suggest that GWAs are still underpowered to find SNPs with small effect size.",
      " Background: The two genome-wide association studies published by us and by the Wellcome Trust Case-Control Consortium (WTCCC) revealed a number of novel loci, but neither had the statistical power to elucidate all of the genetic components of type 1 diabetes risk, a task for which larger effective sample sizes are needed.Methods: We analysed data from two sources: (1) The previously published second stage of our study, with a total sample size of the two stages consisting of 1046 Canadian case-parent trios and 538 multiplex families with 929 affected offspring from the Type 1 Diabetes Genetics Consortium (T1DGC); (2) the Rapid Response 2 (RR2) project of the T1DGC, which genotyped 4417 individuals from 1062 non-overlapping families, including 2059 affected individuals (mostly sibling pairs) for the 1536 markers with the highest statistical significance for type 1 diabetes in the WTCCC results.Results: One locus, mapping to a linkage disequilibrium (LD) block at chr15q14, reached statistical significance by combining results from two markers (rs17574546 and rs7171171) in perfect LD with each other (r 2 = 1).We obtained a joint p value of 1.3610 26 , which exceeds by an order of magnitude the conservative threshold of 3.26610 25 obtained by correcting for the 1536 single nucleotide polymorphisms (SNPs) tested in our study.Meta-analysis with the original WTCCC genome-wide data produced a p value of 5.83610 29 .Conclusions: A novel type 1 diabetes locus was discovered.It involves RASGRP1, a gene known to play a crucial role in thymocyte differentiation and T cell receptor (TCR) signalling by activating the Ras signalling pathway.",
      "  Finally, we examined whether genes identified using our association studies were enriched within diabetes-related pathways.We collated a list of 42 genes to which 53 CpG sites associated with T2D traits (CS score \u22651.77, combined P < 0.017) mapped.Even in this small dataset, pathway analysis (Supplementary Material, Table S12) indicated significant enrichment in 31 pathways (Fisher's exact P < 0.05), including those related to circadian clock (P = 0.005), adipocytokine signaling (P = 0.009), leptin pathway (P = 0.023), HDL-mediated lipid transport (P = 0.031) and insulin signaling (P = 0.033).",
      "  In recent years, progress has been made in following up mechanistic studies of GWAS type 2 diabetes-association signals [6,7,9,[25][26][27][28][29][30], but challenges remain in sifting through the many associated variants at a locus to identify those influencing disease.We hypothesized that a common variant with modest effect underlies the association at the CDC123/CAMK1D locus and evaluated the location of high LD variants (r 2 $.7; n = 11) at the locus relative to known transcripts and to putative DNA regulatory elements.We identified two variants that overlapped putative islet and/or liver regulatory regions and none located in exons.We did not assess variants in lower LD (r 2 ,.7), and additional functional SNPs may exist at this locus acting through alternate functional mechanisms untested in the current study.",
      "  Meta-analysis results for T2D SNPs for insulin and glucose-related traits.",
      "A r t i c l e s  By combining genome-wide association data from 8,130 individuals with type 2 diabetes (T2D) and 38,987 controls of European descent and following up previously unidentified meta-analysis signals in a further 34,412 cases and 59,925 controls, we identified 12 new T2D association signals with combined P < 5 \u00d7 10 \u22128 .These include a second independent signal at the KCNQ1 locus; the first report, to our knowledge, of an X-chromosomal association (near DUSP9); and a further instance of overlap between loci implicated in monogenic and multifactorial forms of diabetes (at HNF1A).The identified loci affect both beta-cell function and insulin action, and, overall, T2D association signals show evidence of enrichment for genes involved in cell cycle regulation.We also show that a high proportion of T2D susceptibility loci harbor independent association signals influencing apparently unrelated complex traits."
    ],
    [
      "Methods  Mouse models of diabetes.All animal studies were conducted according to a protocol approved by the Institutional Animal Care and Use Committee at the Beckman Research Institute of City of Hope.Male type-2 diabetic db/db mice (T2D leptin receptor deficient; Strain BKS.Cg-m \u00fe / \u00fe lepr db/J) and genetic control non-diabetic db/ \u00fe mice (10-12 weeks old), were obtained from The Jackson Laboratory (Bar Harbor, ME) 11,17 .Male C57BL/6 mice (10 week old, The Jackson Laboratory) were injected with 50 mg kg \u00c0 1 of STZ intraperitoneally on 5 consecutive days.Mice injected with diluent served as controls.Diabetes was confirmed by tail vein blood glucose levels (fasting glucose 4300 mg dl \u00c0 1 ).Each group was composed of five to six mice.Mice were sacrificed at 4-5 or 22 (ref.17) weeks post-induction of diabetes.Glomeruli were isolated from freshly harvested kidneys by a sieving technique 11,17 in which renal capsules were removed, and the cortical tissue of each kidney separated by dissection.The cortical tissue was then carefully strained through a stainless sieve with a pore size of 150 mm by applying gentle pressure.Enriched glomerular tissue below the sieve was collected and transferred to another sieve with a pore size of 75 mm.After several washes with cold PBS, the glomerular tissue remaining on top of the sieve was collected.Pooled glomeruli were centrifuged, and the pellet was collected for RNA, protein extraction or for preparing MMCs 11,17 .Male Chop-KO mice were also obtained from the Jackson Laboratory (B6.129S(Cg)-Ddit3 tm2.1Dron /J).Based on our previous experience, sample size was determined to have enough power to detect an estimated difference between two groups.With minimum sample size of 5 in each group, the study can provide at least 80% power to detect an effect size of 2 between diabetic and non-diabetic groups or treated and untreated groups at the 0.05 significant level using two-sided t-test.Since we expected larger variation between groups especially for the mice with oligo-injection, we used more than 5 mice in each group (with 6 mice in each group, we have 80% power to detect an effect size of 1.8 at the 0.05 confidence level).Our actual results with current sample size did show statistical significance for majority of the miRNAs in the cluster.Histopathological and biochemical analysis of tissues or cells derived from animal models were performed by investigators masked to the genotypes or treatments of the animals.",
      "  In these models, adult offspring of diabetic animals were noted to have normal development of the endocrine pancreas (Aerts et al., 1997;Ma et al., 2012).However, they develop glucose intolerance and impaired insulin response to glucose challenge, and display insulin resistance, mainly in the liver and muscle, highlighting the presence of both insulin resistance and b-cell dysfunction (Aerts et al., 1988;Holemans et al., 1991a,b).The key role of the intrauterine environment was demonstrated by a series of embryo transfer experiments, which showed that the diabetes risk in a low genetic risk strain can be substantially increased by the hyperglycaemic environment of a dam with a high genetic risk of diabetes (Gill-Randall et al., 2004).",
      "  Diabetes-obesity syndromes in rodents",
      "However, in other contexts, B6 mice are more likely than D2 to spontaneously develop diabetic syndromes, Aging Clin Exp Res  indicating that risk factors exist on both genetic backgrounds [29]. QTL mapping studies indicate that these murine metabolic traits have a complex genetic architecture that is not dominated by any single allele [29\u201331], much like humans [32, 33]. Prior work identified candidate genes on Chr 13 that might underlie diabetes-related traits, including RASA1, Nnt, and PSK1. RASA1 show strong sequence differences between B6 and D2 strains [34]. Rasche et al.",
      "  Other diet-induced rodent models of type 2 diabetes.Although rats and mice are the most commonly used models for studies of type 2 diabetes, other rodents have also been identified as useful models.These include the desert gerbil and the newly described Nile grass rat, both of which tend to develop obesity in captivity.",
      "  Summary of rodent models of type 2 diabetes",
      "  Since the obesity is induced by environmental manipulation rather than genes, it is thought to model the human situation more accurately than genetic models of obesityinduced diabetes.High fat feeding is often used in transgenic or knock-out models, which may not show an overt diabetic phenotype under normal conditions, but when the beta cells are 'pushed', the gene may be shown to be of importance.It should be noted that the background strain of the mice can determine the susceptibility to diet-induced metabolic changes, and thus, effects could be missed if a more resistant strain is used (Surwit et al., 1995;Bachmanov et al., 2001;Almind and Kahn, 2004).It has also been reported that there is heterogeneity of the response to high fat feeding within the inbred C57BL/6 strain, indicating that differential responses to a high-fat diet are not purely genetic (Burcelin et al., 2002).",
      "Other considerations and limitations  A myriad of factors affect animal experiments.Men elicit a greater stress response in mice than women 292 , likely confounding feeding behaviour.Rodents from different production facilities (for example, Jackson Laboratory and Taconic) have unique gut microbiotas 293 , perhaps contributing to differences in their susceptibility to DIO and related diabetic complications 293 .Similarly, cage position within a rack of cages, single versus group housing, the skill level of the researcher, ambient room temperature or the type of cage bedding can all affect experimental outcomes.",
      "  We believe there are several factors that researchers should consider when conducting obesity and diabetes mellitus research in rodents (FIG.2).Although our list is by no means an exhaustive, it demonstrates the complexity and interconnectedness of the myriad of factors that can confound experimental outcomes.Although it is impossible to control for everything, researchers should accurately detail all experimental conditions and methods to allow for better interpretation of the results and, importantly, for better reproducibility.",
      "  Figure2| Important experimental parameters and potential confounders of experimental outcomes in obesity and diabetes research and their interrelatedness.Countless factors influence experimental outcomes when using animal models, and what is enumerated here is by no means a complete list.This figure is one depiction of the multifactorial and interconnected genetic and environmental matrix that makes it virtually impossible to design the perfect experiment.For example, single-housing mice to obtain more accurate food intake data introduces a stress that in turn affects food intake.The severity of this stress response is both strain-specific and sex-dependent.What is important is to be aware of these challenges and to control for them in the most optimal manner.It is equally, if not more, important to accurately and comprehensively detail all experimental conditions in research papers, as these have bearing on the interpretation and reproducibility of the published results.DIO, diet-induced obesity.",
      "  Another concern pertains to control mice.Compared with free-living mice in the wild, laboratory control mice with ad libitum access to food are sedentary, overweight, glucose intolerant and tend to die at a younger age 297 .Comparisons between mice with DIO and control mice might be analogous to investigating the genetic cause of obesity-resistance by comparing humans who are overweight or obese.This potential problem with control mice could explain why the use of DIO diets that have 40% to 60% of total energy from fat is so prevalent, as this might be necessary to achieve divergent weight gains.With free access to running wheels, C57BL/6J mice voluntarily run 5-10 km per day 298,299 .As is the case with humans 300 , mice get health benefits from regular physical activity including weight loss, decreased adiposity and improved insulin sensitivity 301,302 .Physical activity might also affect the epigenome over several generations 303 .An enriched physical and social cage environment alone improves leptin sensitivity and energy expenditure in mice, independent of physical activity 304,305 .Overall, these data suggest that with standard mouse husbandry, chow-fed laboratory mice are not the ideal healthy and lean control group for meaningful obesity research.",
      "  To better address these points, various animal models have been developed.For example, using HFD-T2DM male rats, the F1 female offspring showed reduced \u03b2 cell area and insulin secretion, together with glucose intolerance, without changes in body weight [145].The islets of the F1 female offspring showed differential expression of many genes involved in Ca 2+ , mitogen-activated protein kinase and Wnt signaling, apoptosis and cell cycle regulation [145].Similarly, in pregnant C57BL6J mice, food deprivation resulted in \u03b2 cell mass reduction and an increased risk of \u03b2 cell failure in offspring [146].",
      "They are probably typical of those few mice that develop diabetes more slowly and do not tax the pancreatic insulin supply as severely early in the course of the disease. Attempts at therapy. Attempts to keep the weight of diabetic mice within normal limits by total or partial food restriction resulted in premature deaths. After it was discovered that gluconeogenesis is greatly increased in diabetic mice, attempts were made to regulate blood sugar levels and also weight gain by feeding rations devoid of carbohydrate.",
      "The degree of dependence of adiposity, hyperglycemia, and islet hypertrophy on food consumption varies among these mice, but in all, the increase in islet volume and consequent fi-eell hyperplasia appears to be an effective  247  means of maintaining blood sugar concentrations at near normal levels. I n contrast, neither the diabetic sand rat [5] nor the diabetic mouse has hypertrophied islets and neither effectively controls blood sugar levels.",
      "HV~MEI,: Studies with the Mutation, Diabetes  almost undetectable. Similarly, the activities of citrate lyase and glucose-6-phosphate dehydrogenase were greatly decreased in these older diabetic as compared  Diabetologia  the diabetic mice have attained m a x i m u m weight, after which no further accumulation of adipose tissue is noted. Fig. 8.",
      "Rodent models of monogenic obesity and diabetes  Obesity and the consequent insulin resistance is a major harbinger of Type 2 diabetes mellitus in humans.Consequently, animal models of obesity have been used in an attempt to gain insights into the human condition.Some strains maintain euglycaemia by mounting a robust and persistent compensatory \u03b2 -cell response, matching the insulin resistance with hyperinsulinaemia.The ob / ob mouse and fa / fa rats are good examples of this phenomenon.Others, such as the db / db mouse and Psammomys obesus (discussed later) rapidly develop hyperglycaemia as their \u03b2 -cells are unable to maintain the high levels of insulin secretion required throughout life.Investigation of these different animal models may help explain why some humans with morbid obesity never develop Type 2 diabetes whilst others become hyperglycaemic at relatively modest levels of insulin resistance and obesity.",
      "  As with the KK mouse, the Israeli sand rat model is particularly useful when studying the effects of diet and exercise [120] on the development of Type 2 diabetes.",
      "Animal models of diabetes in pregnancy and the role of intrauterine environment  Another important field of diabetes research that has relied heavily on animal experimentation is the study of diabetes in pregnancy and the role of the intrauterine environment on the subsequent development of diabetes amongst offspring.",
      "  Animal models of Type 2 diabetes mellitus",
      "Assessment of Diabetes  Mice were monitored for the development of diabetes as described previously (Wicker et al. 1994)."
    ],
    [
      "Methods  Mouse models of diabetes.All animal studies were conducted according to a protocol approved by the Institutional Animal Care and Use Committee at the Beckman Research Institute of City of Hope.Male type-2 diabetic db/db mice (T2D leptin receptor deficient; Strain BKS.Cg-m \u00fe / \u00fe lepr db/J) and genetic control non-diabetic db/ \u00fe mice (10-12 weeks old), were obtained from The Jackson Laboratory (Bar Harbor, ME) 11,17 .Male C57BL/6 mice (10 week old, The Jackson Laboratory) were injected with 50 mg kg \u00c0 1 of STZ intraperitoneally on 5 consecutive days.Mice injected with diluent served as controls.Diabetes was confirmed by tail vein blood glucose levels (fasting glucose 4300 mg dl \u00c0 1 ).Each group was composed of five to six mice.Mice were sacrificed at 4-5 or 22 (ref.17) weeks post-induction of diabetes.Glomeruli were isolated from freshly harvested kidneys by a sieving technique 11,17 in which renal capsules were removed, and the cortical tissue of each kidney separated by dissection.The cortical tissue was then carefully strained through a stainless sieve with a pore size of 150 mm by applying gentle pressure.Enriched glomerular tissue below the sieve was collected and transferred to another sieve with a pore size of 75 mm.After several washes with cold PBS, the glomerular tissue remaining on top of the sieve was collected.Pooled glomeruli were centrifuged, and the pellet was collected for RNA, protein extraction or for preparing MMCs 11,17 .Male Chop-KO mice were also obtained from the Jackson Laboratory (B6.129S(Cg)-Ddit3 tm2.1Dron /J).Based on our previous experience, sample size was determined to have enough power to detect an estimated difference between two groups.With minimum sample size of 5 in each group, the study can provide at least 80% power to detect an effect size of 2 between diabetic and non-diabetic groups or treated and untreated groups at the 0.05 significant level using two-sided t-test.Since we expected larger variation between groups especially for the mice with oligo-injection, we used more than 5 mice in each group (with 6 mice in each group, we have 80% power to detect an effect size of 1.8 at the 0.05 confidence level).Our actual results with current sample size did show statistical significance for majority of the miRNAs in the cluster.Histopathological and biochemical analysis of tissues or cells derived from animal models were performed by investigators masked to the genotypes or treatments of the animals.",
      "Diabetes incidence study. Mice were kept for 20-28 weeks and tested for diabetes monthly by blood glucose and weekly by urine assessment, with a positive indication being followed by twice-weekly blood testing.Mice were diagnosed as diabetic when the blood glucose concentration was over 260 mg/dl (14.4 mM) after 2-3 h of fasting for two sequential tests.Glucose and insulin tolerance tests were performed by injecting glucose (2 g/kg body weight) or insulin (1 U/kg body weight) intraperitoneally in mice fasted for 6-7 h.Tail vein blood was tested by a Contour glucometer.Assessments of plasma insulin, proinsulin and C-peptide levels were performed using commercial ELISA kits, according to the manufacturer's instructions (insulin, proinsulin and C-peptide mouse ELISA kits, R&D Systems Quantikine).Assays were performed with blinding, with mice coded by number until experimental end.",
      "Animal group and study design  First, one set of animals comprising 12-week-old male type 2 diabetic db/db (C57BL/KsJ-db\u2212/db\u2212, n = 8) and contemporary control wild-type (C57BL/KsJ-db+/db\u2212, n = 8) mice (Jackson Laboratories) were included in this study.Their weights and blood glucose levels were analysed to eliminate variation.Erectile functions of the animals were evaluated by the apomorphine-induced penile erection test, according to a previously described protocol (Pan et al. 2014).Afterwards, intracavernous pressure (ICP) investigations and histological measurements were applied to further confirm the results of the function tests.Then, all mice were sacrificed and the corpus cavernosum (CC) was collected from each mouse.Because the tissue of the CC is difficult to crush, we randomly collected the CCs from two mice and mixed them into one subgroup.As a result, four diabetic subgroups (DB groups) and four normal control subgroups (NC groups) were used for molecular measurements.Second, another set of animals, including three T2DMED and three normal control mice that were independent from the original set of animals, were included in the validation experiments using qRT-PCR.Third, another separate set of animals, including five T2DMED and five control mice, were used to verify one of the predicted targets, IGF-1, using ELISA.A luciferase reporter assay was performed to verify the binding of the differentially expressed miRNAs to the target gene IGF-1.All procedures were approved by the Institutional Animal Care and Use committee at Nanjing Medical University.",
      "  Summary of rodent models of type 2 diabetes",
      "  Summary of rodent models of type 1 diabetes",
      "Knock-out and transgenic mice in diabetes research  Transgenic mice have been used to create specific models of type 1 and type 2 diabetes, including hIAPP mice, humanized mice with aspects of the human immune system and mice allowing conditional ablation of beta cells, as outlined above.Beta cells expressing fluorescent proteins can also provide elegant methods of tracking beta cells for use in diabetes research (Hara et al., 2003).",
      "Genetically induced insulin-dependent diabetes  AKITA mice.The AKITA mouse was derived in Akita, Japan from a C57BL/6NSlc mouse with a spontaneous mutation in the insulin 2 gene preventing correct processing of proinsulin.This causes an overload of misfolded proteins and subsequent ER stress.This results in a severe insulindependent diabetes starting from 3 to 4 weeks of age, which is characterized by hyperglycaemia, hypoinsulinaemia, polyuria and polydipsia.Untreated homozygotes rarely survive longer than 12 weeks.The lack of beta cell mass in this model makes it an alternative to streptozotocin-treated mice in transplantation studies (Mathews et al., 2002).It has also been used as a model of type 1 diabetic macrovascular disease (Zhou et al., 2011) and neuropathy (Drel et al., 2011).In addition, this model is commonly used to study potential alleviators of ER stress in the islets and in this respect models some of the pathology of type 2 diabetes (Chen et al., 2011).",
      "  To achieve a slow pathogenesis of T2DM, young adult mice 284 or rats 285 are fed a high-fat or Western diet to elicit DIO and insulin resistance.Single or multiple injections with low-dose streptozotocin (~30-40 mg/kg intraperitoneally) then elicit partial loss of \u03b2-cells, which results in hypoinsulinaemia and hyperglycaemia.Protocols are being continuously refined and likely differ between species and even strains 283 .The HFD streptozotocin rat is sensitive to metformin, further demonstrating the utility of this model 285 .Downsides of streptozotocin treatment include liver and kidney toxicity and mild carcinogenic adverse effects (TABLE 1).",
      "Materials and methods 2.1 Mouse models 2.1.1 Mouse strains 2.1.2 Induction of type 1 diabetes 8 2.1.3 Insulin treatment on diabetic mice 2.1.4 Akita mouse genotyping 2.2 Characterization of diabetic nephropathy in mice 2.2.1 Proteinuria measurement 2.2.2 Glomerular cells quantification 2.2.3 Methenamine silver staining quantification  3. 4. 5. 6.",
      "  ii) Rodent models of diabetic retinopathy",
      "  There are some good reviews available in the literatures describing the transgenic/knockout animal models of type 2 diabetes [114][115][116][117][118] .The transgenic and knockout models are developed for studying the role of genes and their effects on peripheral insulin action such as insulin receptor, IRS-1, IRS-2, glucose transporter (GLUT 4), peroxisome proliferator activated receptor-g (PPAR-g) and tumour necrosis factor-a (TNF-a) as well as in insulin secretion such as GLUT-2, glucokinase (GK), islet amyloid polypeptide (IAPP) and GLP-1 and in hepatic glucose production (expression of PEPCK) associated with development of type 2 diabetes.Further, combination or double knockout mouse models including defect in insulin action and insulin secretion (e.g., IRS-1 +/-/GK +/-double knockout) have been produced which clearly illustrate the mechanisms associated with development of insulin resistance and beta cell dysfunction leading to overt hyperglycaemic state in human type 2 diabetes.These above genetically modified animals exhibit various phenotypic features of type 2 diabetes varying from mild to severe hyperglycaemia, insulin resistance, hyperinsulinaemia, impaired glucose tolerance and others as explained in detail elsewhere 6,9,[114][115][116][117][118] .Very recently, tissue specific knockout mouse models have been achieved, allowing further insight into the insulin action with respect to particular target tissues (muscle, adipose tissue and liver) associated with insulin resistance and type 2 diabetes 115,117,118 .The transgenic/knockout animals are currently used mostly for the mechanistic study in diabetes research and not usually recommended for screening programme as they are more complicated and costly.",
      "Functional deficits refs  Non-Alzheimer-disease mouse [71][72][73][74]76,78,81,85,87 and rat 59,75,77 ,79,95,97  Mouse [81][82][83][84][85] and rat 79,111  Cerebral effects of inducing diabetes or insulin resistance in normal rodents (that is, non-Alzheimer-disease rodent models) and in rodents genetically modified to accumulate amyloid\u03b2 in the brain (that is, rodent models of Alzheimer disease). Common intervetions to induce diabetic conditions in rodents included recessive mutations in the leptin gene (Lep; also known as Ob), defects in the leptin receptor (LEPR; also known as OB-R), diet and administration of streptozotocin. Rodents with pancratic overexpression of human amylin spontaneously develop both type 2 diabetes mellitus and dementia-like pathology.",
      "  Animal models have been used extensively in diabetes research.Early studies used pancreatectomised dogs to confirm the central role of the pancreas in glucose homeostasis, culminating in the discovery and purification of insulin.Today, animal experimentation is contentious and subject to legal and ethical restrictions that vary throughout the world.Most experiments are carried out on rodents, although some studies are still performed on larger animals.Several toxins, including streptozotocin and alloxan, induce hyperglycaemia in rats and mice.Selective inbreeding has produced several strains of animal that are considered reasonable models of Type 1 diabetes, Type 2 diabetes and related phenotypes such as obesity and insulin resistance.Apart from their use in studying the pathogenesis of the disease and its complications, all new treatments for diabetes, including islet cell transplantation and preventative strategies, are initially investigated in animals.In recent years, molecular biological techniques have produced a large number of new animal models for the study of diabetes, including knock-in, generalized knock-out and tissue-specific knockout mice.",
      "  Animal models of Type 2 diabetes mellitus",
      "  As with the KK mouse, the Israeli sand rat model is particularly useful when studying the effects of diet and exercise [120] on the development of Type 2 diabetes.",
      "  Animal models of Type 1 diabetes",
      " Animal models have been used extensively in diabetes research.Early studies used pancreatectomised dogs to confirm the central role of the pancreas in glucose homeostasis, culminating in the discovery and purification of insulin.Today, animal experimentation is contentious and subject to legal and ethical restrictions that vary throughout the world.Most experiments are carried out on rodents, although some studies are still performed on larger animals.Several toxins, including streptozotocin and alloxan, induce hyperglycaemia in rats and mice.Selective inbreeding has produced several strains of animal that are considered reasonable models of Type 1 diabetes, Type 2 diabetes and related phenotypes such as obesity and insulin resistance.Apart from their use in studying the pathogenesis of the disease and its complications, all new treatments for diabetes, including islet cell transplantation and preventative strategies, are initially investigated in animals.In recent years, molecular biological techniques have produced a large number of new animal models for the study of diabetes, including knock-in, generalized knock-out and tissue-specific knockout mice.",
      "Rodent models of monogenic obesity and diabetes  Obesity and the consequent insulin resistance is a major harbinger of Type 2 diabetes mellitus in humans.Consequently, animal models of obesity have been used in an attempt to gain insights into the human condition.Some strains maintain euglycaemia by mounting a robust and persistent compensatory \u03b2 -cell response, matching the insulin resistance with hyperinsulinaemia.The ob / ob mouse and fa / fa rats are good examples of this phenomenon.Others, such as the db / db mouse and Psammomys obesus (discussed later) rapidly develop hyperglycaemia as their \u03b2 -cells are unable to maintain the high levels of insulin secretion required throughout life.Investigation of these different animal models may help explain why some humans with morbid obesity never develop Type 2 diabetes whilst others become hyperglycaemic at relatively modest levels of insulin resistance and obesity.",
      "Introduction  Animal experimentation has a long history in the field of diabetes research.The aim of this article is to review the commonly used animal models and discuss the recent technological advances that are being employed in the discipline.The review is based on an extensive literature search using the terms rodent, mouse, rat, animal model, transgenics, knockout, diabetes and pathogenesis, in scientific journal databases such as MEDLINE \u00ae.In addition, abstracts presented at meetings of Diabetes UK, the European Association for the Study of Diabetes and the American Diabetes Association over the last 5 years were examined in order to gain an appreciation of recent and ongoing research projects.",
      "Assessment of Diabetes  Mice were monitored for the development of diabetes as described previously (Wicker et al. 1994)."
    ],
    [
      "  FIG. 6. Hepatic steatosis during DIO is associated with loss of eAT mass.A: Liver weight (adjusted for body weight) of mice fed a HF diet for 1, 4, 8, 12, 16, and 20 weeks.B: Inverse association of eAT mass and liver weight (as in A) between DIO weeks 12 and 20.C: Representative micrographs of hematoxylin and eosin-stained liver sections demonstrating that hepatic macrosteatosis in HF-fed mice is initially evident at DIO week 12 and increases through week 20.",
      "  RESEARCH DESIGN AND METHODS-Male C57BL/6 mice were fed a high-fat diet for 20 weeks to induce obesity.Every 4 weeks, insulin resistance was assessed by intraperitoneal insulin tolerance tests, and epididymal (eAT) and inguinal subcutaneous AT (iAT) and livers were harvested for histological, immunohistochemical, and gene expression analyses.",
      "BXD and HMDP mouse strains, as well as HXB/BXH rat strains, with higher Cd36 expression had increased fat mass and body weight, as well as decreased VO 2 and liver acid beta\u2212glucosidase activity (Figure S2.4B-C), confirming the involvement of Cd36 in metabolism [126] and suggesting a potential role in Gaucher's disease, which results from the deficiency of acid beta\u2212glucosidase [127]. An association between Abca8a liver transcripts and triglyceride levels was also revealed (Figure S2.4D).",
      "The mice were sacrificed at 9 am after a 4-hour fast. (A-E) PARPi reduced body weight (A; *, #, and $ indicates significant differences between  27 HFHS and CD, HFHS and PAPRi-Prev, and HFHS and PARPi-Ther, respectively), liver weight (B), epididymal fat pad (C), liver triglyceride content (D), and cholesterol (E) in both preventive and therapeutic cohorts (n=8-10). (F,G) Representative images of livers (F) and liver sections stained with H&E and Oil Red O (lipid content appears in red) (G), (n= 4-5).",
      "CD45 positive cells appear brown. (n=4). * P <0.05; ** P < 0.001; *** P< 0.0001. Data are expressed as the mean \u00b1 SEM. One-way ANOVA with a post-hoc Bonferroni test was used for all statistical analyses. Male mice were used in these experiments. Fig. 5. Liver damage in MCD diet-induced NAFLD was reversed by NAD+ repletion. C57BL/6J mice were fed with CD, MCD, or MCD+PARPi (PARPi, 50 mg/kg/day). The mice were sacrificed at 9 am after a 4-hour fast. (A) PARPi reduces global protein PARylation and (B) recovers NAD+ levels in liver tissue (n=6).",
      "At 10 weeks of age, male C57BL/6J mice were challenged with an MCD diet for 5 weeks. Similar to the effects seen in mice on a HFHS diet, MCD-fed mice treated with PARPi in a preventive manner exhibited reduced PARylation and increased hepatic NAD+ levels (Fig. 5A and B). Mice fed with a MCD diet for 5 weeks showed classical pathophysiological characteristics of NAFLD, including hepatic steatosis, inflammation and fibrosis. MCD diet increased AST and ALT levels compared to a control diet, while PARPi treatment reduced their levels (Fig. 5C and D).",
      "  The left inguinal, gonadal, and retroperitoneal fat pads were dissected and weighed individually. (Prior data showed that weights of left and right fat pads are highly correlated. )The mesenteric fat pad was also dissected and weighed.An adiposity index (AI) was computed for each mouse as follows: the left inguinal, gonadal, and retroperitoneal fat pad weights were summed, doubled, added to mesenteric fat pad weight, divided by body weight, and multiplied by 100.The ratios of the individual fat pad weights divided by body weight and expressed as a percentage (for example, 200\u00d7 left gonadal fat pad weight/body weight) were analyzed as separate traits, as were blood glucose level, plasma leptin level (log 10 transformed), body weight, and body length.",
      "Metabolic phenotypes were compared between mice in the upper (Lonp1-high) and lower (Lonp1-low) quartiles with respect to WAT Lonp1 expression (n=9\u201310 mice per Copyright \u00a9 2021 Korean Endocrine Society  VAT mRNA levels of OXPHOS-complex and UPRmt genes in relation to BMI Among 48 patients, 11 were obese (\u226525 kg/m2), 11 were overweight (23 to 24.9 kg/m2), and 26 were of normal or underweight (<22.9 kg/m2), according to the World Health Organization Asia-Pacific Obesity Classification [16]. Clinical characteristics of the participants stratified by BMI (<23 kg/m2 vs. \u226523 kg/m2) are summarized in Table 1.",
      "In an F2 cohort derived from these parental strains, we have shown that the range of blood glucose, insulin levels, and body weight exceeds that of either the C57BL/6 (B6) leptinob/ob or BTBR leptinob/ob parental strains. We went on to identify several diabetesrelated QTL in this F2 sample [21,22]. In the current study, we focused on a subset of 60 F2 mice that have previously been evaluated in detail with regard to liver gene expression profiles [24] to ask if the abundances of hepatic metabolic intermediates would show sufficient heritability to enable us to map metabolic QTL (mQTL).",
      "(E\u2013G) Data from CTB6F2 (E) and HMDP (F) mouse cohorts, and the HXB/BXH rat cohort (G) indicate significant negative correlations between liver Rpl26 levels and body weight, and other metabolic traits. adipose tissue (subWAT) mass (Figure 2D), suggesting pleiotropic effects of Pten. The links between Pten and neurobiological and metabolic phenotypes have been confirmed by independent studies (Kwon et al. , 2006; Ortega-Molina et al. , 2012). Overall, PheWAS showed that 4,230 out of 11,548 genes were associated with at least one phenotypic trait and all genes had significant associated molecular traits after phenome-wide correction (Figures 2E; Table S3).",
      "Curves of weight ( \u2022 ... \u2022 ) and blood sugar concentration with age in a less typical diabetic mouse  Diabetologia  (I  --I  )  Aside from the large accumulations of fat, subcutaneously in axillary and inguinal regions and intraabdominally in mescnteric and gonadal fat pads, the most striking anatomical deviation is the size of the liver. The liver m a y weigh up to 4.5 grams in a 40 gram mouse, compared with 1.2 grams in a 20 gram normal mouse.",
      "In mice, within hours after the last meal, the organs respond with changes in gene expression mainly in general metabolism (70). The role of the liver is to provide energy for glucose-dependent tissues, by glycogenolysis, gluconeogenesis, ketogenesis, and fatty-acid \u03b2-oxidation (71). The basic architecture of the lobules and the zonation are not affected, but the cell size declines in prolonged fasting, when murine liver restores partly its glycogen deposits, and much of gene expression returns to control values (72). In Abcb4-/- mice, collagens, fibronectin and vimentin, responsible for the structural integrity of the ECM, were strongly affected by fasting.",
      "James SJ, Muskhelishvili L. Rates of apoptosis and proliferation vary with caloric intake and may influence incidence of spontaneous hepatoma in C57BL/6 x C3H F1 mice. Cancer Res 1994 Nov 1;54(21):5508-5510. 50. Hakvoort TB, Moerland PD, Frijters R, Sokolovic A, Labruyere WT, Vermeulen JL, et al. Interorgan coordination of the murine adaptive response to fasting. J Biol Chem 2011 May 6;286(18):16332-16343. 51. Lin S, Saxena NK, Ding X, Stein LL, Anania FA. Leptin increases tissue inhibitor of metalloproteinase I (TIMP-1) gene expression by a specificity protein 1/signal transducer and activator of transcription 3 mechanism. Mol Endocrinol 2006 Dec;20(12):3376-3388. 52.",
      "  Characterization of lean and obese control and mGHRKO mice",
      "  Consistent with the broad up-regulation of genes associated with fatty acid synthesis (Table 1), Oil Red O staining of liver sections from 15-d-old pups and naturally aged mice revealed enhanced accumulation of triacylglycerides in both compared to control littermates and 8-wk-old mice (Figure 7C), indicating hepatic steatosis.This and the absence of adipose tissue suggest that Csb m/m /Xpa \u00c0/\u00c0 mice display generalized lipodystrophy (loss and abnormal redistribution of body fat) [31]., and Csb m/m /Xpa \u00c0/\u00c0 mice (n \u00bc 6).The levels of IGF1 (ng/ml) and glucose (mmol/l) in the serum of Csb m/m /Xpa \u00c0/\u00c0 mice are significantly lower than that of control littermates (p , 0.0004 and p , 0.04, respectively). (C) PAS staining for glycogen and Oil Red O staining for triglycerides in livers of 15-d-old wt and Csb m/m /Xpa \u00c0/\u00c0 mice and 96-wk-old wt mice.Pictures were taken at 1003 magnification.Note the large polyploid nuclei in the 96-wk-old wt mouse liver and the reduced glycogen levels in the Csb m/m /Xpa \u00c0/\u00c0 liver after overnight fasting.doi:10.1371/journal.pbio.0050002.g007",
      "Association between lifespan and metabolic organ weights We measured weight of certain metabolic organs and tissues of a subsample of cases on both diets at ~500 days of age. HFD mice (n = 63) had 84% greater fat mass, 25% greater heart mass, 19% greater liver mass, and 18% greater kidney mass at ~500 days compared to controls (n = 71). However, HFD did not influence brain mass (Supplemental Table).",
      "  Young adult dwarf mice have more body fat than normal mice.But, with age, normal mice from this line accumulate fat at a higher rate, and the percent body fat in old DF mice does not differ from that of normal mice, as measured by dual energy X-ray absorptiometry (DEXA) (29).Downregulation of lipid biosynthetic genes and upregulation of \u2424-oxidation-related genes in the liver of DF mice may explain this slower rate of fat deposition.",
      "(b) Serum levels of liver injury markers, triglyceride, and cholesterol profiles of 20-month-old WT (n = 6) and Gdf15 KO (n = 6) mice. (c) Serum levels of pro-inflammatory cytokines of 20-month-old WT (n = 6) and Gdf15 KO (n = 6) mice. (d) H&E staining for liver tissues of 20-month-old WT (n = 6) and Gdf15 KO (n = 6) mice. Scale bar, 200 \u03bcm. Arrows indicate fat accumulation. (e) Fixed adipose tissue from 20-month-old WT (n = 6) and Gdf15 KO (n = 6) mice was stained for F4/80 antibodies. Scale bar, 200 \u03bcm.",
      "(12) studied liver gene expression changes in Stat5b knockout and wild-type mice, finding 1,603 differentially regulated genes, with 850 being male- and 753 female biased (P \u2b0d 0.05 and FC \u2b0e 1.5). A large study consisting of 344 mice comprising an F2 cross between C57B/6J.apoE\u2afa/\u2afa and C3H/HeJ.apoE\u2afa/\u2afa strains (\u2b0350% from each sex) produced two reports (57, 61) that examined sexually dimorphic gene expression in adipose tissue, brain, liver, and muscle. It was reported that 9,250 genes are dimorphic in the liver (P \u2b0d 0.01 and FC \u2b0e 1).",
      "2006) studied liver gene expression changes in Stat5b knockout and wild type mice, finding 1,603 differentially regulated genes, with 850 being male- and 753 female-biased (p<0.05 and FC>1.5). A large study consisting of 344 mice comprising an F2 cross between C57B/6J.apoE-/- and C3H/HeJ.apoE-/- strains (~50% from each sex) produced two reports (Wang et al. 2006; Yang et al. 2006) which examined sexually dimorphic gene expression in adipose tissue, brain, liver and muscle. It was reported that 9,250 genes are dimorphic in the liver (p<0.01 and FC>1)."
    ],
    [
      "However, when the data were adjusted for brain weight, there was a significant (p = 0.008) difference between DBA/2J and C57BL/6J (2.14 \u00b1 0.06 mm2 and 1.96 \u00b1 0.03 mm2, respectively) making the DBA/2J larger by 8.50%. Total brain weight of DBA/2J animals was significantly (p < 0.0001) smaller than that of C57BL/ 6J animals (0.35 \u00b1 0.01 g, 0.42 \u00b1 0.01 g respectively).",
      "Phenotypes are often very different between mouse strains with diverse genetic backgrounds and the strain characteristics of DBA/ 2J are often contrasted with other genetically distinct inbred strains such as C57BL/6J. These defined genetic backgrounds provide an excellent system for mapping modifier genes [20,21,22]. To study these differences a number of DBA/2J-relevant resources have been generated. For instance, a genome-wide panel of congenic strains has been created that contain portions of DBA/2J chromosomes on a C57BL/6J background [23]. These 65 strains contain more than 95% of the DBA/2J genome.",
      "Well-documented behavioral differences between C57 and DBA, including enhanced closed-arm preference and deficits in conditional fear, were observed. This suggests at a minimum that the influence of previous testing in the two parental strains was comparable. The use of DBA/2J donor segments for the GTM panel may have implications for loci identified in tests involving auditory stimuli, as this strain is known to undergo progressive hearing loss with age. While no rigorous examination of hearing capacity in the GTM has been conducted, inspection of time course data for individual mice in both the general  Mol Psychiatry.",
      "Particularly striking is the difference in their locomotor response: the C57BL/6J strain shows a marked locomotor activation following an acute opiate administration, which is virtually absent in DBA/2 mice [6, 25, 29]. After chronic morphine treatment, either tolerance or sensitization of the locomotor response was evidenced in C57BL/6J mice, depending on the treatment paradigm, whereas no altered responses were observed in the DBA/2J strain [1, 22, 29, 31]. Other inter-strain differences in reactions to opioids have also been reported, including a greater sensitivity to opioid reward and stronger withdrawal symptoms in the C57BL/6J strain [2, 6, 17, 30, 35].",
      "Although no differences in attentional performance were detected between C57BL/6J and DBA/2J, in line with previous reports in the 5-CSRTT and five-choice CPT (Loos et al . 2010; Young et al . 2009), we observed significant differences among BXD recombinant inbred strains that transgressed beyond the phenotypes of the founders. This suggested the contribution of multiple genetic loci to these phenotypes, of which we detected a significant one on chromosome 16 for response variability.",
      "Given the large differences that we found previously (Crusio 2013) between C57BL/6 and DBA/2, this is unexpected. One possible explanation for the lower than expected performance of the C57BL/6 and (at least some) BXD strains lies in the housing conditions. Our animal facility was built to house about 500 cages in one large breeding room. However, the cage-washing installation (and the available personnel) could not handle that many cages at a time. As a result, every day one or two racks of cages were changed. C57BL/6 mice are sensitive to such disruptions and, indeed, breeding results were only mediocre.",
      "C57BL/6 and DBA/2 mice is not yet fully understood but involves multiple genetic differences between the two mouse lineages, affecting several pathways and processes (1). Certain influenza viruses grow to higher titers in DBA/2 mice (A/Hong Kong/213/2003 [H5N1] or A/Memphis/33/2008 [H1N1]) (data not shown) while others do not (H7N3 and H10N5) (this study). Irrespective of the difference in viral loads, DBA/2 mice respond more vigorously, producing larger quantities of certain proinflammatory molecules like TNF-\u2423, which was shown to correlate with increased morbidity and mortality in humans (5).",
      "Additionally, in this protocol the strains DBA/2J, A/J, NOD/ShiLt/J, C57BL/10J, SM/J, and C57BR/cdJ are AA sensitive; the strains CAST/EiJ and BTBR T\u2af9 tf/J are resistant; and the strains NZW/LacJ, KK,HIJ, and SWR/J have intermediate resistance to AA-induced acute nephrotoxicity (supplementary data; all supplementary material for this article is available online at the journal web site.). For this QTL study, C57BL/6J and DBA/2J mice were used as resistant and sensitive strains, respectively. Each strain has a complete genomic sequence available, and the genetic basis of differences in their ability to respond to xenobiotics is extensively studied (reviewed in Ref. 8).",
      "The C57BL/6J X DBA/2J (BXD) recombinant inbred (RI) mouse strains, which are unique mosaic of alleles derived from the parental C57BL/6J (B6) and DBA/2J (D2) strains have been constructed as a high precision genetic reference population for systems genetics in unraveling the genetic architecture of polygenic traits (Ashbrook et al. , 2019). The BXD family consists of more than 150 BXD fully inbred strains that segregate for \u223c6 million genetic variants and thus can be used as an informative murine genetic reference panel.",
      "Because we have now shown that the parental strains C57BL/6J and DBA/2J markedly differ in both quantitative measures of cortex area size [6] and shape, this assures variation in the derivative BXD lines, and provides an empirical basis for using the BXD panel to study cortical development. Conclusion C57BL/6J and DBA/2J have markedly different cortical area maps, in both size and shape. These differences suggest polymorphism in genetic factors underlying cortical specification, even between common isogenic strains. Comparing cortical phenotypes between normally varying inbred mice or between genetically modified mice can identify genetic contributions to cortical specification.",
      "The C57BL/6 mice were more accurate than DBA/2 mice at the shorter SD where the task demands were greater, and they also made anticipatory (impulsive) responses at a lower rate. In contrast, the DBA/2 mice made fewer omission errors than the C57BL/6 but this effect was not seen until the final stages of the experimental procedures. These findings are in agreement with those of Greco et al. [18]. Although they used different breeders as well as different test chambers, training protocols and reinforcers, the results were similar: DBA/2 males were less accurate and made more anticipatory responses than C57BL/6 males.",
      "DBA/2 mice perform poorly in other spatial tasks as well as in the 5-CSRTT (see Section 1) but this is by no means true for paradigms that are less spatially demanding. For instance, in the four-arm baited and cued versions of the radial maze, as well as in auditory fear conditioning, C57BL/6 and DBA/2 do not differ [1,30]; DBA/2 mice even perform better than C57BL/6 with regard to two-way active avoidance learning [37].",
      "While the factorial structure of C57BL/6 mice remained the same as under low attentional demands (two factors), there was only one factor for DBA2 mice. This factor was characterised by high positive loadings (>0.78) from the percent of correct responses and omission errors, and a high negative loading (0.87) from anticipatory responses. 4. Discussion The results indicated that both C57BL/6 and DBA/2 mice were able to learn the complex 5-CSRTT task but there were considerable quantitative differences in their performance.",
      "It can be seen that at all SD, accuracy was greater for C57BL/6 than for DBA/2 mice. The clearest difference was at 1 s SD where C57BL/6 mice were responding at a mean accuracy of 80% compared with the DBA/2 group for which the mean was 59% (Fig. 1(A)). With a SD of 5 s there was no significant main effect for group (F1,28 = 3.13), whereas at 2 and 1 s SD significant group effects were achieved (F1,28 = 5.44 and 25.1; P < 0.05 and 0.001, respectively).",
      "In marked contrast, the C57BL/6J strain was found to have the highest level of oral morphine consumption [6]. However, sensitivity to the reinforcing effects of morphine in conditioned place preference and intravenous self-administration paradigms was higher in DBA mice than in C57BL [10]. The two frequently used laboratory strains of mice C57BL/6J and DBA/2J show remarkable differences in analgesic response to morphine. Moreover, several studies have reported profound differences in morphine induced locomotor activity between the sensitive C57BL/6 and insensitive DBA/2 mice [3,7].",
      ", increased exploration of the open areas) in both tests. One explanation is that DBA/2J is \u201csusceptible\u201d to this stressor, whereas C57BL/6J is \u201cresilient.\u201d However, a more circumscribed but potentially more accurate interpretation is that both strains react strongly to this particular stress regime, but differ in the manner in which the response manifests behaviorally. Thus, DBA/2J may develop a classic \u201cpassive\u201d anxiety-like suppression of approach behavior, whereas C57BL/6J may exhibit more of an \u201cactive\u201d response to stress. This could reflect an increased panic-like escape drive or manic-like reaction to stress in C57BL/6J, rather than a decrease in anxiety-like behavior.",
      "Differences in radiation sensitivity between the BXD parental strains were first described by Roderick more than 45 years ago, with DBA/2J succumbing more quickly than C57BL/6J to a lethal dose of radiation (26). At more modest doses, C57BL/6J mice were shown to be more resistant to radiation-induced genomic instability than DBA/2J (38, 84, 85).",
      "Genetic differences between C57 and DBA mice have been shown to translate into a broad spectrum of CNS related functional and molecular correlates, for example, differences in activity, impulsive action, hippocampal related memory and learning tasks, post- and pre-synaptic protein expression, and synaptic transmission and plasticity [27\u201340]. Through genetic linkage analyses, the genetic and phenotypic differences in the BXD panel of RI strains have resulted in identification of genes and loci involved in complex CNS functions, such as impulsivity [41], reversal learning [42], attention [43], neuronal oscillations [44], hearing loss [45], and fear and spatial learning [39,40].",
      "For example, the C57BL/6J (B6) and DBA2/J (D2) inbred mice frequently are used in alcohol research because they clearly differ in various responses to alcohol, including development of functional tolerance (Grieve and Littleton 1979), locomotor activation (Phillips et al. 1998), and sensitivity to withdrawal symptoms (Metten and Crabbe 1994). Because the environmental conditions in these experiments can be controlled, any differences observed between the mouse strains in these phenotypes most likely can be attributed to genetic differences.",
      "For example, when subjected to HFD, DBA/2J had 12.5% more body fat compared to C57BL/6J (P < 0.0001, Fig 1A). Additionally, the F1 offspring generated by DBA/2J dams (DBA/2J x C57BL/6J) had 10.6% more body fat (P < 0.001) compared to the F1 from C57BL/ 2J dams (C57BL/6J x DBA/2J). While the source of these latter effects appears to be maternal, further studies are needed to identify the molecular basis of these differences. In general, genetic differences between strains impacted body weight variation throughout the experiment (P < 0.05) (Fig 1B)."
    ],
    [
      "  Quantitative trait locus (QTL) mapping has been carried out in numerous species to associate regions of the genome to phenotypes even before the structure of the genome was well understood (e.g., [3]).Rodents, especially mice, have been the species most prominently used for biomedically relevant traits.Amongst these, the BXD family of recombinant inbred (RI) strains derived from crossing two inbred strains-C57BL/6J and DBA/2J mice-have been extensively used for almost 50 years in fields such as neuropharmacology [4][5][6], immunology [7][8][9][10][11][12][13], behaviour [13][14][15][16][17][18][19][20][21], aging [21][22][23][24][25][26][27][28][29], neurodegeneration [30][31][32][33], and gut microbiome-host interactions [34].",
      "Milhaud JM, Halley H, Lassalle JM (2002) Two QTLs located on chromosomes 1 and 5 modulate different aspects of the performance of mice of the B6D Ty RI strain series in the Morris navigation task. Behav Genet 32: 69\u201378. 16. Buck KJ, Rademacher BS, Metten P, Crabbe JC (2002) Mapping murine loci for physical dependence on ethanol. Psychopharmacology (Berl) 160: 398\u2013407. 17. Ferraro TN, Golden GT, Smith GG, Schork NJ, St Jean P, et al. (1997) Mapping murine loci for seizure response to kainic acid. Mamm Genome 8: 200\u2013208. 18.",
      "Other aggression QTLs Several lines of mice have been selectively bred for high or low levels of o\u00a1ensive aggression, which con\u00a2rms that a propensity for aggressive behaviours is partially heritable. These lines include the Turku aggressive (TA) and non-aggressive (TNS) strains bred in Finland, the NC900 and NC100 strains bred in North Carolina, and the short attack latency (SAL) and long attack latency (LAL) strains bred in the Netherlands (Miczek et al 2001). In wild mice, there is evidence for a QTL a\u00a1ecting aggressive behaviours in a region of chromosome 17, the t region.",
      "QTL ANALYSIS OF AGGRESSIVE BEHAVIOURS IN MICE  65  Progress towards identifying QTLs that a\u00a1ect aggressive behaviours in mice An example of aggression QTLs identi\u00a2ed as part of a whole genome scan One of the few studies to identify intermale aggression QTLs as part of a whole genome scan was published recently (Brodkin et al 2002). This study used NZB/ B1NJ (extremely aggressive) and A/J (extremely unaggressive) inbred mice as parental strains. The methods chosen for housing and aggression testing were designed to control the e\u00a1ect of non-genetic factors on the phenotype.",
      "Neuroscientist 4:317^323 Brodkin ES, Goforth SA, Keene AH, Fossella JA, Silver LM 2002 Identi\u00a2cation of quantitative trait loci that a\u00a1ect aggressive behavior in mice. J Neurosci 22:1165^1170 Chesler EJ, Lu L, Wang J, Williams RW, Manly KF 2004 WebQTL: rapid exploratory analysis of gene expression and genetic networks for brain and behavior. Nat Neurosci 7:485^486 Darvasi A 1997 Interval-speci\u00a2c congenic strains (ISCS): an experimental design for mapping a QTL into a 1-centimorgan interval. Mamm Genome 8:163^167 Darvasi A 1998 Experimental strategies for the genetic dissection of complex traits in animal models.",
      "Brodkin: Such a course mapping study with only about 400 mice would be unlikely to detect a QTL that accounts for only 2.5% of the phenotypic variance, QTL ANALYSIS OF AGGRESSIVE BEHAVIOURS IN MICE  73  but it should detect a QTL that accounts for approximately 10% of the variance (Lynch & Walsh 1998, Darvasi 1998). QTLs of this magnitude of e\u00a1ect on neurobiological or behavioural traits have been found fairly commonly in crosses between inbred mouse strains (see e.g. Wehner et al 1997).",
      "By correlating genotypes with phenotypes in quantitative trait locus (QTL) analysis, a large number of polymorphic regions harboring trait relevant allelic variation have been defined for a wide range of behavioral phenotypes [17]. At present, there are 340  549 QTLs for behavioral phenotypes in the Mouse Genome Informatics database, which are largely derived from crosses of 2 inbred strains of mice [18].",
      "A search of the Mouse Genome Informatics database (www.informatics.jax.org, March 16,2006) revealed 34 neurobehavioral- and/or pain-related QTLs mapped to >75 cM; these inc1ude seven traits related to alcohol, six to morphine or other drugs, two to painful arthritis, five to emotionality/anxiety, and one to seizure susceptibility. Several ofthese QTLs have been finely mapped near the peak of linkage of our analgesia QTL.",
      "The behavioral QTLs were determined from the MGI database as of October 1, 2004. Alcrsp2 (Erwin et al. , 1997); Ap3q (Bachmanov et al. , 2002); Alcp12 (Gill et al. , 1998). Behavioral QTLs have been mapped using other mouse strains, and their validity in the ILS and ISS strains has not been tested. Mb, megabases. Table 4.",
      "In the fourth step, we sought to identify DNA sequence variants that influence both molecular phenotypes as well as phenotypes at the structural and behavioral level. A remarkable region located on the distal end of mouse Chr 1 (172\u2013178 Mb) was the ideal subject for such an integrative study. This region, which we have named as Qrr1 (QTL rich region on distal Chr 1), is known for its unusually high density of QTLs for neural and behavioral traits, e.g. , traits like anxiety-related behavior, seizure, hippocampal volume, and alcohol preference consistently map to this region.",
      "Overall, these studies reveal the existence of an extensive polygenic system influencing the exploratory behavior of mice similar to the kind of genetic architecture shown to influence behavior in tests of fear and anxiety (Caldarone et al. 1997; Flint et al. 1995; Gill & Boyle 2005; Henderson et al. 2004; Laarakker et al. 2008; Singer et al. 2005; Turri et al. 2001a,b). The significance of the QTL, and also of the polygenic system, is heightened by the finding that roughly the same set of genes has the potential to influence some behaviors from early adulthood to old age.",
      "The behavioral phenotypes with QTLs on distal Chr 17 are (1) prepulse inhibition, assayed by McCaughran et al.41 in a panel of 21 BXD strains (trait ID on Genenetwork is 10396), (2) anxiety trait measure by time spent in open quadrant of zero-maze, assayed in a larger panel of 57 BXD strains42 (trait ID 11696) and (3) handling induced convulsion as an index of ethanol withdrawal severity, measured in 25 BXD strains43 (trait ID 10065). Gene\u2013gene interaction analysis.",
      "Quantitative trait locus (QTL) mapping has been carried out in numerous species to associate regions of the genome to phenotypes even before the structure of the genome was well understood (e.g. , [3]). Rodents, especially mice, have been the species most prominently used for biomedically relevant traits. Amongst these, the BXD family of recombinant inbred (RI) strains derived from crossing two inbred strains\u2014C57BL/6J and DBA/2J mice\u2014have been extensively used for almost 50 years in fields such as neuropharmacology [4\u20136], immunology [7\u201313], behaviour [13\u201321], aging [21\u201329], neurodegeneration [30\u201333], and gut microbiome\u2013host interactions [34].",
      "Two QTLs located on chromosomes 1 and 5 modulate different aspects of the performance of mice of the BXD Ty RI strain series in the Morris navigation task. Behav Genet. 2002; 32:69\u201378. [PubMed: 11958544] Mozhui RT, Ciobanu DC, Schikorski T, Wang XS, Lu L, Williams RW. Dissection of a QTL hotspot on mouse distal chromosome 1 that modulates neurobehavioral phenotypes and gene expression. PLoS Genetics. 2008; 4:e1000260. [PubMed: 19008955] Mulligan MK, Wang X, Adler AL, Mozhui K, Lu L, Williams RW. Complex control of GABA(A) receptor subunit mRNA expression: variation, covariation, and genetic regulation. PLoS One. 2012; 7(4):e34586.",
      "Type I and type II error rates for quantitative trait loci (QTL) mapping studies using recombinant inbred mouse strains. Behav Genet, 26(2): 149-160. Bidwell, L. C., Willcutt, E. G., Defries, J. C., & Pennington, B. F. 2007. Testing for neuropsychological endophenotypes in siblings discordant for attentiondeficit/hyperactivity disorder. Biol Psychiatry, 62(9): 991-998. Bitanihirwe, B. K., Dubroqua, S., Singer, P., Feldon, J., & Yee, B. K. 2011. Sensorimotor gating and vigilance-dependent choice accuracy: a within-subject correlative analysis in wild-type C57BL/6 mice. Behav Brain Res, 217(1): 178-187. 151 References Bitsios, P., & Giakoumaki, S. G. 2005.",
      "Quantitative trait locus (QTL) mapping has been carried out in numerous species to associate regions of the genome to phenotypes even before the structure of the genome was well understood (e.g. , [3]). Rodents, especially mice, have been the species most prominently used for biomedically relevant traits. Amongst these, the BXD family of recombinant inbred (RI) strains derived from crossing two inbred strains\u2014C57BL/6J and DBA/2J mice\u2014have been extensively used for almost 50 years in fields such as neuropharmacology [4\u20136], immunology [7\u201313], behaviour [13\u201321], aging [21\u201329], neurodegeneration [30\u201333], and gut microbiome\u2013host interactions [34].",
      "Other aggression QTLs Several lines of mice have been selectively bred for high or low levels of o\u00a1ensive aggression, which con\u00a2rms that a propensity for aggressive behaviours is partially heritable. These lines include the Turku aggressive (TA) and non-aggressive (TNS) strains bred in Finland, the NC900 and NC100 strains bred in North Carolina, and the short attack latency (SAL) and long attack latency (LAL) strains bred in the Netherlands (Miczek et al 2001). In wild mice, there is evidence for a QTL a\u00a1ecting aggressive behaviours in a region of chromosome 17, the t region.",
      "QTL ANALYSIS OF AGGRESSIVE BEHAVIOURS IN MICE  65  Progress towards identifying QTLs that a\u00a1ect aggressive behaviours in mice An example of aggression QTLs identi\u00a2ed as part of a whole genome scan One of the few studies to identify intermale aggression QTLs as part of a whole genome scan was published recently (Brodkin et al 2002). This study used NZB/ B1NJ (extremely aggressive) and A/J (extremely unaggressive) inbred mice as parental strains. The methods chosen for housing and aggression testing were designed to control the e\u00a1ect of non-genetic factors on the phenotype.",
      "Neuroscientist 4:317^323 Brodkin ES, Goforth SA, Keene AH, Fossella JA, Silver LM 2002 Identi\u00a2cation of quantitative trait loci that a\u00a1ect aggressive behavior in mice. J Neurosci 22:1165^1170 Chesler EJ, Lu L, Wang J, Williams RW, Manly KF 2004 WebQTL: rapid exploratory analysis of gene expression and genetic networks for brain and behavior. Nat Neurosci 7:485^486 Darvasi A 1997 Interval-speci\u00a2c congenic strains (ISCS): an experimental design for mapping a QTL into a 1-centimorgan interval. Mamm Genome 8:163^167 Darvasi A 1998 Experimental strategies for the genetic dissection of complex traits in animal models.",
      "Brodkin: Such a course mapping study with only about 400 mice would be unlikely to detect a QTL that accounts for only 2.5% of the phenotypic variance, QTL ANALYSIS OF AGGRESSIVE BEHAVIOURS IN MICE  73  but it should detect a QTL that accounts for approximately 10% of the variance (Lynch & Walsh 1998, Darvasi 1998). QTLs of this magnitude of e\u00a1ect on neurobiological or behavioural traits have been found fairly commonly in crosses between inbred mouse strains (see e.g. Wehner et al 1997)."
    ],
    [
      "Other cell cyclerelated genes, such as p21, p18 and p27, were also reported to be involved in regulating different types of hematopoietic cells (Cheng 2004; Steinman 2002). For example, p21 and p18 specifically control HSC proliferation, whereas p27 only affects hematopoietic progenitor cells. Further study of the chromosome 3 QTL interval in the congenic mouse model may provide a platform leading to the discovery of novel cycle-active gene and/or functions of already known genes. The apoptotic analyses shown in Table 3.2 are novel.",
      "Bystrykh L, Weersing E, Dontje B, Sutton S, Pletcher MT, Wiltshire T, Su AI, Vellenga E, Wang J, Manly KF, Lu L, Chesler EJ, Alberts R, Jansen RC, Williams RW, Cooke MP, de Haan G: Uncovering regulatory pathways that affect hematopoietic stem cell function using \u2018genetical genomics\u2019. Nat Genet 2005, 37(3):225-32. 29. Overall RW, Kempermann G, Peirce J, Lu L, Goldowitz D, Gage FH, Goodwin S, Smit AB, Airey DC, Rosen GD, Schalkwyk LC, Sutter TR, Nowakowski RS, Whatley S, Williams RW: Genetics of the hippocampal transcriptome in mouse: a systematic survey and online neurogenomics resource.",
      "In summary, I have identified p107 and Snx5 as quantitative trait genes that regulate the number of HSCs in B6 and congenic mice. CAFC assays confirmed that increased expression of both genes increases HSC number in an in vitro setting. Although the increased expression of both Snx5 and p107 resulted in small increases in HSC number, the changes are biologically significant given the extensive proliferative potential of primitive stem cells.",
      "The molecular mechanisms that regulate progenitor cell division and differentiation in the RMS remain largely unknown. Here, we surveyed the mouse genome in an unbiased manner to identify candidate gene loci that regulate proliferation in the adult RMS. We quantified neurogenesis in adult C57BL/6J and A/J mice and 27 recombinant inbred lines derived from those parental strains. We showed that the A/J RMS had greater numbers of bromodeoxyuridine-labeled cells than that of C57BL/6J mice with similar cell cycle parameters, indicating that the differences in the number of bromodeoxyuridine-positive cells reflected the number of proliferating cells between the strains.",
      "Page 10  NIH-PA Author Manuscript  Septin 9 (Sept9) and cyclin-dependent kinase 3 (cdk3) and are two other genes that are worth mentioning because even though they are not directly linked to neurogenesis, they are both cell cycle regulatory genes. Sept9 is involved in the progression through G1 of the cell cycle and it is highly expressed throughout the adult mouse brain (Gonzalez et al. , 2009). Whereas, cdk3 is expressed at low levels throughout the adult mouse brain and it is required for G1-S transition (Braun et al. , 1998).",
      "Bystrykh L, Weersing E, Dontje B, Sutton S, Pletcher MT, Wiltshire T et al. (2005). Uncovering regulatory pathways that effect hematopoietic stem cell function using \u2018genetical genomics\u2019. Nat Genet 37:225\u2013232. Cai L, Morrow EM, Cepko CL (2000). Misexpression of basic helix-loop-helix genes in the murine cerebral cortex affects cell fate choices and neuronal survival. Development 127:3021\u20133030. Caldarone B, Saavedra C, Tartaglia K, Wehner JM, Dudek BC, Flaherty L (1997). Quantitative trait loci analysis affecting contextual conditioning in mice. Nat Genet 17:335\u2013337. Calder AJ, Lawrence AD, Young AW (2001). Neuropsychology of fear and loathing. Nature Rev Neurosci 2:352\u2013363.",
      "As further step, this finding opens the door to study the molecular networks via which LRP6 acts to regulate proliferation. ! '*! ! +&(/. ((&-*)  5.2. Redox regulation of Adult Hippocampal Precursor Cells  5.2.1. Hypoxia increases AHPCs proliferation and neuronal differentiation Oxygen concentration plays an important role in cellular development and tissue homeostasis. In the brain, depending on the tissue, the oxygen concentration varies from 0.1 to 5% and in the rat hippocampus it is around 3.2% (Studer et al. , 2000).",
      "While this study covers only one part in the several conceptual levels of regulation we are confident that this work will lead to finding a central regulatory pathway that regulates adult hippocampal precursor cell proliferation. ! &*! ! +&(/. ((&-*)  5.1.1. Establishment of AHPCs Isolating the precursor cells has become extremely important in order to study them in detail away from the influence of their in vivo niche. Once the cells are in culture they express their autonomous, intrinsic properties without the niche influences such as cell-cell contacts, blood vessels, known and unknown growth factors and network activities.",
      "Gene expression profiling using RNA samples from proliferating cultures of the 20 BXD mice strains yielded two cis eQTL candidates that directly regulated proliferation, LRP6 and Chchd8. LRP6 is well known as a co-receptor of Wnt signaling, but the function of Chchd8 is not known. Further experimentation, using over-  ! I! ! SUMMARY  expression and gene silencing demonstrated that LRP6 negatively regulates AHPCs proliferation. Thus, from this study using a system genetics approach, we were able to identify, LRP6 as a novel regulator of adult hippocampal neurogenesis. ! V! ! INTRODUCTION  2. INTRODUCTION 2.1.",
      "Gene expression profiling ...............................................................68 4.1.8. LRP6 is a novel regulator of AHPCs proliferation .........................73 4.2. Redox regulation of Adult Hippocampal Precursor Cells................78 4.2.1. AHPCs yield increased under hypoxic conditions..........................78  ! T! ! TABLE OF CONTENTS  4.2.2. More neuronal differentiation under hypoxic conditions................79 5. DISCUSSION ..............................................................................................81 5.1. Systems genetic approach to identify genes regulating AHPCs proliferation .................................................................................................81 5.1.1. Establishment of AHPCs................................................................82 5.1.2. Variation in proliferative and differentiative properties of AHPCs83 5.1.3. QTL analysis ...................................................................................86 5.1.4. Candidate genes from gene expression profiling ............................87 5.1.5. Lrp6 as negative regulator of AHPCs proliferation ........................89 5.2. Redox regulation of Adult Hippocampal Precursor Cells................92 5.2.1.",
      "Mapping determinants of human gene expression by regional and genome-wide association. Nature 437, 1365-1369. Chiasson, B.J. , Tropepe, V., Morshead, C.M. , and van der Kooy, D. (1999). Adult mammalian forebrain ependymal and subependymal cells demonstrate proliferative potential, but only subependymal cells have neural stem cell characteristics. Journal of Neuroscience 19, 4462-4471. Cipolleschi, M.G. , Dello Sbarba, P., and Olivotto, M. (1993). The role of hypoxia in the maintenance of hematopoietic stem cells. Blood 82, 20312037. Clarke, D.L. , Johansson, C.B. , Wilbertz, J., Veress, B., Nilsson, E., Karlstrom, H., Lendahl, U., and Frisen, J. (2000).",
      "List of BXD AHPC lines stored  Table 3. List of eQTls in 0.6 threshold range  Table 4. Cis acting genes regulating proliferation trait  ! U#! ! PUBLICATIONS  Publications  A protocol for isolation and enriched monolayer cultivation of neural precursor cells from mouse dentate gyrus. Harish Babu*, Jan-Hendrik Claasen*, Suresh Kannan, Annette E. R\u00fcnker, Theo Palmer, Gerd Kempermann. Front. Neurosci. 5:89. doi: 10.3389/fnins.2011.00089  System genetics approach yields candidate genes regulating adult hippocampal precursor cells proliferation, Manuscript in preparation (first author paper)  ! U##! ! SUMMARY  1. SUMMARY Adult hippocampal neurogenesis is regulated at various levels and by various factors.",
      "A recent study suggesting the role of mitochondria and  ! &&! ! +&(/. ((&-*)  cytochrome  oxidase  in  enhancing  hippocampal  neurogenesis  during  inflammation (Voloboueva et al. , 2010) may reveal the link for Chchd8 gene in adult neurogenesis. 5.1.5. Lrp6 as negative regulator of AHPCs proliferation The results from our gene expression profiling suggest that high expression level of Lrp6 is associated with slow proliferating AHPCs and vice versa. We confirmed this result by over expressing LRP6 in AHPCs. This revealed that LRP6 over expression reduced the proliferation of AHPCs by more than 2fold.",
      "Two types of collagen and N-Cadherin were also in this pathway. The top upstream regulators of this gene set were Huntingtin (HTT) which regulates 32 of the 193 genes analyzed (p = 1.22 \u00d7 10\u221215), and \u03b2-estradiol which may regulate 39 out of 193 genes in the set (p = 4.06 \u00d7 10\u221210). 3.2.2. Genes regulated by ethanol in the NAC following CIE\u2014Three hundred seventy-eight probesets were exclusively altered by ethanol in the NAC only following CIE (Supplemental Fig. 2 and Table 5).",
      "Expression of a subset of these neurogenesis-associated transcripts was controlled in cis across the BXD set. These self-modulating genes are particularly interesting candidates to control neurogenesis. Among these were musashi (Msi1h) and prominin1\u517eCD133 (Prom1), both of which are linked to stem-cell maintenance and division. Twelve neurogenesis-associated transcripts had significant cis-acting quantitative trait loci, and, of these, six had plausible biological association with adult neurogenesis (Prom1, Ssbp2, Kcnq2, Ndufs2, Camk4, and Kcnj9). Only one cis-acting candidate was linked to both neurogenesis and gliogenesis, Rapgef6, a downstream target of ras signaling.",
      "Other cell cyclerelated genes, such as p21, p18 and p27, were also reported to be involved in regulating different types of hematopoietic cells (Cheng 2004; Steinman 2002). For example, p21 and p18 specifically control HSC proliferation, whereas p27 only affects hematopoietic progenitor cells. Further study of the chromosome 3 QTL interval in the congenic mouse model may provide a platform leading to the discovery of novel cycle-active gene and/or functions of already known genes. The apoptotic analyses shown in Table 3.2 are novel.",
      "  and Tgfbr3 (transforming growth factor beta receptor 3).Of the significant genes correlated with the hippocampal cell death phenotype, there were 107 genes that were significant for a strain \u00d7 treatment interaction.Four of these genes also showed an FC > 1.5: Gadd45g (growth arrest and DNA-damage-inducible, gamma), Kcnj13 (potassium inwardly rectifying channel, subfamily J, member 13), Plekhg1 (pleckstrin homology domain containing, family G (with RhoGef domain) member 1), and Sgms2 (sphingomyelin synthase 2).",
      "111 Bystrykh, L., E. Weersing, et al. (2005). \"Uncovering regulatory pathways that affect hematopoietic stem cell function using 'genetical genomics'. \"Nat Genet 37(3): 225-32. Cashman, J., A. C. Eaves, et al. (1985). \"Regulated proliferation of primitive hematopoietic progenitor cells in long-term human marrow cultures. \"Blood 66: 1002-1005. Celeste, A., O. Fernandez-Capetillo, et al. (2003). \"Histone H2AX phosphorylation is dispensable for the initial recognition of DNA breaks. \"Nat Cell Biol 5(7): 675-9. Chen, J., B. A. Astle, et al. (1999). \"Development and aging of primitive hematopoietic stem cells in BALB/cBy mice.\"Exp. Hematol. 27: 928-935. Cheng, T., N. Rodrigues, et al.",
      "  The next category was Cellular Growth and Proliferation, which includes growth, proliferation, expansion and differentiation of cells and is also pertinent to the possible formation of new cells in this area of the hippocampus.37 genes were associated with this function.Not surprisingly, in the Cell Cycle function (Supplementary Table 2) we found thirty genes involved in cell cycle progression indicating the activity of dividing cells in this region.",
      "Lef1 is expressed in cultured hippocampal neural stem cells in response to activation of the Wnt signaling pathway (Cui et al. , 2011). Our evidence and the literature both suggest that genes known to be involved in hippocampal adult neurogenesis are targets of Lef1, an important factor in generating granule cells in the dentate gyrus during development (Galceran et al. , 2000). The only two genes not targeted by Lef1 can be closely associated with it: Mtdh regulates the expression of Lef1 (Hu et al. , 2009; Yoo et al."
    ],
    [
      "QTL Mapping and Identification of Candidate Genes A QTL is a region of the genome shown to be linked to a trait. The purpose of mapping this region is to identify a region of a genome that has a higher probability of harbouring the genetic variations controlling variability in trait values.",
      "Often a local eQTL will be caused by allelic variation in the regulatory region of the gene or within the gene itself. mQTL A metabolite Quantitative Trait Locus is a region in the genome at which allelic variation correlates with the abundance variation of a certain metabolite. pQTL A protein Quantitative Trait Locus is a region in the genome at which allelic variation correlates with the abundance variation of a certain protein. Just like eQTL, pQTL can be local or distant according to the genomic position of the gene encoding for the protein relative to the QTL.",
      "QTLs are regions within the genome whose genetic variation modulates quantitatively a phenotype characteristic of the particular trait under study (Lynch and Walsh, 1998). Determining the association between variations in specific disease phenotypes or a trait, with variations in genotypes of a reference population can be used to locate a QTL. One of the methods used for mapping 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 crosses between inbred lines, or use of the out-bred populations.",
      "Quantitative trait locus-mapping is a statistical method used to map chromosomal intervals (loci) that contribute to heritable variance in phenotypes. The method simply compares the inheritance of allelic variants (B or D genotypes in our case) with differences in phenotypes. A QTL will generally cover a region that includes 10\u2013100 genes, and these positional candidates can then be ranked roughly on the basis of criteria such as the types of DNA variants, patterns of mRNA expression, data from complementary human genetic cohorts (GWAS and linkage) and relevant literature about gene effects on central nervous system structure and function.",
      "Chromosomal regions containing a gene (or genes) that a\u00a1ect the level of a quantitative trait are called quantitative trait loci (QTLs). The relevant genes in these regions have been called quantitative trait genes (QTGs) (Hitzemann et al 2003). Quantitative trait locus (QTL) analysis is an experimental strategy for identifying QTLs, and ultimately QTGs, that a\u00a1ect quantitative traits. Because of the complexity of these traits, progress in identifying QTGs has been slow compared to that in cloning genes underlying Mendelian traits (Glazier et al 2002).",
      "Expression QTL Next, we will examine expression quantitative trait loci (eQTLs). These are QTLs for gene expression traits, a subset of the molecular phenotypes mentioned above. Much like classical phenotypes, expression of transcripts can be influenced by variants within the genome. However, because we know the location of the gene, we can split these eQTL into two categories, trans- (or distal) or cis- (or local) eQTL. A trans-eQTL (or distal-eQTL) describes when the expression of a gene is influenced by a locus far away from that gene, and therefore indicates that the gene of interest is downstream of another gene.",
      "These loci which are associated with changes in transcript expression are often termed expression QTL (eQTL): a variant (or variants) within the locus alters the expression of the gene of interest. An eQTL found near to the location (~ \u2264 1Mbp) of the transcript is described as a local eQTL, and are often called ciseQTL. This is in contrast to trans-eQTL which are found more distally. Cis-eQTL are interesting when they are found for a gene within a QTL for another phenotype (e.g.",
      "The location of these genotypes are quantitative trait loci (QTLs) [Abiola et al. , 2003]. Detected via statistical methods [Doerge, 2002], QTLs are stretches of DNA highly associated with a specific phenotype, analogous to genetic landmarks which roughly indicate the position of the active gene. QTLs are not defined at very fine granularity; they usually correspond to areas large enough to hold several genes. The genetic polymorphism (genotypes) in neighboring areas of a set of loci, as a group, influence structure and function on both molecular and organismic scales.",
      "Quantitative trait loci (QTL)  132  analysis is a means to query the entire genome for DNA variants (markers) that show significant  133  associations with the phenotype (quantitative trait) under investigation. This is the first step to  134  identify candidate genes whose variants (alleles) affect the value of the phenotype. QTL analysis  135  was performed using WebQTL (http://www.genenetwork.org) for each PCA factor. WebQTL  136  performs 2,000 or more permutations of the strain data and significant QTL are defined by the  137  likelihood ratio statistic (LRS) score of correctly ordered data exceeding all other permutations  138  95% of the time, i.e.",
      "Expression QTL Next, we will examine expression quantitative trait loci (eQTLs). These are QTLs for gene expression traits, a subset of the molecular phenotypes mentioned above. Much like classical phenotypes, expression of transcripts can be influenced by variants within the genome. However, because we know the location of the gene, we can split these eQTL into two categories, trans- (or distal) or cis- (or local) eQTL. A trans-eQTL (or distal-eQTL) describes when the expression of a gene is influenced by a locus far away from that gene, and therefore indicates that the gene of interest is downstream of another gene.",
      "These are referred to as expression QTLs, or eQTLs (Schadt et al. , 2003), which control a portion of expression variation of particular genes in a population. eQTLs result from genetic differences in regulatory elements close to or within the gene (apparent cis-acting eQTLs) as well as those that map elsewhere in the genome from the gene whose expression is modulated (trans-acting eQTLs). By combining microarray and QTL analysis on the same mice, much can be learned about the genetic underpinnings of particular alcohol traits (Hitzemann et al. , 2004; Tabakoff et al. , 2003).",
      "Working with complex traits that typically vary in their manifestation across a continuous distribution, in contrast to the binary nature of monogenic traits, QTLs are discovered by simply identifying loci with alleles that consistently covary with a phenotype across a population. Genomic regions that show a sufficiently strong association with a phenotype are considered QTLs. The simplest, or most hopeful, interpretation of a mapped QTL is that the implicated region harbors a single gene affecting manifestation of the associated phenotype.",
      "By definition, a quantitative trait locus is a chromosomal region that contains a gene, or genes, that regulate 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 genes relevant to a specified trait. QTL map locations are commonly determined by initial screening of mice with specific genetic characteristics, such as recombinant inbred strains, the F2 of two inbred strains, or recombinant congenic strains (Flint 2003).",
      "(2003) and others defined the expression QTLs (eQTLs) as either cis (mapping near the gene locus) or trans (mapping elsewhere in the genome). When behavioral QTLs (bQTLs) and cis-eQTLs overlap, the cis-eQTL genes are inferred as strong quantitative trait gene (QTG) candidates (see e.g. Farris et al. 2010). The situation for trans-eQTLs is more complicated since the QTL confidence interval is generally larger and any gene within the QTL interval could have a regulatory role. The application of genetical genomics to mouse has generally focused on segregating populations involving R. Hitzemann et al.",
      "Page 2  Definition of a QTL NIH-PA Author Manuscript  A quantitative trait is one that has measurable phenotypic variation owing to genetic and/or environmental influences. This variation can consist of discrete values, such as the number of separate tumours in the intestine of a cancer-prone mouse, or can be continuous, such as measurements of height, weight and blood pressure. Sometimes a threshold must be crossed for the quantitative trait to be expressed; this is common among complex diseases. A QTL is a genetic locus, the alleles of which affect this variation.",
      "When the phenotype of interest is a quantitative trait, such as blood pressure or cholesterol levels, the underlying genetic locus is referred to as a \u201cQTL\u201d. A common strategy investigates the association between quantitative traits of transcriptional responses and their underlying DNA loci called \u201cresponse QTLs\u201d (reQTLs) (Albert and Kruglyak 2015). Studies have provided clear evidence for the colocalization of reQTLs and disease-related loci (Caliskan et al. 2015).",
      "81 Gene Expression Quantitative Trait Locus Analysis Quantitative trait locus (QTL) mapping is a statistical technique that finds associations between phenotype and genotype in a genetically segregating population (Lander and Botstein 1989). Here, we performed eQTL mapping on the male and female data separately. There were 1,137 significant (q\u22640.5 and p\u22640.025) male and 1,232  female eQTLs. First, we explored differences in patterns of eQTL locations between sexes by plotting the genomic locations of each eQTL versus the transcript location (Figure 4.3a, b).",
      "Chromosomal regions containing a gene (or genes) that a\u00a1ect the level of a quantitative trait are called quantitative trait loci (QTLs). The relevant genes in these regions have been called quantitative trait genes (QTGs) (Hitzemann et al 2003). Quantitative trait locus (QTL) analysis is an experimental strategy for identifying QTLs, and ultimately QTGs, that a\u00a1ect quantitative traits. Because of the complexity of these traits, progress in identifying QTGs has been slow compared to that in cloning genes underlying Mendelian traits (Glazier et al 2002).",
      "1.4  Q u a n tita tiv e T rait L ocu s M a p p in g  Q uantitative tra it loci (QTLs) are genetic regions on a chromosome th a t control certain quantitative traits, such as crop yield or body fat. QTL m apping involves con\u00ad struction of genomic m aps and testing for association between tra its and polymorphic markers. A significant association provides evidence th a t a QTL is near th e m arker.",
      "  Current data processing capabilities have also made it possible to search genome-wide for QTL (quantitative trait loci) [109].QTL mapping seeks to identify the relationship between various genomic locations and a set of quantitative traits, leading to a chromosomal location and ultimately to identification of gene(s) with the final goal of looking at gene expression.Among other things, this will lead to a better understanding of genetic mechanisms of variation and adaptation [121].Results can then be applied to adjust conservation measures in response to rapid change, for example, by identifying the genetic adaptability potential of individuals to be used in assisted migration or reintroduction [122,123]."
    ]
  ]
}