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authorBonface2024-02-13 23:52:26 -0600
committerMunyoki Kilyungi2024-08-09 13:30:43 +0300
commitb2feda451ccfbeaed02dce9088d6dd228cf15861 (patch)
tree3dd2883524985114070a7770cd2e9f9bd7eb1848 /general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619
parentd029d5d7f8ead1f1de8d318045004a4a6f68f5fb (diff)
downloadgn-docs-b2feda451ccfbeaed02dce9088d6dd228cf15861.tar.gz
Update dataset RTF Files.
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-rw-r--r--general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/acknowledgment.rtf3
-rw-r--r--general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/citation.rtf1
-rw-r--r--general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/experiment-design.rtf1
-rw-r--r--general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/processing.rtf5
-rw-r--r--general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/specifics.rtf1
-rw-r--r--general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/summary.rtf3
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diff --git a/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/acknowledgment.rtf b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/acknowledgment.rtf
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+<p>The Authors would like to thank Electron Microscopy, Flow Cytometry, Histology, and Gene Expression Services at The Jackson Laboratory, Rick Libby for careful reading of the manuscript and discussion, Mimi de Vries for assistance with organizing and mouse colonies, Brynn Cardozo and Trip Freeburg for colony maintenance, Jocelyn Thomas for blood collections, Philipp Tauber for assistance with immunofluorescence, and Amy Bell for intraocular pressure measurements.</p>
+
+<p>EY011721 (SWMJ), EY021525 (GRH). Pete Williams is supported by the Karolinska Institutet in the form of a Board of Research Faculty Funded Career Position. Simon John is an Investigator of HHMI.</p>
diff --git a/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/citation.rtf b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/citation.rtf
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+<p>Williams, P.A., Braine, C.E., Kizhatil, K.&nbsp;<i>et al.</i>&nbsp;Inhibition of monocyte-like cell extravasation protects from neurodegeneration in DBA/2J glaucoma.<i>Mol Neurodegeneration</i>&nbsp;14,&nbsp;6 (2019) https://doi.org/10.1186/s13024-018-0303-3</p>
diff --git a/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/experiment-design.rtf b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/experiment-design.rtf
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+<p>To understand the function of these infiltrating monocyte-like cells, we used RNA-sequencing to profile their transcriptomes. Based on their pro-inflammatory molecular signatures, we hypothesized and confirmed that monocyte-platelet interactions occur in glaucomatous tissue. Furthermore, to test monocyte function we used two approaches to inhibit their entry into the optic nerve head: (1) treatment with DS-SILY, a peptidoglycan that acts as a barrier to platelet adhesion to the vessel wall and to monocytes, and (2) genetic targeting of Itgam (CD11b, an immune cell receptor that enables immune cell extravasation).</p>
diff --git a/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/processing.rtf b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/processing.rtf
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+<h3 id="Sec8">RNA-sequencing and analysis</h3>
+
+<p>Monocytes from single optic nerve heads or from peripheral blood (restrained cheek bleed) were FAC sorted into 100&thinsp;&mu;l buffer RLT&thinsp;+&thinsp;1% &beta;ME and frozen at &minus;&thinsp;80&thinsp;&deg;C until further processing. Samples were defrosted on ice and homogenized by syringe in RLT Buffer (total volume 300&thinsp;&mu;l). Total RNA was isolated using RNeasy micro kits as according to manufacturer&rsquo;s protocols (Qiagen) including the optional DNase treatment step, and quality was assessed using an Agilent 2100 Bioanalyzer. The concentration was determined using a Ribogreen Assay from Invitrogen. Amplified dscDNA libraries were created using a Nugen Ovation RNA-seq System V2 and a primer titration was performed to remove primer dimers from the sample to allow sample inputs as low as 50&thinsp;pg RNA. The SPIA dscDNA was sheared to 300&thinsp;bp in length using a Diogenode Disruptor. Quality control was performed using an Agilent 2100 Bioanalyzer and a DNA 1000 chip assay. Library size produced was analysed using qPCR using the Library Quantitation kit/Illumina GA /ABI Prism (Kapa Biosystems). Libraries were barcoded, pooled, and sequenced 6 samples per lane on a HiSeq 2000 sequencer (Illumina) giving a depth of 30&ndash;35 million reads per sample.</p>
+
+<p>Following RNA-sequencing samples were subjected to quality control analysis by a custom quality control python script. Reads with 70% of their bases having a base quality score&thinsp;&ge;&thinsp;30 were retained for further analysis. Read alignment was performed using TopHat v 2.0.7 [<a aria-label="Reference 34" data-test="citation-ref" data-track="click" data-track-action="reference anchor" data-track-label="link" href="https://molecularneurodegeneration.biomedcentral.com/articles/10.1186/s13024-018-0303-3#ref-CR34" id="ref-link-section-d88755e1228" title="Kim D, Pertea G, Trapnell C, Pimentel H, Kelley R, Salzberg SL. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 2013;14:R36.">34</a>] and expression estimation was performed using HTSeq [<a aria-label="Reference 35" data-test="citation-ref" data-track="click" data-track-action="reference anchor" data-track-label="link" href="https://molecularneurodegeneration.biomedcentral.com/articles/10.1186/s13024-018-0303-3#ref-CR35" id="ref-link-section-d88755e1231" title="Anders S, Pyl PT, Huber W. HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31:166–9.">35</a>] with supplied annotations and default parameters against the DBA/2&thinsp;J mouse genome (build-mm10). Bamtools v 1.0.2 [<a aria-label="Reference 36" data-test="citation-ref" data-track="click" data-track-action="reference anchor" data-track-label="link" href="https://molecularneurodegeneration.biomedcentral.com/articles/10.1186/s13024-018-0303-3#ref-CR36" id="ref-link-section-d88755e1234" title="Barnett DW, Garrison EK, Quinlan AR, Strömberg MP, Marth GT. BamTools: a C++ API and toolkit for analyzing and managing BAM files. Bioinformatics. 2011;27:1691–2.">36</a>] were used to calculate the mapping statistics. Differential gene expression analysis between groups was performed using edgeR v 3.10.5 [<a aria-label="Reference 37" data-test="citation-ref" data-track="click" data-track-action="reference anchor" data-track-label="link" href="https://molecularneurodegeneration.biomedcentral.com/articles/10.1186/s13024-018-0303-3#ref-CR37" id="ref-link-section-d88755e1237" title="Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–40.">37</a>] following, batch correction using RUVSeq, the removal of outlier samples and lowly expressed genes by removing genes with less than five reads in more than two samples. Normalization was performed using the trimmed mean of M values (TMM). Unsupervised HC was performed in R (1-cor, Spearman&rsquo;s&nbsp;<i>rho</i>). Following preliminary analysis, 1 sample was removed as an outlier. Adjustment for multiple testing was performed using false discovery rate (FDR). Genes were considered to be significantly differentially expression at a false discovery rate (FDR;&nbsp;<i>q</i>) of&nbsp;<i>q</i>&thinsp;&lt;&thinsp;0.05. Pathway analysis was performed in R, IPA (Ingenuity Pathway Analysis, Qiagen), and using publically available tools (see&nbsp;<a data-track="click" data-track-action="section anchor" data-track-label="link" href="https://molecularneurodegeneration.biomedcentral.com/articles/10.1186/s13024-018-0303-3#Sec15">Results</a>).</p>
diff --git a/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/specifics.rtf b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/specifics.rtf
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+JAX DBA/2J Monocyte 1 vs PBMC RNA-Seq (Jun19) \ No newline at end of file
diff --git a/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/summary.rtf b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/summary.rtf
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+<p>Glaucoma is characterized by the progressive dysfunction and loss of retinal ganglion cells. Recent work in animal models suggests that a critical neuroinflammatory event damages retinal ganglion cell axons in the optic nerve head during ocular hypertensive injury. We previously demonstrated that monocyte-like cells enter the optic nerve head in an ocular hypertensive mouse model of glaucoma (DBA/2&thinsp;J), but their roles, if any, in mediating axon damage remain unclear.</p>
+
+<p><a href="https://molecularneurodegeneration.biomedcentral.com/articles/10.1186/s13024-018-0303-3" target="_blank">https://molecularneurodegeneration.biomedcentral.com/articles/10.1186/s13024-018-0303-3</a></p>