Author: Chad N. Brocker; Donghwan Kim; Tisha Melia; Kritika Karri; Thomas J. Velenosi; Shogo Takahashi; Jessica A. Bonzo; David J. Waxman; Frank J. Gonzalez
Title: Long non-coding RNA Gm15441 attenuates hepatic inflammasome activation in response to metabolic stress Document date: 2019_6_20
ID: dt0b7jnu_50
Snippet: Data were analyzed using a custom RNA-seq analysis pipeline (Connerney et al., 2017) as described elsewhere (Lodato et al., 2017) . Briefly, sequence reads were mapped to the mouse genome (release mm9) using TopHat2 (v2.1.1) (Kim et al., 2013) . Genomic regions that contain exonic sequence in at least one isoform of a gene (exon collapsed regions; (Connerney et al., 2017) ) . CC-BY-NC-ND 4.0 International license is made available under a The cop.....
Document: Data were analyzed using a custom RNA-seq analysis pipeline (Connerney et al., 2017) as described elsewhere (Lodato et al., 2017) . Briefly, sequence reads were mapped to the mouse genome (release mm9) using TopHat2 (v2.1.1) (Kim et al., 2013) . Genomic regions that contain exonic sequence in at least one isoform of a gene (exon collapsed regions; (Connerney et al., 2017) ) . CC-BY-NC-ND 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/675785 doi: bioRxiv preprint were defined for each RefSeq gene and for each lncRNA gene. HTSeq (0.6.1p1) was then used to obtain read counts for exon collapsed regions of RefSeq genes, and featureCounts (1.4.6-p5) was used to obtain read counts for exon collapsed regions of lncRNA genes. A set of 24,197 annotated mouse RefSeq genes (which includes some RefSeq lncRNAs) and a set of 15,558 liver-expressed lncRNA genes (Lodato et al., 2017; Melia and Waxman, 2019) was considered for differential expression analysis. These lncRNAs include intergenic lncRNAs, as well as lncRNAs that are antisense or intragenic with respect to RefSeq genes, and were discovered using a computational pipeline for lncRNA discovery described elsewhere (Melia et al., 2016) based on 186 mouse liver RNA-seq datasets representing 30 different biological conditions. RefSeq and lncRNA genes that showed significant differential expression following exposure to WY-14643 were identified by EdgeR as outlined elsewhere (Melia et al., 2016) . Genes dysregulated with an expression foldchange (i.e., either up regulation or down regulation) >2 at a false discovery rate (FDR), i.e., an adjusted P-value <0.05 were considered significant and are shown in Table S1 and Table S2 . Raw and processed RNA-seq data are available at GEO (https://www.ncbi.nlm.nih.gov/gds) accession numbers GSE132385 and GSE132386.
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