title: RNA-seq of C57 mice
design: Total RNA was extracted from mice colonic tissues as specified experiments using TRIzol Reagent. RNA concentration and integrity were quantified and evaluated by NanoDrop 2000 (Thermo Fisher Scientific, Wilmington, DE) and RNA 6000 Nano, respectively. RNA was applied for constructing sequencing library based on the standard of OD 260/280=1.8-2.2, OD260/230  2.0, RIN6.6 and 28S:18S  1.0. 1 g of total RNA was captured and purified by RNAClean XP beads. mRNA was selected by an anchored oligo (dT) primer, and used for generating cDNA and preparing RNA-seq transcriptome libraries following Hieff NGS Ultima Dual-mode mRNA Library Prep Kit for Illumina. The sequencing run was performed on Illumina NovaSeqTM 6000 Sequencing System (Genewiz, South Plainfield, NJ, USA) using the indexed, 50-cycle single-read protocol. Fragments per kilobase of exon per million mapped reads (FRKM) method was applied for calculating the expression level for each transcript to identify differential expression genes (DEGs). The DESeq2 package from Bioconductor was performed for differential expression analysis. OriginLab Origin 2024 was used to perform principal component analysis (PCA). ToppGene and ToppCluster programs were applied to test for functional annotation enrichment analyses of pathways, immune cell-type enrichments, phenotype, and biological functions. Visualization of the network was plotted by Cytoscape software. A weighted gene correlation network analysis (WGCNA) was performed on normalized expression data applying the R package WGCNA v.1.6953. Heatmaps were plot using multi-experimental viewer (MeV) quickstart guide calculated from scaled (z-scores) normalized read counts of DEGs with a hierarchical clustering of the rows. Genes were filtered to keep only genes that explained more than 50 % of the variance (2,445 kept genes and 24,682 removed) for computational efficiency. By computing the Pearson correlation between each pair of variables and Student asymptotic P values for the correlations applying the WGCNA package, a module-trait correlation analysis was carried out between the ME and the DSS and SSW traits. A GO enrichment analysis of the genes in the different MEs was performed using goseq, with Wallenius approximation and the genome-wide annotation for Mouse (org.Mm.eg.db v.3.13.0). We next explored and determined the relationship between the mitochondrial-related genes and pathways with T cell function markers using correlation analysis, regression models, STRING database and Cytoscape software.
library_name: BT294-001T0014
identifiers.namespace: SUB15194657
identifiers.id: BT294-001T0014