2.4 RNA-sequencing and bioinformatics analysis
The total RNA of liver from Mdr2-/- mice was extracted and then quantitated by NanoRhatometer@spectrophotometer (IMPLEN, USA). The RNA Nano Assay kit was used to measuring the integrity of RNA and the poly-T oligo-attached magnetic beads were applied for purifying the mRNA. After synthesizing the cDNA, the AMPure XP system (Beckman Coulter, USA) was used to purify the library fragments to enrich cDNA fragments in 250-300 bp. Furthermore, the sequencing library was established by the NEBNext UItraTM RNA Library Prep Kit (NEB) and generated on the Illumina Novaseq platform as previously described (Li et al., 2022). Subsequently, sequencing samples were normalized and differentially expressed genes (DEGs) were analyzed using the edgeR software. Gene ontology (GO) enrichment analysis of DEGs was performed using the cluster Profiler R package. Gene set enrichment analysis (GSEA) was used for in-depth analysis of the data, and hierarchical clustering analysis was performed using the heatmap R package. For GSEA analysis, we used DESeq2 as a ranking metric for conducting enrichment analysis of gene sets (http://software.broadinstitute.org/gsea/index.jsp). This method was used to determine whether target genes display statistically significant and consistent differences between two biological samples. For WGCNA analysis, according to these coding genes’ expression profiles, the WGCNA co-expression algorithm was used to mine the co-expressing coding genes and co-expression modules. First, protein-encoding genes’ expression profiles were extracted from the COAD expression profiles in the TCGA database, and the samples were clustered using hierarchical clustering. Outliers were removed and the rest samples were retained; further, the Pearson correlation coefficient was used to calculate the distance between each gene. The R software package WGCNA was used to construct a weighted co-expression network.