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.