Mouse RNA-seq data analysis: differential expression and gene set enrichment

Comparisons of gene expression between sample groups were made using DESeq2 to fit a negative binomial generalized linear model with a group variable. Wald statistics were used to determine the significance of the group coefficient, i.e., the log2-fold change (LFC) in expression between groups. We used the Benjamini-Hochberg method for controlling the false discovery rate (FDR). The P values reported are FDR adjusted. Genes with an adjusted P-value of at most 0.05 were considered differentially expressed (DE) between groups. The LFCs and FDR-adjusted P values were given as input to the fgsea() function from the fgsea R package (v.1.16.0) ⁷⁹, which implements a preranked gene set enrichment analysis. The rankings of the genes were based on the FDR-adjusted P values. The mouse KEGG pathway database (mmuKegg) ⁸⁰ and/or the Gene Ontology Biological Processes (GO-BP) database ^81,82 were the gene sets used in the enrichment analyses. Enriched pathways (i.e., P <0.05) were collapsed to independent pathways to avoid repetitive terms, using the fgsea collapsePathways() function.

This set of DE genes was determined by grouping together “ileum-like” samples, i.e., WT ileum and GATA^∆IEC jejunum samples, and comparing them with WT Jejunum samples. Comparisons were performed separately for the tissue and IECs. A threshold of >0.25 for the absolute value of the LFC was used to filter the very high number of DE genes in the tissue RNA-seq data, whereas no LFC threshold was used for the EC data.

We determined the influence of microbiota on the region-specific GATA4-regulated genes by systematically comparing jejunum tissue samples. For two analyses, we compared genotypes while maintaining a fixed microbiota status; for the third analysis, we jointly analyzed the effects of genotype and microbiota, including an interaction term (we were too underpowered to use only the latter approach). Thus, we identified three groups: (1) DE genes in GATA^∆IEC SPF, relative to WT SPF, (2) DE genes in GATA^∆IEC GF, relative to WT GF, and (3) genes with a significant interaction between genotype and microbiota.

Both sets of genes, (a) and (b), were then intersected with the previously determined set of region-specific, GATA4-regulated genes, resulting in region-specific, GATA4-regulated genes that were either microbiota dependent or independent.