Differential gene expression analysis

The analysis of differentially expressed genes (DEGs) was performed on the count data using the DESeq2 R package [45]. Genes with minimum of ten counts for all the samples in at least one of the experimental groups were retained in the analysis. Pairwise differential gene expression analysis was performed between: (a) VT vs. FT, (b) FTC vs. FT, (c) VTC vs. FTC, and (d) VTC vs. VT. The resulting p values were adjusted using Benjamini and Hochberg’s (BH) approach [46] for controlling the false discovery rate (FDR). Genes with an absolute fold change |FC|> 2 and FDR-adjusted p value (q value) < 0.05 were considered as differentially expressed.

Principal component analysis (PCA) was performed using the plotPCA function from DESeq2 package [45]. Prior to the PCA, we performed variance stabilising transformation (VST) on the raw count data to reduce any potential biases in the clustering analysis.