Modeling microRNA-driven post-transcriptional regulation by using exon-intron split analysis (EISA) in pigs

Abstract

Bulk sequencing of RNA transcripts has typically been used to quantify gene expression levels in different experimental systems. However, linking differentially expressed (DE) mRNA transcripts to gene expression regulators, such as miRNAs or transcription factors (TFs), remains challenging, as in silico or experimental interactions are commonly identified post hoc after selecting differentially expressed genes of interest, thus biasing the interpretation of underlying gene regulatory mechanisms. In this study, we performed an exon-intron split analysis (EISA) to muscle and fat RNA-seq data from two Duroc pig populations subjected to fasting-feeding conditions and with divergent fatness profiles, respectively. We compared the number of reads from exonic and intronic regions for all expressed protein-coding genes and divided their expression profiles into transcriptional and post-transcriptional components, considering intronic and exonic fractions as estimates of the abundance of pre-mRNA and mature mRNA transcripts, respectively. In this way, we obtained a prioritized list of genes showing significant transcriptional and post-transcriptional regulatory signals. After running EISA analyses, protein-coding mRNA genes with downregulated exonic fractions and high post-transcriptional signals were significantly enriched for binding sites of upregulated DE miRNAs. Moreover, these genes showed an increased expression covariation for the exonic fraction compared to that of the intronic fraction. On the contrary, they did not show enrichment for binding sites of highly expressed and/or downregulated DE miRNAs. Among the set of loci displaying miRNA-driven post-transcriptional regulatory signals, we observed genes related to glucose homeostasis (PDK4, NR4A3, CHRNA1 and DKK2), cell differentiation (MYO9A, KLF5 and BACH2) or adipocytes metabolism (LEP, SERPINE2, RNF157, OSBPL10 and PRSS23). Besides, genes showing upregulated intronic fractions with a lack of exonic fractions were significantly enriched for TF-enhancer activity while depleted for miRNA targets, thus suggesting a transient transcription activation regulating skeletal muscle development. Our results highlight an efficient framework to classify mRNA genes showing transcriptional and post-transcriptional signals linked to transient transcription and miRNA-driven downregulation by using exonic and intronic fractions of RNA-seq datasets from muscle and adipose tissues in pigs.