Abstract

Epithelial–mesenchymal transition (EMT) has been a subject of intense scrutiny as it facilitates metastasis and alters drug sensitivity. Although EMT-regulatory roles for numerous miRNAs and transcription factors are known, their functions can be difficult to disentangle, in part due to the difficulty in identifying direct miRNA targets from complex datasets and in deciding how to incorporate ‘indirect’ miRNA effects that may, or may not, represent biologically relevant information. To better understand how miRNAs exert effects throughout the transcriptome during EMT, we employed Exon–Intron Split Analysis (EISA), a bioinformatic technique that separates transcriptional and post-transcriptional effects through the separate analysis of RNA-Seq reads mapping to exons and introns. We find that in response to the manipulation of miRNAs, a major effect on gene expression is transcriptional. We also find extensive co-ordination of transcriptional and post-transcriptional regulatory mechanisms during both EMT and mesenchymal to epithelial transition (MET) in response to TGF-β or miR-200c respectively. The prominent transcriptional influence of miRNAs was also observed in other datasets where miRNA levels were perturbed. This work cautions against a narrow approach that is limited to the analysis of direct targets, and demonstrates the utility of EISA to examine complex regulatory networks involving both transcriptional and post-transcriptional mechanisms.

Highlights

  • MicroRNAs confer robustness to biological systems, buffering against stochastic fluctuations and transcriptional noise [1,2,3,4], fine-tuning gene expression and acting as agents to promote phenotypic switching between mutually exclusive cell states [5]

  • Exon–Intron Split Analysis (EISA) successfully differentiates transcriptional and posttranscriptional gene regulation In an effort to better understand the contributions of miRNAs and miRNA-transcription factors (TFs) regulatory loops within Epithelial–mesenchymal transition (EMT), we first sought to evaluate the capacity of EISA to differentiate between gene regulatory mechanisms within RNAsequencing data

  • Because the miR200 family are prominent regulators of EMT and enforcers of the epithelial phenotype [38,39,40,41,42], we applied EISA analysis to RNA-seq data from mesHMLE cells transfected with miR-200c to evaluate the relative transcriptional and post-transcriptional effects

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Summary

Introduction

MicroRNAs confer robustness to biological systems, buffering against stochastic fluctuations and transcriptional noise [1,2,3,4], fine-tuning gene expression and acting as agents to promote phenotypic switching between mutually exclusive cell states [5] Fundamental to these functions are the close interplay with transcription factors (TFs), with which they form network motifs that integrate transcriptional and post-transcriptional signals, such as feedback loops (where the expression of a miRNA and a TF are directly dependent upon one another) and feedforward loops (where at least one input TF or miRNA regulates the other and where both jointly regulate shared target genes) [6,7,8].

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