A C. elegans genome-scale microRNA network contains composite feedback motifs with high flux capacity

Abstract

MicroRNAs (miRNAs) and transcription factors (TFs) are primary metazoan gene regulators. Whereas much attention has focused on finding the targets of both miRNAs and TFs, the transcriptional networks that regulate miRNA expression remain largely unexplored. Here, we present the first genome-scale Caenorhabditis elegans miRNA regulatory network that contains experimentally mapped transcriptional TF → miRNA interactions, as well as computationally predicted post-transcriptional miRNA → TF interactions. We find that this integrated miRNA network contains 23 miRNA ↔ TF composite feedback loops in which a TF that controls a miRNA is itself regulated by that same miRNA. By rigorous network randomizations, we show that such loops occur more frequently than expected by chance and, hence, constitute a genuine network motif. Interestingly, miRNAs and TFs in such loops are heavily regulated and regulate many targets. This "high flux capacity" suggests that loops provide a mechanism of high information flow for the coordinate and adaptable control of miRNA and TF target regulons.[Keywords: MicroRNA; transcription factor; regulatory network; network motif; feedback; C. elegans] Supplemental material is available at http://www.genesdev.org.

Evolution under canalization and the dual roles of microRNAs—A hypothesis

“…By bioinformatic analysis, Tsang et al (2007) have found that incoherent FFLs are no less common than the coherent types. Similarly, Martinez et al (2008) were able to identify many feedback loops between a transcription factor and a miRNA in the C. elegans genome. In previous reports (Alon 2007), negative feedback loops were rather infrequent, perhaps because only transcription factors were analyzed (TFs).…”

“…A good example of negative feedback loop (Fig. 1E) is given by Martinez et al (2008). In this example, miR is miR-43 and T is lin-26; the latter being expressed in the embryos of C. elegans and involved in epithelial differentiation.…”

“…As noted by both Tsang et al (2007) and Martinez et al (2008), experiments generally are biased against detecting mechanisms of homeostasis, which suppresses phenotypic variation. By bioinformatic analysis, Tsang et al (2007) have found that incoherent FFLs are no less common than the coherent types.…”

“…Within the limited range of environmental perturbations in most experiments, canalization may not be particularly important, but, in the evolutionary timescale, it may be crucial. Indeed, microRNAs have increasingly attracted attention as candidates for canalizing agents Cui et al 2006Cui et al , 2007Hornstein and Shomron 2006;Li et al 2006;Choi et al 2007;Tsang et al 2007;Varghese and Cohen 2007;Martinez et al 2008). …”

Computational and Systems Biology

“…While a genome-wide collection of transcription regulatory interactions has been reported for E. coli and S. cerevisiae, 11,12 transcription regulatory networks for metazoan organisms, including C. elegans, have been mapped experimentally only to a limited extent. In C. elegans, direct transcription factor regulatory interaction networks have been identified through chromatin immunoprecipitation, 13,14 and yeast one-hybrid experiments, [15][16][17] while indirect regulatory interaction networks have mainly been identified through combinations of gene knockout or knockdown and gene reporter, RT-PCR or microarray experiments. [18][19][20][21] In the latter case, cis-regulatory motif finding algorithms have been applied in order to pinpoint the transcription factors directly responsible for the change in gene expression.…”