On the role of extrinsic noise in microRNA-mediated bimodal gene expression

TL;DR

This paper explores how extrinsic noise influences bimodal gene expression in microRNA regulation, showing that noise promotes phenotypic diversity across a broader parameter space, highlighting a robust mechanism for cell differentiation.

Contribution

It demonstrates that extrinsic noise enhances bimodal gene expression in miRNA-mediated regulation, reducing the need for fine-tuning and expanding understanding of phenotypic variability.

Findings

Extrinsic noise favors bimodal distributions over a wider parameter range.

Lower miRNA-target interaction strength still produces bimodality with extrinsic noise.

Protein half-life affects the shape of the distribution.

Abstract

Several studies highlighted the relevance of extrinsic noise in shaping cell decision making and differentiation in molecular networks. Experimental evidences of phenotypic differentiation are given by the presence of bimodal distributions of gene expression levels, where the modes of the distribution often correspond to different physiological states of the system. We theoretically address the presence of bimodal phenotypes in the context of microRNA (miRNA)-mediated regulation. MiRNAs are small noncoding RNA molecules that downregulate the expression of their target mRNAs. The nature of this interaction is titrative and induces a threshold effect: below a given target transcription rate no mRNAs are free and available for translation. We investigate the effect of extrinsic noise on the system by introducing a fluctuating miRNA-transcription rate. We find that the presence of extrinsic noise favours the presence of bimodal target distributions which can be observed for a wider range of parameters compared to the case with intrinsic noise only and for lower miRNA-target interaction strength. Our results suggest that combining threshold-inducing interactions with extrinsic noise provides a simple and robust mechanism for obtaining bimodal populations not requiring fine tuning. We furthermore characterise the protein distributions dependence on protein half-life.