Adaptive gene regulatory networks

TL;DR

This paper investigates the diversity and properties of gene regulatory networks capable of producing specific gene expression levels, revealing a vast space of solutions with certain biases aligned with empirical data.

Contribution

It introduces a simple model to analyze the space of regulatory networks, highlighting their extensive variability and structural biases.

Findings

Exponential number of networks compatible with given expression levels

Networks tend to favor symmetric interactions

Large entropy of possible regulatory configurations

Abstract

Regulatory interactions between genes show a large amount of cross-species variability, even when the underlying functions are conserved: There are many ways to achieve the same function. Here we investigate the ability of regulatory networks to reproduce given expression levels within a simple model of gene regulation. We find an exponentially large space of regulatory networks compatible with a given set of expression levels, giving rise to an extensive entropy of networks. Typical realisations of regulatory networks are found to share a bias towards symmetric interactions, in line with empirical evidence.