Information transmission in genetic regulatory networks: a review

TL;DR

This review discusses how information theory is applied to understand the function and complexity of genetic regulatory networks, highlighting recent experimental evidence that these networks may optimize information transmission during development.

Contribution

It provides a comprehensive overview of recent advances in applying information theory to gene regulatory networks, connecting architecture with functional information transmission.

Findings

Genetic networks can perform complex computations with reliable information transmission.

Experimental data suggest developmental networks maximize positional information.

Information theory offers insights into the functional complexity of gene regulation.

Abstract

Genetic regulatory networks enable cells to respond to the changes in internal and external conditions by dynamically coordinating their gene expression profiles. Our ability to make quantitative measurements in these biochemical circuits has deepened our understanding of what kinds of computations genetic regulatory networks can perform and with what reliability. These advances have motivated researchers to look for connections between the architecture and function of genetic regulatory networks. Transmitting information between network's inputs and its outputs has been proposed as one such possible measure of function, relevant in certain biological contexts. Here we summarize recent developments in the application of information theory to gene regulatory networks. We first review basic concepts in information theory necessary to understand recent work. We then discuss the functional complexity of gene regulation which arrises from the molecular nature of the regulatory interactions. We end by reviewing some experiments supporting the view that genetic networks responsible for early development of multicellular organisms might be maximizing transmitted 'positional' information.