Regulatory motifs: structural and functional building blocks of genetic computation

TL;DR

This paper introduces regulatory motifs as fundamental structural and functional units of gene regulatory networks, revealing their limited functional diversity and implications for genetic computation organization.

Contribution

It establishes a direct link between network structure and function, deriving bounds on motif capabilities and highlighting redundancy in genetic regulatory computation.

Findings

Regulatory motifs have a limited range of functions.

Many different motifs can perform the same task.

Global network behavior is highly constrained by local motifs.

Abstract

Developing and maintaining life requires a lot of computation. This is done by gene regulatory networks. But we have little understanding of how this computation is organized. I show that there is a direct correspondence between the structural and functional building blocks of regulatory networks, which I call regulatory motifs. I derive a simple bound on the range of function that these motifs can perform, in terms of the local network structure. I prove that this range is a small fraction of all possible functions, which severely constrains global network behavior. Part of this restriction is due to redundancy in the function that regulatory motifs can achieve - there are many ways to perform the same task. Regulatory motifs help us understanding how genetic computation is organized and what it can achieve.