Evolution of new regulatory functions on biophysically realistic fitness landscapes

TL;DR

This paper models the evolution of gene regulatory networks, focusing on transcription factor duplication and specialization, revealing how biophysical parameters influence the emergence of new functions and the role of promiscuity-promoting mutations.

Contribution

It introduces a coarse-grained, biophysically realistic framework for understanding the evolution of regulatory functions in gene networks, emphasizing the impact of specific mutations.

Findings

Biophysical parameters bias evolutionary trajectories towards new functions.

Promiscuity-promoting mutations facilitate rapid functional evolution.

The model predicts probabilities of different evolutionary outcomes.

Abstract

Regulatory networks consist of interacting molecules with a high degree of mutual chemical specificity. How can these molecules evolve when their function depends on maintenance of interactions with cognate partners and simultaneous avoidance of deleterious "crosstalk" with non-cognate molecules? Although physical models of molecular interactions provide a framework in which co-evolution of network components can be analyzed, most theoretical studies have focused on the evolution of individual alleles, neglecting the network. In contrast, we study the elementary step in the evolution of gene regulatory networks: duplication of a transcription factor followed by selection for TFs to specialize their inputs as well as the regulation of their downstream genes. We show how to coarse grain the complete, biophysically realistic genotype-phenotype map for this process into macroscopic functional outcomes and quantify the probability of attaining each. We determine which evolutionary and biophysical parameters bias evolutionary trajectories towards fast emergence of new functions and show that this can be greatly facilitated by the availability of "promiscuity-promoting" mutations that affect TF specificity.