Coping with seasons: evolutionary dynamics of gene networks in a changing environment

TL;DR

This study uses evolutionary algorithms to compare diversifying and conservative bet-hedging strategies in gene networks, revealing that conservative bet-hedgers often outcompete diversifying ones due to robustness in fluctuating environments.

Contribution

It introduces a novel simulation approach to evolve and compare bet-hedging strategies in gene regulatory networks under environmental variability.

Findings

Diversifying bet-hedgers evolve first but are later outcompeted.

Conservative bet-hedgers are more robust and tend to dominate in the long run.

Network robustness influences the success of bet-hedging strategies.

Abstract

In environments that vary frequently and unpredictably, bet-hedgers can overtake the population. Diversifying bet-hedgers have a diverse set of offspring so that, no matter the conditions they find themselves in, at least some offspring will have high fitness. In contrast, conservative bet-hedgers have a set of offspring that all have an in-between phenotype compared to the specialists. Here, we use an evolutionary algorithm of gene regulatory networks to de novo evolve the two strategies and investigate their relative success in different parameter settings. We found that diversifying bet-hedgers almost always evolved first, but then eventually got outcompeted by conservative bet-hedgers. We argue that even though similar selection pressures apply to the two bet-hedger strategies, conservative bet-hedgers could win due to the robustness of their evolved networks, in contrast to the sensitive networks of the diversifying bet-hedgers. These results reveal an unexplored aspect of the evolution of bet-hedging that could shed more light on the principles of biological adaptation in variable environmental conditions.