Emergent biases in compensatory mutation can drive gene regulatory network evolution [article]

Yifei Wang, Marios Richards, Steve Dorus, Nicholas K. Priest, Joanna J. Bryson
<span title="2019-12-19">2019</span> <i title="Cold Spring Harbor Laboratory"> bioRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Gene regulatory networks underlie every aspect of life; but, we don't understanding how webs of regulators are assembled through the process of evolution. For example, it is typically assumed that evolution does not occur through low-fitness intermediate pathways; however, this presumes that compensatory mutation can not drive rapid evolutionary recovery. Using a well-established in silico model of gene regulatory networks, we show that compensatory mutation can drive the evolution of
more &raquo; ... pathways because it biases the response to natural selection. In our simulations, we find that compensatory mutation is common during periods of relaxed selection, with 8-15% of degraded networks having regulatory function restored by a single randomly-generated additional mutation. Though this process reduces average robustness, proportionally higher robustness is found in networks where compensatory mutations occur close to the deleterious mutation site, or where the compensatory mutation results in a large regulatory effect size. This location- and size-specific robustness systematically biases which networks are purged by selection for network stability, producing emergent changes to the population of regulatory networks. We show that over time, large-effect and co-located mutations accumulate, assuming only that periods of relaxed selection occur, even rarely. This accumulation serves to increase regulatory complexity. Our findings help explain a process by which large-effect mutations structure complex regulatory networks, and may account for the speed and pervasiveness of observed occurrence of compensatory mutation, for example in the context of antibiotic resistance, which we discuss. If sustained by in vitro experiments, these results promise a significant breakthrough in the understanding of evolutionary and regulatory processes.
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