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Gene network topology drives the mutational landscape of gene expression
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Regulatory mutations, coding sequence alterations, and gene deletions and duplications are generally expected to have qualitatively different effects on fitness. We aim to ground this expectation within a theoretical framework using evolutionary simulations of gene regulatory networks (GRNs) controlling the expression of fitness-related genes. We examined the distribution of fitness effects as a function of the type of mutation and the topology of the gene network. Contrary to our expectation, the GRN topology had more influence on the effect of mutations than the type of mutation itself. In particular, the topology conditioned (i) the speed of adaptation, (ii) the distribution of fitness effects, and (iii) the degree of pleiotropy, acting as explanatory factor for all mutation types. All mutations had the potential to participate in adaptation, although their propensity to generate beneficial variants differed according to the network topology. In scale-free networks, the most common topology for biological networks, coding mutations were more pleiotropic and overrepresented in both beneficial and deleterious mutations, while regulatory mutations were more often neutral. However, this observation was not general, as this pattern was reversed in alternative networks. These results highlight the critical role of network topology in defining mutations' contributions to adaptation.
Title: Gene network topology drives the mutational landscape of gene expression
Description:
Regulatory mutations, coding sequence alterations, and gene deletions and duplications are generally expected to have qualitatively different effects on fitness.
We aim to ground this expectation within a theoretical framework using evolutionary simulations of gene regulatory networks (GRNs) controlling the expression of fitness-related genes.
We examined the distribution of fitness effects as a function of the type of mutation and the topology of the gene network.
Contrary to our expectation, the GRN topology had more influence on the effect of mutations than the type of mutation itself.
In particular, the topology conditioned (i) the speed of adaptation, (ii) the distribution of fitness effects, and (iii) the degree of pleiotropy, acting as explanatory factor for all mutation types.
All mutations had the potential to participate in adaptation, although their propensity to generate beneficial variants differed according to the network topology.
In scale-free networks, the most common topology for biological networks, coding mutations were more pleiotropic and overrepresented in both beneficial and deleterious mutations, while regulatory mutations were more often neutral.
However, this observation was not general, as this pattern was reversed in alternative networks.
These results highlight the critical role of network topology in defining mutations' contributions to adaptation.
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