title: Robustness to noise in gene expression evolves despite epistatic constraints in a model of gene networks.
abstract: Stochastic noise in gene expression causes variation in the development of phenotypes, making such noise a potential target of stabilizing selection. Here, we develop a new simulation model of gene networks to study the adaptive landscape underlying the evolution of robustness to noise. We find that epistatic interactions between the determinants of the expression of a gene and its downstream effect impose significant constraints on evolution, but these interactions do allow the gradual evolution of increased robustness. Despite strong sign epistasis, adaptation rarely proceeds via deleterious intermediate steps, but instead occurs primarily through small beneficial mutations. A simple mathematical model captures the relevant features of the single-gene fitness landscape and explains counterintuitive patterns, such as a correlation between the mean and standard deviation of phenotypes. In more complex networks, mutations in regulatory regions provide evolutionary pathways to increased robustness. These results chart the constraints and possibilities of adaptation to reduce expression noise and demonstrate the potential of a novel modeling framework for gene networks.
authors.affiliation: Department of Zoology, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada. jdraghi@gmail.com.
authors.forename: Jeremy
authors.initials: J
authors.lastname: Draghi
authors.affiliation: Department of Zoology, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
authors.forename: Michael
authors.initials: M
authors.lastname: Whitlock
mesh_terms: D000220:Adaptation, Biological / Q000235:genetics; D005075:Biological Evolution; D004843:Epistasis, Genetic; D015870:Gene Expression; D053263:Gene Regulatory Networks; D056084:Genetic Fitness; D008957:Models, Genetic; D009154:Mutation
keywords: Adaptation; epistasis; models/simulations