The distribution of fitness effects during adaptive walks using a simple genetic network.

The tempo and mode of adaptation depends on the availability of beneficial alleles. Genetic interactions arising from gene networks can restrict this availability. However, the extent to which networks affect adaptation remains largely unknown. Current models of evolution consider additive genotype-phenotype relationships while often ignoring the contribution of gene interactions to phenotypic variance. In this study, we model a quantitative trait as the product of a simple gene regulatory network, the negative autoregulation motif. Using forward-time genetic simulations, we measure adaptive walks towards a phenotypic optimum in both additive and network models. A key expectation from adaptive walk theory is that the distribution of fitness effects of new beneficial mutations is exponential. We found that both models instead harbored distributions with fewer large-effect beneficial alleles than expected. The network model also had a complex and bimodal distribution of fitness effects among all mutations, with a considerable density at deleterious selection coefficients. This behavior is reminiscent of the cost of complexity, where correlations among traits constrain adaptation. Our results suggest that the interactions emerging from genetic networks can generate complex and multimodal distributions of fitness effects.

Digest: Stable phenotypes, fluid genotypes: how stochasticity impacts network evolution and speciation.

A longstanding goal of evolutionary biology is to understand the relationship between genotype and phenotype. Schiffman and Ralph use mathematical modeling to theoretically examine how the genetic network underlying a conserved phenotype can change over time. They found that when phenotypically identical populations with different gene network configurations interbreed, hybrid incompatibilities can arise. These results suggest that neutral processes could play a major role in driving speciation.