title: Environmental noise, genetic diversity and the evolution of evolvability and robustness in model gene networks.
abstract: The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or "evolvability") can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise) compared to populations in stable or randomly varying (white noise) environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions.
authors.affiliation: Department of Biological Sciences, Wayne State University, Detroit, Michigan, USA. csteiner@wayne.edu
authors.forename: Christopher F
authors.initials: CF
authors.lastname: Steiner
mesh_terms: D005075:Biological Evolution; D053263:Gene Regulatory Networks / Q000235:genetics / Q000502:physiology*; D014644:Genetic Variation / Q000235:genetics / Q000502:physiology*; D008957:Models, Genetic; D009622:Noise