PgmNr P2041: Experimental evolution of drift robustness in digital organisms.

Authors:
T. LaBar; C. Adami


Institutes
Michigan State University, East Lansing, MI.


Abstract:

Both recurring deleterious mutations and mutation accumulation due to genetic drift can reduce a population’s average fitness. To counteract these effects, selection should favor genetic architectures that are robust and limit these deleterious effects. For instance, populations can evolve mutational robustness by reducing the average deleterious effect of a mutation so as to minimize the mutational load. Here, we test whether populations can evolve to limit the reduction in fitness caused by deleterious mutation accumulation and genetic drift in small populations (i.e., the drift load) using experimental evolution with digital organisms. In other words, we ask whether populations can evolve robustness to genetic drift (“drift robustness”) when adapting to survive in small populations, similar to populations evolving mutational robustness to survive high mutation rates. We found that small populations do evolve drift robustness, while large populations evolve drift fragility. Drift robustness emerges from the evolution of genetic architectures that reduce the likelihood of deleterious mutations with small effect sizes. We discuss specifically the role selection plays in the spread of drift robust genotypes, and show that drift robustness can arise from mutations that drastically decrease the likelihood of deleterious mutations while significantly increasing the likelihood of lethal mutations. These findings may have implications for genome evolution of organisms with small population sizes, such as bacterial endosymbionts and eukaryotic organelles.