title: The effect of recombination on the neutral evolution of genetic robustness.
abstract: Conventional population genetics considers the evolution of a limited number of genotypes corresponding to phenotypes with different fitness. As model phenotypes, in particular RNA secondary structure, have become computationally tractable, however, it has become apparent that the context dependent effect of mutations and the many-to-one nature inherent in these genotype-phenotype maps can have fundamental evolutionary consequences. It has previously been demonstrated that populations of genotypes evolving on the neutral networks corresponding to all genotypes with the same secondary structure only through neutral mutations can evolve mutational robustness [E. van Nimwegen, J.P. Crutchfield, M. Huynen, Neutral evolution of mutational robustness, Proc. Natl. Acad. Sci. USA 96(17), 9716-9720 (1999)], by concentrating the population on regions of high neutrality. Introducing recombination we demonstrate, through numerically calculating the stationary distribution of an infinite population on ensembles of random neutral networks that mutational robustness is significantly enhanced and further that the magnitude of this enhancement is sensitive to details of the neutral network topology. Through the simulation of finite populations of genotypes evolving on random neutral networks and a scaled down microRNA neutral network, we show that even in finite populations recombination will still act to focus the population on regions of locally high neutrality.
authors.affiliation: Biological Physics Department, Eötvös University, H-1117, Budapest, Hungary. ssolo@angel.elte.hu
authors.forename: Gergely J
authors.initials: GJ
authors.lastname: Szöllosi
authors.forename: Imre
authors.initials: I
authors.lastname: Derényi
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D019143:Evolution, Molecular; D005828:Genetics, Population / Q000379:methods; D005838:Genotype; D035683:MicroRNAs / Q000737:chemistry / Q000235:genetics; D008957:Models, Genetic; D009154:Mutation / Q000235:genetics; D016571:Neural Networks, Computer; D009690:Nucleic Acid Conformation; D010641:Phenotype; D011157:Population Dynamics; D011995:Recombination, Genetic / Q000235:genetics*
chemical_list: D035683:MicroRNAs