Speaker
Description
(work with Paulo R. A. Campos, Universidade Federal de Pernambuco, Brazil)
By defining a discrete set of available mutation vectors, the mapping from trait vector to fitness provided by Fisher's Geometric Model (FGM) has been previously extended to a mapping from genotype to fitness. We examine evolutionary rescue across this genotypic landscape. We first
provide a simple derivation of the distribution of fitness effects for a phenotype at a given distance from the optimum, and use this to approximate the probability of evolutionary rescue via de novo mutation. Confirming our theoretical predictions with simulation, we also explore how the probability of evolutionary rescue in the genotypic model varies with distance from the optimum, mean mutational effect size, and the dimensionality of trait space. Unsurprisingly, rescue probability is reduced when genotypes are limited to a discrete number
of available mutations. Unlike other complex features of these
landscapes, however, the probability of rescue increases monotonically with genome length, and approaches the behaviour of the classical FGM as genome length approaches infinity.
