title: The structured ancestral selection graph and the many-demes limit.
abstract: We show that the unstructured ancestral selection graph applies to part of the history of a sample from a population structured by restricted migration among subpopulations, or demes. The result holds in the limit as the number of demes tends to infinity with proportionately weak selection, and we have also made the assumptions of island-type migration and that demes are equivalent in size. After an instantaneous sample-size adjustment, this structured ancestral selection graph converges to an unstructured ancestral selection graph with a mutation parameter that depends inversely on the migration rate. In contrast, the selection parameter for the population is independent of the migration rate and is identical to the selection parameter in an unstructured population. We show analytically that estimators of the migration rate, based on pairwise sequence differences, derived under the assumption of neutrality should perform equally well in the presence of weak selection. We also modify an algorithm for simulating genealogies conditional on the frequencies of two selected alleles in a sample. This permits efficient simulation of stronger selection than was previously possible. Using this new algorithm, we simulate gene genealogies under the many-demes ancestral selection graph and identify some situations in which migration has a strong effect on the time to the most recent common ancestor of the sample. We find that a similar effect also increases the sensitivity of the genealogy to selection.
authors.affiliation: School of Mathematics and Statistics, SUBIT, University of Sydney, New South Wales 2006, Australia. paul.slade@adelaide.edu.au
authors.forename: Paul F
authors.initials: PF
authors.lastname: Slade
authors.forename: John
authors.initials: J
authors.lastname: Wakeley
mesh_terms: D000465:Algorithms; D000483:Alleles; D003198:Computer Simulation; D004641:Emigration and Immigration; D005787:Gene Frequency; D005828:Genetics, Population; D008390:Markov Chains; D008957:Models, Genetic; D009010:Monte Carlo Method; D009154:Mutation; D010375:Pedigree; D012641:Selection, Genetic