Title of article :
Competing islands limit the rate of adaptation in structured populations
Author/Authors :
Pokalyuk، نويسنده , , Cornelia and Mathew، نويسنده , , Lisha A. and Metzler، نويسنده , , Dirk and Pfaffelhuber، نويسنده , , Peter، نويسنده ,
Issue Information :
دوماهنامه با شماره پیاپی سال 2013
Pages :
11
From page :
1
To page :
11
Abstract :
Beneficial mutations can co-occur when population structure slows down adaptation. Here, we consider the process of adaptation in asexual populations distributed over several locations (“islands”). New beneficial mutations arise at constant rate u b , and each mutation has the same selective advantage s > 0 . We assume that populations evolve within islands according to the successional mutations regime of Desai and Fisher (2007), that is, the time to local fixation of a mutation is short compared to the expected waiting time until the next mutation occurs. To study the rate of adaptation, we introduce an approximate model, the successional mutations (SM) model, which can be simulated efficiently and yields accurate results for a wide range of parameters. In the SM model, mutations fix instantly within islands, and migrants can take over the destination island if they are fitter than the residents. For the special case of a population distributed equally across two islands with population size N , we approximate the model further for small and large migration rates in comparison to the mutation rate. These approximations lead to explicit formulas for the rate of adaptation which fit the original model for a large range of parameter values. For the d island case we provide some heuristics on how to extend the explicit formulas and check these with computer simulations. We conclude that the SM model is a good approximation of the adaptation process in a structured population, at least if mutation or migration is limited.
Keywords :
Island model , Rate of adaptation , Population structure , Beneficial mutations , Successional mutations regime
Journal title :
Theoretical Population Biology
Serial Year :
2013
Journal title :
Theoretical Population Biology
Record number :
1567756
Link To Document :
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