Population genetics of polymorphism and divergence under fluctuating selection.
Current methods for detecting fluctuating selection require time series data on genotype frequencies. Here, we propose an alternative approach that makes use of DNA polymorphism data from a sample of individuals collected at a single point in time. Our method uses classical diffusion approximations to model temporal fluctuations in the selection coefficients to find the expected distribution of mutation frequencies in the population. Using the Poisson random-field setting we derive the site-frequency spectrum (SFS) for three different models of fluctuating selection. We find that the general effect of fluctuating selection is to produce a more "U"-shaped site-frequency spectrum with an excess of high-frequency derived mutations at the expense of middle-frequency variants. We present likelihood-ratio tests, comparing the fluctuating selection models to the neutral model using SFS data, and use Monte Carlo simulations to assess their power. We find that we have sufficient power to reject a neutral hypothesis using samples on the order of a few hundred SNPs and a sample size of approximately 20 and power to distinguish between selection that varies in time and constant selection for a sample of size 20. We also find that fluctuating selection increases the probability of fixation of selected sites even if, on average, there is no difference in selection among a pair of alleles segregating at the locus. Fluctuating selection will, therefore, lead to an increase in the ratio of divergence to polymorphism similar to that observed under positive directional selection.
Huerta-Sanchez
Emilia
E
Center for Applied Mathematics, Deparmtent of Mathematics, Cornell University, Ithaca, New York 14853, USA.
Durrett
Rick
R
Bustamante
Carlos D
CD
D000818:Animals; D003198:Computer Simulation; D016001:Confidence Intervals; D005828:Genetics, Population; D016013:Likelihood Functions; D009010:Monte Carlo Method; D011110:Polymorphism, Genetic; D012641:Selection, Genetic