Statistical Inference of Selection and Divergence from a Time-Dependent Poisson Random Field Model

摘要: We apply a recently developed time-dependent Poisson random field model to aligned DNA sequences from two related biological species estimate selection coefficients and divergence time. use Markov chain Monte Carlo methods time for each locus. The assumes that the selective effects of non-synonymous mutations are normally distributed across genetic loci but constant within loci, synonymous selectively neutral. In contrast with previous models, we do not assume individual at population equilibrium after divergence. Using data set 91 genes in Drosophila species, D. melanogaster simulans, (or 1.68 million years, assuming haploid effective size years) mean coefficient per generation . Although average is positive, magnitude quite small. Results numerical simulations also presented as an accuracy check model.