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

Amei Amei,Stanley Sawyer,Attila Szolnoki

doi:10.1371/journal.pone.0034413

Amei Amei, Stanley Sawyer + Show 1 more

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https://doi.org/10.1371/journal.pone.0034413

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Abstract

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

Highlights

Mutation, selection, and genetic drift are important forces that shape pattern of genetic polymorphism within and between species [1]
The results of this study suggest that a majority of newly-arisen non-synonymous mutations observed as polymorphisms is beneficial, the magnitude of selection is very small, which is consistent with the conclusion drawn by Bustamante et al [4] where a timeindependent fixed effects Poisson random field (PRF) model was applied to 34 genes from D. melanogaster and D. simulans
The set of 91 D. melanogaster genes studied here has previously been analyzed in a time equilibrium random effects PRF model [6]

Summary

Introduction

Selection, and genetic drift are important forces that shape pattern of genetic polymorphism within and between species [1]. A quantitative theory for the amount of selection between two recently diverged species was developed by Sawyer and Hartl [3], who developed a sampling theory in which the set of frequencies of mutant sites is modeled as a Poisson random field (PRF). This theory was applied to the sample configurations of nucleotides in the Adh gene in Drosophila and led to maximum likelihood estimates of silent and replacement mutation rates, an average selection coefficient, and the species divergence time. Abel [7] considered similar models with more heavy-tailed distributions within loci (Laplace and chi-square distributions) and found similar numerical results

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