Robust estimates of divergence times and selection with a poisson random field model: A case study of comparative phylogeographic data

8Citations
Citations of this article
36Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Mutation frequencies can be modeled as a Poisson random field (PRF) to estimate speciation times and the degree of selection on newly arisen mutations. This approach provides a quantitative theory for comparing intraspecific polymorphism with interspecific divergence in the presence of selection and can be used to estimate population genetic parameters. Although the original PRF model has been extended to more general biological settings to make statistical inference about selection and divergence among model organisms, it has not been incorporated into phylogeographic studies that focus on estimating population genetic parameters for nonmodel organisms. Here, we modified a recently developed time-dependent PRF model to independently estimate genetic parameters from a nuclear and mitochondrial DNA data set of 22 sister pairs of birds that have diverged across a biogeographic barrier. We found that species that inhabit humid habitats had more recent divergence times and larger effective population sizes than those that inhabit drier habitats, and divergence time estimated from the PRF model were similar to estimates from a coalescent species-tree approach. Selection coefficients were higher in sister pairs that inhabited drier habitats than in those in humid habitats, but overall the mitochondrial DNA was under weak selection. Our study indicates that PRF models are useful for estimating various population genetic parameters and serve as a framework for incorporating estimates of selection into comparative phylogeographic studies. © 2014 by the Genetics Society of America.

Cite

CITATION STYLE

APA

Amei, A., & Smith, B. T. (2014). Robust estimates of divergence times and selection with a poisson random field model: A case study of comparative phylogeographic data. Genetics, 196(1), 225–233. https://doi.org/10.1534/genetics.113.157776

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free