A Bayesian Method for Estimating Evolutionary History

Abstract

Phylogeography is the study of evolutionary history among populations in a species associated with geographic genetic variation. This paper examines the phylogeography of three African gorilla subspecies based on two types of DNA sequence data. One type is HV1, the first hyper-variable region in the control region of the mitochondrial genome. The other type is nuclear mitochondrial DNA (Numt DNA), which results from the introgression of a copy of HV1 from the mitochondrial genome into the nuclear genome. Numt and HV1 sequences evolve independently when in different organelles, but they share a common evolutionary history at the same locus in the mitochondrial genome prior to introgression. This study estimates the evolutionary history of gorilla populations in terms of population divergence times and effective population sizes. Also, this study estimates the number of introgression events. The estimates are obtained in a Bayesian framework using novel Markov chain Monte Carlo methods. The method is based on a hybrid coalescent process that combines separate coalescent processes for HV1 and Numt sequences along with a transfer model for introgression events within a single population tree. This Bayesian method for the analysis of Numt and HV1 sequences is the first approach specifically designed to model the evolutionary history of homologous multi-locus sequences within a population tree framework. The data analysis reveals highly discordant estimates of the divergence time between eastern and western gorilla populations for HV1 and Numt sequences. The discordant east-west split times are evidence of male-mediated gene flow between east and west long after female gorillas stopped this migration. In addition, the analysis estimates multiple independent introgression events.