Phylogeny Estimation by Integration over Isolation with Migration Models. (20th August 2018)

• Record Type: Journal Article
• Authors: Hey, Jody; Chung, Yujin; Sethuraman, Arun; Lachance, Joseph; Tishkoff, Sarah; Sousa, Vitor C; Wang, Yong
• Editors: Kim, Yuseob
• Is Part Of: Molecular biology and evolution. Volume 35:Number 11(2018)
• Page Start: 2805
• Page End: 2818
• Publication Date: 2018-08-20
• Subjects: isolation with migration -- speciation -- population genetics -- coalescent -- gene flow -- divergence; Molecular biology -- Periodicals; Molecular evolution -- Periodicals; Evolution, Molecular -- Periodicals; Molecular Biology -- Periodicals; 572.8
• DOI: 10.1093/molbev/msy162
• Languages: English
• ISSNs: 0737-4038

Abstract

Abstract: Phylogeny estimation is difficult for closely related populations and species, especially if they have been exchanging genes. We present a hierarchical Bayesian, Markov-chain Monte Carlo method with a state space that includes all possible phylogenies in a full Isolation-with-Migration model framework. The method is based on a new type of genealogy augmentation called a "hidden genealogy" that enables efficient updating of the phylogeny. This is the first likelihood-based method to fully incorporate directional gene flow and genetic drift for estimation of a species or population phylogeny. Application to human hunter-gatherer populations from Africa revealed a clear phylogenetic history, with strong support for gene exchange with an unsampled ghost population, and relatively ancient divergence between a ghost population and modern human populations, consistent with human/archaic divergence. In contrast, a study of five chimpanzee populations reveals a clear phylogeny with several pairs of populations having exchanged DNA, but does not support a history with an unsampled ghost population.