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Phylogeny estimation by integration over isolation with migration models
Hey, J Chung, Y Sethuraman, A Lachance, J Tishkoff, S Sousa, VC Wang, Y
Hey, J
Chung, Y
Sethuraman, A
Lachance, J
Tishkoff, S
Sousa, VC
Wang, Y
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Journal Article
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2018-01-01
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10.1093/molbev/msy162
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© The Author(s) 2018. 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.
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Oxford University Press (OUP)
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Molecular Biology and Evolution
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