Bayesian species delimitation using multilocus sequence data |
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Authors: | Ziheng Yang Bruce Rannala |
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Institution: | aCenter for Computational and Evolutionary Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China;;bDepartment of Biology, University College London, London WC1E 6BT, United Kingdom; and;cGenome Center and Department of Evolution and Ecology, University of California, Davis, CA 95616 |
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Abstract: | In the absence of recent admixture between species, bipartitions of individuals in gene trees that are shared across loci can potentially be used to infer the presence of two or more species. This approach to species delimitation via molecular sequence data has been constrained by the fact that genealogies for individual loci are often poorly resolved and that ancestral lineage sorting, hybridization, and other population genetic processes can lead to discordant gene trees. Here we use a Bayesian modeling approach to generate the posterior probabilities of species assignments taking account of uncertainties due to unknown gene trees and the ancestral coalescent process. For tractability, we rely on a user-specified guide tree to avoid integrating over all possible species delimitations. The statistical performance of the method is examined using simulations, and the method is illustrated by analyzing sequence data from rotifers, fence lizards, and human populations. |
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Keywords: | Bayesian phylogenetic inference biological species concept coalescent Markov chain Monte Carlo reversible jump |
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