Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 107, Issue 20, Pages 9264-9269Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.0913022107
Keywords
Bayesian phylogenetic inference; biological species concept; coalescent; Markov chain Monte Carlo; reversible jump
Categories
Funding
- National Institutes of Health [R01-HG01988]
- Miller Institute
- Biotechnology and Biological Sciences Research Council
- Royal Society
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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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