Abstract:
:Reticulate species evolution, such as hybridization or introgression, is relatively common in nature. In the presence of reticulation, species relationships can be captured by a rooted phylogenetic network, and orthologous gene evolution can be modeled as bifurcating gene trees embedded in the species network. We present a Bayesian approach to jointly infer species networks and gene trees from multilocus sequence data. A novel birth-hybridization process is used as the prior for the species network, and we assume a multispecies network coalescent prior for the embedded gene trees. We verify the ability of our method to correctly sample from the posterior distribution, and thus to infer a species network, through simulations. To quantify the power of our method, we reanalyze two large data sets of genes from spruces and yeasts. For the three closely related spruces, we verify the previously suggested homoploid hybridization event in this clade; for the yeast data, we find extensive hybridization events. Our method is available within the BEAST 2 add-on SpeciesNetwork, and thus provides an extensible framework for Bayesian inference of reticulate evolution.
journal_name
Mol Biol Evoljournal_title
Molecular biology and evolutionauthors
Zhang C,Ogilvie HA,Drummond AJ,Stadler Tdoi
10.1093/molbev/msx307subject
Has Abstractpub_date
2018-02-01 00:00:00pages
504-517issue
2eissn
0737-4038issn
1537-1719pii
4705834journal_volume
35pub_type
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