Species trees from highly incongruent gene trees in rice.
Several methods have recently been developed to infer multilocus phylogenies by incorporating information from topological incongruence of the individual genes. In this study, we investigate 2 such methods, Bayesian concordance analysis and Bayesian estimation of species trees. Our test data are a collection of genes from cultivated rice (genus Oryza) and the most closely related wild species, generated using a high-throughput sequencing protocol and bioinformatics pipeline. Trees inferred from independent genes display levels of topological incongruence that far exceed that seen in previous data sets analyzed with these species tree methods. We identify differences in phylogenetic results between inference methods that incorporate gene tree incongruence. Finally, we discuss the challenges of scaling these analyses for data sets with thousands of gene trees and extensive levels of missing data.
Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85721, USA. kcranston@fieldmuseum.org
Karen A
KA
Cranston
Bonnie
B
Hurwitz
Doreen
D
Ware
Lincoln
L
Stein
Rod A
RA
Wing
D001483:Base Sequence; D001499:Bayes Theorem; D002965:Classification / Q000379:methods*; D019295:Computational Biology / Q000379:methods*; D005796:Genes / Q000235:genetics*; D008957:Models, Genetic; D012275:Oryza / Q000235:genetics*; D010802:Phylogeny; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA; D012984:Software