Genome-scale phylogenetics: Inferring the plant tree of life from 18,896 gene trees

96Citations
Citations of this article
199Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Phylogenetic analyses using genome-scale data sets must confront incongruence among gene trees, which in plants is exacerbated by frequent gene duplications and losses. Gene tree parsimony (GTP) is a phylogenetic optimization criterion in which a species tree that minimizes the number of gene duplications induced among a set of gene trees is selected. The run time performance of previous implementations has limited its use on large-scale data sets. We used new software that incorporates recent algorithmic advances to examine the performance of GTP on a plant data set consisting of 18,896 gene trees containing 510,922 protein sequences from 136 plant taxa (giving a combined alignment length of >2.9 million characters). The relationships inferred from the GTP analysis were largely consistent with previous large-scale studies of backbone plant phylogeny and resolved some controversial nodes. The placement of taxa that were present in few gene trees generally varied the most among GTP bootstrap replicates. Excluding these taxa either before or after the GTP analysis revealed high levels of phylogenetic support across plants. The analyses supported magnoliids sister to a eudicot + monocot clade and did not support the eurosid I and II clades. This study presents a nuclear genomic perspective on the broad-scale phylogenic relationships among plants, and it demonstrates that nuclear genes with a history of duplication and loss can be phylogenetically informative for resolving the plant tree of life. © 2011 The Author(s).

Cite

CITATION STYLE

APA

Burleigh, J. G., Bansal, M. S., Eulenstein, O., Hartmann, S., Wehe, A., & Vision, T. J. (2011). Genome-scale phylogenetics: Inferring the plant tree of life from 18,896 gene trees. Systematic Biology, 60(2), 117–125. https://doi.org/10.1093/sysbio/syq072

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free