Improved gene tree error correction in the presence of horizontal gene transfer.

Bioinformatics
Authors
Keywords
Abstract

MOTIVATION: The accurate inference of gene trees is a necessary step in many evolutionary studies. Although the problem of accurate gene tree inference has received considerable attention, most existing methods are only applicable to gene families unaffected by horizontal gene transfer. As a result, the accurate inference of gene trees affected by horizontal gene transfer remains a largely unaddressed problem.

RESULTS: In this study, we introduce a new and highly effective method for gene tree error correction in the presence of horizontal gene transfer. Our method efficiently models horizontal gene transfers, gene duplications and losses, and uses a statistical hypothesis testing framework [Shimodaira-Hasegawa (SH) test] to balance sequence likelihood with topological information from a known species tree. Using a thorough simulation study, we show that existing phylogenetic methods yield inaccurate gene trees when applied to horizontally transferred gene families and that our method dramatically improves gene tree accuracy. We apply our method to a dataset of 11 cyanobacterial species and demonstrate the large impact of gene tree accuracy on downstream evolutionary analyses.

AVAILABILITY AND IMPLEMENTATION: An implementation of our method is available at http://compbio.mit.edu/treefix-dtl/

CONTACT: : mukul@engr.uconn.edu or manoli@mit.edu

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Year of Publication
2015
Journal
Bioinformatics
Volume
31
Issue
8
Pages
1211-8
Date Published
2015 Apr 15
ISSN
1367-4811
URL
DOI
10.1093/bioinformatics/btu806
PubMed ID
25481006
PubMed Central ID
PMC4393519
Links
Grant list
RC2 HG005639 / HG / NHGRI NIH HHS / United States