Constrained models of evolution lead to improved prediction of functional linkage from correlated gain and loss of genes

被引:69
作者
Barker, Daniel
Meade, Andrew
Pagel, Mark
机构
[1] Univ St Andrews, Sch Biol, St Andrews KY16 9TH, Fife, Scotland
[2] Univ Reading, Sch Biol Sci, Reading RG6 6AJ, Berks, England
基金
英国自然环境研究理事会;
关键词
D O I
10.1093/bioinformatics/btl558
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation: We compare phylogenetic approaches for inferring functional gene links. The approaches detect independent instances of the correlated gain and loss of pairs of genes from species' genomes. We investigate the effect on results of basing evidence of correlations on two phylogenetic approaches, Dollo parsminony and maximum likelihood (ML). We further examine the effect of constraining the ML model by fixing the rate of gene gain at a low value, rather than estimating it from the data. Results: We detect correlated evolution among a test set of pairs of yeast (Saccharomyces cerevisiae) genes, with a case study of 21 eukaryotic genomes and test data derived from known yeast protein complexes. If the rate at which genes are gained is constrained to be low, ML achieves by far the best results at detecting known functional links. The model then has fewer parameters but it is more realistic by preventing genes from being gained more than once. Availability: BayesTraits by M. Pagel and A. Meade, and a script to configure and repeatedly launch it by D. Barker and M. Pagel, are available at http://www.evolution.reading.ac.uk .
引用
收藏
页码:14 / 20
页数:7
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