© 2007 Society of Systematic Biologists
Accounting for Gene Rate Heterogeneity in Phylogenetic Inference
1 McGill Centre for Bioinformatics, McGill University Duff Medical Building, 3775 University Street, Montréal, Quebec, H3A 2B4, Canada E-mail: rbbevan{at}gmail.com
2 Program in Evolutionary Biology, Canadian Institute for Advanced Research Centre Robert Cedergren, Département de Biochimie, Université de Montréal 2900 Boulevard Edouard–Montpetit, Montréal, Québec, H3T 1J4, Canada
3 Department of Mathematics, The University of Auckland Private Bag 92019, Auckland New Zealand
Edited by Tim Collins: Associate Editor
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Abstract |
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Traditionally, phylogenetic analyses over many genes combine data into a contiguous block. Under this concatenated model, all genes are assumed to evolve at the same rate. However, it is clear that genes evolve at very different rates and that accounting for this rate heterogeneity is important if we are to accurately infer phylogenies from heterogeneous multigene data sets. There remain open questions regarding how best to incorporate gene rate parameters into phylogenetic models and which properties of real data correlate with improved fit over the concatenated model. In this study, two methods of accounting for gene rate heterogeneity are compared: the n-parameter method, which allows for each of the n gene partitions to have a gene rate parameter, and the 
-parameter method, which fits a distribution to the gene rates. Results demonstrate that the n-parameter method is both computationally faster and in general provides a better fit over the concatenated model than the -parameter method. Furthermore, improved model fit over the concatenated model is highly correlated with the presence of a gene with a slow relative rate of evolution.
Keywords: AIC; gene rates; phylogenetic integration; phylogenomics; rate heterogeneity
Received April 4, 2006; Revised June 20, 2006; Accepted October 15, 2006
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