© 2005 Society of Systematic Biologists
Calculating the Evolutionary Rates of Different Genes: A Fast, Accurate Estimator with Applications to Maximum Likelihood Phylogenetic Analysis
1 McGill Centre for Bioinformatics Duff Medical Building, 3775 University Street, Montréal, Quebec, H3A 2B4, Canada; E-mail: rachel{at}mcb.mcgill.ca. (R.B.B.)
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
Edited by Tim Collins
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Abstract |
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In phylogenetic analyses with combined multigene or multiprotein data sets, accounting for differing evolutionary dynamics at different loci is essential for accurate tree prediction. Existing maximum likelihood (ML) and Bayesian approaches are computationally intensive. We present an alternative approach that is orders of magnitude faster. The method, Distance Rates (DistR), estimates rates based upon distances derived from gene/protein sequence data. Simulation studies indicate that this technique is accurate compared with other methods and robust to missing sequence data. The DistR method was applied to a fungal mitochondrial data set, and the rate estimates compared well to those obtained using existing ML and Bayesian approaches. Inclusion of the protein rates estimated from the DistR method into the ML calculation of trees as a branch length multiplier resulted in a significantly improved fit as measured by the Akaike Information Criterion (AIC). Furthermore, bootstrap support for the ML topology was significantly greater when protein rates were used, and some evident errors in the concatenated ML tree topology (i.e., without protein rates) were corrected.
Keywords: Bayesian credible intervals; DistR method; multigene phylogeny; PHYML; rate heterogeneity
Received November 24, 2004; Revised March 18, 2005; Accepted May 24, 2005
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