Literature DB >> 17056642

Testing for covarion-like evolution in protein sequences.

Huai-Chun Wang1, Matthew Spencer, Edward Susko, Andrew J Roger.   

Abstract

The covarion hypothesis of molecular evolution proposes that selective pressures on an amino acid or nucleotide site change through time, thus causing changes of evolutionary rate along the edges of a phylogenetic tree. Several kinds of Markov models for the covarion process have been proposed. One model, proposed by Huelsenbeck (2002), has 2 substitution rate classes: the substitution process at a site can switch between a single variable rate, drawn from a discrete gamma distribution, and a zero invariable rate. A second model, suggested by Galtier (2001), assumes rate switches among an arbitrary number of rate classes but switching to and from the invariable rate class is not allowed. The latter model allows for some sites that do not participate in the rate-switching process. Here we propose a general covarion model that combines features of both models, allowing evolutionary rates not only to switch between variable and invariable classes but also to switch among different rates when they are in a variable state. We have implemented all 3 covarion models in a maximum likelihood framework for amino acid sequences and tested them on 23 protein data sets. We found significant likelihood increases for all data sets for the 3 models, compared with a model that does not allow site-specific rate switches along the tree. Furthermore, we found that the general model fit the data better than the simpler covarion models in the majority of the cases, highlighting the complexity in modeling the covarion process. The general covarion model can be used for comparing tree topologies, molecular dating studies, and the investigation of protein adaptation.

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Year:  2006        PMID: 17056642     DOI: 10.1093/molbev/msl155

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  29 in total

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9.  PROCOV: maximum likelihood estimation of protein phylogeny under covarion models and site-specific covarion pattern analysis.

Authors:  Huai-Chun Wang; Edward Susko; Andrew J Roger
Journal:  BMC Evol Biol       Date:  2009-09-08       Impact factor: 3.260

10.  Branch length estimation and divergence dating: estimates of error in Bayesian and maximum likelihood frameworks.

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