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MBE Advance Access originally published online on October 19, 2005
Molecular Biology and Evolution 2006 23(2):327-337; doi:10.1093/molbev/msj038
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© The Author 2005. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org

Research Article

A Single Determinant Dominates the Rate of Yeast Protein Evolution

D. Allan Drummond*, Alpan Raval{dagger},{ddagger} and Claus O. Wilke§

* Program in Computation and Neural Systems, California Institute of Technology, Pasadena; {dagger} Keck Graduate Institute, Claremont; {ddagger} School of Mathematical Sciences, Claremont Graduate University; and § Section of Integrative Biology and Center for Computational Biology and Bioinformatics, University of Texas at Austin

E-mail: cwilke{at}mail.utexas.edu.

A gene's rate of sequence evolution is among the most fundamental evolutionary quantities in common use, but what determines evolutionary rates has remained unclear. Here, we carry out the first combined analysis of seven predictors (gene expression level, dispensability, protein abundance, codon adaptation index, gene length, number of protein-protein interactions, and the gene's centrality in the interaction network) previously reported to have independent influences on protein evolutionary rates. Strikingly, our analysis reveals a single dominant variable linked to the number of translation events which explains 40-fold more variation in evolutionary rate than any other, suggesting that protein evolutionary rate has a single major determinant among the seven predictors. The dominant variable explains nearly half the variation in the rate of synonymous and protein evolution. We show that the two most commonly used methods to disentangle the determinants of evolutionary rate, partial correlation analysis and ordinary multivariate regression, produce misleading or spurious results when applied to noisy biological data. We overcome these difficulties by employing principal component regression, a multivariate regression of evolutionary rate against the principal components of the predictor variables. Our results support the hypothesis that translational selection governs the rate of synonymous and protein sequence evolution in yeast.

Key Words: Saccharomyces cerevisiae • evolutionary rate • gene expression • protein-protein interactions • dispensability • translational selection


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