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MBE Advance Access originally published online on April 29, 2007
Molecular Biology and Evolution 2007 24(8):1667-1677; doi:10.1093/molbev/msm085
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© The Author 2007. 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 Articles

Population Genetics Without Intraspecific Data

Jeffrey L. Thorne*,{dagger}, Sang Chul Choi{dagger}, Jiaye Yu{ddagger}, Paul G. Higgs§ and Hirohisa Kishino||

* Wissenschaftskolleg zu Berlin, Institute for Advanced Study, Berlin, Germany
{dagger} Bioinformatics Research Center, North Carolina State University
{ddagger} Bioinformatics Centre, University of Copenhagen, Copenhagen, Denmark
§ Department of Physics and Astronomy, McMaster University, Hamilton, Ontario, Canada
|| Laboratory of Biometrics, University of Tokyo, Tokyo, Japan

E-mail: thorne{at}statgen.ncsu.edu.

Accepted for publication April 18, 2007.

A central goal of computational biology is the prediction of phenotype from DNA and protein sequence data. Recent models of sequence change use in silico prediction systems to incorporate the effects of phenotype on evolutionary rates. These models have been designed for analyzing sequence data from different species and have been accompanied by statistical techniques for estimating model parameters when the incorporation of phenotype induces dependent change among sequence positions. A difficulty with these efforts to link phenotype and interspecific evolution is that evolution occurs within populations, and parameters of interspecific models should have population genetic interpretations. We show, with two examples, how population genetic interpretations can be assigned to evolutionary models. The first example considers the impact of RNA secondary structure on sequence change, and the second reflects the tendency for protein tertiary structure to influence nonsynonymous substitution rates. We argue that statistical fit to data should not be the sole criterion for assessing models of sequence change. A good interspecific model should also yield a clear and biologically plausible population genetic interpretation.

Key Words: dependence among sites • fixation probability • protein structure • RNA structure

Ziheng Yang, Associate Editor


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