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MBE Advance Access originally published online on December 19, 2007
Molecular Biology and Evolution 2008 25(4):634-642; doi:10.1093/molbev/msm281
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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

Mammalian Nonsynonymous Sites Are Not Overdispersed: Comparative Genomic Analysis of Index of Dispersion of Mammalian Proteins

Seong-Ho Kim1 and Soojin V. Yi

School of Biology, Georgia Institute of Technology

E-mail: soojinyi{at}gatech.edu.

Accepted for publication December 13, 2007.

It is often stated that patterns of nonsynonymous rate variation among mammalian lineages are more irregular than expected or overdispersed under the neutral model, whereas synonymous sites conform to the neutral model. Here we reexamined genome-wide patterns of the variance to mean ratio, or index of dispersion (R), of substitutions in proteins from human, mouse, and dog. Contrary to the prevailing notion, we found that the mean index of dispersion for nonsynonymous sites of mammalian proteins is not significantly different from 1. We propose that earlier analyses were biased because the data included disproportionately more protein hormones, which tend to be more dispersed than genes in other functional categories. Synonymous sites exhibit greater degree of dispersion than nonsynonymous sites, although similar to earlier estimates and potentially due to errors associated with correction for multiple hits. Overall, our analysis identifies strong genome-wide generation-time effect and natural selection as important determinants of among-lineage variation of protein evolutionary rates. Furthermore, patterns of lineage-specific selective constraint are consistent with the nearly neutral model of molecular evolution.

Key Words: index of dispersion • lineage effects • neutral theory • nearly neutral theory • comparative genomics • gene ontology


1 Present address: Division of Biostatistics, School of Medicine, Indiana University, Indianapolis, IN.

Koichiro Tamura, Associate Editor


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