Codon Usage and Selection on Proteins

  • Joshua B. Plotkin
  • Jonathan Dushoff
  • Michael M. Desai
  • Hunter B. Fraser
Article
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Abstract

Selection pressures on proteins are usually measured by comparing homologous nucleotide sequences (Zuckerkandl and Pauling 1965). Recently we introduced a novel method, termed volatility, to estimate selection pressures on proteins on the basis of their synonymous codon usage (Plotkin and Dushoff 2003; Plotkin et al. 2004). Here we provide a theoretical foundation for this approach. Under the Fisher-Wright model, we derive the expected frequencies of synonymous codons as a function of the strength of selection on amino acids, the mutation rate, and the effective population size. We analyze the conditions under which we can expect to draw inferences from biased codon usage, and we estimate the time scales required to establish and maintain such a signal. We find that synonymous codon usage can reliably distinguish between negative selection and neutrality only for organisms, such as some microbes, that experience large effective population sizes or periods of elevated mutation rates. The power of volatility to detect positive selection is also modest—requiring approximately 100 selected sites—but it depends less strongly on population size. We show that phenomena such as transient hyper-mutators can improve the power of volatility to detect selection, even when the neutral site heterozygosity is low. We also discuss several confounding factors, neglected by the Fisher-Wright model, that may limit the applicability of volatility in practice.

Keywords

Codon usage Selection Fisher-Wright Diffusion Volatility Protein evolution 
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Notes

Acknowledgments

We thank Daniel Fisher, Andrew Murray, and Michael Turelli for their input during the preparation of the manuscript. We also thank an anonymous referee for substantial conceptual input. J.B.P. acknowledges support from the Harvard Society of Fellows, the Milton Fund, and the Burroughs Wellcome Fund. M.M.D. acknowledges support from a Merck Award for Genome-Related Research.

Supplementary material

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Supplementary material

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Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Joshua B. Plotkin
    • 1
  • Jonathan Dushoff
    • 2
  • Michael M. Desai
    • 3
  • Hunter B. Fraser
    • 4
  1. 1.Department of BiologyUniversity of PennsylvaniaPhiladelphiaUSA
  2. 2.Department of Ecology and Evolutionary BiologyPrinceton UniversityPrincetonUSA
  3. 3.Department of Molecular and Cellular Biology and Department of PhysicsHarvard UniversityCambridgeUSA
  4. 4.Department of Molecular and Cellular BiologyUniversity of California, BerkeleyBerkeleyUSA

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