Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Protein dispensability and rate of evolution

Abstract

If protein evolution is due in large part to slightly deleterious amino acid substitutions1,2, then the rate of evolution should be greater in proteins that contribute less to individual fitness. The rationale for this prediction is that relatively dispensable proteins should be subject to weaker purifying selection, and should therefore accumulate mildly deleterious substitutions more rapidly. Although this argument was presented3 over twenty years ago, and is fundamental to many applications of evolutionary theory4, the prediction has proved difficult to confirm. In fact, a recent study showed that essential mouse genes do not evolve more slowly than non-essential ones5. Thus, although a variety of factors influencing the rate of protein evolution have been supported by extensive sequence analysis6,7,8,9,10,11,12, the relationship between protein dispensability and evolutionary rate has remained unconfirmed. Here we use the results from a highly parallel growth assay of single gene deletions in yeast13 to assess protein dispensability, which we relate to evolutionary rate estimates that are based on comparisons of sequences drawn from twenty-one fully annotated genomes. Our analysis reveals a highly significant relationship between protein dispensability and evolutionary rate, and explains why this relationship is not detectable by categorical comparison of essential versus non-essential proteins. The relationship is highly conserved, so that protein dispensability in yeast is also predictive of evolutionary rate in a nematode worm.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: The relationship between a protein's contribution to fitness in yeast (fi) and its rate of evolution as estimated by di, the evolutionary distance to the protein's reciprocal best hit in worm (linear regression: di = -3.482fi + 2.806, P = 0.001; Spearman rank correlation, P = 6.6 × 10-5).
Figure 2: Schematic representation of phylogenetic relationships among yeast (S. cerevisiae), the worm (C. elegans), and outgroup species.
Figure 3: The relationship between fitness effect in yeast and the rate of evolution from the fungi–animal ancestor to yeast or the worm.
Figure 4: Expected probability of fixation of novel substitutions, E(p), plotted as a function of the fitness effect of a protein, f (see Box 1).

Similar content being viewed by others

References

  1. Ohta, T. The nearly neutral theory of molecular evolution. Annu. Rev. Ecol. Syst. 23, 263–286 (1992).

    Article  Google Scholar 

  2. Ohta, T. Slightly deleterious mutant substitutions in evolution. Nature 246, 96–98 (1973).

    Article  CAS  Google Scholar 

  3. Wilson, A. C., Carlson, S. S. & White, T. J. Biochemical evolution. Annu. Rev. Biochem. 46, 573–639 (1977).

    Article  CAS  Google Scholar 

  4. Wagner, A. Robustness against mutations in genetic networks of yeast. Nature Genet. 24, 355–361 (2000).

    Article  CAS  Google Scholar 

  5. Hurst, L. D. & Smith, N. G. C. Do essential genes evolve slowly? Curr. Biol. 9, 747–750 (1999).

    Article  CAS  Google Scholar 

  6. Kuma, K., Iwabe, N. & Miyata, T. Functional constraints against variations on molecules from the tissue level—slowly evolving brain-specific genes demonstrated by protein-kinase and immuno globulin supergene families. Mol. Biol. Evol. 12, 123–130 (1995).

    Article  CAS  Google Scholar 

  7. Williams, E. J. B. & Hurst, L. D. The proteins of linked genes evolve at similar rates. Nature 407, 900–903 (2000).

    Article  CAS  Google Scholar 

  8. Hughes, A. L. Rapid evolution of immunoglobulin superfamily C2 domains expressed in immune system cells. Mol. Biol. Evol. 14, 1–5 (1997).

    Article  CAS  Google Scholar 

  9. Stockbauer, K. E. et al. Hypervariability generated by natural selection in an extracellular complement-inhibiting protein of serotype M1 strains of group A Streptococcus. Proc. Natl Acad. Sci. USA 95, 3128–3133 (1998).

    Article  CAS  Google Scholar 

  10. Yamaguchi, Y. & Gojobori, T. Evolutionary mechanisms and population dynamics of the third variable envelope region of HIV within single hosts. Proc. Natl Acad. Sci. USA 94, 1264–1269 (1997).

    Article  CAS  Google Scholar 

  11. Makalowski, W. & Boguski, M. S. Synonymous and nonsynonymous substitution distances are correlated in mouse and rat genes. J. Mol. Evol. 47, 119–121 (1998).

    Article  CAS  Google Scholar 

  12. Tourasse, N. J. & Li, W. H. Selective constraints, amino acid composition, and the rate of protein evolution. Mol. Biol. Evol. 17, 656–664 (2000).

    Article  CAS  Google Scholar 

  13. Winzeler, E. A., Shoemaker, D. D., Astromoff, A. & Liang, H. Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. Science 285, 901–906 (1999).

    Article  CAS  Google Scholar 

  14. Rivera, M. C., Jain, R., Moore, J. E. & Lake, J. A. Genomic evidence for two functionally distinct gene classes. Proc. Natl Acad. Sci. USA 95, 6239–6244 (1998).

    Article  CAS  Google Scholar 

  15. Chervitz, S. A. et al. Comparison of the complete protein sets of worm and yeast: orthology and divergence. Science 282, 2022–2028 (1998).

    Article  CAS  Google Scholar 

  16. Robinson, M., Gouy, M., Gautier, C. & Mouchiroud, D. Sensitivity of the relative-rate test to taxonomic sampling. Mol. Biol. Evol. 15, 1091–1098 (1998).

    Article  CAS  Google Scholar 

  17. Sarich, V. M. & Wilson, A. C. Generation time and genomic evolution in primates. Science 179, 1144–1147 (1973).

    Article  CAS  Google Scholar 

  18. Wu, C.-I. & Li, W.-H. Evidence for higher rates of nucleotide substitution in rodents than in man. Proc. Natl Acad. Sci. USA 82, 1741–1745 (1985).

    Article  CAS  Google Scholar 

  19. Ashburner, M. et al. An exploration of the sequence of a 2.9-Mb region of the genome of Drosophila melanogaster: The Adh region. Genetics 153, 179–219 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Fraser, A. G. et al. Functional genomic analysis of C. elegans chromosome I by systematic RNA interference. Nature 408, 325–330 (2000).

    Article  CAS  Google Scholar 

  21. Smith, V., Chou, K. N., Lashkari, D., Botstein, D. & Brown, P. O. Functional analysis of the genes of yeast chromosome V by genetic footprinting. Science 274, 2069–2074 (1996).

    Article  CAS  Google Scholar 

  22. Grishin, N. V. Estimation of the number of amino acid substitutions per site when the substitution rate varies among sites. J. Mol. Evol. 41, 675–679 (1995).

    Article  CAS  Google Scholar 

  23. Grishin, N. V., Wolf, Y. I. & Koonin, E. V. From complete genomes to measures of substitution rate variability within and between proteins. Genome Res. 10, 991–1000 (2000).

    Article  CAS  Google Scholar 

  24. Feng, D. & Doolittle, R. Converting amino acid alignment scores into measures of evolutionary time: A simulation study of various relationships. J. Mol. Evol. 44, 361–370 (1997).

    Article  CAS  Google Scholar 

  25. Huynen, M. & Bork, P. Measuring genome evolution. Proc. Natl Acad. Sci. USA 95, 5849–5856 (1998).

    Article  CAS  Google Scholar 

  26. Tatusov, R. L., Galperin, M. Y., Nalale, D. A. & Koonin, E. V. The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 28, 33–36 (2000).

    Article  CAS  Google Scholar 

  27. Ewens, W. H. Mathematical Population Genetics (eds Krickeberg, K. & Levin, S. A.) (Springer, New York, 1979).

    MATH  Google Scholar 

  28. Kimura, M. On the probability of fixation of mutant genes in a population. Genetics 47, 713–719 (1962).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Zhang, J. & Gu, X. Correlation between the substitution rate and rate variation among sites in protein evolution. Genetics 149, 1615–1625 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank D. Petrov and M. Feldman for much guidance and support. M. Cherry and A. Chu provided assistance with genomic and functional genomic data.

Author information

Authors

Additional information

Center for Computational Genetics and Biological Modeling, Department of Biological Sciences, Stanford University, Stanford, California, USA

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hirsh, A., Fraser, H. Protein dispensability and rate of evolution. Nature 411, 1046–1049 (2001). https://doi.org/10.1038/35082561

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1038/35082561

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing