The deleterious mutation load is insensitive to recent population history (original) (raw)

Nature Genetics volume 46, pages 220–224 (2014)Cite this article

Subjects

Abstract

Human populations have undergone major changes in population size in the past 100,000 years, including recent rapid growth. How these demographic events have affected the burden of deleterious mutations in individuals and the frequencies of disease mutations in populations remains unclear. We use population genetic models to show that recent human demography has probably had little impact on the average burden of deleterious mutations. This prediction is supported by two exome sequence data sets showing that individuals of west African and European ancestry carry very similar burdens of damaging mutations. We further show that for many diseases, rare alleles are unlikely to contribute a large fraction of the heritable variation, and therefore the impact of recent growth is likely to be modest. However, for those diseases that have a direct impact on fitness, strongly deleterious rare mutations probably do have an important role, and recent growth will have increased their impact.

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

Access options

Subscribe to this journal

Receive 12 print issues and online access

$209.00 per year

only $17.42 per issue

Buy this article

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

Additional access options:

Similar content being viewed by others

References

  1. Coventry, A. et al. Deep resequencing reveals excess rare recent variants consistent with explosive population growth. Nat. Commun. 1, 131 (2010).
    Article Google Scholar
  2. Marth, G.T. et al. The functional spectrum of low-frequency coding variation. Genome Biol. 12, R84 (2011).
    Article Google Scholar
  3. Keinan, A. & Clark, A.G. Recent explosive human population growth has resulted in an excess of rare genetic variants. Science 336, 740–743 (2012).
    Article CAS Google Scholar
  4. Nelson, M.R. et al. An abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people. Science 337, 100–104 (2012).
    Article CAS Google Scholar
  5. Tennessen, J.A. et al. Evolution and functional impact of rare coding variation from deep sequencing of human exomes. Science 337, 64–69 (2012).
    Article CAS Google Scholar
  6. Fu, W. et al. Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants. Nature 493, 216–220 (2013).
    Article CAS Google Scholar
  7. Keinan, A., Mullikin, J.C., Patterson, N. & Reich, D. Measurement of the human allele frequency spectrum demonstrates greater genetic drift in East Asians than in Europeans. Nat. Genet. 39, 1251–1255 (2007).
    Article CAS Google Scholar
  8. Wall, J.D. & Przeworski, M. When did the human population size start increasing? Genetics 155, 1865–1874 (2000).
    CAS PubMed PubMed Central Google Scholar
  9. Voight, B.F. et al. Interrogating multiple aspects of variation in a full resequencing data set to infer human population size changes. Proc. Natl. Acad. Sci. USA 102, 18508–18513 (2005).
    Article CAS Google Scholar
  10. Gutenkunst, R.N., Hernandez, R.D., Williamson, S.H. & Bustamante, C.D. Inferring the joint demographic history of multiple populations from multidimensional SNP frequency data. PLoS Genet. 5, e1000695 (2009).
    Article Google Scholar
  11. Lohmueller, K.E. et al. Proportionally more deleterious genetic variation in European than in African populations. Nature 451, 994–997 (2008).
    Article CAS Google Scholar
  12. Casals, F. & Bertranpetit, J. Human genetic variation, shared and private. Science 337, 39–40 (2012).
    Article CAS Google Scholar
  13. Pritchard, J.K. Are rare variants responsible for susceptibility to complex diseases? Am. J. Hum. Genet. 69, 124–137 (2001).
    Article CAS Google Scholar
  14. Eyre-Walker, A. Genetic architecture of a complex trait and its implications for fitness and genome-wide association studies. Proc. Natl. Acad. Sci. USA 107, 1752–1756 (2010).
    Article CAS Google Scholar
  15. Gibson, G. Rare and common variants: twenty arguments. Nat. Rev. Genet. 13, 135–145 (2011).
    Article Google Scholar
  16. Manolio, T.A. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009).
    Article CAS Google Scholar
  17. Schaffner, S.F. et al. Calibrating a coalescent simulation of human genome sequence variation. Genome Res. 15, 1576–1583 (2005).
    Article CAS Google Scholar
  18. Hartl, D.L. A Primer of Population Genetics (Sinauer Associates, Inc., 2000).
  19. Travis, J.M. et al. Deleterious mutations can surf to high densities on the wave front of an expanding population. Mol. Biol. Evol. 24, 2334–2343 (2007).
    Article CAS Google Scholar
  20. Lynch, M., Conery, J. & Burger, R. Mutational meltdowns in sexual populations. Evolution 49, 1067–1080 (1995).
    Article Google Scholar
  21. The 1000 Genomes Project Consortium. A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010).
  22. Adzhubei, I.A. et al. A method and server for predicting damaging missense mutations. Nat. Methods 7, 248–249 (2010).
    Article CAS Google Scholar
  23. Thornton, K.R., Foran, A.J. & Long, A.D. Properties and modeling of GWAS when complex disease risk is due to non-complementing, deleterious mutations in genes of large effect. PLoS Genet. 9, e1003258 (2013).
    Article CAS Google Scholar
  24. Johnson, T. & Barton, N. Theoretical models of selection and mutation on quantitative traits. Phil. Trans. R. Soc. Lond. B 360, 1411–1425 (2005).
    Article CAS Google Scholar
  25. Charlesworth, B. & Charlesworth, D. Elements of Evolutionary Genetics (Roberts and Company Publishers, 2010).
  26. McVicker, G., Gordon, D., Davis, C. & Green, P. Widespread genomic signatures of natural selection in hominid evolution. PLoS Genet. 5, e1000471 (2009).
    Article Google Scholar
  27. Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010).
    Article Google Scholar
  28. Kumar, P., Henikoff, S. & Ng, P.C. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat. Protoc. 4, 1073–1081 (2009).
    Article CAS Google Scholar
  29. Chun, S. & Fay, J.C. Identification of deleterious mutations within three human genomes. Genome Res. 19, 1553–1561 (2009).
    Article CAS Google Scholar
  30. Schwarz, J.M., Rödelsperger, C., Schuelke, M. & Seelow, D. MutationTaster evaluates disease-causing potential of sequence alterations. Nat. Methods 7, 575–576 (2010).
    Article CAS Google Scholar

Download references

Acknowledgements

This work was supported by grants from the US National Institutes of Health (NIH) (MH084703 to J.K.P. and GM083228 to G.S.), the Israel Science Foundation (grant 1492/10 to G.S.) and the Howard Hughes Medical Institute (J.K.P.). M.C.T. was supported in part by NIH grant T32 GM007197. We thank D. Reich and S. Sunyaev for helpful discussions and generous input regarding the interpretation of PolyPhen-2, I. Adzhubey for human-independent PolyPhen scores, J. Akey for assistance in accessing data, J. Akey, A. Siepel, G. Coop, I. Eshel, R. Hudson and two anonymous reviewers for comments on the manuscript and M. Przeworski for many discussions and comments on the manuscript.

Author information

Author notes

  1. Guy Sella
    Present address: Present address: Department of Biological Sciences, Columbia University, New York, New York, USA.,
  2. Yuval B Simons and Michael C Turchin: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Ecology, Evolution and Behavior, Hebrew University of Jerusalem, Jerusalem, Israel
    Yuval B Simons
  2. Department of Human Genetics, University of Chicago, Chicago, Illinois, USA
    Michael C Turchin & Jonathan K Pritchard
  3. Howard Hughes Medical Institute, Stanford University, Stanford, California, USA
    Jonathan K Pritchard
  4. Department of Biology, Stanford University, Stanford, California, USA
    Jonathan K Pritchard
  5. Department of Genetics, Stanford University, Stanford, California, USA
    Jonathan K Pritchard
  6. Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, USA
    Guy Sella

Authors

  1. Yuval B Simons
    You can also search for this author inPubMed Google Scholar
  2. Michael C Turchin
    You can also search for this author inPubMed Google Scholar
  3. Jonathan K Pritchard
    You can also search for this author inPubMed Google Scholar
  4. Guy Sella
    You can also search for this author inPubMed Google Scholar

Contributions

J.K.P. and G.S. conceived and supervised the research. Y.B.S., G.S. and J.K.P. developed theory. Y.B.S. performed simulations. M.C.T. and J.K.P. performed data analysis. J.K.P. and G.S. wrote the manuscript with input from Y.B.S. and M.C.T.

Corresponding authors

Correspondence toJonathan K Pritchard or Guy Sella.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Rights and permissions

About this article

Cite this article

Simons, Y., Turchin, M., Pritchard, J. et al. The deleterious mutation load is insensitive to recent population history.Nat Genet 46, 220–224 (2014). https://doi.org/10.1038/ng.2896

Download citation

This article is cited by