Evidence of widespread selection on standing variation in Europe at height-associated SNPs

Nature Genetics volume 44, pages1015–1019(2012)Cite this article

Subjects

Abstract

Strong signatures of positive selection at newly arising genetic variants are well documented in humans1,2,3,4,5,6,7,8, but this form of selection may not be widespread in recent human evolution9. Because many human traits are highly polygenic and partly determined by common, ancient genetic variation, an alternative model for rapid genetic adaptation has been proposed: weak selection acting on many pre-existing (standing) genetic variants, or polygenic adaptation10,11,12. By studying height, a classic polygenic trait, we demonstrate the first human signature of widespread selection on standing variation. We show that frequencies of alleles associated with increased height, both at known loci and genome wide, are systematically elevated in Northern Europeans compared with Southern Europeans (P < 4.3 × 10−4). This pattern mirrors intra-European height differences and is not confounded by ancestry or other ascertainment biases. The systematic frequency differences are consistent with the presence of widespread weak selection (selection coefficients ∼10−3–10−5 per allele) rather than genetic drift alone (P < 10−15).

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

Rent or Buy

All prices are NET prices.

Figure 1: Mean allele frequency difference of height SNPs, matched SNPs and genome-wide SNPs between Northern- and Southern-European populations.
Figure 2: Within-family analyses of height and the Northern-predominant alleles across the genome.

References

  1. 1

    Tishkoff, S.A. et al. Haplotype diversity and linkage disequilibrium at human G6PD: recent origin of alleles that confer malarial resistance. Science 293, 455–462 (2001).

    CAS  Article  Google Scholar 

  2. 2

    Hamblin, M.T. & Di Rienzo, A. Detection of the signature of natural selection in humans: evidence from the Duffy blood group locus. Am. J. Hum. Genet. 66, 1669–1679 (2000).

    CAS  Article  Google Scholar 

  3. 3

    Bersaglieri, T. et al. Genetic signatures of strong recent positive selection at the lactase gene. Am. J. Hum. Genet. 74, 1111–1120 (2004).

    CAS  Article  Google Scholar 

  4. 4

    The International HapMap Consortium. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851–861 (2007).

  5. 5

    Sabeti, P.C. et al. Genome-wide detection and characterization of positive selection in human populations. Nature 449, 913–918 (2007).

    CAS  Article  Google Scholar 

  6. 6

    Voight, B.F., Kudaravalli, S., Wen, X. & Pritchard, J.K. A map of recent positive selection in the human genome. PLoS Biol. 4, e72 (2006).

    Article  Google Scholar 

  7. 7

    Williamson, S.H. et al. Localizing recent adaptive evolution in the human genome. PLoS Genet. 3, e90 (2007).

    Article  Google Scholar 

  8. 8

    Hancock, A.M. et al. Adaptations to climate-mediated selective pressures in humans. PLoS Genet. 7, e1001375 (2011).

    CAS  Article  Google Scholar 

  9. 9

    Hernandez, R.D. et al. Classic selective sweeps were rare in recent human evolution. Science 331, 920–924 (2011).

    CAS  Article  Google Scholar 

  10. 10

    Pritchard, J.K. & Di Rienzo, A. Adaptation—not by sweeps alone. Nat. Rev. Genet. 11, 665–667 (2010).

    CAS  Article  Google Scholar 

  11. 11

    Novembre, J. & Di Rienzo, A. Spatial patterns of variation due to natural selection in humans. Nat. Rev. Genet. 10, 745–755 (2009).

    CAS  Article  Google Scholar 

  12. 12

    Hermisson, J. & Pennings, P.S. Soft sweeps: molecular population genetics of adaptation from standing genetic variation. Genetics 169, 2335–2352 (2005).

    CAS  Article  Google Scholar 

  13. 13

    Sabeti, P.C. et al. Positive natural selection in the human lineage. Science 312, 1614–1620 (2006).

    CAS  Article  Google Scholar 

  14. 14

    Przeworski, M., Coop, G. & Wall, J.D. The signature of positive selection on standing genetic variation. Evolution 59, 2312–2323 (2005).

    Article  Google Scholar 

  15. 15

    Barrett, R.D. & Schluter, D. Adaptation from standing genetic variation. Trends Ecol. Evol. 23, 38–44 (2008).

    Article  Google Scholar 

  16. 16

    Pritchard, J.K., Pickrell, J.K. & Coop, G. The genetics of human adaptation: hard sweeps, soft sweeps, and polygenic adaptation. Curr. Biol. 20, R208–R215 (2010).

    CAS  Article  Google Scholar 

  17. 17

    Orr, H.A. Testing natural selection versus genetic drift in phenotypic evolution using quantitative trait locus data. Genetics 149, 2099–2104 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. 18

    Lewontin, R.C. Race and intelligence. Bull. At. Sci. 26, 2–8 (1970).

    Article  Google Scholar 

  19. 19

    Cavelaars, A.E. et al. Persistent variations in average height between countries and between socio-economic groups: an overview of 10 European countries. Ann. Hum. Biol. 27, 407–421 (2000).

    CAS  Article  Google Scholar 

  20. 20

    Lango Allen, H. et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature 467, 832–838 (2010).

    CAS  Article  Google Scholar 

  21. 21

    Myocardial Infarction Genetics Consortium. Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants. Nat. Genet. 41, 334–341 (2009).

  22. 22

    Nelson, M.R. et al. The Population Reference Sample, POPRES: a resource for population, disease, and pharmacological genetics research. Am. J. Hum. Genet. 83, 347–358 (2008).

    CAS  Article  Google Scholar 

  23. 23

    Yang, J. et al. Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 42, 565–569 (2010).

    CAS  Article  Google Scholar 

  24. 24

    Campbell, C.D. et al. Demonstrating stratification in a European American population. Nat. Genet. 37, 868–872 (2005).

    CAS  Article  Google Scholar 

  25. 25

    Hirschhorn, J.N. & Daly, M.J. Genome-wide association studies for common diseases and complex traits. Nat. Rev. Genet. 6, 95–108 (2005).

    CAS  Article  Google Scholar 

  26. 26

    Freedman, M.L. et al. Assessing the impact of population stratification on genetic association studies. Nat. Genet. 36, 388–393 (2004).

    CAS  Article  Google Scholar 

  27. 27

    Lander, E.S. & Schork, N.J. Genetic dissection of complex traits. Science 265, 2037–2048 (1994).

    CAS  Article  Google Scholar 

  28. 28

    Ayodo, G. et al. Combining evidence of natural selection with association analysis increases power to detect malaria-resistance variants. Am. J. Hum. Genet. 81, 234–242 (2007).

    CAS  Article  Google Scholar 

  29. 29

    The 1000 Genomes Project Consortium. A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010).

  30. 30

    Yi, X. et al. Sequencing of 50 human exomes reveals adaptation to high altitude. Science 329, 75–78 (2010).

    CAS  Article  Google Scholar 

  31. 31

    Simonson, T.S. et al. Genetic evidence for high-altitude adaptation in Tibet. Science 329, 72–75 (2010).

    CAS  Article  Google Scholar 

  32. 32

    Splansky, G.L. et al. The third generation cohort of the National Heart, Lung, and Blood Institute's Framingham Heart Study: design, recruitment, and initial examination. Am. J. Epidemiol. 165, 1328–1335 (2007).

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank E.L. Altmaier, K.E. Samocha, S.R. Grossman, G. Coop, other attendees of the Biology of Genomes 2011 conference, B.F. Voight, M. McCarthy, P. Visscher and other members of the Reich and Hirschhorn labs for their discussions and helpful comments. We gratefully thank the GIANT consortium and particularly the members of the height working group for making unpublished association data available. We thank the MIGen consortium for making allele frequency data available. This research was conducted using data and resources from the FHS of the National Heart, Lung, and Blood Institute of the US National Institutes of Health and Boston University School of Medicine based on analyses by FHS investigators participating in the SNP Health Association Resource project. This work was supported by the National Heart, Lung and Blood Institute's FHS (contract no. N01-HC-25195) and its contract with Affymetrix, Inc., for genotyping services (contract no. N02-HL-6-4278). A portion of this research used the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. This work was also supported by a graduate research fellowship from the National Science Foundation (to C.W.K.C.), the March of Dimes (6-FY09-507 to J.N.H.) and the National Institute of Diabetes and Digestive and Kidney Diseases (1R01DK075787 to J.N.H.).

Author information

Author notes

  1. Michael C Turchin and Charleston WK Chiang: These authors contributed equally to this work.

Affiliations

  1. Division of Genetics, Children's Hospital Boston, Boston, Massachusetts, USA

    Michael C Turchin, Charleston WK Chiang, Cameron D Palmer & Joel N Hirschhorn

  2. Division of Endocrinology, Children's Hospital Boston, Boston, Massachusetts, USA

    Michael C Turchin, Charleston WK Chiang, Cameron D Palmer & Joel N Hirschhorn

  3. Program in Genomics, Children's Hospital Boston, Boston, Massachusetts, USA

    Michael C Turchin, Charleston WK Chiang, Cameron D Palmer & Joel N Hirschhorn

  4. Metabolism Initiative, Broad Institute, Cambridge, Massachusetts, USA

    Michael C Turchin, Charleston WK Chiang, Cameron D Palmer & Joel N Hirschhorn

  5. Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA

    Michael C Turchin, Charleston WK Chiang, Cameron D Palmer, Sriram Sankararaman, David Reich & Joel N Hirschhorn

  6. Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA

    Charleston WK Chiang, Sriram Sankararaman, David Reich & Joel N Hirschhorn

Authors
  1. Michael C Turchin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Charleston WK Chiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Cameron D Palmer
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sriram Sankararaman
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. David Reich
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Joel N Hirschhorn
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

Genetic Investigation of ANthropometric Traits (GIANT) Consortium

Contributions

M.C.T., C.W.K.C., C.D.P., S.S., D.R. and J.N.H. conceived of and designed the experiments; M.C.T. and C.D.P. performed the analyses; M.C.T., C.W.K.C. and J.N.H. interpreted the data; C.W.K.C., C.D.P., D.R. and the GIANT Consortium contributed materials; M.C.T., C.W.K.C. and J.N.H. wrote the paper with input from all coauthors.

Corresponding author

Correspondence to Joel N Hirschhorn.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

A full list of members and institutions is provided in the Supplementary Note.

Supplementary information

Supplementary Text and Figures

Supplementary Tables 1–13, Supplementary Figures 1–10 and Supplementary Note (PDF 3944 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Turchin, M., Chiang, C., Palmer, C. et al. Evidence of widespread selection on standing variation in Europe at height-associated SNPs. Nat Genet 44, 1015–1019 (2012). https://doi.org/10.1038/ng.2368

Download citation

Further reading

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