Article

Worldwide patterns of human epigenetic variation

  • Nature Ecology & Evolutionvolume 1pages15771583 (2017)
  • doi:10.1038/s41559-017-0299-z
  • Download Citation
Received:
Accepted:
Published online:

Abstract

DNA methylation is an epigenetic modification, influenced by both genetic and environmental variation, that plays a key role in transcriptional regulation and many organismal phenotypes. Although patterns of DNA methylation have been shown to differ between human populations, it remains to be determined how epigenetic diversity relates to the patterns of genetic and gene expression variation at a global scale. Here we measured DNA methylation at 485,000 CpG sites in five diverse human populations, and analysed these data together with genome-wide genotype and gene expression data. We found that population-specific DNA methylation mirrors genetic variation, and has greater local genetic control than mRNA levels. We estimated the rate of epigenetic divergence between populations, which indicates far greater evolutionary stability of DNA methylation in humans than has been observed in plants. This study provides a deeper understanding of worldwide patterns of human epigenetic diversity, as well as initial estimates of the rate of epigenetic divergence in recent human evolution.

  • Subscribe to Nature Ecology & Evolution for full access:

    $99

    Subscribe

Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. 1.

    Cavalli-Sforza, L. L., Menozzi, P. & Piazza, A. The History and Geography of Human Genes (Princeton Univ. Press, Princeton, NJ, 1994).

  2. 2.

    Li, J. Z. et al. Worldwide human relationships inferred from genome-wide patterns of variation. Science 319, 1100–1104 (2008).

  3. 3.

    Novembre, J. et al. Genes mirror geography within Europe. Nature 456, 98–101 (2008).

  4. 4.

    Jakobsson, M. et al. Genotype, haplotype and copy-number variation in worldwide human populations. Nature 451, 998–1003 (2008).

  5. 5.

    Ramachandran, S. et al. Support from the relationship of genetic and geographic distance in human populations for a serial founder effect originating in Africa. Proc. Natl Acad. Sci. USA 102, 15942–15947 (2005).

  6. 6.

    Rosenberg, N. A. et al. Clines, clusters, and the effect of study design on the inference of human population structure. PLoS Genet. 10, e70 (2005).

  7. 7.

    Price, A. L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).

  8. 8.

    Heyn, H. et al. DNA methylation contributes to natural human variation. Genome Res. 23, 1363–1372 (2013).

  9. 9.

    Fraser, H. B., Lam, L. L., Neumann, S. M. & Kobor, M. S. Population-specificity of human DNA methylation. Genome Biol. 13, R8 (2012).

  10. 10.

    Moen, E. L. et al. Genome-wide variation of cytosine modifications between European and African populations and the implications for complex traits. Genetics 194, 987–996 (2013).

  11. 11.

    Fagny, M. et al. The epigenomic landscape of african rainforest hunter-gatherers and farmers. Nat. Commun. 6, 10047 (2015).

  12. 12.

    Stranger, B. E. et al. Patterns of cis regulatory variation in diverse human populations. PLoS Genet. 8, e1002639 (2012).

  13. 13.

    Martin, A. R. et al. Transcriptome sequencing from diverse human populations reveals differentiated regulatory architecture. PLoS Genet. 10, e1004549 (2014).

  14. 14.

    Jirtle, R. L. & Skinner, M. K. Environmental epigenomics and disease susceptibility. Nat. Rev. Genet. 8, 253–262 (2007).

  15. 15.

    Feil, R. & Fraga, M. F. Epigenetics and the environment: emerging patterns and implications. Nat. Rev. Genet. 13, 97–109 (2012).

  16. 16.

    Cann, H. M. et al. A human genome diversity cell line panel. Science 296, 261–262 (2002).

  17. 17.

    Henn, B. M., Cavalli-Sforza, L. L. & Feldman, M. W. The great human expansion. Proc. Natl Acad. Sci. USA 109, 17758–17764 (2012).

  18. 18.

    Sandoval, J. et al. Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome. Epigenetics 6, 692–702 (2011).

  19. 19.

    Trapnell, C. et al. Differential gene and transcript expression analysis of rna-seq experiments with tophat and cufflinks. Nat. Protoc. 7, 562–578 (2012).

  20. 20.

    Cavalli-Sforza, L. L., Piazza, A., Menozzi, P. & Mountain, J. Reconstruction of human evolution: bringing together genetic, archaeological, and linguistic data. Proc. Natl Acad. Sci. USA 16(85), 6002–6006 (1988).

  21. 21.

    Conrad, D. F. et al. A worldwide survey of haplotype variation and linkage disequilibrium in the human genome. Nat. Genet. 38, 1251–1260 (2006).

  22. 22.

    Creanza, N. et al. A comparison of worldwide phonemic and genetic variation in human populations. Proc. Natl Acad. Sci. USA 112, 1265–1272 (2015).

  23. 23.

    Rosenberg, N. A. et al. Genetic structure of human populations. Science 298, 2381–2385 (2002).

  24. 24.

    Lovmar, L., Ahlford, A., Jonsson, M. & Syvänen, A.-C. Silhouette scores for assessment of SNP genotype clusters. BMC Genom. 6, 35 (2005).

  25. 25.

    Cavalli-Sforza, L. L. & Feldman, M. W. The application of molecular genetic approaches to the study of human evolution. Nat. Genet. 33, 266–275 (2003).

  26. 26.

    Henn, B. M., Cavalli-Sforza, L. L. & Feldman, M. W. The great human expansion. Proc. Natl Acad. Sci. USA 109, 17758–17764 (2012).

  27. 27.

    Pujol, B., Wilson, A. J., Ross, R. I. C. & Pannell, J. R. Are Qst-Fst comparisons for natural populations meaningful? Mol. Ecol. 17, 4782–4785 (2008).

  28. 28.

    Edelaar, P., Burraco, P. & Mestre, I. G. Comparisons between Qst and Fst — how wrong have we been? Mol. Ecol. 20, 4830–4839 (2011).

  29. 29.

    Leinonen, T., McCairns, R. J. S., O’Hara, R. B. & Merilä, J. Qst–Fst comparisons: evolutionary and ecological insights from genomic heterogeneity. Nat. Rev. Genet. 14, 179–190 (2013).

  30. 30.

    Weir, B. S. & Cockerham, C. C. Estimating F-statistics for the analysis of population structure. Evolution 38, 1358–1370 (1984).

  31. 31.

    Zuckerkandl, E. & Pauling, L. Horizons in Biochemistry. (Academic, New York, 1962).

  32. 32.

    Caliskan, M., Cusanovich, D. A., Ober, C. & Gilad, Y. The effects of EBV transformation on gene expression levels and methylation profiles. Human Mol. Genet. 20, 1643–1652 (2011).

  33. 33.

    Van der Graaf, A. et al. Rate, spectrum, and evolutionary dynamics of spontaneous epimutations. Proc. Natl Acad. Sci. USA 112, 6676–6681 (2015).

  34. 34.

    Becker, C. et al. Spontaneous epigenetic variation in the Arabidopsis thaliana methylome. Nature 480, 245–249 (2011).

  35. 35.

    Schmitz, R. J. et al. Transgenerational epigenetic instability is a source of novel methylation variants. Science 334, 369–373 (2011).

  36. 36.

    Lynch, M. Rate, molecular spectrum, and consequences of human mutation. Proc. Natl Acad. Sci. USA 107, 961–968 (2010).

  37. 37.

    Mikkelsen, T. S. et al. The Chimpanzee Sequencing and Analysis Consortium. Initial sequence of the chimpanzee genome and comparison with the human genome. Nature 437, 69–87 (2005).

  38. 38.

    Bell, J. T. et al. DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol. 120, R10 (2011).

  39. 39.

    Feinberg, A. P. Phenotypic plasticity and the epigenetics of human disease. Nature 447, 433–440 (2007).

  40. 40.

    Maksimovic, J., Gordon, L. & Oshlack, A. SWAN: Subset-quantile within array normalization for Illumina Infinium HumanMethylation450 BeadChips. Genome Biol. 13, R44 (2012).

  41. 41.

    Scally, A. & Durbin, R. Revising the human mutation rate: implications for understanding human evolution. Nat. Rev. Genet. 13, 745–753 (2012).

Download references

Acknowledgements

O.C. and M.W.F. acknowledge support from the Morrison Institute for Population and Resource Studies at Stanford and the Stanford Centre for Computational, Evolutionary and Human Genomics. B.M.H. acknowledges support from NIH grant 3R01HG003229 to C. B. Bustamante. M.S.K. is a Senior Fellow of the Canadian Institute for Advanced Research and the Canada Research Chair in Social Epigenetics. We thank members of the Feldman Laboratory, in particular N. Creanza and J. Granka, for helpful discussions, and M. Jones for comments. This research was done using resources provided by the Open Science Grid, which is supported by the National Science Foundation award 1148698, and the US Department of Energy’s Office of Science.

Author information

Author notes

    • Oana Carja

    Present address: Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA

Affiliations

  1. Department of Biology, Stanford University, Stanford, CA, 94305, USA

    • Oana Carja
    • , Marcus W. Feldman
    •  & Hunter B. Fraser
  2. Centre for Molecular Medicine and Therapeutics, BC Children’s Hospital Research Institute, University of British Columbia, Vancouver, BC, V5Z 4H4, Canada

    • Julia L. MacIsaac
    • , Sarah M. Mah
    •  & Michael S. Kobor
  3. Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada

    • Julia L. MacIsaac
    • , Sarah M. Mah
    •  & Michael S. Kobor
  4. Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY, 11790, USA

    • Brenna M. Henn

Authors

  1. Search for Oana Carja in:

  2. Search for Julia L. MacIsaac in:

  3. Search for Sarah M. Mah in:

  4. Search for Brenna M. Henn in:

  5. Search for Michael S. Kobor in:

  6. Search for Marcus W. Feldman in:

  7. Search for Hunter B. Fraser in:

Contributions

O.C., B.M.H., M.S.K., M.W.F. and H.B.F. designed the study. J.L.M., S.M.M. and M.S.K. generated the methylation data set. O.C. analysed the data and O.C., B.M.H., M.S.K., M.W.F. and H.B.F. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Oana Carja.

Electronic supplementary material

  1. Supplementary Information

    Supplementary Figures 1,2; Supplementary Tables 1–4