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.

Global diversity and evidence for coevolution of KIR and HLA

Nature Genetics volume 39, pages 1114–1119 (2007)Cite this article

Abstract

The killer immunoglobulin-like receptor (KIR) gene cluster shows extensive genetic diversity, as do the HLA class I loci, which encode ligands for KIR molecules. We genotyped 1,642 individuals from 30 geographically distinct populations to examine population-level evidence for coevolution of these two functionally related but unlinked gene clusters. We observed strong negative correlations between the presence of activating KIR genes and their corresponding HLA ligand groups across populations, especially KIR3DS1 and its putative HLA-B Bw4-80I ligands (r = −0.66, P = 0.038). In contrast, we observed weak positive relationships between the various inhibitory KIR genes and their ligands. We observed a negative correlation between distance from East Africa and frequency of activating KIR genes and their corresponding ligands, suggesting a balance between selection on HLA and KIR loci. Most KIR-HLA genetic association studies indicate a primary influence of activating KIR-HLA genotypes in disease risk1,2; concomitantly, activating receptor-ligand pairs in this study show the strongest signature of coevolution of these two complex genetic systems as compared with inhibitory receptor-ligand pairs.

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

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

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

Figure 1: Map of the world showing the location of sampled populations.
Figure 2: KIR and HLA ligand carrier frequencies across populations.
Figure 3: Correlation between KIR and HLA ligand frequencies.

References

  1. Carrington, M. & Martin, M.P. The impact of variation at the KIR gene cluster on human disease. Curr. Top. Microbiol. Immunol. 298, 225–257 (2006).

    CAS  PubMed  Google Scholar 

  2. Parham, P. MHC class I molecules and KIRs in human history, health and survival. Nat. Rev. Immunol. 5, 201–214 (2005).

    Article  CAS  Google Scholar 

  3. Carrington, M. & Cullen, M. Justified chauvinism: Advances in defining meiotic recombination through sperm typing. Trends Genet. 20, 196–205 (2004).

    Article  CAS  Google Scholar 

  4. Khakoo, S.I. & Carrington, M. KIR and disease: A model system or system of models? Immunol. Rev. 214, 186–201 (2006).

    Article  CAS  Google Scholar 

  5. Apanius, V., Penn, D., Slev, P.R., Ruff, L.R. & Potts, W.K. The nature of selection on the major histocompatibility complex. Crit. Rev. Immunol. 17, 179–224 (1997).

    Article  CAS  Google Scholar 

  6. Borghans, J.A., Beltman, J.B. & De Boer, R.J. MHC polymorphism under host-pathogen coevolution. Immunogenetics 55, 732–739 (2004).

    Article  CAS  Google Scholar 

  7. Hedrick, P.W. Pathogen resistance and genetic variation at MHC loci. Evolution Int. J. Org. Evolution 56, 1902–1908 (2002).

    Article  Google Scholar 

  8. Khakoo, S.I. et al. Rapid evolution of NK cell receptor systems demonstrated by comparison of chimpanzees and humans. Immunity 12, 687–698 (2000).

    Article  CAS  Google Scholar 

  9. Vilches, C. & Parham, P. KIR: Diverse, Rapidly Evolving Receptors of Innate and Adaptive Immunity. Annu. Rev. Immunol. 20, 217–251 (2002).

    Article  CAS  Google Scholar 

  10. Hiby, S.E. et al. Combinations of maternal KIR and fetal HLA-C genes influence the risk of preeclampsia and reproductive success. J. Exp. Med. 200, 957–965 (2004).

    Article  CAS  Google Scholar 

  11. Carr, W.H., Pando, M.J. & Parham, P. KIR3DL1 polymorphisms that affect NK cell inhibition by HLA-Bw4 ligand. J. Immunol. 175, 5222–5229 (2005).

    Article  CAS  Google Scholar 

  12. Cella, M., Longo, A., Ferrara, G.B., Strominger, J.L. & Colonna, M. NK3-specific natural killer cells are selectively inhibited by Bw4- positive HLA alleles with isoleucine 80. J. Exp. Med. 180, 1235–1242 (1994).

    Article  CAS  Google Scholar 

  13. Gumperz, J.E. et al. Conserved and variable residues within the Bw4 motif of HLA-B make separable contributions to recognition by the NKB1 killer cell- inhibitory receptor. J. Immunol. 158, 5237–5241 (1997).

    CAS  PubMed  Google Scholar 

  14. Martin, M.P. et al. Epistatic interaction between KIR3DS1 and HLA-B delays the progression to AIDS. Nat. Genet. 31, 429–434 (2002).

    Article  CAS  Google Scholar 

  15. Qi, Y. et al. KIR/HLA pleiotropism: Protection against both HIV and opportunistic infections. PLoS Pathog. 2, e79 (2006)(doi:10.1371/journal.ppat.0020079).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Bamshad, M. & Wooding, S.P. Signatures of natural selection in the human genome. Nat. Rev. Genet. 4, 99–111 (2003).

    Article  CAS  Google Scholar 

  17. Lopez-Vazquez, A. et al. Protective effect of the HLA-Bw4I80 epitope and the killer cell immunoglobulin-like receptor 3DS1 gene against the development of hepatocellular carcinoma in patients with hepatitis C virus infection. J. Infect. Dis. 192, 162–165 (2005).

    Article  CAS  Google Scholar 

  18. Prugnolle, F. et al. Pathogen-driven selection and worldwide HLA class I diversity. Curr. Biol. 15, 1022–1027 (2005).

    Article  CAS  Google Scholar 

  19. Su, B. et al. Polynesian origins: insights from the Y chromosome. Proc. Natl. Acad. Sci. USA 97, 8225–8228 (2000).

    Article  CAS  Google Scholar 

  20. Meyer, D., Single, R.M., Mack, S.J., Erlich, H.A. & Thomson, G. Signatures of demographic history and natural selection in the human major histocompatibility complex Loci. Genetics 173, 2121–2142 (2006).

    Article  CAS  Google Scholar 

  21. Hedrick, P.W., Whittam, T.S. & Parham, P. Heterozygosity at individual amino acid sites: extremely high levels for HLA-A and -B genes. Proc. Natl. Acad. Sci. USA 88, 5897–5901 (1991).

    Article  CAS  Google Scholar 

  22. Salamon, H. et al. Evolution of HLA class II molecules: allelic and amino acid site variability across populations. Genetics 152, 393–400 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Osier, M.V. et al. ALFRED: An allele frequency database for anthropology. Am. J. Phys. Anthropol. 119, 77–83 (2002).

    Article  Google Scholar 

  24. Martin, M.P. & Carrington, M. KIR locus polymorphisms: Genotyping and disease association analysis. in Methods in Molecular Biology: Innate Immunity (eds. Ewbank, J. & Vivier, E.) (Humana Press, Totowa, New Jersey, in the press).

  25. Martin, M.P. et al. Cutting edge: Susceptibility to psoriatic arthritis: Influence of activating killer Ig-like receptor genes in the absence of specific HLA-C alleles. J. Immunol. 169, 2818–2822 (2002).

    Article  CAS  Google Scholar 

  26. Lancaster, A., Nelson, M.P., Meyer, D., Thomson, G. & Single, R.M. PyPop: a software framework for population genomics: analyzing large-scale multi-locus genotype data. Pac. Symp. Biocomput. 514–525 (2003).

  27. Single, R.M., Meyer, D. & Thomson, G. Statistical methods for analysis of population genetic data. in Immunobiology of the Human MHC: Proceedings of the 13th International Histocompatibility Workshop and Conference Vol. 1 (ed. Hansen, J.A.) (IHWG Press, Seattle, 2007).

    Google Scholar 

  28. Williams, R.C., Steinberg, A.G., Knowler, W.C. & Pettitt, D.J. Gm 3;5,13,14 and stated-admixture: independent estimates of admixture in American Indians. Am. J. Hum. Genet. 39, 409–413 (1986).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Cramer, H. Mathematical Methods of Statistics (Princeton Univ. Press, Princeton, New Jersey, 1946).

    Google Scholar 

  30. Fisher, R. Statistical Methods for Research Workers (Oliver & Boyd, Edinburgh, 1970).

    Google Scholar 

Download references

Acknowledgements

We thank H. Rajeevan and M. Osier for their assistance with the ALFRED database. This project has been funded in whole or in part with federal funds from the US National Cancer Institute (National Institutes of Health) under contract N01-CO-12400. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products or organizations imply endorsement by the US Government. This research was supported in part by the Intramural Research Program of the US National Institutes of Health (NIH), National Cancer Institute, Center for Cancer Research. R.M.S. was supported by NIH grant GM35326, Department of Energy grant DE-FG02-00ER45828 and the Vermont Advanced Computing Center under NASA grant NNG-05GO96G. D.M. was supported by FAPESP grant 03/08973-6.

Author information

Author notes

  1. Richard M Single and Maureen P Martin: These authors contributed equally to this work.

Authors and Affiliations

  1. The Department of Mathematics and Statistics, University of Vermont, Burlington, 05405, Vermont, USA

    Richard M Single

  2. Laboratory of Genomic Diversity, SAIC-Frederick, National Cancer Institute-Frederick, Frederick, 21702, Maryland, USA

    Maureen P Martin, Xiaojiang Gao & Mary Carrington

  3. Departamento de Genética e Biologia Evolutiva, Universidade de São Paulo, Rua do Matão 277, São Paulo, 05608-900, SP, Brazil

    Diogo Meyer

  4. Core Genotyping Facility, Advanced Technology Program, SAIC-Frederick, Inc., National Cancer Institute-Frederick, Maryland, 21702, USA

    Meredith Yeager

  5. Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, US National Institutes of Health, Rockville, 20852, Maryland, USA

    Meredith Yeager

  6. Department of Genetics, Yale University School of Medicine, 333 Cedar Street, New Haven, 06510, Connecticut, USA

    Judith R Kidd & Kenneth K Kidd

Authors
  1. Richard M Single
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maureen P Martin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiaojiang Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Diogo Meyer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Meredith Yeager
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Judith R Kidd
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kenneth K Kidd
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Mary Carrington
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.C. designed and supervised the project and prepared the manuscript; R.M.S. contributed to the design of the project, developed the statistical methods and prepared the manuscript; M.P.M. performed KIR genotyping and prepared the manuscript; X.G. performed HLA genotyping; D.M. and M.Y. provided intellectual input; J.R.K. and K.K.K. provided samples and intellectual input; all authors discussed the results and commented on the manuscript.

Corresponding author

Correspondence to Mary Carrington.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Note, Supplementary Figure 1 (PDF 85 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Single, R., Martin, M., Gao, X. et al. Global diversity and evidence for coevolution of KIR and HLA. Nat Genet 39, 1114–1119 (2007). https://doi.org/10.1038/ng2077

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng2077

This article is cited by

Search

Advanced 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