, Volume 64, Issue 3, pp 165–175 | Cite as

Signatures of historical demography and pathogen richness on MHC class I genes

  • Nouar QutobEmail author
  • Francois Balloux
  • Towfique Raj
  • Hua Liu
  • Sophie Marion de Procé
  • John Trowsdale
  • Andrea Manica
Original Paper


The extreme polymorphism of MHC class I has been argued to be driven by balancing selection from pathogens, with the prediction that populations exposed to a wider variety of diseases should have higher diversity. We assembled a global database of allotype frequencies for MHC class I genes and investigated possible drivers of genetic diversity, measured in different ways. We first looked for a decline in diversity with distance from Africa (a consequence of drift during human expansions) and then investigated the link with pathogen richness once the effect of drift had been corrected for. Using heterozygosity, we recovered a clear decline in diversity from Africa and confirmed the positive relationship between genetic diversity and pathogen richness for all three classical MHC class I genes. However, when we considered a sequence-based measure of genetic diversity, the correlation with geographic distance from Africa vanished for HLA-C, and the correlations with pathogen richness for the three MHC class I genes were much weaker. HLA-C is known to consist of two functional classes of allotypes (classified with respect to the 80th residue), which interact with different KIR receptors. While this separation provided some improvement in the fit between genetic diversity and distance from Africa for one class, much clearer and consistent patterns were recovered when we used the 90th residue to separate HLA-C allotypes into two new classes. This suggests that this residue, which is also involved in the binding of KIR, might have had an important evolutionary role that has been overlooked.


MHC MHC diversity Dempography Pathogen richness Natural selection 



This work was supported by the Wellcome Trust (RG56540), the Medical Research Council (G0800681 and G0901682), the Biotechnology and Biological Sciences Research Council (BB/H005854/1 and BB/H008802/1), the Leverhulme Trust (Philip Leverhulme Award), the Karim Rida Said foundation (Karim Rida Said Scholarship‬) and the Cambridge Overseas Trust and in part by the Cambridge NIHR Biomedical Research Centre. We would like to thank Derek Smith, Rufus Johnstone, Stuart Piertney and two anonymous referees for the comments on the manuscript. We would also like to thank Thibaut Jombart for his help with the statistical analyses.

Supplementary material

251_2011_576_MOESM1_ESM.pdf (113 kb)
ESM Table 1 (PDF 113 kb)
251_2011_576_MOESM2_ESM.pdf (78 kb)
ESM Table 2 (PDF 78 kb)
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ESM Table 3 (PDF 5 kb)
251_2011_576_MOESM4_ESM.xls (107 kb)
ESM Table 4 (XLS 107 kb)
251_2011_576_MOESM5_ESM.pdf (63 kb)
ESM Table 5 (PDF 62 kb)


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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Nouar Qutob
    • 1
    Email author
  • Francois Balloux
    • 2
  • Towfique Raj
    • 3
    • 4
  • Hua Liu
    • 5
  • Sophie Marion de Procé
    • 6
  • John Trowsdale
    • 7
  • Andrea Manica
    • 1
  1. 1.Department of ZoologyUniversity of CambridgeCambridgeUK
  2. 2.MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease EpidemiologyImperial College Faculty of MedicineLondonUK
  3. 3.Harvard School of Public HealthBostonUSA
  4. 4.Division of Genetics, Department of Medicine, Brigham & Women’s HospitalHarvard Medical SchoolBostonUSA
  5. 5.Department of GeneticsUniversity of CambridgeCambridgeUK
  6. 6.Institute of Evolutionary BiologyUniversity of EdinburghEdinburghUK
  7. 7.Department of PathologyUniversity of CambridgeCambridgeUK

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