Geographical structure and differential natural selection among North European populations

  1. Brian P. McEvoy1,17,
  2. Grant W. Montgomery1,
  3. Allan F. McRae1,
  4. Samuli Ripatti2,3,4,
  5. Markus Perola2,3,
  6. Tim D. Spector5,
  7. Lynn Cherkas5,
  8. Kourosh R. Ahmadi5,
  9. Dorret Boomsma6,
  10. Gonneke Willemsen6,
  11. Jouke J. Hottenga6,
  12. Nancy L. Pedersen4,
  13. Patrik K.E. Magnusson4,
  14. Kirsten Ohm Kyvik7,8,
  15. Kaare Christensen7,
  16. Jaakko Kaprio3,9,10,
  17. Kauko Heikkilä9,
  18. Aarno Palotie3,141516,
  19. Elisabeth Widen3,
  20. Juha Muilu3,
  21. Ann-Christine Syvänen11,
  22. Ulrika Liljedahl11,
  23. Orla Hardiman12,
  24. Simon Cronin13,
  25. Leena Peltonen2,3,1415,
  26. Nicholas G. Martin1 and
  27. Peter M. Visscher1
  1. 1 Queensland Institute of Medical Research, Brisbane, Queensland 4029, Australia;
  2. 2 National Institute for Health and Welfare (THL), Helsinki FI-00271, Finland;
  3. 3 Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki FI-00014, Finland;
  4. 4 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm SE-171 77, Sweden;
  5. 5 Department of Twin Research and Genetic Epidemiology, King's College London, St. Thomas' Hospital Campus, London SE1 7EH, United Kingdom;
  6. 6 Department of Biological Psychology, Vrije Universiteit, Amsterdam 1081 BT, The Netherlands;
  7. 7 Department of Epidemiology, Institute of Public Health, University of Southern Denmark, Odense DK-5000, Denmark;
  8. 8 Institute of Regional Health Services Research, University of Southern Denmark, Odense DK-5000, Denmark;
  9. 9 Faculty of Medicine, Department of Public Health, University of Helsinki, Helsinki FI-00014, Finland;
  10. 10 Department of Mental Health, National Institute for Health and Welfare (THL), Helsinki FI-00271, Finland;
  11. 11 Department of Medical Sciences, Uppsala University, Uppsala 75185, Sweden;
  12. 12 Trinity College Institute of Neuroscience, Trinity College, Dublin 2, Ireland;
  13. 13 Department of Clinical Neurological Sciences, Royal College of Surgeons in Ireland, Dublin 2, Ireland;
  14. 14 The Broad Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA;
  15. 15 Wellcome Trust Sanger Institute–Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, United Kingdom;
  16. 16 Department of Clinical Chemistry, University of Helsinki, Helsinki FI-00014, Finland

    Abstract

    Population structure can provide novel insight into the human past, and recognizing and correcting for such stratification is a practical concern in gene mapping by many association methodologies. We investigate these patterns, primarily through principal component (PC) analysis of whole genome SNP polymorphism, in 2099 individuals from populations of Northern European origin (Ireland, United Kingdom, Netherlands, Denmark, Sweden, Finland, Australia, and HapMap European-American). The major trends (PC1 and PC2) demonstrate an ability to detect geographic substructure, even over a small area like the British Isles, and this information can then be applied to finely dissect the ancestry of the European-Australian and European-American samples. They simultaneously point to the importance of considering population stratification in what might be considered a small homogeneous region. There is evidence from FST-based analysis of genic and nongenic SNPs that differential positive selection has operated across these populations despite their short divergence time and relatively similar geographic and environmental range. The pressure appears to have been focused on genes involved in immunity, perhaps reflecting response to infectious disease epidemic. Such an event may explain a striking selective sweep centered on the rs2508049-G allele, close to the HLA-G gene on chromosome 6. Evidence of the sweep extends over a 8-Mb/3.5-cM region. Overall, the results illustrate the power of dense genotype and sample data to explore regional population variation, the events that have crafted it, and their implications in both explaining disease prevalence and mapping these genes by association.

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