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5 - Population diversity, genomes and disease

Published online by Cambridge University Press:  17 August 2009

By
Gianpiero L. Cavalleri  and
David B. Goldstein
Edited by
Alan Wright  and
Nicholas Hastie
Alan Wright
Affiliation:
MRC Human Genetics Unit, Edinburgh
Nicholas Hastie
Affiliation:
MRC Human Genetics Unit, Edinburgh
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Summary

Introduction

The striking success in mapping Mendelian disease genes, coupled with the rapid development of genomic methodologies have generated an initial wave of enthusiasm that progress in understanding the genetics of common diseases might experience similar success. Over the past five years however, this optimism has diminished sharply as the difficulty of the task has become apparent. This difficulty is highlighted by the fact that, to date, very few genes have convincingly been shown to harbor variants that influence predisposition to a common disease (Glazier et al., 2002; Lohmueller et al., 2003).

However, recent progress has been relatively rapid in a number of relevant methodologies for genetic association studies. In particular, there has been considerable progress in making use of linkage disequilibrium (LD) to more efficiently and comprehensively represent human genetic variation in association studies. There now appears reason to be cautiously optimistic that the field may begin to progress more rapidly.

This chapter focuses primarily on factors influencing patterns of human genetic variation, and the implications of the patterns of variation in medical genetics. A central theme is the role of the HapMap project in facilitating genetic association studies. We consider both the use of the HapMap to identify single nucleotide polymorphisms (SNPs) that efficiently represent other SNPs (that is, tagging SNPs), and also the use of the HapMap data to help optimise methods for identifying the causal variants that underlie genotype–phenotype correlations.

Type
Chapter
Information
Genes and Common Diseases
Genetics in Modern Medicine
 , pp. 80 - 91
Publisher: Cambridge University Press
Print publication year: 2007

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References

Akey, J. M., Zhang, G., Zhang, K., Jin, L. and Shriver, M. D. (2002). Interrogating a high-density SNP map for signatures of natural selection. Genome Res, 12, 1805–14.CrossRefGoogle ScholarPubMed
Altshuler, D., Brooks, L. D., Chakravarti, A.et al. (2005). International HapMap Consortium. A haplotype map of the human genome. Nature, 437, 1299–320.Google Scholar
Anderson, E. C. and Slatkin, M. (2004). Population-genetic basis of haplotype blocks in the 5q31 region. Am J Hum Genet, 74, 40–9.CrossRefGoogle ScholarPubMed
Bamshad, M. and Wooding, S. P. (2003). Signatures of natural selection in the human genome. Nat Rev Genet, 4, 99–111.CrossRefGoogle ScholarPubMed
Bersaglieri, T., Sabeti, P. C., Patterson, N.et al. (2004). Genetic signatures of strong recent positive selection at the lactase gene. Am J Hum Genet, 74, 1111–20.CrossRefGoogle ScholarPubMed
Carlson, C. S., Eberle, M. A., Rieder, M. J.et al. (2003). Additional SNPs and linkage-disequilibrium analyses are necessary for whole-genome association studies in humans. Nat Genet, 33, 518–21.CrossRefGoogle ScholarPubMed
Chakraborty, R. and Weiss, K. M. (1988). Admixture as a tool for finding linked genes and detecting that difference from allelic association between loci. Proc Natl Acad Sci USA, 85, 9119–23.CrossRefGoogle ScholarPubMed
Chakravarti, A., Buetow, K. H., Antonarakis, S. E.et al. (1984). Nonuniform recombination within the human beta-globin gene cluster. Am J Hum Genet, 36, 1239–58.Google ScholarPubMed
Chapman, J. M., Cooper, J. D., Todd, J. A. and Clayton, D. G. (2003). Detecting disease associations due to linkage disequilibrium, a class of tests and the determinants of statistical power. Hum Hered, 56, 18–31.CrossRefGoogle ScholarPubMed
Collins-Schramm, H. E., Chima, B., Operario, D. J., Criswell, L. A. and Seldin, M. F. (2003). Markers informative for ancestry demonstrate consistent megabase-length linkage disequilibrium in the African American population. Hum Genet, 113, 211–19.Google ScholarPubMed
Daly, M. J., Rioux, J. D., Schaffner, S. F., Hudson, T. J. and Lander, E. S. (2001). High-resolution haplotype structure in the human genome. Nat Genet, 29, 229–32.CrossRefGoogle ScholarPubMed
Gabriel, S. B., Schaffner, S. F., Nguyen, H.et al. (2002). The structure of haplotype blocks in the human genome. Science, 296, 2225–9.CrossRefGoogle ScholarPubMed
Glazier, A. M., Nadeau, J. H. and Aitman, T. J. (2002). Finding genes that underlie complex traits. Science, 298, 2345–9.CrossRefGoogle ScholarPubMed
Goldstein, D. B., Ahmadi, K. R., Weale, M. E. and Wood, N. W. (2003). Genome scans and candidate gene approaches in the study of common diseases and variable drug responses. Trends Genet, 19, 615–22.CrossRefGoogle Scholar
Jeffreys, A. J., Ritchie, A. and Neumann, R. (2000). High resolution analysis of haplotype diversity and meiotic crossover in the human TAP2 recombination hotspot. Hum Mol Genet, 9, 725–33.CrossRefGoogle ScholarPubMed
Jeffreys, A. J., Kauppi, L. and Neumann, R. (2001). Intensely punctate meiotic recombination in the class II region of the major histocompatibility complex. Nat Genet, 29, 217–22.CrossRefGoogle ScholarPubMed
Johnson, G. C., Esposito, L., Barratt, B. J.et al. (2001). Haplotype tagging for the identification of common disease genes. Nat Genet, 29, 233–7.CrossRefGoogle ScholarPubMed
Kauppi, L., Jeffreys, A. J. and Keeney, S. (2004). Where the crossovers are: recombination distributions in mammals. Nat Rev Genet, 5, 413–24.CrossRefGoogle ScholarPubMed
Kidd, J. R., Pakstis, A. J., Zhao, H.et al. (2000). Haplotypes and linkage disequilibrium at the phenylalanine hydroxylase locus, PAH, in a global representation of populations. Am J Hum Genet, 66, 1882–99.CrossRefGoogle Scholar
Kruglyak, L. (1999). Prospects for whole-genome linkage disequilibrium mapping of common disease genes. Nat Genet, 22, 139–44.CrossRefGoogle ScholarPubMed
Lohmueller, K. E., Pearce, C. L., Pike, M., Lander, E. S. and Hirschhorn, J. N. (2003). Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet, 33, 177–82.CrossRefGoogle ScholarPubMed
McVean, G. A., Myers, S., Hunt, S.et al. (2004). The fine-scale structure of recombination rate variation in the human genome. Science, 304, 581–4.CrossRefGoogle ScholarPubMed
Nei, M. and Li, W. H. (1973). Linkage disequilibrium in subdivided populations. Genetics, 75, 213–19.Google ScholarPubMed
Pagani, F. and Baralle, F. E. (2004). Genomic variants in exons and introns, identifying the splicing spoilers. Nat Rev Genet, 5, 389–96.CrossRefGoogle ScholarPubMed
Patterson, N., Hattangadi, N., Lane, B.et al. (2004). Methods for high-density admixture mapping of disease genes. Am J Hum Genet, 74, 979–1000.CrossRefGoogle ScholarPubMed
Pritchard, J. K. and Przeworski, M. (2001). Linkage disequilibrium in humans: models and data. Am J Hum Genet, 69, 1–14.CrossRefGoogle ScholarPubMed
Pritchard, J. K. and Rosenberg, N. A. (1999). Use of unlinked genetic markers to detect population stratification in association studies. Am J Hum Genet, 65, 220–8.CrossRefGoogle ScholarPubMed
Reich, D. E., Cargill, M., Bolk, S. et al. (2001). Linkage disequilibrium in the human genome. Nature, 411, 199–204.CrossRefGoogle ScholarPubMed
Rybicki, B. A., Iyengar, S. K., Harris, T.et al. (2002). The distribution of long range admixture linkage disequilibrium in an African-American population. Hum Hered, 53, 187–96.CrossRefGoogle Scholar
Sabeti, P. C., Reich, D. E., Higgins, J. M.et al. (2002). Detecting recent positive selection in the human genome from haplotype structure. Nature, 419, 832–7.CrossRefGoogle ScholarPubMed
Slatkin, M. (1994). Linkage disequilibrium in growing and stable populations. Genetics, 137, 331–6.Google ScholarPubMed
Smith, M. W., Patterson, N., Lautenberger, J. A.et al. (2004). A high-density admixture map for disease gene discovery in African Americans. Am J Hum Genet, 74, 1001–13.CrossRefGoogle ScholarPubMed
Soranzo, N., Cavalleri, G. L., Weale, M. E.et al. (2004). Identifying candidate causal variants responsible for altered activity of the ABCB1 multidrug resistance gene. Genome Res, 14, 1333–44.CrossRefGoogle ScholarPubMed
Soubrier, F., Martin, S., Alonso, A.et al. (2002). High-resolution genetic mapping of the ACE-linked QTL influencing circulating ACE activity. Eur J Hum Genet, 10, 553–61.CrossRefGoogle ScholarPubMed
The International HapMap Consortium. (2003). The International HapMap Project. Nature, 426, 789–96.CrossRef
Thomas, M. G., Parfitt, T., Weiss, D. A.et al. (2000). Y chromosomes traveling south: the cohen modal haplotype and the origins of the Lemba – the “Black Jews of Southern Africa”. Am J Hum Genet, 66, 674–86.CrossRefGoogle Scholar
Tishkoff, S. A., Dietzsch, E., Speed, W.et al. (1996). Global patterns of linkage disequilibrium at the CD4 locus and modern human origins. Science, 271, 1380–7.CrossRefGoogle ScholarPubMed
Weale, M. E., Depondt, C., Macdonald, S. J.et al. (2003). Selection and evaluation of tagging SNPs in the neuronal-sodium-channel gene SCN1A: implications for linkage-disequilibrium gene mapping. Am J Hum Genet, 73, 551–65.CrossRefGoogle ScholarPubMed
Wilson, J. F. and Goldstein, D. B. (2000). Consistent long-range linkage disequilibrium generated by admixture in a Bantu-Semitic hybrid population. Am J Hum Genet, 67, 926–35.CrossRefGoogle Scholar

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