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Effect of genetic architecture on the power of human linkage studies to resolve the contribution of quantitative trait loci
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  • Original Article
  • Published: 01 February 1994

Effect of genetic architecture on the power of human linkage studies to resolve the contribution of quantitative trait loci

  • Lindon J Eaves1 

Heredity volume 72, pages 175–192 (1994)Cite this article

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  • 44 Citations

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Abstract

The effect of genetic architecture (linkage relationships, dominance and two forms of non-allelic interaction) on the power of marker studies to detect, locate and analyse the contributions of specific quantitative trait loci (QTLs) to continuous human traits is considered for randomly mating populations in linkage equilibrium under a two-locus model. The expected regression of the within-sibling-pair mean-square on number of alleles identical by descent (IBD) at two marker loci is explored for every possible pair of markers over a region of the genome containing two QTLs linked loosely (50 CM) or more tightly (20 CM).

For the cases examined, it is shown that epistasis between the pair of QTLs reduces considerably the total amount of information available for the location and analysis of the QTL effects. The overall effects of epistasis are more marked when there are duplicate gene interactions (i.e. genes operate in parallel) than when there are complementary interactions (i.e. genes operate in series). However, when there are complementary interactions, the regression approach is almost certain to fail to detect any evidence of epistasis. The numerical analysis suggests that methods of QTL analysis based on IBD in humans are unlikely to offer the resolving power that is desirable if QTLs are to be located precisely unless inheritance is very simple or prohibitively large numbers of highly selected individuals are available.

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References

  • Carey, G, and Williamson, J. 1991. Linkage analysis of quantitative traits: increased power by using selected samples. Am J Hum Genet, 49, 786–796.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Caten, C E. 1979. Quantitative genetic variation in fungi. In: Thompson, J. N., Jr and Thoday, J. M. (eds) Quantitative Genetic Variation, pp. 35–60. Academic Press, New York.

    Chapter  Google Scholar 

  • Eaves, L J. 1988. Dominance alone is not enough. Behav Genet, 18, 27–33.

    Article  CAS  PubMed  Google Scholar 

  • Greenberg, D A. 1993. Linkage analysis of ‘necessary’ disease loci versus ‘susceptibility’ loci. Am J Hum Genet, 52, 135–143.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Haley, C S, and Knott, S A. 1992. A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Heredity, 69, 315–324.

    Article  CAS  PubMed  Google Scholar 

  • Haseman, J K, and Elston, R C. 1972. The investigation of linkage between a quantitative trait and a marker locus. Behav Genet, 2, 3–19.

    Article  CAS  PubMed  Google Scholar 

  • Jinks, J L. 1977. Discussion of ‘Inferring causes of human variation’. J R Stat Soc Lond (A), 140, 353.

    Google Scholar 

  • Jinks, J L, and Towey, P M. 1976. Estimating the number of genes in a polygenic system by genotype assay. Heredity, 37, 69–81.

    Article  CAS  PubMed  Google Scholar 

  • Knott, S A, and Haley, C S. 1992. Maximum likelihood mapping of quantitative trait loci using full-sib families. Genetics, 132, 1211–1222.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Lalouel, J M, Rao, D C, Morton, N E, and Elston, R C. 1983. A unified model for complex segregation analysis. Am J Hum Genet, 35, 816–826.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Lander, E S, and Botstein, D. 1986. Strategies for studying heterogeneous genetic traits in humans by using a linkage map of restriction fragment length polymorphisms. Proc Nat Acad Sci USA, 83, 7353–7357.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lander, E S, and Botstein, D. 1989. Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics, 121, 185–199.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Luo, Z W, and Kearsey, M J. 1989. Maximum likelihood estimation of linkage between a marker gene and a quantitative locus. Heredity, 63, 401–408.

    Article  PubMed  Google Scholar 

  • Luo, Z W, and Kearsey, M J. 1991. Maximum likelihood estimation of linkage between a marker gene and a quantitative locus. II. Application to backcross and doubled haploid populations. Heredity, 66, 117–124.

    Article  PubMed  Google Scholar 

  • Maclean, C J, Morton, N E, and Lew, R. 1975. Analysis of family resemblance. IV. Operational characteristics of segregation analysis. Am J Hum Genet, 27, 365–384.

    CAS  PubMed  PubMed Central  Google Scholar 

  • McGuire, T R. 1992. A biometrical genetic approach to chromosome analysis of Drosophila: detection of epistatic interactions in geotaxis. Behav Genet, 22, 453–467.

    Article  CAS  PubMed  Google Scholar 

  • Martin, N G, Eaves, L J, Kearsey, M J, and Davies, P. 1978. The power of the classical twin study. Heredity, 9, 539–552.

    Google Scholar 

  • Mather, K. 1949. Biometrical Genetics, 1st edn. Methuen, London.

    Google Scholar 

  • Mather, K. 1974. Non-allelic interaction in continuous variation of randomly breeding populations. Heredity, 32, 414–419.

    Article  CAS  PubMed  Google Scholar 

  • Mather, K, and Jinks, J L. 1982. Biometrical Genetics: The Study of Continuous Variation, 3rd edn. Chapman and Hall, London.

    Book  Google Scholar 

  • Morton, N E, and Maclean, C J. 1974. Analysis of family resemblance. III. Complex segregation of quantitative traits. Am J Hum Genet, 26, 489–503.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Motro, U, and Thomson, G. 1985. The affected sib pair method. I. Statistical features of the affected sib pair method. Genetics, 110, 525–538.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Nelder, J A, and Wedderburn, R W M. 1972. Generalized linear models. J R Stat Soc Lond (A), 135, 370–384.

    Google Scholar 

  • Neuman, R J, and Rice, J P. 1992. Two locus models of disease. Genet Epidemiol, 9, 347–365.

    Article  CAS  PubMed  Google Scholar 

  • NUMERICAL Algorithms Group. 1990. NAG FORTRAN Library: Mark 14. Numerical Algorithms Group, Oxford.

  • Paterson, A H, Damon, S, Hewitt, J D, Zamir, D, Rabinowitch, H, Lincoln, S E, Lander, E S, and Tanksley, S D. 1991. Mendelian factors underlying quantitative triats in tomato: comparison across species, generations and environments. Genetics, 127, 181–197.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Paterson, A H, Deverna, J W, Lanini, B, and Tanksley, S D. 1990. Fine mapping of quantitative trait loci using selected overlapping recombinant chromosomes in an interspecies cross of tomato. Genetics, 124, 735–742.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Paterson, A H, Lander, E S, Hewitt, J D, Peterson, S, Lincoln, S E, and Tanksley, S D. 1988. Resolution of quantitative traits into Mendelian factors by using a complete linkage map of restriction fragment length polymorphisms. Nature, 335, 721–725.

    Article  CAS  PubMed  Google Scholar 

  • Perkins, J M, and Jinks, J L. 1970. Detection and estimation of genotype-environmental, linkage and epistatic components of variation for a metrical trait. Heredity, 26, 203–209.

    Article  Google Scholar 

  • Risch, N. 1990. Linkage strategies for genetically complex traits. I. Multilocus models. Am J Hum Genet, 46, 222–228.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Schlager, O, and Chao, C S. 1991. The role of dominance and epistasis in the genetic control of blood pressure in rodent models of hypertension. Clin Exp Hypertens, 13, 947–953.

    CAS  Google Scholar 

  • Spickett, S G, and Thoday, J M. 1966. Regular responses to selection: 3. Interaction between located polygenes. Genet Res, 7, 96–121.

    Article  CAS  PubMed  Google Scholar 

  • Spielman, R S, McGinnis, R E, and Ewens, W J. 1993. Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). Am J Hum Genet, 52, 506–516.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Van Der Veen, J H. 1959. Tests of non-allelic interaction and linkage for quantitative characters in generations derived from two diploid pure lines. Genetica, 30, 201–232.

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Human Genetics, Virginia Commonwealth University, P O Box 3, Richmond, VA 23298-0003, USA

    Lindon J Eaves

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  1. Lindon J Eaves
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Eaves, L. Effect of genetic architecture on the power of human linkage studies to resolve the contribution of quantitative trait loci. Heredity 72, 175–192 (1994). https://doi.org/10.1038/hdy.1994.25

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  • Received: 30 June 1993

  • Issue date: 01 February 1994

  • DOI: https://doi.org/10.1038/hdy.1994.25

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Keywords

  • epistasis
  • linkage
  • power
  • QTLs
  • RFLPs
  • sib-pairs

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