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. 1997 Nov;147(3):1445–1457. doi: 10.1093/genetics/147.3.1445

Advances in Statistical Methods to Map Quantitative Trait Loci in Outbred Populations

I Hoeschele 1, P Uimari 1, F E Grignola 1, Q Zhang 1, K M Gage 1
PMCID: PMC1208265  PMID: 9383084

Abstract

Statistical methods to map quantitative trait loci (QTL) in outbred populations are reviewed, extensions and applications to human and plant genetic data are indicated, and areas for further research are identified. Simple and computationally inexpensive methods include (multiple) linear regression of phenotype on marker genotypes and regression of squared phenotypic differences among relative pairs on estimated proportions of identity-by-descent at a locus. These methods are less suited for genetic parameter estimation in outbred populations but allow the determination of test statistic distributions via simulation or data permutation; however, further inferences including confidence intervals of QTL location require the use of Monte Carlo or bootstrap sampling techniques. A method which is intermediate in computational requirements is residual maximum likelihood (REML) with a covariance matrix of random QTL effects conditional on information from multiple linked markers. Testing for the number of QTLs on a chromosome is difficult in a classical framework. The computationally most demanding methods are maximum likelihood and Bayesian analysis, which take account of the distribution of multilocus marker-QTL genotypes on a pedigree and permit investigators to fit different models of variation at the QTL. The Bayesian analysis includes the number of QTLs on a chromosome as an unknown.

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Selected References

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  1. Amos C. I., Elston R. C. Robust methods for the detection of genetic linkage for quantitative data from pedigrees. Genet Epidemiol. 1989;6(2):349–360. doi: 10.1002/gepi.1370060205. [DOI] [PubMed] [Google Scholar]
  2. Amos C. I., Elston R. C., Wilson A. F., Bailey-Wilson J. E. A more powerful robust sib-pair test of linkage for quantitative traits. Genet Epidemiol. 1989;6(3):435–449. doi: 10.1002/gepi.1370060306. [DOI] [PubMed] [Google Scholar]
  3. Churchill G. A., Doerge R. W. Empirical threshold values for quantitative trait mapping. Genetics. 1994 Nov;138(3):963–971. doi: 10.1093/genetics/138.3.963. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Haley C. S., Knott S. A., Elsen J. M. Mapping quantitative trait loci in crosses between outbred lines using least squares. Genetics. 1994 Mar;136(3):1195–1207. doi: 10.1093/genetics/136.3.1195. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Jansen R. C., Stam P. High resolution of quantitative traits into multiple loci via interval mapping. Genetics. 1994 Apr;136(4):1447–1455. doi: 10.1093/genetics/136.4.1447. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Knott S. A., Haley C. S. Maximum likelihood mapping of quantitative trait loci using full-sib families. Genetics. 1992 Dec;132(4):1211–1222. doi: 10.1093/genetics/132.4.1211. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Knott S. A., Haley C. S., Thompson R. Methods of segregation analysis for animal breeding data: a comparison of power. Heredity (Edinb) 1992 Apr;68(Pt 4):299–311. doi: 10.1038/hdy.1992.44. [DOI] [PubMed] [Google Scholar]
  8. Knott S. A., Haley C. S., Thompson R. Methods of segregation analysis for animal breeding data: parameter estimates. Heredity (Edinb) 1992 Apr;68(Pt 4):313–320. doi: 10.1038/hdy.1992.45. [DOI] [PubMed] [Google Scholar]
  9. Lin S. A scheme for constructing an irreducible Markov chain for pedigree data. Biometrics. 1995 Mar;51(1):318–322. [PubMed] [Google Scholar]
  10. Lin S. Multipoint linkage analysis via Metropolis jumping kernels. Biometrics. 1996 Dec;52(4):1417–1427. [PubMed] [Google Scholar]
  11. Lin S., Thompson E., Wijsman E. Achieving irreducibility of the Markov chain Monte Carlo method applied to pedigree data. IMA J Math Appl Med Biol. 1993;10(1):1–17. doi: 10.1093/imammb/10.1.1. [DOI] [PubMed] [Google Scholar]
  12. Lin S., Thompson E., Wijsman E. Finding noncommunicating sets for Markov chain Monte Carlo estimations on pedigrees. Am J Hum Genet. 1994 Apr;54(4):695–704. [PMC free article] [PubMed] [Google Scholar]
  13. Mackinnon M. J., Weller J. I. Methodology and accuracy of estimation of quantitative trait loci parameters in a half-sib design using maximum likelihood. Genetics. 1995 Oct;141(2):755–770. doi: 10.1093/genetics/141.2.755. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Meuwissen T. H., Goddard M. E. Estimation of effects of quantitative trait loci in large complex pedigrees. Genetics. 1997 May;146(1):409–416. doi: 10.1093/genetics/146.1.409. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Olson J. M., Wijsman E. M. Linkage between quantitative trait and marker loci: methods using all relative pairs. Genet Epidemiol. 1993;10(2):87–102. doi: 10.1002/gepi.1370100202. [DOI] [PubMed] [Google Scholar]
  16. Satagopan J. M., Yandell B. S., Newton M. A., Osborn T. C. A bayesian approach to detect quantitative trait loci using Markov chain Monte Carlo. Genetics. 1996 Oct;144(2):805–816. doi: 10.1093/genetics/144.2.805. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Sheehan N., Thomas A. On the irreducibility of a Markov chain defined on a space of genotype configurations by a sampling scheme. Biometrics. 1993 Mar;49(1):163–175. [PubMed] [Google Scholar]
  18. Shrimpton A. E., Robertson A. The Isolation of Polygenic Factors Controlling Bristle Score in Drosophila Melanogaster. II. Distribution of Third Chromosome Bristle Effects within Chromosome Sections. Genetics. 1988 Mar;118(3):445–459. doi: 10.1093/genetics/118.3.445. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Spelman R. J., Coppieters W., Karim L., van Arendonk J. A., Bovenhuis H. Quantitative trait loci analysis for five milk production traits on chromosome six in the Dutch Holstein-Friesian population. Genetics. 1996 Dec;144(4):1799–1808. doi: 10.1093/genetics/144.4.1799. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Stricker C., Fernando R. L., Elston R. C. Linkage analysis with an alternative formulation for the mixed model of inheritance: the finite polygenic mixed model. Genetics. 1995 Dec;141(4):1651–1656. doi: 10.1093/genetics/141.4.1651. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Thomas D. C., Cortessis V. A Gibbs sampling approach to linkage analysis. Hum Hered. 1992;42(1):63–76. doi: 10.1159/000154046. [DOI] [PubMed] [Google Scholar]
  22. Uimari P., Hoeschele I. Mapping-linked quantitative trait loci using Bayesian analysis and Markov chain Monte Carlo algorithms. Genetics. 1997 Jun;146(2):735–743. doi: 10.1093/genetics/146.2.735. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Uimari P., Thaller G., Hoeschele I. The use of multiple markers in a Bayesian method for mapping quantitative trait loci. Genetics. 1996 Aug;143(4):1831–1842. doi: 10.1093/genetics/143.4.1831. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Van Arendonk J. A., Tier B., Kinghorn B. P. Use of multiple genetic markers in prediction of breeding values. Genetics. 1994 May;137(1):319–329. doi: 10.1093/genetics/137.1.319. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Visscher P. M., Thompson R., Haley C. S. Confidence intervals in QTL mapping by bootstrapping. Genetics. 1996 Jun;143(2):1013–1020. doi: 10.1093/genetics/143.2.1013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Weller J. I. Maximum likelihood techniques for the mapping and analysis of quantitative trait loci with the aid of genetic markers. Biometrics. 1986 Sep;42(3):627–640. [PubMed] [Google Scholar]
  27. Xu S., Atchley W. R. A random model approach to interval mapping of quantitative trait loci. Genetics. 1995 Nov;141(3):1189–1197. doi: 10.1093/genetics/141.3.1189. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Zeng Z. B. Precision mapping of quantitative trait loci. Genetics. 1994 Apr;136(4):1457–1468. doi: 10.1093/genetics/136.4.1457. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Zeng Z. B. Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci. Proc Natl Acad Sci U S A. 1993 Dec 1;90(23):10972–10976. doi: 10.1073/pnas.90.23.10972. [DOI] [PMC free article] [PubMed] [Google Scholar]

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