Skip to main content
NCBI home page
Genetics logoLink to Genetics
. 2000 Dec;156(4):2081–2092. doi: 10.1093/genetics/156.4.2081

Mapping quantitative trait loci in complex pedigrees: a two-step variance component approach.

A W George 1, P M Visscher 1, C S Haley 1
PMCID: PMC1461399  PMID: 11102397

Abstract

There is a growing need for the development of statistical techniques capable of mapping quantitative trait loci (QTL) in general outbred animal populations. Presently used variance component methods, which correctly account for the complex relationships that may exist between individuals, are challenged by the difficulties incurred through unknown marker genotypes, inbred individuals, partially or unknown marker phases, and multigenerational data. In this article, a two-step variance component approach that enables practitioners to routinely map QTL in populations with the aforementioned difficulties is explored. The performance of the QTL mapping methodology is assessed via its application to simulated data. The capacity of the technique to accurately estimate parameters is examined for a range of scenarios.

Full Text

The Full Text of this article is available as a PDF (317.9 KB).

Selected References

These references are in PubMed. This may not be the complete list of references from this article.

  1. Almasy L., Blangero J. Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet. 1998 May;62(5):1198–1211. doi: 10.1086/301844. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Amos C. I. Robust variance-components approach for assessing genetic linkage in pedigrees. Am J Hum Genet. 1994 Mar;54(3):535–543. [PMC free article] [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. Elston R. C., Stewart J. A general model for the genetic analysis of pedigree data. Hum Hered. 1971;21(6):523–542. doi: 10.1159/000152448. [DOI] [PubMed] [Google Scholar]
  5. Fulker D. W., Cherny S. S., Cardon L. R. Multipoint interval mapping of quantitative trait loci, using sib pairs. Am J Hum Genet. 1995 May;56(5):1224–1233. [PMC free article] [PubMed] [Google Scholar]
  6. George A. W., Mengersen K. L., Davis G. P. Localization of a quantitative trait locus via a Bayesian approach. Biometrics. 2000 Mar;56(1):40–51. doi: 10.1111/j.0006-341x.2000.00040.x. [DOI] [PubMed] [Google Scholar]
  7. Heath S. C. Markov chain Monte Carlo segregation and linkage analysis for oligogenic models. Am J Hum Genet. 1997 Sep;61(3):748–760. doi: 10.1086/515506. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Hoeschele I., Uimari P., Grignola F. E., Zhang Q., Gage K. M. Advances in statistical methods to map quantitative trait loci in outbred populations. Genetics. 1997 Nov;147(3):1445–1457. doi: 10.1093/genetics/147.3.1445. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Jansen R. C., Johnson D. L., Van Arendonk J. A. A mixture model approach to the mapping of quantitative trait loci in complex populations with an application to multiple cattle families. Genetics. 1998 Jan;148(1):391–399. doi: 10.1093/genetics/148.1.391. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Jayakar S. D. On the detection and estimation of linkage between a locus influencing a quantitative character and a marker locus. Biometrics. 1970 Sep;26(3):451–464. [PubMed] [Google Scholar]
  11. Lander E., Kruglyak L. Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results. Nat Genet. 1995 Nov;11(3):241–247. doi: 10.1038/ng1195-241. [DOI] [PubMed] [Google Scholar]
  12. 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]
  13. 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]
  14. Stram D. O., Lee J. W. Variance components testing in the longitudinal mixed effects model. Biometrics. 1994 Dec;50(4):1171–1177. [PubMed] [Google Scholar]
  15. 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]
  16. 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]
  17. Visscher P. M., Haley C. S., Heath S. C., Muir W. J., Blackwood D. H. Detecting QTLs for uni- and bipolar disorder using a variance component method. Psychiatr Genet. 1999 Jun;9(2):75–84. doi: 10.1097/00041444-199906000-00005. [DOI] [PubMed] [Google Scholar]
  18. Xie C., Gessler D. D., Xu S. Combining different line crosses for mapping quantitative trait loci using the identical by descent-based variance component method. Genetics. 1998 Jun;149(2):1139–1146. doi: 10.1093/genetics/149.2.1139. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. 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]

Articles from Genetics are provided here courtesy of Oxford University Press

RESOURCES