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. 2001 Jan;157(1):445–454. doi: 10.1093/genetics/157.1.445

Mapping epistatic quantitative trait loci with one-dimensional genome searches.

J L Jannink 1, R Jansen 1
PMCID: PMC1461463  PMID: 11139524

Abstract

The discovery of epistatically interacting QTL is hampered by the intractability and low power to detect QTL in multidimensional genome searches. We describe a new method that maps epistatic QTL by identifying loci of high QTL by genetic background interaction. This approach allows detection of QTL involved not only in pairwise but also higher-order interaction, and does so with one-dimensional genome searches. The approach requires large populations derived from multiple related inbred-line crosses as is more typically available for plants. Using maximum likelihood, the method contrasts models in which QTL allelic values are either nested within, or fixed over, populations. We apply the method to simulated doubled-haploid populations derived from a diallel among three inbred parents and illustrate the power of the method to detect QTL of different effect size and different levels of QTL by genetic background interaction. Further, we show how the method can be used in conjunction with standard two-locus QTL detection models that use two-dimensional genome searches and find that the method may double the power to detect first-order epistasis.

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Selected References

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  1. Allard R. W. The Wilhelmine E. Key 1987 invitational lecture. Genetic changes associated with the evolution of adaptedness in cultivated plants and their wild progenitors. J Hered. 1988 Jul-Aug;79(4):225–238. doi: 10.1093/oxfordjournals.jhered.a110503. [DOI] [PubMed] [Google Scholar]
  2. Alonso-Blanco C., El-Assal S. E., Coupland G., Koornneef M. Analysis of natural allelic variation at flowering time loci in the Landsberg erecta and Cape Verde Islands ecotypes of Arabidopsis thaliana. Genetics. 1998 Jun;149(2):749–764. doi: 10.1093/genetics/149.2.749. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Cheverud J. M., Routman E. J. Epistasis and its contribution to genetic variance components. Genetics. 1995 Mar;139(3):1455–1461. doi: 10.1093/genetics/139.3.1455. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Doebley J., Stec A., Gustus C. teosinte branched1 and the origin of maize: evidence for epistasis and the evolution of dominance. Genetics. 1995 Sep;141(1):333–346. doi: 10.1093/genetics/141.1.333. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Fijneman R. J., de Vries S. S., Jansen R. C., Demant P. Complex interactions of new quantitative trait loci, Sluc1, Sluc2, Sluc3, and Sluc4, that influence the susceptibility to lung cancer in the mouse. Nat Genet. 1996 Dec;14(4):465–467. doi: 10.1038/ng1296-465. [DOI] [PubMed] [Google Scholar]
  6. Haley C. S., Knott S. A. A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Heredity (Edinb) 1992 Oct;69(4):315–324. doi: 10.1038/hdy.1992.131. [DOI] [PubMed] [Google Scholar]
  7. Jansen R. C. Controlling the type I and type II errors in mapping quantitative trait loci. Genetics. 1994 Nov;138(3):871–881. doi: 10.1093/genetics/138.3.871. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. 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]
  9. Kao C. H., Zeng Z. B., Teasdale R. D. Multiple interval mapping for quantitative trait loci. Genetics. 1999 Jul;152(3):1203–1216. doi: 10.1093/genetics/152.3.1203. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Lander E. S., Botstein D. Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics. 1989 Jan;121(1):185–199. doi: 10.1093/genetics/121.1.185. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Lark K. G., Chase K., Adler F., Mansur L. M., Orf J. H. Interactions between quantitative trait loci in soybean in which trait variation at one locus is conditional upon a specific allele at another. Proc Natl Acad Sci U S A. 1995 May 9;92(10):4656–4660. doi: 10.1073/pnas.92.10.4656. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. McMullen M. D., Byrne P. F., Snook M. E., Wiseman B. R., Lee E. A., Widstrom N. W., Coe E. H. Quantitative trait loci and metabolic pathways. Proc Natl Acad Sci U S A. 1998 Mar 3;95(5):1996–2000. doi: 10.1073/pnas.95.5.1996. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Orr H. A. The population genetics of speciation: the evolution of hybrid incompatibilities. Genetics. 1995 Apr;139(4):1805–1813. doi: 10.1093/genetics/139.4.1805. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Stuber C. W., Lincoln S. E., Wolff D. W., Helentjaris T., Lander E. S. Identification of genetic factors contributing to heterosis in a hybrid from two elite maize inbred lines using molecular markers. Genetics. 1992 Nov;132(3):823–839. doi: 10.1093/genetics/132.3.823. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. 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]

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