Empirical Threshold Values for Quantitative Trait Mapping (original) (raw)

Abstract

The detection of genes that control quantitative characters is a problem of great interest to the genetic mapping community. Methods for locating these quantitative trait loci (QTL) relative to maps of genetic markers are now widely used. This paper addresses an issue common to all QTL mapping methods, that of determining an appropriate threshold value for declaring significant QTL effects. An empirical method is described, based on the concept of a permutation test, for estimating threshold values that are tailored to the experimental data at hand. The method is demonstrated using two real data sets derived from F(2) and recombinant inbred plant populations. An example using simulated data from a backcross design illustrates the effect of marker density on threshold values.

Full Text

The Full Text of this article is available as a PDF (1.6 MB).

Selected References

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

  1. 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]
  2. 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]
  3. 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]
  4. 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]
  5. Lander E. S., Green P. Construction of multilocus genetic linkage maps in humans. Proc Natl Acad Sci U S A. 1987 Apr;84(8):2363–2367. doi: 10.1073/pnas.84.8.2363. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Lincoln S. E., Lander E. S. Systematic detection of errors in genetic linkage data. Genomics. 1992 Nov;14(3):604–610. doi: 10.1016/s0888-7543(05)80158-2. [DOI] [PubMed] [Google Scholar]
  7. Paterson A. H., Lander E. S., Hewitt J. D., Peterson S., Lincoln S. E., Tanksley S. D. Resolution of quantitative traits into Mendelian factors by using a complete linkage map of restriction fragment length polymorphisms. Nature. 1988 Oct 20;335(6192):721–726. doi: 10.1038/335721a0. [DOI] [PubMed] [Google Scholar]
  8. 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]
  9. 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]
  10. 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]