Open Access

Detection and parameter estimation for quantitative trait loci using regression models and multiple markers

Genetics Selection Evolution200032:357

https://doi.org/10.1186/1297-9686-32-4-357

Received: 12 July 1999

Accepted: 12 April 2000

Published: 15 July 2000

Abstract

A strategy of multi-step minimal conditional regression analysis has been developed to determine the existence of statistical testing and parameter estimation for a quantitative trait locus (QTL) that are unaffected by linked QTLs. The estimation of marker-QTL recombination frequency needs to consider only three cases: 1) the chromosome has only one QTL, 2) one side of the target QTL has one or more QTLs, and 3) either side of the target QTL has one or more QTLs. Analytical formula was derived to estimate marker-QTL recombination frequency for each of the three cases. The formula involves two flanking markers for case 1), two flanking markers plus a conditional marker for case 2), and two flanking markers plus two conditional markers for case 3). Each QTL variance and effect, and the total QTL variance were also estimated using analytical formulae. Simulation data show that the formulae for estimating marker-QTL recombination frequency could be a useful statistical tool for fine QTL mapping. With 1 000 observations, a QTL could be mapped to a narrow chromosome region of 1.5 cM if no linked QTL is present, and to a 2.8 cM chromosome region if either side of the target QTL has at least one linked QTL.

Keywords

multiple markersregression analysisquantitative trait lociQTL detectionQTL parameters

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Authors’ Affiliations

(1)
Department of Animal Science, University of Minnesota
(2)
Animal Improvement Programs Laboratory, ARS-USDA
(3)
Department of Veterinary Pathobiology, University of Minnesota

Copyright

© INRA, EDP Sciences 2000

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