Genet. Sel. Evol. 32 (2000) 357-381
Detection and parameter estimation for quantitative trait loci using
regression models and multiple markers
Yang Daa -
Paul M. VanRadenb -
Lawrence B. Schookc
aDepartment of Animal Science,
University of Minnesota, Saint Paul,
MN 55108, USA
bAnimal Improvement Programs Laboratory, ARS-USDA, Beltsville,
Maryland 20705, USA
cDepartment of Veterinary Pathobiology, University
of Minnesota, Saint Paul, MN 55108, USA
(Received 12 July 1999; accepted 12 April 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 1000 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 markers / regression analysis / quantitative trait loci / QTL detection / QTL parameters
Correspondence and reprints: Yang Da
e-mail: yda@tc.umn.edu
Copyright INRA, EDP Sciences