Free Access
Genet. Sel. Evol.
Volume 37, Number 6, November-December 2005
Page(s) 601 - 614
Genet. Sel. Evol. 37 (2005) 601-614
DOI: 10.1051/gse:2005021

Power of QTL detection by either fixed or random models in half-sib designs

Davood Kolbehdaria, b, Gerald B. Jansenc, Lawrence R. Schaeffera and Brian O. Allend

a  Center for Genetic Improvement of Livestock, Department of Animal and Poultry Science, University of Guelph, Guelph, Ontario N1G 2W1, Canada
b  Department of Animal Science, Abureihan Higher Education Complex, University of Tehran, Iran
c  Dekoppel Consulting, Guelph, Ontario N1G 2Y8, Canada
d  Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario N1G 2W1, Canada

(Received 3 February 2005; accepted 16 August 2005)

Abstract - The aim of this study was to compare the variance component approach for QTL linkage mapping in half-sib designs to the simple regression method. Empirical power was determined by Monte Carlo simulation in granddaughter designs. The factors studied (base values in parentheses) included the number of sires (5) and sons per sire (80), ratio of QTL variance to total genetic variance ( $\lambda = 0.1$), marker spacing (10 cM), and QTL allele frequency (0.5). A single bi-allelic QTL and six equally spaced markers with six alleles each were simulated. Empirical power using the regression method was 0.80, 0.92 and 0.98 for 5, 10, and 20 sires, respectively, versus 0.88, 0.98 and 0.99 using the variance component method. Power was 0.74, 0.80, 0.93, and 0.95 using regression versus 0.77, 0.88, 0.94, and 0.97 using the variance component method for QTL variance ratios ($\lambda$) of 0.05, 0.1, 0.2, and 0.3, respectively. Power was 0.79, 0.85, 0.80 and 0.87 using regression versus 0.80, 0.86, 0.88, and 0.85 using the variance component method for QTL allele frequencies of 0.1, 0.3, 0.5, and 0.8, respectively. The log10 of type ${\rm I}$ error profiles were quite flat at close marker spacing (1 cM), confirming the inability to fine-map QTL by linkage analysis in half-sib designs. The variance component method showed slightly more potential than the regression method in QTL mapping.

Key words: quantitative trait loci / QTL detection / half-sib design / power

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© INRA, EDP Sciences 2005