title: Transmission disequilibrium test for quantitative trait loci detection in livestock populations.
abstract: The performance of several transmission disequilibrium tests (TDT) for detection of quantitative trait loci (QTL) in data structures typical of outbred livestock populations were investigated. Factorial mating designs were simulated with 10 sires mated to either 50 or 200 dams, each family having five or eight full sibs. A single marker and QTL, both bi-allelic, were simulated using a disequilibrium coefficient based on complete initial disequilibrium and 50 generations of recombination [i.e. D = D(0)(1 - theta)50], where theta is the recombination fraction between marker and QTL. The QTL explained either 10% (small QTL) or 30% (large QTL) of the genetic variance for a trait with heritability of 0.3. Methods were: TDT for QTL (Q-TDT; both parents known), 1-TDT (only one parent known) and sibling-based TDT (S-TDT; neither parent known, but sibs available). All were found to be effective tests for association and linkage between the QTL and a tightly linked marker (theta < 0.02) in these designs. For a large QTL, theta = 0.01, and five full sibs per family, the empirical power for Q-TDT, 1-TDT and S-TDT was 0.966, 0.602 and 0.974, respectively, in a large population, versus 0.700, 0.414 and 0.654, respectively, in a small population. For a small QTL effect, theta = 0.01, large population the empirical power of these tests were 0.709, 0.287 and 0.634. The power of Q-TDT, 1-TDT and S-TDT was satisfactory for large populations, for QTL with large effects and for five full sibs per family. The 1-TDT based on a linear model was more powerful than the normal 1-TDT. The empirical power for Q-TDT and 1-TDT with a linear model was 0.978 and 0.995 respectively. TDT based on analogous linear models, incorporating the polygenic covariance structure, provided only small increases in power compared with the usual TDT for QTL.
authors.affiliation: Center for Genetic Improvement of Livestock, Department of Animal and Poultry Science, University of Guelph, Guelph, ON, Canada. dkolbehd@uoguelph.ca
authors.forename: D
authors.initials: D
authors.lastname: Kolbehdari
authors.forename: G B
authors.initials: GB
authors.lastname: Jansen
authors.forename: L R
authors.initials: LR
authors.lastname: Schaeffer
authors.forename: B O
authors.initials: BO
authors.lastname: Allen
mesh_terms: D000465:Algorithms; D000483:Alleles; D000818:Animals; D000829:Animals, Domestic / Q000235:genetics*; D001947:Breeding; D003198:Computer Simulation; D005260:Female; D005819:Genetic Markers / Q000235:genetics; D014644:Genetic Variation; D005838:Genotype; D016014:Linear Models; D008297:Male; D008957:Models, Genetic; D011156:Population Density; D040641:Quantitative Trait Loci / Q000235:genetics*
chemical_list: D005819:Genetic Markers