Research Article Open Access

QTL Mapping Using Multiple Markers Simultaneously

D. Kolbehdari1 and J.A.B. Robinson1
  • 1 Center for Genetic Improvement of Livestock, Department of Animal and Poultry Science, University of Guelph, Guelph, Ontario N1G 2W1, Canada

Abstract

Methods for detecting and locating a single QTL within a 10 cM region of DNA using 10 equally spaced SNP markers were compared. The QTL was assumed to be bi-allelic and located between markers 5 and 6. Monte Carlo simulation of a granddaughter design with 30 sires and 400 sons was used. Linear regression nested within sire using either two or four marker haplotypes at a time was used. In addition, the scoring of haplotype transmissions from sire to sons were varied in three ways. Another method assumed linkage disequilibrium and estimated haplotype interval effects for all intervals simultaneously. Other variables compared were the ratio of QTL variance to total genetic variance, the number of generations of historical recombination, and frequencies of marker alleles. Empirical power was dependent on the scoring method in the linear regression method. Four-marker haplotypes gave slightly higher empirical power than two-marker haplotypes. Reducing the proportion of QTL variance decreased empirical power. Empirical power was greater for 25 generations of historical recombination over 100 generations. Empirical power was lower when marker allele frequencies were 0.8 compared to 0.5. The linkage disequilibrium model gave results similar to those of the linear regression model.

American Journal of Agricultural and Biological Sciences
Volume 2 No. 3, 2007, 195-201

DOI: https://doi.org/10.3844/ajabssp.2007.195.201

Submitted On: 4 April 2007 Published On: 30 September 2007

How to Cite: Kolbehdari, D. & Robinson, J. (2007). QTL Mapping Using Multiple Markers Simultaneously. American Journal of Agricultural and Biological Sciences, 2(3), 195-201. https://doi.org/10.3844/ajabssp.2007.195.201

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Keywords

  • QTL mapping
  • linear regression
  • simultaneous haplotypes model