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Genetics, Vol. 178, 2265-2274, April 2008, Copyright © 2008
doi:10.1534/genetics.107.084871

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Genetic Expectations of Quantitative Trait Loci Main and Interaction Effects Obtained With the Triple Testcross Design and Their Relevance for the Analysis of Heterosis

A. E. Melchinger*,1, H. F. Utz* and C. C. Schön{dagger}

* Institute of Plant Breeding, Seed Science, and Population Genetics, University of Hohenheim, 70599 Stuttgart, Germany and {dagger} Plant Breeding, Center of Life and Food Sciences, Technical University of Munich, 85350 Freising, Germany

1 Corresponding author: Institute of Plant Breeding, Seed Science, and Population Genetics, University of Hohenheim, Fruwirthstrasse 21, 70599 Stuttgart, Germany.
E-mail: melchinger{at}uni-hohenheim.de

Interpretation of experimental results from quantitative trait loci (QTL) mapping studies on the predominant type of gene action can be severely affected by the choice of statistical model, experimental design, and provision of epistasis. In this study, we derive quantitative genetic expectations of (i) QTL effects obtained from one-dimensional genome scans with the triple testcross (TTC) design and (ii) pairwise interactions between marker loci using two-way analyses of variance (ANOVA) under the F2- and the F{infty}-metric model. The theoretical results show that genetic expectations of QTL effects estimated with the TTC design are complex, comprising both main and epistatic effects, and that genetic expectations of two-way marker interactions are not straightforward extensions of effects estimated in one-dimensional scans. We also demonstrate that the TTC design can partially overcome the limitations of the design III in separating QTL main effects and their epistatic interactions in the analysis of heterosis and that dominance x additive epistatic interactions of individual QTL with the genetic background can be estimated with a one-dimensional genome scan. Furthermore, we present genetic expectations of variance components for the analysis of TTC progeny tested in a split-plot design, assuming digenic epistasis and arbitrary linkage.






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