Genet. Sel. Evol. 39 (2007) 105-121
DOI: 10.1051/gse:2006037

Random regression models for detection of gene by environment interaction

Marie Lillehammer, Jørgen Ødegård and Theo H.E. Meuwissen

Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, 1432 Ås, Norway

(Received 25 January 2006; accepted 6 November 2006; published online 17 February 2007)

Abstract - Two random regression models, where the effect of a putative QTL was regressed on an environmental gradient, are described. The first model estimates the correlation between intercept and slope of the random regression, while the other model restricts this correlation to 1 or -1, which is expected under a bi-allelic QTL model. The random regression models were compared to a model assuming no gene by environment interactions. The comparison was done with regards to the models ability to detect QTL, to position them accurately and to detect possible QTL by environment interactions. A simulation study based on a granddaughter design was conducted, and QTL were assumed, either by assigning an effect independent of the environment or as a linear function of a simulated environmental gradient. It was concluded that the random regression models were suitable for detection of QTL effects, in the presence and absence of interactions with environmental gradients. Fixing the correlation between intercept and slope of the random regression had a positive effect on power when the QTL effects re-ranked between environments.

Key words: gene by environment interaction / QTL detection / random regression / reaction norms

Correspondence and reprints: marie.lillehammer@umb.no

© INRA, EDP Sciences 2007