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Genetics Selection Evolution

Open Access

Random regression models for detection of gene by environment interaction

  • Marie Lillehammer1Email author,
  • Jørgen Ødegård1 and
  • Theo H.E. Meuwissen1
Genetics Selection Evolution200739:105

Received: 25 January 2006

Accepted: 6 November 2006

Published: 17 February 2007


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.


gene by environment interactionQTL detectionrandom regressionreaction norms

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Authors’ Affiliations

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


© INRA, EDP Sciences 2007