Dealing with the genotype x environment interaction via a modelling approach: a comparison of QTLs of maize leaf length or width with QTLs of model parameters.

Quantitative genetics of adaptive traits is made difficult by the genotypexenvironment interaction. A classical assumption is that QTLs identified in both stressed and control conditions correspond to constitutive traits whereas those identified only in stressed treatments are stress-specific and correspond to adaptive traits. This hypothesis was tested by comparing, in the same set of experiments, two ways of analysing the genetic variability of the responses of maize leaf growth to water deficit. One QTL detection was based on raw phenotypic traits (length and width of leaf 6) of 100 recombinant inbred lines (RILs) in four experiments with either well-watered or stressing conditions in the field or in the greenhouse. Another detection followed a method proposed recently which consists of analysing intrinsic responses of the same RILs to environmental conditions, determined jointly over several experiments. QTLs of three responses were considered: (i) leaf elongation rate per unit thermal time in the absence of stress, (ii) its response to evaporative demand in well-watered plants, and (iii) its response to soil water status in the absence of evaporative demand. The QTL of leaf length differed between experiments, but colocalized in seven cases out of 13 with QTLs of the intrinsic leaf elongation rate, even in experiments with stressing conditions. No colocalization was found between QTLs of leaf length under water deficit and QTLs of responses to air or soil water status. By contrast, QTLs of leaf width colocalized in all experiments, regardless of environmental conditions. The classical method of identifying the QTL of constitutive versus adaptive traits therefore did not apply to the experiments presented here. It is suggested that identification of the QTL of parameters of response curves provides a promising alternative for dealing with the genetic variability of adaptive traits.