Méthodes statistiques pour la détection de QTL : nouveaux développements et applications chez le canard mulard

The mule duck, an interspecific hybrid obtained by crossing Common duck (Anas Platyrhynchos) females with Muscovy (Cairina moschata) drakes, is widely used for fatty liver production. The purpose of the present study is to detect and map single and pleitropic QTL segregating in the Common duck species, having an influence on the expression of traits in their overfed mule ducks offspring. To this end, a Common duck back-cross (BC) design was generated by crossing Kaiya duck and heavy Pekin duck experimental lines, which differ notably in the bodyweight and overfeeding ability of their mule progeny. The BC females were mated to Muscovy drakes and on average, 4 male mule ducks per BC female 1600 in total were hatched and measured for growth, metabolism during growth and overfeeding period, overfeeding ability and breast meat and fatty liver qualities. The phenotypic value of the BC females was estimated for each trait by assigning the mean value of its offspring’s phenotype, taking the variance, depending on the number of sons measured per BC and the heritability of the trait considered, into account. The genetic map used for QTL detection has 91 microsatellite markers aggregated into 16 linkage groups (LG), covering a total of 778 cM. Twenty-two QTL were found significant at the 1% chromosome-wise threshold level, using the single trait detection option of the QTLMap software. Most QTL were detected for breast meat and fatty liver qualities: QTL for meat pH 20 minutes post mortem were mapped on LG4 (at 1% genome-wide level) and QTL for meat lipid content and cooking losses were found both on LG2a. For the fatty liver weight and composition in protein and lipid, QTL were mainly detected on LG2c and LG9 and multiple traits analyses highlighted pleiotropic effects of QTL in these chromosome regions. Apart for the strong QTL on chromosome Z for plasma triglyceride content at the end of overfeeding period detected in single trait analysis, all metabolic traits QTL were revealed with the multi-traits approach: QTL on LG14 and LG21 affected the plasma cholesterol and triglyceride contents whereas QTL on LG2a seemed to impact glycaemia and the basal plasma corticosterone content. A higher density genetic map will be needed for fine mapping of the QTL.