Detection of QTL controlling metabolism, meat quality, and liver quality traits of the overfed interspecific hybrid mule duck

Kileh-Wais M., Elsen Jean-Michel, Vignal Alain, Feve K., Vignoles F., Fernandez Xavier, Manse Hélène, Davail S., André J.M., Bastianelli Denis, Bonnal Laurent, Filangri O., Baéza Elisabeth, Guéméné D., Genêt C., Bernadet Marie-Dominique, Dubos F., Marie-Etancelin Christelle. 2013. Detection of QTL controlling metabolism, meat quality, and liver quality traits of the overfed interspecific hybrid mule duck. Journal of Animal Science, 91 (2) : pp. 588-604.

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Abstract : The mule duck, an interspecifi c 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 was to detect and map single and pleiotropic QTL that segregate in the common duck species, and infl uence the expression of traits in their overfed mule duck offspring. To this end, we generated a common duck backcross (BC) population by crossing Kaiya and heavy Pekin experimental lines, which differ notably in regard to the BW and overfeeding ability of their mule progeny. The BC females were mated to Muscovy drakes and, on average, 4 male mule ducks hatched per BC female (1600 in total) and were measured for growth, metabolism during growth and the overfeeding period, overfeeding ability, and the quality of their breast meat and fatty liver. The phenotypic value of BC females was estimated for each trait by assigning to each female the mean value of the phenotypes of her offspring. Estimations allowed for variance, which depended on the number of male offspring per BC and the heritability of the trait considered. The genetic map used for QTL detection consisted of 91 microsatellite markers aggregated into 16 linkage groups (LG) covering a total of 778 cM. Twenty-two QTL were found to be signifi cant at the 1% chromosome-wide threshold level using the single-trait detection option of the QTLMap software. Most of the QTL detected were related to the quality of breast meat and fatty liver: QTL for meat pH 20 min post mortem were mapped to LG4 (at the 1% genome-wide signifi cance level), and QTL for meat lipid content and cooking losses were mapped to LG2a. The QTL related to fatty liver weight and liver protein and lipid content were for the most part detected on LG2c and LG9. Multitrait analysis highlighted the pleiotropic effects of QTL in these chromosome regions. Apart from the strong QTL for plasma triglyceride content at the end of the overfeeding period mapped to chromosome Z using single-trait analysis, all metabolic trait QTL were detected with the multitrait approach: the QTL mapped to LG14 and LG21 affected the plasma cholesterol and triglyceride contents, whereas the QTL mapped to LG2a seemed to impact glycemia and the basal plasma corticosterone content. A greater density genetic map will be needed to further fi ne map the QTL. (Résumé d'auteur)

Mots-clés Agrovoc : Canard de Barbarie, Anas, Hybride, Canard, Foie, Muscle, Qualité, Viande de canard, Abats, Métabolisme des lipides, Physiologie animale, Carte génétique, Amélioration des animaux, Génotype, Locus des caractères quantitatifs, Modèle mathématique

Mots-clés géographiques Agrovoc : France

Mots-clés complémentaires : QTL, Anas platyrhynchos

Classification Agris : L10 - Animal genetics and breeding
L52 - Animal physiology - Growth and development
Q04 - Food composition
U10 - Computer science, mathematics and statistics
U30 - Research methods

Champ stratégique Cirad : Axe 3 (2005-2013) - Alimentation accessible et de qualité

Auteurs et affiliations

  • Kileh-Wais M., INRA (FRA)
  • Elsen Jean-Michel, INRA (FRA)
  • Vignal Alain, INRA (FRA)
  • Feve K., INRA (FRA)
  • Vignoles F., INRA (FRA)
  • Fernandez Xavier, ENSAT (FRA)
  • Manse Hélène, ENSAT (FRA)
  • Davail S., UPPA (FRA)
  • André J.M., UPPA (FRA)
  • Bastianelli Denis, CIRAD-ES-UMR SELMET (FRA) ORCID: 0000-0002-6394-5920
  • Bonnal Laurent, CIRAD-ES-UMR SELMET (FRA) ORCID: 0000-0001-5038-7432
  • Filangri O., INRA (FRA)
  • Baéza Elisabeth, ITAVI (FRA)
  • Guéméné D., ITAVI (FRA)
  • Genêt C., INRA (FRA)
  • Bernadet Marie-Dominique, INRA (FRA)
  • Dubos F., INRA (FRA)
  • Marie-Etancelin Christelle, INRA (FRA)

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