P0638
Genome-Wide Interval Mapping using SNP Identifies New QTL for Growth, Body Composition and Meat Quality in an F2 Intercross Between Fat and Lean Chicken Lines

Date: Monday, January 14, 2013
Room: Grand Exhibit Hall
Olivier Demeure , INRA - Agrocampus Ouest, UMR1348 PEGASE, Rennes, France
Michel J. Duclos , INRA - UR83 Recherches Avicoles, Nouzilly, France
Nicola Bacciu , Italian Breeder Association, Rome, Italy
Guillaume Le Mignon , INRA - Agrocampus Ouest, UMR1348 PEGASE, Rennes, France
Olivier Filangi , INRA - Agrocampus Ouest, UMR1348 PEGASE, Rennes, France
Frédérique Pitel , INRA - UMR444 Génétique Cellulaire, Castanet-Tolosan, France
Anne Boland , Centre National de Génotypage, Evry, France
Sandrine Lagarrigue , Agrocampus Ouest - INRA, UMR1348 PEGASE, Rennes, France
Larry A. Cogburn , University of Delaware, Newark, DE
Jean Simon , INRA - UR83 Recherches Avicoles, Nouzilly, France
Pascale Le Roy , INRA - Agrocampus Ouest, UMR1348 PEGASE, Rennes, France
Cécile Berri , INRA - UR83 Recherches Avicoles, Nouzilly, France
Elisabeth Le Bihan-Duval , INRA - UR83 Recherches Avicoles, Nouzilly, France
Availability of the chicken genome brings new possibilities for improving selection. The identification of chromosomal regions (QTL) controlling the traits is a first step to marker assisted selection. This study aims at using a F2 design produced by crossing INRA lines divergently selected for abdominal fatness and a medium density genetic map (127 microsatellites and 1285 SNP) allowing the study of all the available chicken genome (28 first chromosomes and the Z chromosome), including genomic regions not covered in previous studies. QTL mapping was performed for growth and body composition at 9 weeks, meat quality and some physiological parameters; for a total of 26 traits. Two mapping strategies were applied using QTLMap: single-QTL or multi-QTL, the later testing if more than one QTL affecting the same trait could be carried by a same linkage group. These analyses allowed the identification of 93 QTLs, most of them never described in the literature. In details, 69 QTLs were identified by single-QTL analysis and 24 through multi-QTL, illustrating the efficiency of this strategy. An important criteria for a possible marker assisted selection is to identify markers as close as possible from the causal mutations ; using a genetic map with 1412 markers has permitted to identify QTLs with interval localizations reduced to 14cM in average compared to the 32cM observed when using only the 127 microsatellites.