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Open Access Research article

Identification of QTL controlling meat quality traits in an F2 cross between two chicken lines selected for either low or high growth rate

Javad Nadaf1, Hélène Gilbert2, Frédérique Pitel3, Cécile M Berri1, Katia Feve3, Catherine Beaumont1, Michel J Duclos1, Alain Vignal3, Tom E Porter4, Jean Simon1, Samuel E Aggrey5, Larry A Cogburn6 and Elisabeth Le Bihan-Duval1*

Author Affiliations

1 Station de Recherches Avicoles, INRA, Centre de Recherches de Tours, 37380 Nouzilly, France

2 Station de Génétique Quantitative et Appliquée, INRA, Centre de Recherches de Jouy-en-Josas, 78352 Jouy-en-Josas, France

3 Laboratoire de Génétique Cellulaire, INRA, Centre de Recherches de Toulouse, 31326 Castanet-Tolosan, France

4 University of Maryland, Department of Animal & Avian Sciences, College Park, MD 20742, USA

5 University of Georgia, Department of Poultry Science, Athens, GA 30602, USA

6 University of Delaware, Department of Animal & Food Sciences, Newark, DE 19717, USA

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BMC Genomics 2007, 8:155  doi:10.1186/1471-2164-8-155

Published: 8 June 2007

Abstract

Background

Meat technological traits (i.e. meat pH, water retention and color) are important considerations for improving further processing of chicken meat. These quality traits were originally characterized in experimental lines selected for high (HG) and low (LG) growth. Presently, quantitative trait loci (QTL) for these traits were analyzed in an F2 population issued from the HG × LG cross. A total of 698 animals in 50 full-sib families were genotyped for 108 microsatellite markers covering 21 linkage groups.

Results

The HG and LG birds exhibit large differences in body weight and abdominal fat content. Several meat quality traits [pH at 15 min post-slaughter (pH15) and ultimate pH (pHu), breast color-redness (BCo-R) and breast color-yellowness (BCo-Y)] were lower in HG chickens. In contrast, meat color-lightness (BCo-L) was higher in HG chickens, whereas meat drip loss (DL) was similar in both lines. HG birds were more active on the shackle line. Association analyses were performed using maximum-likelihood interval mapping in QTLMAP. Five genome-wide significant QTLs were revealed: two for pH15 on GGA1 and GGA2, one for DL on GGA1, one for BCo-R and one for BCo-Y both on GGA11. In addition, four suggestive QTLs were identified by QTLMAP for BCo-Y, pHu, pH15 and DL on GGA1, GGA4, GGA12 and GGA14, respectively. The QTL effects, averaged on heterozygous families, ranged from 12 to 31% of the phenotypic variance. Further analyses with QTLExpress confirmed the two genome-wide QTLs for meat color on GGA11, failed to identify the genome-wide QTL for pH15 on GGA2, and revealed only suggestive QTLs for pH15 and DL on GGA1. However, QTLExpress qualified the QTL for pHu on GGA4 as genome-wide.

Conclusion

The present study identified genome-wide significant QTLs for all meat technological traits presently assessed in these chickens, except for meat lightness. This study highlights the effects of divergent selection for growth rate on some behavioral traits, muscle biochemistry and ultimately meat quality traits. Several QTL regions were identified that are worthy of further characterization. Some QTLs may in fact co-localize, suggesting pleiotropic effects for some chromosomal regions.