Meat Quality

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Prairie Swine Centre is an affiliate of the University of Saskatchewan


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Author(s): H. D. Li, M. S. Lund, O. F. Christensen, V. R. Gregersen, P. Henckel, and C. Bendixen
Publication Date: August 5, 2011
Reference: J. Anim. Sci. 2010. 88:2904–2912

Summary:

A QTL study was performed in large half-sib families to characterize the genetic background of variation in pork quality traits as well as to examine the possibilities of including QTL in a marker-assisted selection scheme. The quality traits included ultimate pH in LM and the semimembranosus, drip loss, and the Minolta color measurements L*, a*, and b* representing meat lightness, redness, and yellowness, respectively. The families consist of 3,883 progenies of 12 Duroc boars that were evaluated to identify the QTL. The linkage map consists of 462 SNP markers on 18 porcine autosomes. Quantitative trait loci were mapped using a linear mixed model with fixed factors (sire, sex, herd, month, sow age) and random factors (polygenic effect, QTL effects, and litter). Chromosome-wide and genome-wide significance thresholds were determined by Peipho’s approach, and 95% Bayes credibility intervals were estimated from a posterior distribution of the QTL position. In total, 31 QTL for the 6 meat quality traits were found to be significant at the 5% chromosome- wide level, among which 11 QTL were significant at the 5% genome-wide level and 5 of these were significant at the 0.1% genome-wide level. Segregation of the identified QTL in different families was also investigated. Most of the identified QTL segregated in 1 or 2 families. For the QTL affecting ultimate pH in LM and semimembranosus and L* and b* value on SSC6, the positions of the QTL and the shapes of the likelihood curves were almost the same. In addition, a strong correlation of the estimated effects of these QTL was found between the 4 traits, indicating that the same genes control these traits. A similar pattern was seen on SSC15 for the QTL affecting ultimate pH in the 2 muscles and drip loss. The results from this study will be helpful for fine mapping and identifying genes affecting meat quality traits, and tightly linked markers may be incorporated into marker-assisted selection programs.

For more information the full article can be found at http://jas.fass.org/

 
 
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