Search

Porcine chromosome 4 harbours many quantitative trait loci (QTL) affecting meat quality, fatness and carcass composition traits, detected in resource pig populations previously. However, prior to selection in commercial breeds, QTL identified in an intercross between divergent breeds require confirmation, so that they can be segregated. Consequently, the objective of this study was to validate several QTL on porcine chromosome 4 responsible for meat and carcass quality traits. The experimental population consisted of 14 crossbred paternal half-sib families. The region of investigation was the q arm of SSC4 flanked by the markers S0073 and S0813. Regression analysis resulted in the validation of three QTL within the interval: Minolta a* loin, back fat thickness and the weight of trimmed ham. The results were additionally confirmed by factor analysis. Candidate genes were proposed for meat colour, which was the most evident QTL validated in this study. [ABSTRACT FROM AUTHOR]

In a previous study, QTL for carcass composition and meat quality were identified in a commercial finisher cross. The main objective of the current study was to confirm and fine map the QTL on SSC4 and SSC11 by genotyping an increased number of individuals and markers and to analyze the data using a combined linkage and linkage disequilibrium analysis method. A modified version of the method excludes linkage disequilibrium information from the analysis, enabling the comparison of results based on linkage information only or results based on combined linkage and linkage disequilibrium information. Nine additional paternal half-sib families were genotyped for 18 markers, resulting in a total of 1,855 animals genotyped for 15 and 13 markers on SSC4 and SSC11, respectively. The QTL affecting meat color on SSC4 was confirmed, whereas the QTL affecting LM weight could not be confirmed. The combined linkage and linkage disequilibrium analysis resulted in the identification of new significant effects for 14 traits on the 2 chromosomes. Heritabilities of the QTL effects ranged from 1.8 to 13.2%. The analysis contributed to a more accurate positioning of QTL and further characterized their phenotypic effect. However, results showed that even greater marker densities are required to take full advantage of linkage disequilibrium information and to identify haplotypes associated with favorable QTL alleles. [ABSTRACT FROM AUTHOR]