Hostname: page-component-7479d7b7d-767nl Total loading time: 0 Render date: 2024-07-15T18:55:47.898Z Has data issue: false hasContentIssue false

Evidence for a new major gene influencing meat quality in pigs

Published online by Cambridge University Press:  14 April 2009

Pascale Le Roy*
INRA–SAGA BP 27 Auzeville 31326 Castanet-Tolosan Cedex, France
J. Naveau
Pen ar Lan BP3 Maxent 35380 Plelan le Grand, France
J. M. Elsen
INRA–SAGA BP 27 Auzeville 31326 Castanet-Tolosan Cedex, France
P. Sellier
INRA-SGQA 78350 Jouy en Josas, France
* Corresponding author.


Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The present investigation primarily deals with the inheritance of a pigmeat quality trait, the Napole technological yield (RTN), a measure of cooked weight to fresh weight. This trait as well as lean percentage at 100 kg liveweight and fattening length from 20 to 100 kg liveweight were recorded on 3459 offspring from 67 sires and 433 dams, and 3052 offspring from 64 sires and 405 dams in Penshire (P66) and Pen Ar Lan (P77) composite lines respectively. The hypothesis of a major 2-allele locus contributing to RTN was tested by use of a segregation analysis method. Highly significant likelihood ratios (mixed vs. polygenic transmission models) lead us to conclude that a major gene RN exerting an unfavourable effect on RTN is segregating in both lines. Maximum likelihood estimates of the parameters under the hypothesis of mixed (monogenic + polygenic) inheritance show that the difference between the means of the 2 homozygotes amounts to about 3 phenotypic standard deviations of the trait, whereas the complete dominance of RN cannot be rejected. The frequency of RN is about 0·6 in both lines. These results are discussed in connection with the previously reported ‘Hampshire effect’ on pigmeat quality, as the Hampshire breed is a common component of the foundation stock of the 2 composite lines under study.

Research Article
Copyright © Cambridge University Press 1990


Charpentier, J., Monin, G. & Ollivier, L. (1971). Correlations between carcass characteristics and meat quality in Large White pigs. In Proceedings of 2nd International Symposium on Condition and Meat Quality of Pigs, pp. 255260, Pudoc, Wageningen.Google Scholar
Demenais, F., Lathrop, M. & Lalouel, J. M. (1986). Robustness and power of the unified model in the analysis of quantitative measurements. American Journal of Human Genetics 38, 228234.Google ScholarPubMed
Elston, R. C. & Stewart, J. (1971). A general model for the genetic analysis of pedigree data. Human Heredity 21, 523542.CrossRefGoogle ScholarPubMed
Le Roy, P. & Elsen, J. M. (1989). Comparison of four statistical methods for detection of a major gene in a progeny test design. Genetics, Selection, Evolution 21 (in the press).CrossRefGoogle Scholar
MacLachlan, G. J. & Basford, K. E. (1988). Mixture Models. Inference and Applications to Clustering. New York: Dekker.Google Scholar
MacLean, C. J., Morton, N. E. & Lew, R. (1975). Analysis of family resemblance. IV. Operational characteristics of segregation analysis. American Journal of Human Genetics 27, 365384.Google ScholarPubMed
MacLean, C. J., Morton, N. E., Elston, R. C. & Yee, S. (1976). Skewness in commingled distributions. Biometrics 32, 695699.CrossRefGoogle ScholarPubMed
Monin, G. & Sellier, P. (1985). Pork of low technological quality with a normal rate of muscle pH fall in the immediate post-mortem period: the case of the Hampshire breed. Meat Science 13, 4963.CrossRefGoogle ScholarPubMed
Monin, G., Mejenes-Quijano, A., Talmant, A. & Sellier, P. (1987). Influence of breed and muscle metabolic type on muscle glycolytic potential and meat pH in pigs. Meat Science 20, 149158.CrossRefGoogle ScholarPubMed
Naveau, J. (1986). Contribution à l'étude du déterminisme génétique de la qualité de viande porcine. Héritabilité du Rendement Technologique Napole. In 18es Journées de la Recherche Porcine en France, pp. 265276. Paris: Institut Technique du Porc.Google Scholar
Naveau, J. & Flého, J. Y. (1980). Héritabilité des performances contrôlées dans un élevage de porcs. Choix d'un critère pour la croissance. 31st EAAP Meeting, Commission on Pig Production, P5/6.2.Google Scholar
Naveau, J., Pommeret, P. & Lechaux, P. (1985). Proposition d'une méthode de mesure du rendement technologique: ‘la méthode NAPOLE’. Techni-porc 8(6), 713.Google Scholar
Sellier, P. (1987). Crossbreeding and meat quality in pigs. In Evaluation and Control of Meat Quality in Pigs (ed. Tarrant, P., Eikelenboom, G. and Monin, G.), pp. 329342. Dordrecht: Martinus Nijhoff Publishers.CrossRefGoogle Scholar
Sellier, P. (1988). Aspects génétiques des qualités technologiques et organoleptiques de la viande chez le porc. In 20es Journées de la Recherche Porcine en France, pp. 227242. Paris: Institut Technique du Porc.Google Scholar
Sellier, P., Mejenes-Quijano, A., Marinova, P., Talmant, A., Jacquet, B. & Monin, G. (1988). Meat quality as influenced by halothane sensitivity and ultimate pH in three porcine breeds. Livestock Production Science 18, 171186.CrossRefGoogle Scholar
Webb, A. J., Southwood, O. I., Simpson, S. P. & Carden, A. E. (1985). Genetics of porcine stress syndrome. In Stress Susceptibility and Meat Quality in Pigs (ed. Ludvigsen, J. B.), EAAP Publication no. 33, pp. 930.Google Scholar
Wolfe, J. H. (1971). A Monte Carlo study of the sampling distribution of the likelihood ratio for mixture of multinormal distributions. Technical Bulletin, STB 72–2, Naval Personnel and Training Research Laboratory, San Diego.Google Scholar