Issue |
Genet. Sel. Evol.
Volume 35, Number 4, July-August 2003
|
|
---|---|---|
Page(s) | 385 - 402 | |
DOI | https://doi.org/10.1051/gse:2003030 |
DOI: 10.1051/gse:2003030
Likelihood and Bayesian analyses reveal major genes affecting body composition, carcass, meat quality and the number of false teats in a Chinese European pig line
Marie-Pierre Sancheza, Jean-Pierre Bidanela, Siqing Zhanga, Jean Naveaub, Thierry Burlotb and Pascale Le Royaa Institut national de la recherche agronomique, Station de génétique quantitative et appliquée, 78352 Jouy-en-Josas Cedex, France
b PEN AR LAN, BP 3, 35380 Maxent, France
(Received 3 June 2002; accepted 26 December 2002)
Abstract
Segregation analyses were performed using both maximum likelihood
- via a Quasi Newton algorithm - (ML-QN) and Bayesian
- via Gibbs sampling - (Bayesian-GS) approaches in the
Chinese European Tiameslan pig line. Major genes were
searched for average ultrasonic backfat thickness (ABT), carcass fat
(X2 and X4) and lean (X5) depths, days from 20 to 100 kg (D20100),
Napole technological yield (NTY), number of false (FTN) and good (GTN)
teats, as well as total teat number (TTN). The discrete nature of FTN
was additionally considered using a threshold model under ML
methodology. The results obtained with both methods consistently
suggested the presence of major genes affecting ABT, X2, NTY, GTN and
FTN. Major genes were also suggested for X4 and X5 using ML-QN, but
not the Bayesian-GS, approach. The major gene affecting FTN was
confirmed using the threshold model. Genetic correlations as well as
gene effect and genotype frequency estimates suggested the presence of
four different major genes. The first gene would affect fatness traits
(ABT, X2 and X4), the second one a leanness trait (X5), the third one
NTY and the last one GTN and FTN. Genotype frequencies of breeding
animals and their evolution over time were consistent with the
selection performed in the Tiameslan line.
Key words: segregation analysis / likelihood / Bayesian / major gene / pig
Correspondence and reprints: Marie-Pierre Sanchez
e-mail: sanchez@dga2.jouy.inra.fr
© INRA, EDP Sciences 2003