Bayesian genetic analysis of milk yield in Tunisian Holstein dairy cattle population

Houcine Ilahi, Mohamed Ben Hammouda, Mohamed Houcine Othmane

Centre Régional des Recherches Agricoles de Sidi Bouzid, Sidi Bouzid, Tunisia.
Institution de Recherche et de l’Enseignement Supérieur Agricoles (IRESA), Ministère de l’Agriculture et de l’environnement, Tunis, Tunisia.
Université de Carthage, Institut Préparatoire aux Etudes d’Ingénieurs de Bizerte, Zarzouna, Tunisia.

DOI: 10.4236/ojgen.2012.22015                

Abstract

The genetic determinism of 305-d milk yield and its genetic parameters were investigated in Tunisian Holstein dairy cattle population through Bayesian segregation analyses using a Monte Carlo Markov Chains (MCMC) method. Data included 49,709 records of 305-d milk yield collected between 1996 and 2003 from 114 dairy herds. The postulated major gene was assumed to be additive biallelic locus with Mendelian transmission probabilities and priors used for variance components were uniform. Gibbs sampling was used to generate a chain of 500,000 samples, which were used to obtain posterior means of genetic parameters. Estimated marginal posterior means ± posterior standard deviations of variance components of milk yield were 402866.28 ± 23629.97, 271256.66 ± 34477.83, 68276.83 ± 233027.62 and 1098855.75 ± 10009.52 for polygenic variance (σ²_u), permanent environmental variance (σ²_ne), major gene variance (σ²_G) and error variance (σ²_e), respectively. The main finding of this paper showed the postulated major locus was not significant, since the 95% highest posterior density regions (HPDs_95%) of most major gene parameters included 0, and particularly for the major gene variance. Estimated transmission probabilities for the 95% highest posterior density regions (HPDs_95%) were overlapped. Genetic parameters of 305-d milk yield were very similar under both mixed inheritance and polygenic models. These results indicated that the genetic determinism of milk yield in Tunisian Holstein dairy cattle population is purely polygenic. Based on 50,000 Gibbs samples, heritability and repeatability estimates using polygenic model were h² = 0.22 ± 0.012 and r = 0.38 ± 0.006, respectively.

Keywords

Bayesian Analysis; Segregation; Major Gene; Genetic Parameters; Milk Yield; Holstein Dairy Cattle

Conflicts of Interest

The authors declare no conflicts of interest.

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