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Complex Segregation Analysis of Total Milk Yield in Churra Dairy Ewes

  • Ilahi, Houcine ;
  • Othmane, M. Houcine
  • Received : 2010.08.07
  • Accepted : 2010.11.15
  • Published : 2011.03.01

Abstract

The mode of inheritance of total milk yield and its genetic parameters were investigated in Churra dairy sheep through segregation analyses using a Monte Carlo Markov Chains (MCMC) method. Data which consisted of 7,126 lactations belonging to 5,154 ewes were collected between 1999 and 2002 from 15 Spanish Churra dairy flocks. A postulated major gene was assumed to be additive and priors used for variance components were uniform. Based on 50 000 Gibbs samples from ten replicates chains of 100,000 cycles, the estimated marginal posterior means${\pm}$posterior standard deviations of variance components of milk yield were $23.17{\pm}18.42$, $65.20{\pm}25.05$, $120.40{\pm}42.12$ and $420.83{\pm}40.26$ for major gene variance ($\sigma_G^2$), polygenic variance ($\sigma_u^2$), permanent environmental variance ($\sigma_{pe}^2$) and error variance ($\sigma_e^2$), respectively. The results of this study showed the postulated major locus was not significant, and the 95% highest posterior density regions ($HPDs_{95%}$) of most major gene parameters included 0, and particularly for the major gene variance. The estimated transmission probabilities for the 95% highest posterior density regions ($HPDs_{95%}$) were overlapped. These results indicated that segregation of a major gene was unlikely and that the mode of inheritance of total milk yield in Churra dairy sheep is purely polygenic. Based on 50,000 Gibbs samples from ten replicates chains of 100,000 cycles, the estimated polygenic heritability and repeatability were $h^2=0.20{\pm}0.05$ and r=$0.34{\pm}0.06$, respectively.

Keywords

Segregation Analysis;Bayesian Method;Major Gene;Genetic Parameters;Milk Yield;Dairy Sheep

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