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The objective of this study was to determine the inbreeding depression on growth traits in Moghani sheep. Pedigree information of 8836 animals collected during the years of 1987 to 2006 by Moghani Breed Center in Jafar Abad Moghan, were used for analysis. The base population year was 1988. Analysis of the records was performed by ASReml software. Inbreeding depression was estimated as the regression of performance on the individual inbreeding coefficients via fitting an animal model. The mean inbreeding for all animals, females and males, were 0.500, 0.515 and 0.484 %, respectively. Totally, 24.22 % of all the animals were inbred. The mean of inbreeding for inbreed animals was 2.062 %. The rate of increased inbreeding per year for all animals was 0.05%. The inbreeding depression for body weight traits at birth, 3, 6, 9 and 12 months of age was , respectively, -0.007, - 0.291, - 0.026, -0.018 and -0.041 kg, per 1% increase in individual coefficient.

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The objective of this study was to compare the accuracy of genomic breeding values prediction with different marker densities before and after the imputation in the simulated purebred and crossbred populations based on different scenarios of reference population and methods of marker effects estimation. The simulated populations included two purebred populations (lines A and B) and two crossbred populations (Cross and Backcross). Three different scenarios on selection of animals in the reference set including: (1) A high relationship with validation population, (2) Random, and (3) High inbreeding rate, were evaluated for imputation of validation population with the densities of 5 and 50K to 777K single marker polymorphism. Then, the accuracy of breeding values estimation in the validation population before and after the imputation was calculated by ABLUP, GBLUP, and SSGBLUP methods in two heritability levels of 0.25 and 0.5. The results showed that the highest accuracy of breeding values prediction in the purebred populations was obtained by GBLUP method and in the scenario of related reference population with validation set. However, in the crossbred population for the trait with low heritability (h²= 0.25), the highest accuracy of breeding values prediction in the weighting mechanism was equal to (=0.2). Also, results showed that in the scenario of related reference population selection when 50K panel was used for genotype imputation to 777K SNPs, the prediction accuracy of genomic breeding values increased. But, in most scenarios of random and inbred reference set selection, there was no significant difference in the accuracy of genomic breeding values prediction between 5K and 50K SNPs after genotype imputation to 777K.