Sh. Barjasteh - Department of Animal Science, Faculty of Agriculture, University of Zabol, Zabol, Islamic Republic of Iran.
Gh. R. Dashab - Department of Animal Science, Faculty of Agriculture, University of Zabol, Zabol, Islamic Republic of Iran.
M. Rokouei - Department of Animal Science, Faculty of Agriculture, University of Zabol, Zabol, Islamic Republic of Iran.
M. Shariati - Department of Animal Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Islamic Republic of Iran.
M. Vafaye Valleh - Department of Animal Science, Faculty of Agriculture, University of Zabol, Zabol, Islamic Republic of Iran.

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: (۱) A high relationship with validation population, (۲) Random, and (۳) High inbreeding rate, were evaluated for imputation of validation population with the densities of ۵ and ۵۰K to ۷۷۷K 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 ۰.۲۵ and ۰.۵. 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 (h۲= ۰.۲۵), the highest accuracy of breeding values prediction in the weighting mechanism was equal to (=۰.۲). Also, results showed that in the scenario of related reference population selection when ۵۰K panel was used for genotype imputation to ۷۷۷K 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 ۵K and ۵۰K SNPs after genotype imputation to ۷۷۷K.

Genomic selection, Genotype imputation, Marker density, Prediction accuracy.