Abstract

• Dominance and epistasis effects are important for the average daily gain traits and could be added to evaluation models. • Adding the non-additive genetic effects to models led to increase the accuracy of estimated breeding values. • The adgbww3 and adgbww6 traits can be the basis of selection for the next generation. Considering the dominance and epistasis effects in the analysis can increase the accuracy of estimating breeding values. The objective of this study was to fit the best model for each average daily gain trait (average daily gain from birth to weaning (adgbwww), from birth to 3 months (adgbww3), from birth to 6 months (adgbww6), from weaning to 3 months (adgwww3), from 3 to 6 months (adgw3w6), from 6 to 9 months (adgw6w9), and from 9 to 12 months (adgw9w12)) and the estimation of the genetic parameters and variance components, especially non-additive genetic effects, in Adani goats. Analyses were carried out using the Bayesian method via the Gibbs sampler animal model by fitting 18 different models. With the best model, direct heritability estimates were 0.093, 0.250, 0.256, 0.084, 0.036, 0.048, and 0.151 for adgbwww, adgbww3, adgbww6, adgwww3, adgw3w6, adgw6w9 and adgw9w12 traits, respectively. Maternal genetic and maternal permanent environmental effects were significant only for adgbwww trait. Dominance and epistasis effects were significant almost for all traits and as a proportion of phenotypic variance was the range from 0.068 to 0.221 and 0.106 to 0.237, respectively. Adding dominance and epistasis effects to models reduced the error variance and the accuracy of estimating breeding values was increased. The accuracy of breeding values of these traits with the best models ranged from 0.456 to 0.674, 0.493 to 0.656, and 0.424 to 0.674 for all animals, 10 % of best males and 50 % of the best females, respectively. The result of the present study suggests that dominance and epistasis effect was important for average daily gain traits of Adani goats and should be included in evaluation models.

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