Genetic evaluation of growth in Barki sheep using random regression models

The objective of the current study was to estimate covariance components of growth at different ages from birth to yearling in Barki lambs. A total of 16,496 records for body weights at birth (W0), 3 (W3), 6 (W6), 9 (W9), and 12 (12) months of age for Barki lambs were available. Two statistical approaches were used; multi-trait (MT) and random regression (RR) animal models assuming two random effects only, additive genetic effect (sigma(2)(a)) and permanent environmental effect (sigma(2)(pe)) of the animal. Regarding the RR model, Legendre polynomials (LP) of different orders for the random parts were compared in order to evaluate the most appropriate model. Bayesian information and Akaike information criteria suggested that the optimal RR model included the third order for fixed effect of lamb age and sigma(2)(pe), and fourth order of LP for sigma(2)(a) (LP343). Estimates of direct heritability (h(a)(2)) from LP343 showed an ascending pattern, as it was 0.06 +/- 0.03 for birth weight and reached to the peak at 9 months (0.42 +/- 0.02). Thereafter, it declined again at the end of trajectory (12 months of age; 0.27 +/- 0.03). The MT model showed a fluctuated pattern and lower estimates of h(a)(2) (0.19 +/- 0.03, 0.11 +/- 0.02, 0.12 +/- 0.02, 0.11 +/- 0.03, and 0.16 +/- 0.04 for W0, W3, W6, W9, and W12, respectively). Considerably, similar ascending patterns of the ratio of sigma(2)(pe) to phenotypic variance were reported from both RR (from 3 to 50%) and MT models (from 5 to 20%). Of interest, the RR model showed higher predicting ability of the breeding values compared with the MT model, which is an indicator for the suitability of RR models for analyzing the consecutive growth traits in sheep. Results suggested that the Barki sheep has a potential for genetic selection based on weight at different ages with selection likely to be more efficient at 9 months of age.