Using random regression models to estimate genetic variation in growth pattern and its association with sexual maturity of Thai native chickens

Abstract

ABSTRACT 1. Genetic (co)variances and parameters between body weights (BW) across the growth trajectory were estimated using a univariate random regression (RR) animal model. The effect of growth rates (GH) on age at first egg (AFE) and egg weight at first egg (EWFE) were explored using a series of univariate and bivariate analyses. 2. Body weights were taken from Thai native chickens at hatch day to 168 days of age. The model included interactions between age with hatch nested within year and sex as fixed effects, and random effects of direct additive genetic, direct permanent environmental, maternal genetic and maternal permanent environmental effects. All random effects were fitted as regressions to animals’ age via quadratic Legendre polynomials and fitting six classes of residual variances was identified as an optimal variance structure to estimate parameters. 3. Genetic and phenotypic variances for BW increased with increasing age. Estimated heritabilities for direct additive (h2 a) and maternal genetic (h2 m) effects on BW traits ranged from 0.34 to 0.54, and 0.04 to 0.06, respectively. Estimated variance ratios for direct (c2 ape) and maternal permanent environmental (c2 mpe) effects ranged from 0.19 to 0.48 and 0.10 to 0.12, respectively. Estimated correlations between weights at different ages were high for all random effects. 4. Estimated h2 a for six GH traits ranged from 0.06 to 0.28, while for AFE and EWFE these were 0.24 and 0.16, respectively. Estimated h2 m and c2 mpe were low for GH. Estimated genetic correlations between GH and AFE ranged from −0.22 to 0.02 and, between GH and EWFE, ranged from −0.05 to 0.40. These estimates suggested that selecting high GH chickens at 28 days of age can be expected to reduce AFE and to increase EWFE.