Using a random regression model to estimate additive and non-additive genetic variance components for body weight traits in Japanese quail.

Abstract

1. Estimating genetic parameters accurately is crucial in breeding programmes. Random regression models (RRM) are used to analyse longitudinal data or repeated records over time. The following study genetically evaluated body weight traits of quail using different regression models that considered dominance effects, as well as direct additive genetic effects, maternal effects and the bird's permanent environment.2. For this purpose, 30 363 body weight records from 3836 quails aged between 1 and 45 d were used with a 5‑d recording interval. After editing, the data were analysed using various random regression models (RRM), each varying in terms of the number of effects and the order of Legendre polynomials. The appropriate model was selected using the log-likelihood, Bayesian Information Criterion (BIC), Akaike Information Criterion (AIC), variance components and genetic parameters of body weight traits at different ages were estimated.3. The results of the model comparison showed that the model containing direct additive genetics (4th order), maternal genetics (3rd order), the bird's permanent environment (1st order) and dominance (1st order) was deemed suitable. Maternal permanent environment did not have a significant effect on body weight. The increasing trend of variance components was observed with bird age, although they were different in terms of relative increase.4. Heritability of body weight traits was estimated to range from 0.151 to 0.639. The ratio of maternal genetic, bird's permanent environment and dominance to the phenotypic variance of body weight traits was high in early ages, but decreased in later ages. Estimated correlations for ages older than 20 d were higher than those for younger birds.5. The results indicated that permanent environment, maternal genetics and dominance effects should be considered in the model to accurately estimate genetic parameters. Additionally, body weight at 20 d of age can serve as a selection criterion to enhance body weight at older ages, given its strong correlation with later body weight traits and high heritability.