Bayesian Genetic Estimation Towards Optimising Selection Strategy for Higher Egg Production in White Leghorn Chickens

Long-term directional selection in a population can severely reduce the additive genetic variability for the desired trait. Therefore, it is really important to assess the genetic parameters of a population at definite time intervals for designing effective breeding programmes. The present study was designed for the genetic evaluation of a White Leghorn strain (IWI) which has been intensely selected for higher egg numbers up to 64 weeks of age at ICAR-Directorate of Poultry Research, Hyderabad, Telangana, India. The genetic parameters were estimated for egg production up to 24 (EP24), 32 (EP32), 40 (EP40), 52 (EP52), 64 (EP64) and 72 (EP72) weeks of age along with other traits (egg weight, reproductive and body weight traits) utilising six models with different random effects in a Bayesian framework. The normalised mean value for the primary selection trait, EP64, was 218.16 ± 1.24 eggs while the total egg production up to 72 weeks was 242.85 ± 1.72. Comparative evaluation of different models based on Deviance Information Criterion (DIC) revealed that model 6 (including direct additive, maternal genetic and maternal permanent environment effects) was the most accurate for early production traits like EP24, whereas model 3 (including direct additive and maternal genetic effects) was the best-fitted for egg production traits like EP32 and EP40. The trait variance for late egg production traits like EP52, EP64 and EP72 was best defined by model 1, which only included the direct additive effect. Furthermore, it was found that the posterior mean additive heritability of egg production traits declined as the laying cycle progressed. Particularly, for later traits like egg production up to 52 (EP52), 64 (EP64) and 72 (EP72) weeks, the direct additive heritability estimate was very low (0.02 ± 0.009; 0.04 ± 0.01 and 0.02 ± 0.0009 respectively). Subsequently, posterior genetic correlations (r_G) were estimated between late egg production traits and the rest of the traits. It was found that there was a highly negative r_G between egg weight at 40 weeks (EW40), body weight at 52 weeks (BW52) and the later egg production traits (EP52, EP64 and EP72). Therefore, depending on the trait correlations, multivariate analysis was done for improving the accuracy of evaluations. Posterior estimates of direct additive heritability for EP52 increased to 0.08 ± 0.05 when analysed together with EW40 and BW52 traits in a multivariate model, whereas the corresponding estimate for EP64 increased to 0.11 ± 0.05 when analysed with EW40 and BW52. Based on these results, we can conclude that although the additive genetic variability for the selection trait is very low in the population, multitrait evaluations can be more effective for making selection decisions for higher egg production in White Leghorns.