Elucidating genotype by environment interaction over the growth trajectory of Malpura sheep in the semi-arid region of India through Random regression model

Abstract

The Presence of genotype by environment (GxE) interaction over different ages across growth trajectory in different environments leads to alteration in sires ranking, it may cause problem in any breeding program by affecting efficiency of selection. The objective of the present study was to compare the random regression models (RRM) and conventional animal models and also to plot the trajectory of the growth curve using Legendre polynomial (LP) function of the RRM for better genetic evaluation for growth traits of the Malpura sheep. The data was collected from 8299 animals descended from 2529 dams and 525 sires for growth traits of Malpura sheep, selected over 45 years (1975–2019) maintained at the Animal Genetics and Breeding Division, ICAR-Central Sheep and Wool Research Institute (CSWRI), Avikanagar, Rajasthan, India. The Legendre polynomial based random regression models (LP-RRM) was more robust as compared to conventional animal model and it included direct genetic, direct maternal, maternal permanent environmental and animal permanent environmental effects as a random effects in different orders of fit. The estimates for the additive direct heritability (h2) using best LP-RRM (4444) were 0.176 ± 0.022, 0.367 ± 0.024, 0.314 ± 0.021, 0.323 ± 0.023 and 0.314 ± 0.023, respectively for live body weight at birth (BWT), three-month (WWT), six-month (6WT), nine-month (9WT) and twelve-month (12WT). The comparable trends of variances were found in LP-RRM with trends obtained from the inclusive univariate animal model that included the direct genetic, direct maternal and maternal permanent environmental components. The h2 estimates indicated the further scope of genetic improvement through selection. The maternal proportion of variance was accounting for 1–15 % variance across growth trajectory indicating the low influence of maternal effects that reduced significantly post-weaning. However, we observed that the animal permanent environment accounted for 42–58 % of variance across growth trajectory. The estimates of genetic correlation in LP-RRM were positive and higher (mostly >0.80) between most of the time points as compared to the estimates obtained from animal model, indicating less GxE when RRM is used. Currently selection of Malpura sheep is carried out at the age of six month for growth traits. The presence of genotype by environment (GxE) interaction resulted in to significant re-ranking of sires at 12WT on the basis of breeding values using animal model. However, more consistency in sires ranking were found in the reaction norms plotted for breeding values at 6WT and 12WT using LP-RRM. The RRM have property for accounting (GxE) interaction across growth trajectories more precisely. Therefore, it is recommended that the RRM approach should be used for genetic evaluation of Malpura sheep at 6-month age for unbiased, accurate, and consistent prediction of breeding values for growth traits.