پژوهشهای علوم دامی ایران (Oct 2021)
Estimation of genetic and phenotypic parameters of logistic growth curve and their inter-relationship in Zandi Sheep
Abstract
Introduction Growth, defined as changes of body weight over time, is an economically important trait in sheep that directly determines meat production.Increase in live weight or dimension against age has been described as growth. Changes in live weight or dimension for a period of time are explained by the growth curves. Animal breeders are interested in the genotypic and phenotypic relationships during all phases of growth. Knowledge of genotypic and phenotypic relationships among live weights, degree of maturity and growth rate during all phases of growth is necessary to formulate breeding programs to improve lifetime efficiency. Growth models are mathematical functions which are applied for describing the growth pattern. Understanding, estimating, and capturing the defining characteristics of growth processes are key components of developmental research. The aim of the present study was to estimate the genetic parameters for growth traits in Zandi sheep, by determining the most appropriate animal models to be fitted. In addition, genetic, phenotypic and environmental correlations between traits were estimated.Materials and Methods The data used in this study were obtained from the Animal Breeding Center of Iran. The data were screened several times to remove the defective and out of range records. Growth curve parameters used in study were asymptomatic mature weight (A), Growth rate (B) and maturity rate (K). The procedure of SAS software was used for studying of fix effects. Based on body weight at different ages and using different initial values, each of the growth curve parameters was estimated using SAS software version 9.1 and NLIN procedure. Estimation of (co)variance components of growth curve parameters was conducted using Bayesian approach implemented in MTGSAM and Wombat software. The number of Gibbs sampling rounds used was 200,000 rounds. Ten percent of these numbers (20,000 rounds) was burn-in. The convergence criterion for stopping repetitions in this analysis was also considered as 10 decimals (10-10). Sampling intervals of 200 and Gouss- Seidel 10000 repetitions were considered. In order to find the best model incorporating the constant and random effects affecting each of the parameters of the growth pattern, the following models, with and without regard to maternal effects including maternal additive genetic effects and permanent maternal environmental effects in the model (Meyer’s models) were tested.Results and Discussion Environmental factors such as year of birth and sex of lamb showed significant influence on growth curve parameters (A, B and k) in Zandi sheep. Estimates of direct heritability is based on best models using REML and Bayesian methods for A, B and K were 0.064 and 0.14, 0.17and 0.16, 0.16and 0.18 respectively. Maternal heritability was in range of 0.006 - 0.08 and Proportion of environmental variance to phenotypic variance in range of 0.03 - 0.05 parameters growth curve. Among the growth curve parameters, only A and k have biological interpretation and therefore, relationship between them may provide necessary conclusions. Estimates of direct genetic correlation between growth curve parameters were 0.323, -0.429 and 0.803 between A-B, A-K and B-K, respectively. The positive and high genetic correlation between A and B parameters is evident as expected for common genetic and physiological mechanisms controlling these traits. Positive genetic correlation between these traits suggests that selection in one parameter of the growth curve would also improve the other parameter. Residual correlations between growth curve parameters varied form −0.296 (between A-K) to 0.732 (between B-K). Phenotypic correlations between growth curve parameters varied form −0.184 (between A-K) to 0.743 (between B-K). The phenotypic and genetic antagonism between A and k indicates that rapid reduction in growth rate after inflexion point results in lower mature weights. This finding would be helpful for improving selection by identifying the animal who reaches inflexion point earlier and attend higher mature weights later. Conclusion Current genetic estimates for growth curve parameters in Zandi sheep could be applied in designing selection program in this breed. The low estimates of heritability for A, B and K parameters could be assigned to the high phenotypic variance arising from large environmental variation. This therefore implies that much of the improvement in these growth curve parameters could be obtained by improvement of environment rather than genetic selection. It is important to provide good environmental conditions along with optimal management strategies in the flock to achieve a desired shape of growth curve through changing the parameters of model.
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