Genetic Parameters for Growth Traits of Santa Ines Sheep Using Gibbs Sampling

Abstract

-This study sought to estimate (co)variance and genetic parameters for birth weight (BWT) and weaning weight (WWT) in Santa Ines sheep. A total of 2,111 records were obtained from EMBRAPA/CPATC experimental herds, dating from the years 1998 to 2008. (Co)variance parameters were obtained through a twotrait analysis with the Gibbs sampling algorithm using the MTGSAM program. The mixed model included the environmental effects of sex, contemporary group and type of birth, in addition to residual, direct and maternal additive effects. Mean estimates of direct heritability for BWT and WWT were 0.25 and 0.09, respectively. Mean estimates of maternal heritability were 0.34 for BWT and 0.24 for WWT. The genetic correlation between BWT and WWT was 0.14. The results suggest that breeding Santa Ines sheep for meat production must take into consideration direct and maternal additive genetic effects.Keywords: Bayesian analysis. Maternal effect. Birth weight. Weaning weight. High-density intervals. PARÂMETROS GENÉTICOS DAS CARACTERÍSTICAS DE CRESCIMENTO DE OVINOS

Estimation of genetic parameters for weaning weight of Awassi lambs by using classical and Bayesian methods

“…This is an indication of antagonism between the additive genetic effect and the maternal effect. Barbosa et al [19] reported that the antagonist relationships between additive genetic effects and maternal genetic effects may be due to natural selection. Some researchers reported that, if maternal effects were not included in the model, they increased the estimations of additive genetic effects and, as a result, increased the value of heritability and decreased the efficiency of selection [9,[39][40][41].…”

“…In this study, the value of direct heritability of WW was 0.35, which is higher than the values of Aguirre et al [48] in the Santa Ines (0.20), Hammoud and Salem [49] in the Barki (0.012) and in Rahmani (0.139), Kumar et al [50] in Nellore (0.03), Mallick et al [51] in Bharat Merino lamb (0.16), Jawasreh et al [27] in Awassi (0.19), and Tariq et al [28] in Mengali sheep (0.125); it is similar to the results of Kariuki et al [52] in Dorper (0.28), Aksoy et al [29] in Karayaka (0.27), Hassen et al [30] in Awassi sheep in Ethiopia (0.33), Gamasaee et al [53] in Mehraban (0.30), El-Wakil and Gad [31] in Barki (0.30), and Hassen et al [30] in Nation (0.31); and it is lower than the values of El-Awady et al [54] in Rahmani (0.42) via Reml. In addition, the direct heritability of WW was estimated by Nassiri et al [55] in Zandi lambs (0.169), Barbosa et al [19] in Santa Ines (0.09), and Gowane et al [18] in Malpura (0.40) using Bayesian methodology.…”

“…At the same time, no negative variance can be estimated under the Bayesian approach [18]. In the genetic evaluation of animals, the use of the MCMC algorithm in Bayesian approach has been a good option and this approach has been reducing bias in the estimations even when the dataset is too small [19]. At the same time, the Bayesian approach is statistically more flexible for estimations of variance components than the REML procedure [15].…”

“…In the literature, there are many studies using the REML method to estimate genetic parameters of different breeds [27][28][29][30][31][32]. However, some researchers used different animal models under the Bayesian approach in small ruminant animals [18,19]. Therefore, in this study, we aimed to estimate genetic parameters of the weaning weight of Awassi lambs by using 6 different animal models with both the classical approach (REML algorithm) and Bayesian approach (MCMC algorithms).…”