Abstract
ABSTRACT: The objective of this work was to verify the presence of genotype-environment interactions (GEI) on the weight adjusted to 365 days of age (W365) for Tabapua cattle in the Northeast of Brazil, using reaction norm (RN) models. The reaction norm model with homogeneous residual variance and 1-step provided the best fit to the data by the criteria information of deviance, deviance based on the conditional predictive ordinate and deviance based on the Bayes factors. Direct and maternal heritability estimates for the animal model were 0.17±0.04 and 0.07±0.03, respectively. The direct heritability for model reaction norm in the low and high management environment were 0.21±0.06 and 0,70±0.04, respectively. The correlations between the slope and intercept of the reaction norm were 0.68±0.10 and 0.96±0.06 for the direct and maternal effect, indicating that the animals with high genetic values respond positively to environment improvements, especially for the maternal effect. The Spearman correlations between the sire classifications ranged from 0.14 to 0.94 in the different environments and models. Genetic values of most animals were robust to environmental variation, however, considering the sires with the highest number of progeny, there is the presence of GEI.
Highlights
The genetic merit of an animal can be significantly influenced by changes in the breeding environment, and the progenies of a sire may not repeat the performance of their progenitors if they are raised in a different micro-regions or farms, denoting the need for care when buying sires or semen due to the presence of genotype-environment interactions (GEI). (NOBRE et al, 1987)
The results presented were the standard animal model (AM), the hierarchical reaction norm model homoscedastic 1-step (HRNMHO1S) and the hierarchical reaction norm model heteroscedastic 1step (HRNMHE1S)
Correa et al (2009), Cardoso et al (2011), Mattar et al (2011) and Cardoso Tempelman (2012) used reaction norm models for studies on postweaning weight gain of breeds Angus, Hereford, Canchim and Devon respectively, comparing the HRNM with the AM, and observed that the adjustment was higher for HRNMHO than for HRNMHE models
Summary
In Brazil, cattle production systems are very heterogeneous due to the large biomes diversity, which is a challenge to the effective definition of selection criteria to assist in the choice of suitable sires to each production system, especially when the genetic evaluation of the herd is carried nationally (NEPOMUCENO et al, 2013).The genetic merit of an animal can be significantly influenced by changes in the breeding environment, and the progenies of a sire may not repeat the performance of their progenitors if they are raised in a different micro-regions or farms, denoting the need for care when buying sires or semen due to the presence of genotype-environment interactions (GEI). (NOBRE et al, 1987).GEI exist when the relative merit of two or more genotypes is dependent on the environments in which they are compared (MASCIOLI et al, 2006).According to Streit et al (2012), if the GEI is disregarded, the predicted genetic values may be biased and the response to selection reduced.The use of a multi-character approach is a logical choice if the environment may be considered as a distinct variable, the use of reaction norms may be more suitable if the environment changes gradually and can be measured on a continuous scale. The genetic merit of an animal can be significantly influenced by changes in the breeding environment, and the progenies of a sire may not repeat the performance of their progenitors if they are raised in a different micro-regions or farms, denoting the need for care when buying sires or semen due to the presence of genotype-environment interactions (GEI). According to Streit et al (2012), if the GEI is disregarded, the predicted genetic values may be biased and the response to selection reduced. The use of a multi-character approach is a logical choice if the environment may be considered as a distinct variable, the use of reaction norms may be more suitable if the environment changes gradually and can be measured on a continuous scale. There are less parameters to be estimated and there is no need for grouping individuals into different classes (STREIT et al., 2012)
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