Genotype-environment interaction effects on weight gain in cattle using reaction norms

Authors

DOI:

https://doi.org/10.33448/rsd-v10i13.21244

Keywords:

Bayesian analysis; Genetic parameters; Heterogeneity of variances; Performance.

Abstract

The existence of genotype-environment interaction (GEI) using reaction norm models and their impact on the genetic evaluation of Nellore sires for body weight at 120, 210, 365 and 450 days of age was verified. Three models were used: animal model (AM) that disregards GEI and the one-step reaction norm model with homogeneous and heterogeneous residual variance (1SRNMH_het). Bayes Inference via Gibbs Sampling was used to estimate the variance components. The AM model better fits to weights at 120 and 210 days of age, while 1SRNMH_het was more adequate for body weights at 365 and 450 days of age, suggesting the existence of GEI. The posterior means of direct heritability were 0.33±0.01 and 0.36±0.01 and maternal heritability of 0.21±0.01 and 0.19±0.01 for body weights at 120 and 210 days of age, respectively. For body weights at 365 and 450 days of age, posterior means of heritability varied along the environmental gradient, but the ranking of sires based on breeding values was not changed by different environmental gradients. All rank correlations were greater than 0.80, strongly suggesting a scale effect of GEI. Despite the evidence of GEI on post-weaning weight gain, it did not change the ranking of sires. Therefore, it did not have a relevant impact on the genetic evaluation of sires because they are robust to environmental changes.

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Published

12/10/2021

How to Cite

ZUBLER, R.; ARAÚJO, C. V. de; MENEZES, F. L. de .; MOTA, R. R.; ARAÚJO, S. I.; LÔBO, R. B. .; NAKABASHI, L. R. M. Genotype-environment interaction effects on weight gain in cattle using reaction norms . Research, Society and Development, [S. l.], v. 10, n. 13, p. e278101321244, 2021. DOI: 10.33448/rsd-v10i13.21244. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/21244. Acesso em: 19 apr. 2024.

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Section

Agrarian and Biological Sciences