Genotype × environment interaction for age at first calving, scrotal circumference, and yearling weight in Nellore cattle using reaction norms in multitrait random regression models

Chiaia, Hermenegildo Lucas Justino; Lemos, M. V. F.; Venturini, G. C.; Aboujaoude, Carolyn; Berton, Mariana Piatto; Feitosa, F. B.; Carvalheiro, Roberto; Albuquerque, Lúcia Galvão de; Oliveira, Henrique Nunes de; Baldi, Fernando

doi:10.2527/jas.2014-8217

Cited by 32 publications

(37 citation statements)

References 27 publications

(5 reference statements)

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“…The genetic correlations have been used to assess the degree of animal sensitivity to environmental changes (Robertson, ). These estimates are in agreement with other results reported by Santana et al (, ) and Chiaia et al (), in which the magnitude of genetic correlation estimates decreased when differences between EC levels increased, indicating the occurrence of G×E interaction with re‐ranking of EBVs across EC levels.…”

Section: Resultssupporting

confidence: 93%

“…under less restrictive EC levels the genetic variance estimates increased. This tendency was previously described for SC (Santana et al ; Chiaia et al ) and HP (Santana et al ) in Nellore. The differences in heritability estimates at different EC levels occur as a consequence of the G×E interaction (Fordyce, ).…”

Section: Resultssupporting

confidence: 80%

“…These estimates using RNM_A and RNM_H were respectively 0.31 and 0.33 for SC and 0.29 and 0.32 for HP, whereas with BLUP and ssGBLUP the values were 0.31 and 0.34 for SC and 0.30 and 0.33 for HP (data not shown). The heritability estimates were lowest of those described in the literature for SC of 0.51-0.67 (Santana et al 2013;Chiaia et al 2015) and HP of 0.40-0.76 (Santana et al 2018) in Nellore cattle considering G9E interaction. These differences in heritability estimates are directly associated with population and the environmental conditions used to define the production level used in RNM.…”

Section: Genetic Parameterscontrasting

confidence: 73%

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Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle

et al. 2020

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Summary Brazilian beef cattle are raised predominantly on pasture in a wide range of environments. In this scenario, genotype by environment (G×E) interaction is an important source of phenotypic variation in the reproductive traits. Hence, the evaluation of G×E interactions for heifer’s early pregnancy (HP) and scrotal circumference (SC) traits in Nellore cattle, belonging to three breeding programs, was carried out to determine the animal’s sensitivity to the environmental conditions (EC). The dataset consisted of 85 874 records for HP and 151 553 records for SC, from which 1800 heifers and 3343 young bulls were genotyped with the BovineHD BeadChip. Genotypic information for 826 sires was also used in the analyses. EC levels were based on the contemporary group solutions for yearling body weight. Linear reaction norm models (RNM), using pedigree information (RNM_A) or pedigree and genomic information (RNM_H), were used to infer G×E interactions. Two validation schemes were used to assess the predictive ability, with the following training populations: (a) forward scheme—dataset was split based on year of birth from 2008 for HP and from 2011 for SC; and (b) environment‐specific scheme—low EC (−3.0 and −1.5) and high EC (1.5 and 3.0). The inclusion of the H matrix in RNM increased the genetic variance of the intercept and slope by 18.55 and 23.00% on average respectively, and provided genetic parameter estimates that were more accurate than those considering pedigree only. The same trend was observed for heritability estimates, which were 0.28–0.56 for SC and 0.26–0.49 for HP, using RNM_H, and 0.26–0.52 for SC and 0.22–0.45 for HP, using RNM_A. The lowest correlation observed between unfavorable (−3.0) and favorable (3.0) EC levels were 0.30 for HP and −0.12 for SC, indicating the presence of G×E interaction. The G×E interaction effect implied differences in animals’ genetic merit and re‐ranking of animals on different environmental conditions. SNP marker–environment interaction was detected for Nellore sexual precocity indicator traits with changes in effect and variance across EC levels. The RNM_H captured G×E interaction effects better than RNM_A and improved the predictive ability by around 14.04% for SC and 21.31% for HP. Using the forward scheme increased the overall predictive ability for SC (20.55%) and HP (11.06%) compared with the environment‐specific scheme. The results suggest that the inclusion of genomic information combined with the pedigree to assess the G×E interaction leads to more accurate variance components and genetic parameter estimates.

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Section: Resultssupporting

confidence: 93%

Section: Resultssupporting

confidence: 80%

Section: Genetic Parameterscontrasting

confidence: 73%

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Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle

et al. 2020

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“…However, some authors have reported the existence of G × E in herds evaluated within the same country and among countries (Cardoso et al, 2011;Ambrosini et al, 2014). A more robust way to study G × E is through random regression models with reaction norm (Cardoso and Tempelman, 2012;Chiaia et al, 2015). Reaction norm models relate, linearly, the genetic merit of animals to changes in the environment gradient (EG) (Silva et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…Studies that consider reaction norm models for beef cattle yearling weight (YW) evaluations have been conducted using pedigree and phenotypic information (Cardoso et al, 2011;Chiaia et al, 2015). The inclusion of molecular marker information can be beneficial for reaction norm models because the effect of each marker can be calculated in different environments, instead of assuming an average environment.…”

Section: Introductionmentioning

confidence: 99%

Reaction norm for yearling weight in beef cattle using single-step genomic evaluation1

Oliveira

Lourenço

Tsuruta

et al. 2018

Journal of Animal Science

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When the environment on which the animals are raised is very diverse, selecting the best sires for different environments may require the use of models that account for genotype by environment interaction (G × E). The main objective of this study was to evaluate the existence of G × E for yearling weight (YW) in Nellore cattle using reaction norm models with only pedigree and pedigree combined with genomic relationships. Additionally, genomic regions associated with each environment gradient were identified. A total of 67,996 YW records were used in reaction norm models to calculate EBV and genomic EBV. The method of choice for genomic evaluations was single-step genomic BLUP (ssGBLUP). Traditional and genomic models were tested on the ability to predict future animal performance. Genetic parameters for YW were obtained with the average information restricted maximum likelihood method, with and without adding genomic information for 5,091 animals. Additive genetic variances explained by windows of 200 adjacent SNP were used to identify genomic regions associated with the environmental gradient. Estimated variance components for the intercept and the slope in traditional and genomic models were similar. In both models, the observed changes in heritabilities and genetic correlations for YW across environments indicate the occurrence of genotype by environment interactions. Both traditional and genomic models were capable of identifying the genotype by environment interaction; however, the inclusion of genomic information in reaction norm models improved the ability to predict animals' future performance by 7.9% on average. The proportion of genetic variance explained by the top SNP window was 0.77% for the regression intercept (BTA5) and 0.82% for the slope (BTA14). Single-step GBLUP seems to be a suitable model to predict genetic values for YW in different production environments.

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Genotype × environment interactions in reproductive traits of Nellore cattle in northeastern Brazil

Ambrosini

Malhado

Filho

et al. 2016

Trop Anim Health Prod

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We evaluate genotype × environment (G × E) interactions for age at first calving (AFC) and calving interval (CI) of Nellore cattle in northeastern Brazil using four hierarchical reaction norm models (HRNMs). The best-fit model for the traits was the one step heteroscedastic hierarchical reaction norm model. Heritability was close to zero in the worst environments and increased as the environments improved (from 0.06 to 0.12 for AFC and from 0.01 to 0.03 for CI). The correlations between the intercept and the slope of the reaction norms for CI and AFC were from medium to high magnitude (0.75 ± 0.10 and 0.90 ± 0.04, respectively), indicating that animals with higher average breeding values had the greatest responses to the improvement of environmental conditions. The variation in heritability indicates different response to selection according to the environment in which the animals of the population are evaluated. The G × E was evident in bulls with more female offspring. In conclusion, our data demonstrate that selection for AFC in medium- and high-level environments leads to higher genetic gains.

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Genotype × environment interaction for age at first calving, scrotal circumference, and yearling weight in Nellore cattle using reaction norms in multitrait random regression models

Cited by 32 publications

References 27 publications

Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle

Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle

Reaction norm for yearling weight in beef cattle using single-step genomic evaluation1

Genotype × environment interactions in reproductive traits of Nellore cattle in northeastern Brazil

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