Genotype × environment interactions and genetic parameters for fecal egg count and production traits of Merino sheep1

Pollott, G. E.; Greeff, J. C.

doi:10.2527/2004.82102840x

Cited by 62 publications

(53 citation statements)

References 7 publications

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“…Strongly negative to positive correlations have been reported by Strandberg et al (2000 and for productive and reproductive traits of Dairy Nordic and Holstein cattle. The same was observed by Pollott and Greeff (2004) for fecal egg count and six productive traits in Merino sheep. According to Corrê a et al (2009), these correlation estimates indicate that the genetics necessary for production in adverse environments is not the same as that necessary for production in intermediate and favorable environments.…”

Section: Resultssupporting

confidence: 66%

Phenotypic plasticity of composite beef cattle performance using reaction norms model with unknown covariate

Júnior

Eler

Cardoso

et al. 2013

Animal

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The objective of the present study was to determine the presence of genotype by environment interaction (G 3 E) and to characterize the phenotypic plasticity of birth weight (BW), weaning weight (WW), postweaning weight gain (PWG) and yearling scrotal circumference (SC) in composite beef cattle using the reaction norms model with unknown covariate. The animals were born between 1995 and 2008 on 33 farms located throughout all Brazilian biomes between latitude 278 and 2318, longitude 2408 and 2638. The contemporary group was chosen as the environmental descriptor, that is, the environmental covariate of the reaction norms. In general, higher estimates of direct heritability were observed in extreme favorable environments. The mean of direct heritability across the environmental gradient ranged from 0.05 to 0.51, 0.09 to 0.43, 0.01 to 0.43 and from 0.12 to 0.26 for BW, WW, PWG and SC, respectively. The variation in direct heritability observed indicates a different response to selection according to the environment in which the animals of the population are evaluated. The correlation between the level and slope of the reaction norm for BW and PWG was high, indicating that animals with higher average breeding values responded better to improvement in environmental conditions, a fact characterizing a scale of G 3 E. Low correlation between the intercept and slope was obtained for WW and SC, implying re-ranking of animals in different environments. Genetic variation exists in the sensitivity of animals to the environment, a fact that permits the selection of more plastic or robust genotypes in the population studied. Thus, the G 3 E is an important factor that should be considered in the genetic evaluation of the present population of composite beef cattle.

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Section: Resultssupporting

confidence: 66%

Phenotypic plasticity of composite beef cattle performance using reaction norms model with unknown covariate

Júnior

Eler

Cardoso

et al. 2013

Animal

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“…As variâncias genéticas tiveram considerável efeito em escala, deixando explícita grande diferença de sensibilidade ambiental entre os indivíduos. Pollott & Greeff (2004), avaliando características de produção (peso corporal, peso de velo) e de resistência a parasitas (contagem de ovos nas fezes) em ovinos Merino Australiano por modelo polinomial de regressão aleatória, também demonstraram efeito de interação G*A. As herdabilidades variaram conforme o ambiente para as características de peso corporal e a contagem de ovos nas fezes, evidenciando claramente a interação G*A.…”

Section: Resultsunclassified

“…Os Os resultados deste estudo permitem concluir, de acordo com diversos autores (Kolmodin et al, 2002;Calus & Veerkamp, 2003;Calus et al, 2004;Pollott & Greeff, 2004;Cardoso et al, 2005a;Su et al, 2006), que há interação genótipo-ambiente na população Devon estudada essencialmente em virtude do efeito de escala, pois, quando consideradas as normas de reação, os valores genéticos apresentaram maior variação nos valores positivos do gradiente ambiental em comparação aos níveis ambientais mais baixos. Ou seja, à medida que o ambiente se torna mais favorável, aumenta a diferença entre os valores genéticos dos indivíduos, uma vez que esses indivíduos expressam melhor seu potencial.…”

Section: Resultsunclassified

Caracterização da interação genótipo-ambiente e comparação entre modelos para ajuste do ganho pós-demama de bovinos Devon via normas de reação

2009

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RESUMO -Os objetivos com este estudo foram verificar a presença de interação genótipo-ambiente e comparar modelos para o ajuste do ganho pós-desmama padronizado para 345 dias de bovinos da raça Devon, via normas de reação obtidas por regressão aleatória. Genotype by environment interaction characterization and model comparison for post weaning gain adjustment of Devon cattle via reaction normsABSTRACT -The objectives of this study were to verify the presence of the genotype by environment interaction and to compare different models to fit Devon cattle post weaning gain standardized to 345 days, via reaction norms obtained by random regression. Data from 14,973 calves collected by the beef cattle improvement program from 1980 to 2005 were used. The INTERGEN program was used for data analysis. First, a standard animal model (AM) was fitted to serve as comparison basis and to provide estimates of the environmental gradient, based on contemporary group (CG) deviations and, next, the reaction norms hierarchical models with homogeneous (RNHM) and heterogeneous (RNHMH) residual variances were run. In these last two models, fixed effects of age of dam and age of calf at yearling and random contemporary group and genetic effects (level and slope of animal's reaction norms) were included. For the RNHM estimates of residual variance, reaction norm level and slope additive genetic variances and their genetic correlation were, respectively, 272.02 ± 8.51; 340.38 ± 17.11; 0.119 ± 0.006 and 0.83 ± 0.01, while for the RNHHM were 401.96 ± 11.91; 177.86 ± 16.60; 0.076 ± 0.006 and 0.72 ± 0.02, respectively. The heritability asa well as the genetic variance increased on the environmental gradient, characterizing that there is genotype by environment interaction. Based on the Deviance Information Criterion, Bayes Factors and Pseudo Bayes Factors, the NRHM provided superior fit to the data, being the most appropriate model to consider the genotype by environmental interaction of this population.

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“…Such genotype by environment interactions (G × E) have been observed in sheep and other species (e.g. Maniatis and Pollott, 2002;Pollott and Greeff, 2004;Steinheim et al, 2008).…”

Section: Introductionmentioning

confidence: 71%

Heterogeneous variances and genetics by environment interactions in genetic evaluation of crossbred lambs

Márquez

Haresign

Davies

et al. 2015

Animal

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Accounting for environmental heteroscedasticity and genetics by environment interaction (G × E) in genetic evaluation is important because animals may not perform predictably across environments. The objectives of this study were to evaluate the presence and consequences of heteroscedasticity and G × E on genetic evaluation. The population considered was crossbred lambs sired by terminal sires and reared under commercial conditions in the UK. Data on 6325 lambs sired by Charollais, Suffolk and Texel rams were obtained. The experiment was conducted between 1999 and 2002 on three farms located in England, Scotland and Wales. There were 2322, 2137 and 1866 lambs in England, Scotland and Wales, respectively. A total of 89 sires were mated to 1984 ewes of two types (Welsh and Scottish Mules). Most rams were used for two breeding seasons with some rotated among farms to create genetic links. Lambs were reared on pasture and had their parentage, birth, 5 week, 10 week, and slaughter weights recorded. Lambs were slaughtered at a constant fatness, at which they were ultrasonically scanned for fat and muscle depth. Heteroscedasticity was evaluated in two ways. First, data were separated into three subsets by farm. Within-farm variance component estimates were then compared with those derived from the complete data (Model 1). Second, the combined data were fitted, but with a heterogeneous (by farm) environmental variance structure (Model 2). To investigate G × E, a model with a random farm by sire (F × S) interaction was used (Model 3). The ratio of the F × S variance to total variance was a measure of the level of G × E in the population. Heterogeneity in environmental variability across farm was identified for all traits ( P < 0.01). Rank correlations of sire estimated breeding value between farms differed for Model 1 for all traits. However, sires ranked similarly (rank correlation of 0.99) for weight traits with Model 2, but less so for ultrasonic measures. Including the F × S interaction (Model 3) improved model fit for all traits. However, the F × S term explained a small proportion of variation in weights (<2%) although more in ultrasonic traits (at least 10%). In conclusion, heteroscedasticity and G × E were not large for these data, and can be ignored in genetic evaluation of weight but, perhaps, not ultrasonic traits. Still, before incorporating heteroscedasticity and G × E into routine evaluations of even ultrasonic traits, their consequences on selection response in the breeding goal should be evaluated.

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Genotype × environment interactions and genetic parameters for fecal egg count and production traits of Merino sheep1

Cited by 62 publications

References 7 publications

Phenotypic plasticity of composite beef cattle performance using reaction norms model with unknown covariate

Phenotypic plasticity of composite beef cattle performance using reaction norms model with unknown covariate

Caracterização da interação genótipo-ambiente e comparação entre modelos para ajuste do ganho pós-demama de bovinos Devon via normas de reação

Heterogeneous variances and genetics by environment interactions in genetic evaluation of crossbred lambs

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