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 | Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Leite. Para informações adicionais entre em contato com rosangela.lacerda@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
13/08/2021 |
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Data da última atualização: |
13/08/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SILVA, D. A.; LOPES, P. S.; COSTA, C. N.; SILVA, A. A.; SILVA, H. T.; SILVA, F. F.; VERONEZE, R.; THOMPSON, G.; CARVALHEIRA, J. |
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Afiliação: |
Universidade Federal de Viçosa; Universidade Federal de Viçosa; CLAUDIO NAPOLIS COSTA, CNPGL; Universidade Federal de Viçosa; Universidade Federal de Viçosa; Universidade Federal de Viçosa; Universidade Federal de Viçosa; Universidade do Porto; Universidade do Porto. |
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Título: |
Genotype by environment interaction for Holstein cattle populations using autoregressive and within- and across-country multi-trait reaction norms test-day models. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Animal, v. 15, 100084, 2021. |
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DOI: |
https://doi.org/10.1016/j.animal.2020.100084 |
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Idioma: |
Inglês |
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Conteúdo: |
The progenies of international bulls in diverse climatic conditions and management levels may lead to different expressions of their genetic potential resulting in a re-ranking of these bulls. Therefore, evaluate the presence of genotype by environment interaction (G×E)within and across countries is important to guide the decision-making on alternative selection strategies. Thus, a two-step reaction norm(RN) approachwas used to investigate the presence of G×E in Portuguese and Brazilian Holstein cattle. In step 1, we performed a within-country genetic evaluation using an autoregressive model to obtain precorrected phenotypes and environmental gradients (herd test-day solutions, HTD levels). In step 2, the precorrected phenotypes were considered as two distinct traits in a bi-trait RN model to estimate variance components across HTD levels, genetic correlation between HTD levels in Portugal and Brazil, and RN of the estimated breeding values. Additionally, the genetic correlation between countries using a bi-trait random regression (RR) sire model was obtained. In step 1, genetic additive variance formilk yield (MY) in Portugalwas 14.1% higher than in Brazil. For somatic cell score (SCS), the genetic additive variance in Portugalwas 12.7% lower than in Brazil. Although similar heritability estimates for SCS were observed in both countries, MY heritabilities were 0.31 for Portugal and 0.23 for Brazil. Genetic correlations (SD) between both countries obtained using RR siremodelwere 0.78 (0.051) forMY and 0.75 (0.062) for SCS. In step 2, MY genetic correlations among HTD levels within countrieswere higher than 0.94 for Portugal and 0.98 for Brazil. Somatic cell score genetic correlations among HTD levels ranged from 0.70 to 0.99 for Portugal and from 0.84 to 0.99 for Brazil. The average (SD) of genetic correlation estimates between Portuguese and Brazilian HTD levels were 0.74 (0.009) for MY and 0.57 (0.060) for SCS. These results suggest the presence of G×E for MY and SCS of Holstein cattle between both countries. Although there was no indication of G×E between Brazilian herd environments, the lowgenetic correlation for SCS indicates potential re-ranking of bulls between extreme environmental gradient in Portugal. Overall, the results of this study evidence the importance of national and international genetic evaluation systems to assist dairy farmers in the selection of the best genotypes to obtain the expected returns from investments in imported semen and to realize genetic progress in dairy populations under local environmental conditions. MenosThe progenies of international bulls in diverse climatic conditions and management levels may lead to different expressions of their genetic potential resulting in a re-ranking of these bulls. Therefore, evaluate the presence of genotype by environment interaction (G×E)within and across countries is important to guide the decision-making on alternative selection strategies. Thus, a two-step reaction norm(RN) approachwas used to investigate the presence of G×E in Portuguese and Brazilian Holstein cattle. In step 1, we performed a within-country genetic evaluation using an autoregressive model to obtain precorrected phenotypes and environmental gradients (herd test-day solutions, HTD levels). In step 2, the precorrected phenotypes were considered as two distinct traits in a bi-trait RN model to estimate variance components across HTD levels, genetic correlation between HTD levels in Portugal and Brazil, and RN of the estimated breeding values. Additionally, the genetic correlation between countries using a bi-trait random regression (RR) sire model was obtained. In step 1, genetic additive variance formilk yield (MY) in Portugalwas 14.1% higher than in Brazil. For somatic cell score (SCS), the genetic additive variance in Portugalwas 12.7% lower than in Brazil. Although similar heritability estimates for SCS were observed in both countries, MY heritabilities were 0.31 for Portugal and 0.23 for Brazil. Genetic correlations (SD) between both countries obtained using RR siremodel... Mostrar Tudo |
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Palavras-Chave: |
Environment gradient; Reaction norm model. |
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Thesagro: |
Bovino; Clima Temperado; Clima Tropical; Gado Leiteiro. |
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Thesaurus Nal: |
Dairy cattle. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 03546naa a2200313 a 4500
001 2133537
005 2021-08-13
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.animal.2020.100084$2DOI
100 1 $aSILVA, D. A.
245 $aGenotype by environment interaction for Holstein cattle populations using autoregressive and within- and across-country multi-trait reaction norms test-day models.$h[electronic resource]
260 $c2021
520 $aThe progenies of international bulls in diverse climatic conditions and management levels may lead to different expressions of their genetic potential resulting in a re-ranking of these bulls. Therefore, evaluate the presence of genotype by environment interaction (G×E)within and across countries is important to guide the decision-making on alternative selection strategies. Thus, a two-step reaction norm(RN) approachwas used to investigate the presence of G×E in Portuguese and Brazilian Holstein cattle. In step 1, we performed a within-country genetic evaluation using an autoregressive model to obtain precorrected phenotypes and environmental gradients (herd test-day solutions, HTD levels). In step 2, the precorrected phenotypes were considered as two distinct traits in a bi-trait RN model to estimate variance components across HTD levels, genetic correlation between HTD levels in Portugal and Brazil, and RN of the estimated breeding values. Additionally, the genetic correlation between countries using a bi-trait random regression (RR) sire model was obtained. In step 1, genetic additive variance formilk yield (MY) in Portugalwas 14.1% higher than in Brazil. For somatic cell score (SCS), the genetic additive variance in Portugalwas 12.7% lower than in Brazil. Although similar heritability estimates for SCS were observed in both countries, MY heritabilities were 0.31 for Portugal and 0.23 for Brazil. Genetic correlations (SD) between both countries obtained using RR siremodelwere 0.78 (0.051) forMY and 0.75 (0.062) for SCS. In step 2, MY genetic correlations among HTD levels within countrieswere higher than 0.94 for Portugal and 0.98 for Brazil. Somatic cell score genetic correlations among HTD levels ranged from 0.70 to 0.99 for Portugal and from 0.84 to 0.99 for Brazil. The average (SD) of genetic correlation estimates between Portuguese and Brazilian HTD levels were 0.74 (0.009) for MY and 0.57 (0.060) for SCS. These results suggest the presence of G×E for MY and SCS of Holstein cattle between both countries. Although there was no indication of G×E between Brazilian herd environments, the lowgenetic correlation for SCS indicates potential re-ranking of bulls between extreme environmental gradient in Portugal. Overall, the results of this study evidence the importance of national and international genetic evaluation systems to assist dairy farmers in the selection of the best genotypes to obtain the expected returns from investments in imported semen and to realize genetic progress in dairy populations under local environmental conditions.
650 $aDairy cattle
650 $aBovino
650 $aClima Temperado
650 $aClima Tropical
650 $aGado Leiteiro
653 $aEnvironment gradient
653 $aReaction norm model
700 1 $aLOPES, P. S.
700 1 $aCOSTA, C. N.
700 1 $aSILVA, A. A.
700 1 $aSILVA, H. T.
700 1 $aSILVA, F. F.
700 1 $aVERONEZE, R.
700 1 $aTHOMPSON, G.
700 1 $aCARVALHEIRA, J.
773 $tAnimal$gv. 15, 100084, 2021.
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