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| Registros recuperados : 20 | |
| 1. |  | ATAIDES, K. da S.; SHIOTSUKI, L.; GARCIA, B. F.; SILVA, D. A.; VARGAS, G.; CARVALHEIRO, R. Impacto do efeito de ambiente comum em características morfométricas de tambaqui (Colossoma macropomum) avaliadas aos 6 e 12 meses de idade. In: SIMPÓSIO BRASILEIRO DE MELHORAMENTO ANIMAL, 14., 2021, Santa Catarina. Passado, presente e futuro: anais. Santa Catarina: Sociedade Brasileira de Melhoramento Animal, 2021.| Biblioteca(s): Embrapa Pesca e Aquicultura. |
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| 2. | | GARCIA, J. F.; CARMO, A. S. DO; UTSUNOMIYA, Y. T.; NEVES, H. H. DE R.; CARVALHEIRO, R.; TASSELL, C. V.; SONSTEGARD, T. S.; SILVA, M. V. G. B. How bioinformatics enables livestock applied sciences in the genomic era. In: BRAZILIAN SYMPOSIUM ON BIOINFORMATICS, 2012, Heidelberg. Proceedings... Porto Alegre: Sociedade Brasileira e Computação, 2012.| Biblioteca(s): Embrapa Gado de Leite. |
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| 3. | | BOISON, S. A.; NEVES, H. H. R.; O'BRIEN, A. M. P.; UTSUNOMIYA, Y. T.; CARVALHEIRO, R.; SILVA, M. V. G. B.; SÖLKNER, J.; GARCIA, J. F. Imputation of non-genotyped individuals using genotyped progeny in Nellore, a Bos indicus cattle breed. Livestock Science, v. 166, p. 176-189, 2014.| Biblioteca(s): Embrapa Gado de Leite. |
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| 4. | | CHUD, T. C. S.; VENTURA, R. V.; SCHENKEL. F. S.; URBINATI, I.; CARVALHEIRO, R.; REGITANO, L. C. de A.; MARCONDES, C. R.; MINARI, D. P. Accuracy of genotype imputation in Canchim cattle using FImpute and Beagle software., In: INTERNATIONAL SYMPOSIUM ON ANIMAL FUNCTIONAL GENOMICS, 5., 2013, Guarujá. Abstract... Guarujá:[ s.n.], 2013. AB.20.| Biblioteca(s): Embrapa Pecuária Sudeste. |
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| 5. | | O'BRIEN, A. M. P.; MÉSZÁROS, G.; UTSUNOMIYA, Y. T.; SONSTEGARD, T. S.; GARCIA, J. F.; TASSEL, C. P. V.; CARVALHEIRO, R.; SILVA, M. V. G. B.; SÖLKNER, J. Linkage disequilibrium levels in Bos indicus and Bos taurus cattle using medium and high density SNP chip data and different minor allele frequency distributions. Livestock Science, v. 166, p. 121-132, 2014.| Biblioteca(s): Embrapa Gado de Leite. |
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| 6. | | SANTOS, N. P. da S.; SARMENTO, J. L. R.; CARVALHEIRO, R.; CAMPELO, J. E. G.; SOUSA, W. H. de; FIGUEIREDO FILHO, L. A. S.; REGO NETO, A. de A.; BIAGIOTTI, D. Contribuição genética ótima aplicada à seleção de ovinos Santa Inês. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 51, n. 6, p. 745-750, jun. 2016. Título em inglês: Optimum genetic contribution applied to the selection of Santa Ines sheep.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 7. | | BOISON, S. A.; UTSUNOMIYA, A. T. H.; SANTOS, D. J. A.; NEVES, H. H. R.; MÉSZÁROS, G.; CARVALHEIRO, R.; GARCIA, J. F.; SILVA, M. V. G. B.; SÖLKNER, J. Accuracy of genomic predictions for dairy traits in Gyr cattle (Bos indicus) Warsaw: EAAP, 2015.| Biblioteca(s): Embrapa Gado de Leite. |
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| 8. | | MORALES, D. DA S.; SILVA, D. O.; AYRES, D. R.; SANTANA JÚNIOR, M. L.; BIGNARDI, A. B.; VENTURA, R. V.; MENEZES, G. R. de O.; CARVALHEIRO, R.; PICCOLI, M. L.; ROSO, V. M.; PEREIRA, R. J. Genetic associations between stayability to consecutive calvings and traits of economic interest in taurine and zebu breeds. Journal of Animal Breeding and Genetics, v. 140, 2023. 13 p.| Biblioteca(s): Embrapa Gado de Corte. |
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| 9. | | CAMPOS, G. S.; CARDOSO, F. F.; GULIAS GOMES, C. C.; DOMINGUES, R.; REGITANO, L. C. de A.; OLIVEIRA, M. C. de S.; OLIVEIRA, H. N. DE; CARVALHEIRO, R.; ALBUQUERQUE, L. G.; MILLER, S.; MISTZAL, I.; LOURENCO, D. Development of genomic predictions for Angus cattle in Brazil incorporating genotypes from related american sires. Journal of Animal Science, v. 100, n. 2, p. 1-13, Feb. 2022. skac009.| Biblioteca(s): Embrapa Pecuária Sudeste; Embrapa Pecuária Sul. |
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| 10. | | CHUD, T. C. S.; VENTURA, R. V.; SCHENKEL, F. S.; CARVALHEIRO, R.; BUZANSKAS, M. E.; ROSA, J. O.; MUDADU, M. de A.; SILVA, M. V. G. B.; MARCONDES, C. R.; REGITANO, L. C. de A.; MUNARI, D. P. Strategies for genotype imputation in composite beef cattle BMC Genetics, v. 16, p. 99, 2015. 10 p.| Biblioteca(s): Embrapa Gado de Leite. |
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| 11. | | BOISON, S. A.; SANTOS, D. J. A.; UTSONOMIYA, A. H. T.; CARVALHEIRO, R.; NEVES, H. H. R.; O'BRIEN, A. M. P.; GARCIA, J. F.; SÖLKNER, J.; SILVA, M. V. G. B. Strategies for single nucleotide polymorphism (SNP) genotyping to enhance genotype imputation in Gyr (Bos indicus) dairy cattle: Comparison of commercially available SNP chips. Journal of Dairy Science, v. 98, n. 7, p. 4969-4989, 2015.| Biblioteca(s): Embrapa Gado de Leite. |
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| 12. | | NEVES, H. H.; CARVALHEIRO, R.; O'BRIEN, A. M.; UTSUNOMIYA, Y. T.; CARMO, A. S. do; SCHENKEL, F. S.; SÖLKNER, J.; MCEWAN, J. C.; VAN TASSELL, C. P.; COLE, J. B.; SILVA, M. V. G. B.; QUEIROZ, S. A.; SONSTEGARD, T. S.; GARCIA, J. F. Accuracy of genomic predictions in Bos indicus (Nellore) cattle. Genetics Selection Evolution, v. 46, article 17, 2014.| Biblioteca(s): Embrapa Gado de Leite. |
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| 13. | | BOISON, S. A.; UTSUNOMIYA, A. T. H.; SANTOS, D. J. A.; NEVES, H. H. R.; CARVALHEIRO, R.; MÉSZÁROS, G.; UTSUNOMIYA, Y. T.; CARMO, A. S. do; VERNEQUE, R. da S.; MACHADO, M. A.; PANETTO, J. C. do C.; GARCIA, J. F.; SÖLKNER, J.; SILVA, M. V. G. B. Accuracy of genomic predictions in Gyr (Bos indicus) dairy cattle. Journal of Dairy Science, v. 100, n. 7, p. 5479-5490, 2017.| Biblioteca(s): Embrapa Gado de Leite. |
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| 14. | | ZAVAREZ, L. B.; UTSUNOMIYA, Y. T.; CARMO, A. S.; NEVES, H. H.; CARVALHEIRO, R.; FERENCAKOVIC, M.; O'BRIEN, A. M. P.; CURIK, I.; COLE, J. B.; TASSELL, C. P. V.; SILVA, M. V. G. B.; SONSTEGARD, T. S.; SÖLKNER, J.; GARCIA, J. F. Assessment of autozygosity in Nellore cows (Bos indicus) through high-density SNP genotypes. Frontiers in Genetics, v. 6, n. 5, p. 286-293, 2015.| Biblioteca(s): Embrapa Gado de Leite. |
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| 15. | | UTSUNOMIYA, Y. T.; CARMO, A. S. do; CARVALHEIRO, R.; NEVES, H. H. R.; MATOS, M. C.; ZAVAREZ, L. B.; O'BRIEN, A. M. P.; SÖLKNER, J.; McEWAN, J. C.; COLE, J. B.; TASSEL, C. P. V.; SCHENKEL, F. S.; SILVA, M. V. G. B.; PORTO NETO, L. R.; SONSTEGARD, T. S.; GARCIA, J. F. Genome-wide association study for birth weight in Nellore cattle points to previously described orthologous genes affecting human and bovine height. BMC Genetics, London, v. 14, article 52, 2013.| Biblioteca(s): Embrapa Gado de Leite. |
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| 16. | | UTSUNOMIYA, Y. T.; CARMO, A. S.; NEVES, H. H. R.; CARVALHEIRO, R.; MATOS, M. C.; ZAVAREZ, L. B.; ITO, P. K. R. K.; O'BRIEN, A. M. P.; SOLKNER, J.; PORTO-NETO, L. R.; SCHENKEL, F. S.; McEWAN, J.; COLE, J. B.; SILVA, M. V. G. B.; VAN TASSELL, C. P.; SONSTEGARD, T. S.; GARCIA, J. F. Genome-wide mapping of loci explaining variance in scrotal circumference in Nellore Cattle. Plos One v. 9, n. 2, p. 1-9, 2014.| Biblioteca(s): Embrapa Gado de Leite. |
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| 17. | | O'BRIEN, A. M. P.; HÖLLER, D.; BOISON, S. A.; MILANESI, M.; BOMBA, L.; UTSUNOMIYA, Y. T.; CARVALHEIRO, R.; NEVES, H. H. R.; SILVA, M. V. G. B.; VAN TASSEL, C. P.; SOSTENGARD, T. S.; MÉSZÁROS, G.; AJMONE-MARSAN, P.; GARCIA, J. F.; SÖLKNER, J. Low levels of taurine introgression in the current Brazilian Nelore and Gir indicine cattle populations. Genetics Selection Evolution, v. 47, article 31, 2015.| Biblioteca(s): Embrapa Gado de Leite. |
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| 18. | | CHUD, T. C. S.; VENTURA, R. V.; SCHENKEL, F. S.; CARVALHEIRO, R.; BUZANSKAS, M. E.; ROSA, J. O.; MUDADU, M. de A.; SILVA, M. V. G. B.; MOKRY, F. B.; MARCONDES, C. R.; REGITANO, L. C. de A.; MUNARI, D. P. Strategies for genotype imputation in composite beef cattle. BMC Genomics, v. 16, n. 99, 2015. 10 p.| Biblioteca(s): Embrapa Pecuária Sudeste. |
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| 19. | | CARDOSO, D. F.; FERNANDES JÚNIOR, G. A.; SCALEZ, D. C. B.; ALVEZ, A. A. C.; MAGALHÃES, A. F. B.; BRESOLIN, T.; VENTURA, R. V.; LI, C.; OLIVEIRA, M. C. de S.; PORTO NETO, L. R.; CARVALHEIRO, R.; OLIVEIRA, H. N. de; TONHATI, H.; ALBUQUERQUE, L. G. Uncovering sub-structure and genomic profiles in across-countries subpopulations of Angus Cattle. Scientific Reports, v. 10, article 8770, 2020. 11 p.| Biblioteca(s): Embrapa Pecuária Sudeste. |
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| 20. | | SÖLKNER, J.; PEREZ O'BRIEN, A. M.; HÖLLER, D.; BOISON, S. A.; MILANESI, M.; BOMBA, L.; UTSUNOMIYA, Y. T.; CARVALHEIRO, R.; NEVES, H. H. R.; SILVA, M. V. G. B.; VAN TASSEL, C. P.; SOSTENGARD, T. S.; MÉSZÁROS, G.; AJMONE-MARSAN, P.; GARCIA, J. F. Zebuines kerngenom und taurine Mitochondrien: admixtur von Nelore, der größten brasilianischen rinderrasse. Nova Acta Leopoldina, NF 119, n. 404, p. 69-75, 2016.| Biblioteca(s): Embrapa Gado de Leite. |
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| Registros recuperados : 20 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
04/06/2014 |
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Data da última atualização: |
06/02/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 4 |
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Autoria: |
NEVES, H. H.; CARVALHEIRO, R.; O'BRIEN, A. M.; UTSUNOMIYA, Y. T.; CARMO, A. S. do; SCHENKEL, F. S.; SÖLKNER, J.; MCEWAN, J. C.; VAN TASSELL, C. P.; COLE, J. B.; SILVA, M. V. G. B.; QUEIROZ, S. A.; SONSTEGARD, T. S.; GARCIA, J. F. |
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Afiliação: |
Haroldo HR Neves; Roberto Carvalheiro; Ana M Pérez O'Brien; Yuri T Utsunomiya; Adriana S. do Carmo; Flávio S Schenkel; Johann Sölkner; John C McEwan; Curtis P Van Tassell; John B Cole; MARCOS VINICIUS GUALBERTO B SILVA, CNPGL; Sandra A Queiroz; Tad S Sonstegard; José Fernando Garcia. |
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Título: |
Accuracy of genomic predictions in Bos indicus (Nellore) cattle. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
Genetics Selection Evolution, v. 46, article 17, 2014. |
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DOI: |
https://doi.org/10.1186/1297-9686-46-17 |
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Idioma: |
Inglês |
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Conteúdo: |
Background- Nellore cattle play an important role in beef production in tropical systems and there is great interest in determining if genomic selection can contribute to accelerate genetic improvement of production and fertility in this breed. We present the first results of the implementation of genomic prediction in a Bos indicus (Nellore) population. Methods - Influential bulls were genotyped with the Illumina Bovine HD chip in order to assess genomic predictive ability for weight and carcass traits, gestation length, scrotal circumference and two selection indices. 685 samples and 320 238 single nucleotide polymorphisms (SNPs) were used in the analyses. A forward-prediction scheme was adopted to predict the genomic breeding values (DGV). In the training step, the estimated breeding values (EBV) of bulls were deregressed (dEBV) and used as pseudo-phenotypes to estimate marker effects using four methods: genomic BLUP with or without a residual polygenic effect (GBLUP20 and GBLUP0, respectively), a mixture model (Bayes C) and Bayesian LASSO (BLASSO). Empirical accuracies of the resulting genomic predictions were assessed based on the correlation between DGV and dEBV for the testing group. Results - Accuracies of genomic predictions ranged from 0.17 (navel at weaning) to 0.74 (finishing precocity). Across traits, Bayesian regression models (Bayes C and BLASSO) were more accurate than GBLUP. The average empirical accuracies were 0.39 (GBLUP0), 0.40 (GBLUP20) and 0.44 (Bayes C and BLASSO). Bayes C and BLASSO tended to produce deflated predictions (i.e. slope of the regression of dEBV on DGV greater than 1). Further analyses suggested that higher-than-expected accuracies were observed for traits for which EBV means differed significantly between two breeding subgroups that were identified in a principal component analysis based on genomic relationships. Conclusions -Bayesian regression models are of interest for future applications of genomic selection in this population, but further improvements are needed to reduce deflation of their predictions. Recurrent updates of the training population would be required to enable accurate prediction of the genetic merit of young animals. The technical feasibility of applying genomic prediction in a Bos indicus (Nellore) population was demonstrated. Further research is needed to permit cost-effective selection decisions using genomic information. MenosBackground- Nellore cattle play an important role in beef production in tropical systems and there is great interest in determining if genomic selection can contribute to accelerate genetic improvement of production and fertility in this breed. We present the first results of the implementation of genomic prediction in a Bos indicus (Nellore) population. Methods - Influential bulls were genotyped with the Illumina Bovine HD chip in order to assess genomic predictive ability for weight and carcass traits, gestation length, scrotal circumference and two selection indices. 685 samples and 320 238 single nucleotide polymorphisms (SNPs) were used in the analyses. A forward-prediction scheme was adopted to predict the genomic breeding values (DGV). In the training step, the estimated breeding values (EBV) of bulls were deregressed (dEBV) and used as pseudo-phenotypes to estimate marker effects using four methods: genomic BLUP with or without a residual polygenic effect (GBLUP20 and GBLUP0, respectively), a mixture model (Bayes C) and Bayesian LASSO (BLASSO). Empirical accuracies of the resulting genomic predictions were assessed based on the correlation between DGV and dEBV for the testing group. Results - Accuracies of genomic predictions ranged from 0.17 (navel at weaning) to 0.74 (finishing precocity). Across traits, Bayesian regression models (Bayes C and BLASSO) were more accurate than GBLUP. The average empirical accuracies were 0.39 (GBLUP0), 0.40 (GBLUP20) and 0.44 (Bayes ... Mostrar Tudo |
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Palavras-Chave: |
Genomic selection; Nellore cattle. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/116427/1/Cnpgl-2014-Genetics-Selection-Evolution-Accuracy-of-genomic.pdf
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Marc: |
LEADER 03329naa a2200313 a 4500
001 1987574
005 2024-02-06
008 2014 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1186/1297-9686-46-17$2DOI
100 1 $aNEVES, H. H.
245 $aAccuracy of genomic predictions in Bos indicus (Nellore) cattle.$h[electronic resource]
260 $c2014
520 $aBackground- Nellore cattle play an important role in beef production in tropical systems and there is great interest in determining if genomic selection can contribute to accelerate genetic improvement of production and fertility in this breed. We present the first results of the implementation of genomic prediction in a Bos indicus (Nellore) population. Methods - Influential bulls were genotyped with the Illumina Bovine HD chip in order to assess genomic predictive ability for weight and carcass traits, gestation length, scrotal circumference and two selection indices. 685 samples and 320 238 single nucleotide polymorphisms (SNPs) were used in the analyses. A forward-prediction scheme was adopted to predict the genomic breeding values (DGV). In the training step, the estimated breeding values (EBV) of bulls were deregressed (dEBV) and used as pseudo-phenotypes to estimate marker effects using four methods: genomic BLUP with or without a residual polygenic effect (GBLUP20 and GBLUP0, respectively), a mixture model (Bayes C) and Bayesian LASSO (BLASSO). Empirical accuracies of the resulting genomic predictions were assessed based on the correlation between DGV and dEBV for the testing group. Results - Accuracies of genomic predictions ranged from 0.17 (navel at weaning) to 0.74 (finishing precocity). Across traits, Bayesian regression models (Bayes C and BLASSO) were more accurate than GBLUP. The average empirical accuracies were 0.39 (GBLUP0), 0.40 (GBLUP20) and 0.44 (Bayes C and BLASSO). Bayes C and BLASSO tended to produce deflated predictions (i.e. slope of the regression of dEBV on DGV greater than 1). Further analyses suggested that higher-than-expected accuracies were observed for traits for which EBV means differed significantly between two breeding subgroups that were identified in a principal component analysis based on genomic relationships. Conclusions -Bayesian regression models are of interest for future applications of genomic selection in this population, but further improvements are needed to reduce deflation of their predictions. Recurrent updates of the training population would be required to enable accurate prediction of the genetic merit of young animals. The technical feasibility of applying genomic prediction in a Bos indicus (Nellore) population was demonstrated. Further research is needed to permit cost-effective selection decisions using genomic information.
653 $aGenomic selection
653 $aNellore cattle
700 1 $aCARVALHEIRO, R.
700 1 $aO'BRIEN, A. M.
700 1 $aUTSUNOMIYA, Y. T.
700 1 $aCARMO, A. S. do
700 1 $aSCHENKEL, F. S.
700 1 $aSÖLKNER, J.
700 1 $aMCEWAN, J. C.
700 1 $aVAN TASSELL, C. P.
700 1 $aCOLE, J. B.
700 1 $aSILVA, M. V. G. B.
700 1 $aQUEIROZ, S. A.
700 1 $aSONSTEGARD, T. S.
700 1 $aGARCIA, J. F.
773 $tGenetics Selection Evolution$gv. 46, article 17, 2014.
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Embrapa Gado de Leite (CNPGL) |
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