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| Registros recuperados : 29 | |
| 10. |  | CHUD, T. C. S.; BICKHART, D. M.; ZERLOTINI NETO, A.; COLE, J. B.; SILVA, M. V. G. B.; MUNARI, D. P. Copy number variation in dairy cattle using next-generation sequencing. In: PLANT AND ANIMAL GENOME CONFERENCE, 26., 2018, San Diego. Abstracts... [S.l.: s.n.], 2018. 1 p. PAG 2018. P0490. Na publicação: Adhemar Zerlotini, Marcos Vinicius B. da Silva.| Biblioteca(s): Embrapa Agricultura Digital. |
|    |
| 11. | | SUL, W. J.; COLE, J. R.; WANG, Q.; FARRIS, R. J.; FISH, J. A.; TIEDJE, J. M.; JESUS, E. da C. Bacterial community comparisons by taxonomy-supervised analysis independent of sequence alignment and clustering. Proceedings of the National Academy of Sciences of the United States of America, v. 108, n. 35, p. 14637-14642, 2011.| Biblioteca(s): Embrapa Agrobiologia. |
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| 12. | | ORTEGA, M. S.; WOHLGEMUTH, S.; TRIBULO, P.; SIQUEIRA, L. G. B.; NULL, D. J.; COLE, J. B.; SILVA, M. V. G. B.; HANSEN, P. J. A single nucleotide polymorphism in COQ9 affects mitochondrial and ovarian function and fertility in Holstein cows. Biology of Reproduction, v. 96, n. 3, p. 652-663, 2017.| Biblioteca(s): Embrapa Gado de Leite. |
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| 13. | | OLIVEIRA JÚNIOR, G. A.; CHUD, T. C. S.; VENTURA, R. V.; GARRICK, D. J.; COLE, J. B.; MUNARI, D. P.; FERRAZ, J. B. S.; MULLART, E.; DeNISE, S.; SMITH, S.; SILVA, M. V. G. B. Genotype imputation in a tropical crossbred dairy cattle population. Journal of Dairy Science, v. 100, n. 12, p. 9623-9634, 2017.| Biblioteca(s): Embrapa Gado de Leite. |
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| 14. | | SILVA, M. V. G. B.; SANTOS, D. J. A. dos; BOISON, S. A.; UTSUNOMIYA, A. T. H.; CARMO, A. S.; SONSTEGARD, T. S.; COLE, J. B.; TASSELL, C. P. V. The development of genomics applied to dairy breeding. Livestock Science, v. 166, p. 66-75, 2014.| Biblioteca(s): Embrapa Gado de Leite. |
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| 15. | | ROMMENS, J. M.; IANNUZZI, M. C.; KEREM, B.-S.; DRUMM, M. L.; R.; COLE, J. M.; KENNEDY, D.; HIDAKA, N.; ZSIGA, M.; BUCHWALD, M.; RIORDAN, J. R.; TSUI, L. -C.; COLLINS, F. S. Identification of the cystic fibrosis gene: Cromosome walking and jumping. Science, Washington, v. 245, n. 4922, p. 1059-1065, 1989.| Biblioteca(s): Embrapa Trigo. |
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| 16. | | VERARDO, L. L.; STAFUZZA, N. B.; MUNARI, D. P.; ZERLOTINI NETO, A.; CHUD, T. C. S.; GARRICK, D. J.; COLE, J. B.; PANETTO, J. C. do C.; MACHADO, M. A.; MARTINS, M. F.; SILVA, M. V. G. B. A gene-transcription factor network associated with residual feed intake based on SNVs/InDels identified in Gir, Girolando and Holstein cattle breeds. In: WORLD CONGRESS ON GENETICS APPLIED TO LIVESTOCK PRODUCTION, 11., 2018, Auckland. Proceedings... [S.l.: s.n.], 2018.| Biblioteca(s): Embrapa Gado de Leite. |
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| 17. | | VERARDO, L. L.; STAFUZZA, N. B.; MUNARI, D. P.; ZERLOTINI NETO, A.; CHUD, T. C. S.; GARRICK, D. J.; COLE, J. B.; PANETTO, J. C. do C.; MACHADO, M. A.; MARTINS, M. F.; SILVA, M. V. G. B. A gene-transcription factor network associated with residual feed intake based on SNVs/InDels identified in Gir, Girolando and Holstein cattle breeds. In: WORLD CONGRESS ON GENETICS APPLIED TO LIVESTOCK PRODUCTION, 11., 2018, Auckland. Proceedings... [S.l.: s.n.], 2018. 6 p. Na publicação: A. Zerlotini, J. C. C. Panetto. WCGALP 2018.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 18. | | CARMO, A. S. do; OLIVEIRA JÚNIOR, G. A. de; CHUD, T. de O. S.; PANETTO, J. C. do C.; VERNEQUE, R. da S.; MACHADO, M. A.; COLE, J. B.; SILVA, M. V. G. B. Identificação de CNVs associados com características reprodutivas e produtivas em animais Gir Leiteiro. In: CONGRESSO BRASILEIRO DE ZOOTECNIA, 25., 2015, Fortaleza. Dimensões tecnológicas e sociais da zootecnia: anais. Fortaleza: Sociedade Brasileira de Zootecnia, 2015. 3 p. ZOOTEC| Biblioteca(s): Embrapa Gado de Leite. |
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| 19. | | 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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| 20. | | 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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| Registros recuperados : 29 | |
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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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