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4. | | SILVA, M. V. G. B.; TASSELL, C. P. V.; SONSTEGARD, T. S.; MATUKUMALLI, L.; SCHROEDER, S.; VANRADEN, P.; WIGGANS, G. Predição do valor genético total de touros da raça Holandesa por meio de mapas densos de marcadores. In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA. 45., 2008, Lavras, MG. Anais... Viçosa, MG: Sociedade Brasileira de Zootecnia, 2008. Biblioteca(s): Embrapa Gado de Leite. |
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5. | | BENAVIDES, M. V.; ECHEVARRIA, F. A. M.; SONSTEGARD, T. S.; VAN TESSEL, C. P.; GASBARRE, L. C. Genetic variability of a Bos taurus x Bos indicus cross population and validation of genomic regions influencing nematode resistance. In: SIMPOSIO DE RECURSOS GENETICOS PARA AMERICA LATINA Y EL CARIBE, 5., 2005, Montevideo, Uruguay. Resumenes... Montevideo: INIA :Facultad de Agronomía de la Universidad de la República, 2005. p. 105 SIRGEALC. Resumo 305. Biblioteca(s): Embrapa Pecuária Sul. |
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8. | | 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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9. | | LIU, G. E.; LI, R. W.; SONSTEGARD, T. S.; MATUKUMALLI, L. K.; SILVA, M. V. G. B.; VAN TASSELL, C. P. Characterization of a novel microdeletion polymorphism on BTA5 in cattle. Animal Genetics, v. 39, n. 6, p. 655-658, 2008. Biblioteca(s): Embrapa Gado de Leite. |
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11. | | PORTO NETO, L. R.; SONSTEGARD, T. S.; LIU, G.; BICKHART, D.; GONDRO, C.; SILVA, M. V. G. B.; UTSUNOMIYA, Y. T.; GARCIA, J. F.; VAN TASSELL, C. P. Genomic divergence of indicine and taurine cattle identified through high-density SNP gebotyping. In: ADSA-ASAS ANNUAL MEETINGS, 2013, Indianápolis, Indiana. Abstracts... Indianápolis: [s.n.], 2013. Biblioteca(s): Embrapa Gado de Leite. |
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12. | | 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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13. | | ANDREOTE, A. P. D.; ROSÁRIO, M. F. do; LEDUR, M. C.; JORGE, E. C.; SONSTEGARD, T. S.; MATUKUMALLI, L.; COUTINHO, L. L. Identification and characterization of microRNAs expressed in chicken skeletal muscle. Genetics and Molecular Research, v. 6, n. 1, p. 1465-1479, 2014. Biblioteca(s): Embrapa Suínos e Aves. |
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14. | | VENERONI, G. B.; MEIRELLES, S. L.; SANTIAGO, A. C.; SONSTEGARD, T. S.; OLIVEIRA, H. N.; YAMAGISHI, M. E. B.; ALENCAR, M. M. de; REGITANO, L. C. de A. Identification of genomic regions associated with backfat thickness in synthetic cattle. In: WORKSHOP DA REDE GENÔMICA ANIMAL, 1., 2009, Fortaleza. Anais... Fortaleza, Rede Genômica Animal, 2009. Biblioteca(s): Embrapa Pecuária Sudeste. |
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15. | | BENAVIDES, M. V.; SONSTEGARD, T. S.; KEMP, S.; MUGAMBI, J. M.; GIBSON, J. P.; BAKER, R. L.; HANOTTE, O.; MARSHALL, K.; VAN TASSELL, C. Identification of novel loci associated with gastrointestinal parasite resistance in a Red Maasai x Dorper backcross population. Plos One, v. 10, n. 4, e0122797, Apr. 2015. Biblioteca(s): Embrapa Pecuária Sul; Embrapa Pesca e Aquicultura. |
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16. | | SILVA, M. V. G. B.; VERNEQUE, R. da S.; MACHADO, M. A.; PEIXOTO, M. G. C. D.; GUIMARAES, M. F. M.; ARBEX, W. A.; GUEDES, E.; VAN TASSELL, C. P.; SONSTEGARD, T. S. Genome-wide association analysis to identify loci for milk yield in Gyr breed. In: INTERNATIONAL CONFERENCE ON ANIMAL GENETICS, 32., 2010, Edinburgh. Proceedings... Edinburgh: International Society for Animal Genetics, 2010. Biblioteca(s): Embrapa Gado de Leite. |
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17. | | MYTATA, M.; GASPARIN, G.; COUTINHO, L. L.; MARTINEZ, M. L.; MACHADO, M. A.; SILVA, M. V. G. B. da; CAMPOS, A. L.; SONSTEGARD, T. S.; REGITANO, L. C. de A. Mapeamento de QTLS para peso ao nascimento no cromossomo 14 de bovinos In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 42., 2005, Goiânia. A Produção animal e o foco no agronegócio: anais. Goiânia: SBZ, 2005. 1 CD-ROM. Biblioteca(s): Embrapa Pecuária Sudeste. |
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18. | | GASPARIN, G.; MIYATA, M.; COUTINHO, M. L.; MARTINEZ, M. L.; TEODORO, R. L.; FURLONG, J.; MACHADO, M. A.; SILVA, M. V. G. B.; SONSTEGARD, T. S.; REGITANO, L. C. de A. Mapping of quantitative trait loci controlling tick [Riphicephalus (Boophilus) microplus] resistance on bovine chromosomes 5, 7, and 14. Animal Genetics, v. 38, n. 5, p. 453-459, oct. 2007. Biblioteca(s): Embrapa Pecuária Sudeste. |
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19. | | GASPARIN, G.; MIYATA, M.; COUTINHO, L. L.; MARTINEZ, M. L.; TEODORO, R. L.; FURLONG, J.; MACHADO, M. A.; SILVA, M. V. G. B. da; SONSTEGARD, T. S.; REGITANO, L. C. de A. Mapping of quatitative trait loci controlling tick [Riphicephalus (Boophilus) microplus] resistance on bovine chromosomes 5, 7 and 14. Animal Genetics, Oxford, v. 38, n. 5, p. 453-459, 2007. Biblioteca(s): Embrapa Gado de Leite. |
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20. | | O'BRIEN, A. M. P.; UTSUNOMIYA, Y. T.; MÉSZÁROS, G.; BICKHART, D. M.; LIU, G. E.; TASSEL, C. P. V.; SONSTEGARD, T. S.; SILVA, M. V. G. B.; GARCIA, J. F.; SÖLKNER, J. Assessing signatures of selection through variation in linkage disequilibrium between taurine and indicine cattle. Genetics Selection Evolution, v. 46, n. 19, 2014. 14 p. Biblioteca(s): Embrapa Gado de Leite. |
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Registros recuperados : 55 | |
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Registro Completo
Biblioteca(s): |
Embrapa Gado de Leite. |
Data corrente: |
04/06/2014 |
Data da última atualização: |
06/02/2024 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 4 |
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. |
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. |
Título: |
Accuracy of genomic predictions in Bos indicus (Nellore) cattle. |
Ano de publicação: |
2014 |
Fonte/Imprenta: |
Genetics Selection Evolution, v. 46, article 17, 2014. |
DOI: |
https://doi.org/10.1186/1297-9686-46-17 |
Idioma: |
Inglês |
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 |
Palavras-Chave: |
Genomic selection; Nellore cattle. |
Categoria do assunto: |
G Melhoramento Genético |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/116427/1/Cnpgl-2014-Genetics-Selection-Evolution-Accuracy-of-genomic.pdf
|
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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