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| Registros recuperados : 4 | |
| 1. |  | LAGROTTA, M. R.; SILVA, F. F. e; RESENDE, M. D. V. de; NASCIMENTO, M.; DUARTE, D. A. S.; AZEVEDO, C. F.; MOTA, R. R. Computação paralela aplicada à seleção genômica via inferência Bayesiana. Revista Brasileira de Biometria, Lavras, v. 35, n. 3, p. 440-448, 2017.| Biblioteca(s): Embrapa Florestas. |
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| 2. | | SILVA, F. F.; ROCHA, G. S.; RESENDE, M. D. V. de; GUIMARÃES, S. E. F.; PETERNELLI, L. A.; DUARTE, D. A. S.; AZEVEDO, C. Seleção genômica ampla para curvas de crescimento. Arquivo Brasileiro de Medicina Veterinária e Zootecnia, v. 65, n. 5, p. 1519-1526, 2013.| Biblioteca(s): Embrapa Florestas. |
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| 3. | | DUARTE, D. A. S.; FORTES, M. R. S.; DUARTE, M. de S.; GUIMARÃES, S. E. F.; VERARDO, L. L.; VERONEZE, R.; RIBEIRO, A. M. F.; LOPES, P. S.; RESENDE, M. D. V. de; SILVA, F. F. e. Genome-wide association studies, meta-analyses and derived gene network for meat quality and carcass traits in pigs. Animal Production Science, v. 58, n. 6, p. 1100-1008, May 2018.| Biblioteca(s): Embrapa Florestas. |
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| 4. | | SILVA, F. F. e; RESENDE, M. D. V. de; ROCHA, G. S.; DUARTE, D. A. S.; LOPES, P. S.; BRUSTOLIN, O. J. B.; THUS, S.; VIANA, J. M. S.; GUIMARÃES, S. E. F. Genomic growth curves of an outbred pig population. Genetics and Molecular Biology, v. 36, n. 4, p. 520-527, 2013.| Biblioteca(s): Embrapa Florestas. |
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| Registros recuperados : 4 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
21/03/2014 |
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Data da última atualização: |
18/02/2015 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 1 |
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Autoria: |
SILVA, F. F. e; RESENDE, M. D. V. de; ROCHA, G. S.; DUARTE, D. A. S.; LOPES, P. S.; BRUSTOLIN, O. J. B.; THUS, S.; VIANA, J. M. S.; GUIMARÃES, S. E. F. |
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Afiliação: |
FABIANO FONSECA E SILVA, UFV; MARCOS DEON VILELA DE RESENDE, CNPF; GILSON SILVÉRIO ROCHA, UVF; DARLENE ANA S. DUARTE, UFV; PAULO SÁVIO LOPES, UFV; OTÁVIO J. B. BRUSTOLIN, UFV; SANDER THUS, WAGENINGEN UNIVERSITY; JOSÉ MARCELO S. VIANA, UFV; SIMONE E. F. GUIMARÃES, UFV. |
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Título: |
Genomic growth curves of an outbred pig population. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
Genetics and Molecular Biology, v. 36, n. 4, p. 520-527, 2013. |
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Idioma: |
Inglês |
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Conteúdo: |
In the current post-genomic era, the genetic basis of pig growth can be understood by assessing SNP marker effects and genomic breeding values (GEBV) based on estimates of these growth curve parameters as phenotypes. Although various statistical methods, such as random regression (RR-BLUP) and Bayesian LASSO (BL), have been applied to genomic selection (GS), none of these has yet been used in a growth curve approach. In this work, we compared the accuracies of RR-BLUP and BL using empirical weight-age data from an outbred F2 (Brazilian Piau X commercial) population. The phenotypes were determined by parameter estimates using a nonlinear logistic regression model and the halothane gene was considered as a marker for evaluating the assumptions of the GS methods in relation to the genetic variation explained by each locus. BL yielded more accurate values for all of the phenotypes evaluated and was used to estimate SNP effects and GEBV vectors. The latter allowed the construction of genomic growth curves, which showed substantial genetic discrimination among animals in the final growth phase. The SNP effect estimates allowed identification of the most relevant markers for each phenotype, the positions of which were coincident with reported QTL regions for growth traits. |
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Palavras-Chave: |
Melhoramento genético. |
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Thesagro: |
Curva de Crescimento; Porco. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/99868/1/2013-API-GenomicGrowth.pdf
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Marc: |
LEADER 02003naa a2200253 a 4500
001 1983083
005 2015-02-18
008 2013 bl uuuu u00u1 u #d
100 1 $aSILVA, F. F. e
245 $aGenomic growth curves of an outbred pig population.$h[electronic resource]
260 $c2013
520 $aIn the current post-genomic era, the genetic basis of pig growth can be understood by assessing SNP marker effects and genomic breeding values (GEBV) based on estimates of these growth curve parameters as phenotypes. Although various statistical methods, such as random regression (RR-BLUP) and Bayesian LASSO (BL), have been applied to genomic selection (GS), none of these has yet been used in a growth curve approach. In this work, we compared the accuracies of RR-BLUP and BL using empirical weight-age data from an outbred F2 (Brazilian Piau X commercial) population. The phenotypes were determined by parameter estimates using a nonlinear logistic regression model and the halothane gene was considered as a marker for evaluating the assumptions of the GS methods in relation to the genetic variation explained by each locus. BL yielded more accurate values for all of the phenotypes evaluated and was used to estimate SNP effects and GEBV vectors. The latter allowed the construction of genomic growth curves, which showed substantial genetic discrimination among animals in the final growth phase. The SNP effect estimates allowed identification of the most relevant markers for each phenotype, the positions of which were coincident with reported QTL regions for growth traits.
650 $aCurva de Crescimento
650 $aPorco
653 $aMelhoramento genético
700 1 $aRESENDE, M. D. V. de
700 1 $aROCHA, G. S.
700 1 $aDUARTE, D. A. S.
700 1 $aLOPES, P. S.
700 1 $aBRUSTOLIN, O. J. B.
700 1 $aTHUS, S.
700 1 $aVIANA, J. M. S.
700 1 $aGUIMARÃES, S. E. F.
773 $tGenetics and Molecular Biology$gv. 36, n. 4, p. 520-527, 2013.
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