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Registro Completo |
Biblioteca(s): |
Embrapa Florestas. |
Data corrente: |
19/12/2014 |
Data da última atualização: |
24/08/2015 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
MUNOZ, P. R.; RESENDE JUNIOR, M. F. R.; HUBER, D. A.; QUESADA, T.; RESENDE, M. D. V. de; NEALE, D. B.; WEGRZYN, J. L.; KIRST, M.; PETER, G. F. |
Afiliação: |
Patricio R. Munoz, University of Florida; Marcio F. R. Resende Junior, University of Florida; Dudley A. Huber, University of Florida; Tania Quesada, University of Florida; MARCOS DEON VILELA DE RESENDE, CNPF; David B. Neale, University of California; Jill L. Wegrzyn, University of California; Matias Kirst, University of Florida; Gary F. Peter, University of Florida. |
Título: |
Genomic relationship matrix for correcting pedigree errors in breeding populations: impact on genetic parameters and genomic selection accuracy. |
Ano de publicação: |
2014 |
Fonte/Imprenta: |
Crop Science, v. 54, p. 115-1123, May/June 2014. |
Idioma: |
Inglês |
Conteúdo: |
Quantitative genetic analyses aim to estimate genetic parameters and breeding values to select superior parents, families, and individuals. For these estimates a relationship matrix derived from the pedigree typically is used in a mixed model framework. However, breeding is a complex, multistep process and errors in the pedigree are common. Because errors reduce the accuracy of genetic parameter estimates and affect genetic gain, it is important to correct these errors. Here we show that a realized relationship matrix (RRM) derived from single nucleotide polymorphism markers based on the normality of the relationship coefficients can be used to correct pedigree errors. For a loblolly pine (Pinus taeda L.) breeding population, errors in the pedigree were detected and corrected with the RRM. With the corrected pedigree, best linear unbiased predictor (BLUP) models fit the data significantly better for 14 out of 15 traits evaluated, and the predictive ability of the genomic selection models using ridge regression BLUP increased for 13 traits. The corrected pedigree based on the normality of the relationship coefficients improves accuracy of traditional estimations of heritability and breeding values as well as genomic selection predictions. As more breeding programs begin to use genomic selection, we recommend first using the dense panel of markers to correct pedigree errors and then using the improved information to develop genomic selection prediction models. |
Palavras-Chave: |
Genética quantitativa; Melhoramento genético. |
Thesagro: |
Parâmetro Genético. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/114177/1/2014-API-Deon-GenomicRelationship.pdf
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Marc: |
LEADER 02285naa a2200253 a 4500 001 2003359 005 2015-08-24 008 2014 bl uuuu u00u1 u #d 100 1 $aMUNOZ, P. R. 245 $aGenomic relationship matrix for correcting pedigree errors in breeding populations$bimpact on genetic parameters and genomic selection accuracy.$h[electronic resource] 260 $c2014 520 $aQuantitative genetic analyses aim to estimate genetic parameters and breeding values to select superior parents, families, and individuals. For these estimates a relationship matrix derived from the pedigree typically is used in a mixed model framework. However, breeding is a complex, multistep process and errors in the pedigree are common. Because errors reduce the accuracy of genetic parameter estimates and affect genetic gain, it is important to correct these errors. Here we show that a realized relationship matrix (RRM) derived from single nucleotide polymorphism markers based on the normality of the relationship coefficients can be used to correct pedigree errors. For a loblolly pine (Pinus taeda L.) breeding population, errors in the pedigree were detected and corrected with the RRM. With the corrected pedigree, best linear unbiased predictor (BLUP) models fit the data significantly better for 14 out of 15 traits evaluated, and the predictive ability of the genomic selection models using ridge regression BLUP increased for 13 traits. The corrected pedigree based on the normality of the relationship coefficients improves accuracy of traditional estimations of heritability and breeding values as well as genomic selection predictions. As more breeding programs begin to use genomic selection, we recommend first using the dense panel of markers to correct pedigree errors and then using the improved information to develop genomic selection prediction models. 650 $aParâmetro Genético 653 $aGenética quantitativa 653 $aMelhoramento genético 700 1 $aRESENDE JUNIOR, M. F. R. 700 1 $aHUBER, D. A. 700 1 $aQUESADA, T. 700 1 $aRESENDE, M. D. V. de 700 1 $aNEALE, D. B. 700 1 $aWEGRZYN, J. L. 700 1 $aKIRST, M. 700 1 $aPETER, G. F. 773 $tCrop Science$gv. 54, p. 115-1123, May/June 2014.
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Embrapa Florestas (CNPF) |
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Registros recuperados : 48 | |
8. | | NEVES, L. G.; PAPPAS JUNIOR, G. J.; PAQUALI, G.; KIRST, M.; GRATTAPAGLIA, D. Advancing to a high density gene-rich map based on single feature polymorphisms in tropical eucalyptus. In: INTERNATIONAL PLANT & ANIMAL GENOMES CONFERENCE, 17., 2009, San Diego, CA. [Proceedings...]. [S. l.: s.n.], 2009. W185Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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10. | | BRONDANI, R. P. V.; GAIOTTO, F. A.; MISSIAGGIA, A. A.; KIRST, M.; GRIBELS, R.; GRATTAPAGLIA, D. Microsatellite markers for Ceiba pentandra (Bombacaceae), an endangered tree species of the amazon forest Molecular Ecology Notes, v.3, p.177-179, 2003.Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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11. | | MUNOZ, P.; RESENDE JUNIOR, M.; RESENDE, M. D. V. de; GEZAN, S.; KIRST, M.; PETER, G. The re-discovery of the dominance variation by using the observed relationship matrix and itis implications in breeding. In: INTERNATIONAL CONFERENCE ON QUANTITATIVE GENETICS, 4., 2012, Edinburgh. Understanding Variation in Complex Traits. . [S.l.: s.n], 2012. Poster abstracts. P-367.Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Florestas. |
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12. | | GRATTAPAGLIA, D.; NOVAES, E.; PAPPAS, G. J.; PASQUALI, G.; KIRST, M. Single feature polymorphism discovery and validation in Eucalyptus by pseudo-testcross inheritance and mapping. In: THE INTERNATIONAL CONFERENCE ON THE STATUS OF PLANT & ANIMAL GENOME RESEARCH, 16., 2008, San Diego. Final abstracts guide. San Diego, 2008, W172.Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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14. | | PROSDOCIMI, P; BITTENCOURT, D.; SILVA, F. R. da; KIRST, M.; MOTA, P. C.; RECH, E. L. Spinning gland transcriptomics from two main Clades of Spiders (Order: Araneae) - insights on their molecular, anatomical and behavioral evolution. Plos One, San Francisco, v. 6, n. 6, p. 1-15, June 2011.Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
Biblioteca(s): Embrapa Agricultura Digital; Embrapa Amazônia Ocidental; Embrapa Recursos Genéticos e Biotecnologia. |
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17. | | MISSIAGGIA, A. A.; KIRST, M.; SILVEIRA, F. Q.; GAIOTTO, F. A.; BRONDANI, R. P. V.; GRIBEL, R.; GRATTAPAGLIA, D. Análise da herança de locos microsatélites marcados com fluorescência em sumaúma (Ceiba pentandra) e estimativa de fecundação cruzada em populações naturais. In: WORKSHOP DO TALENTO ESTUDANTIL DA EMBRAPA RECURSOS GENÉTICOS E BIOTECNOLOGIA, 4., 1999, Brasília. Anais: resumos dos trabalhos. Brasília, DF: EMBRAPA-CENARGEN, 1999. p. 67.Tipo: Resumo em Anais de Congresso | Circulação/Nível: -- - -- |
Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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18. | | NOVAES, E.; DROST, D. R.; FARMERIE, W. G.; PAPPAS JUNIOR, G. J.; GRATTAPAGLIA, D.; SEDEROFF, R. R.; KIRST, M. High-throughput gene and SNP discovery in Eucalyptus grandis, an uncharacterized genome. BMC Genomic, v.9, p. 312, 2008.Tipo: Artigo em Periódico Indexado | Circulação/Nível: Internacional - A |
Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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20. | | RIOS, E.; RESENDE, M.; KIRST, M.; RESENDE, M. D. V. de; ALMEIDA FILHO, J. E. de; MUNOZ, P. Predictive ability of Genomic Estimated Family Values (GEFV). In: PLANT & ANIMAL GENOME CONFERENCE, 24., 2016, San Diego. [Abstracts...]. San Diego: [s.n.], 2016. Pôster P1186.Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Florestas. |
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Registros recuperados : 48 | |
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