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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
14/07/2017 |
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Data da última atualização: |
03/01/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
GOIS, I. B.; BORÉM, A.; CRISTOFANI-YALY, M.; RESENDE, M. D. V. de; AZEVEDO, C. F.; BASTIANEL, M.; NOVELLI, V. M.; MACHADO, M. A. |
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Afiliação: |
I. B. Gois, Departamento de Fitotecnia, Universidade Federal de Viçosa; A. Borém, Departamento de Fitotecnia, Universidade Federal de Viçosa; M. Cristofani-Yaly, Instituto Agronômico de Campinas, Centro APTA Citros Sylvio Moreira; MARCOS DEON VILELA DE RESENDE, CNPF; C. F. Azevedo, Departamento de Estatística, Universidade Federal de Viçosa; M. Bastianel, Instituto Agronômico de Campinas, Centro APTA Citros Sylvio Moreira; V. M. Novelli, Instituto Agronômico de Campinas, Centro APTA Citros Sylvio Moreira; M. A. Machado, Instituto Agronômico de Campinas, Centro APTA Citros Sylvio Moreira. |
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Título: |
Genome wide selection in citrus breeding. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
Genetics and Molecular Research, v. 15, n. 4, gmr15048863, Oct. 2016. |
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DOI: |
http://dx.doi.org/10.4238/gmr15048863 |
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Idioma: |
Inglês |
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Conteúdo: |
Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seqTM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus. MenosGenome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seqTM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citr... Mostrar Tudo |
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Palavras-Chave: |
DarT_seq; Molecular markers; Seleção precoce; Selective accuracy. |
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Thesagro: |
Fruta cítrica; Marcador Molecular; Melhoramento vegetal. |
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Thesaurus Nal: |
Citrus; early selection; linkage disequilibrium; Plant breeding. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/161818/1/2016-M.Deon-GMR-Genome.pdf
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Marc: |
LEADER 02672naa a2200349 a 4500
001 2072713
005 2018-01-03
008 2016 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.4238/gmr15048863$2DOI
100 1 $aGOIS, I. B.
245 $aGenome wide selection in citrus breeding.$h[electronic resource]
260 $c2016
520 $aGenome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seqTM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.
650 $aCitrus
650 $aearly selection
650 $alinkage disequilibrium
650 $aPlant breeding
650 $aFruta cítrica
650 $aMarcador Molecular
650 $aMelhoramento vegetal
653 $aDarT_seq
653 $aMolecular markers
653 $aSeleção precoce
653 $aSelective accuracy
700 1 $aBORÉM, A.
700 1 $aCRISTOFANI-YALY, M.
700 1 $aRESENDE, M. D. V. de
700 1 $aAZEVEDO, C. F.
700 1 $aBASTIANEL, M.
700 1 $aNOVELLI, V. M.
700 1 $aMACHADO, M. A.
773 $tGenetics and Molecular Research$gv. 15, n. 4, gmr15048863, Oct. 2016.
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Registro original: |
Embrapa Florestas (CNPF) |
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Biblioteca |
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Origem |
Tipo/Formato |
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Registro |
Volume |
Status |
URL |
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| Registros recuperados : 77 | |
| 21. |  | TEODORO, P. E.; FARIAS, F. J. C.; CARVALHO, L. P. de; RIBEIRO, L. P.; NASCIMENTO, M.; AZEVEDO, C. F.; CRUZ, C. D.; BHERING, L. L. Adaptability and stability of cotton genotypes regarding fiber yield and quality traits. Crop Science, v. 59, p. 518?524, March?April 2019.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Algodão. |
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| 22. | | RESENDE, R. T.; RESENDE, M. D. V.; SILVA, F. F.; AZEVEDO, C. F.; TAKAHASHI, E. K.; SILVA JUNIOR, O. B.; GRATTAPAGLIA, D. Assessing the expected response to genomic selection of individuals and families in Eucalyptus breeding with an additive-dominant model. Heredity, v. 119, p. 245-255, 2017.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Florestas; Embrapa Recursos Genéticos e Biotecnologia. |
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| 23. | | PEREIRA, V. C. S.; DIAS, R. V.; AZEVEDO, C. F. e O.; PEREIRA, I. S.; HONDA, L. S.; PINHEIRO, E. F. M.; CAMPOS, D. V. B. de. Agregação do solo sob diferentes usos e cobertura vegetal no bioma Cerrado. In: CONGRESSO LATINO-AMERICANO DE CIÊNCIA DO SOLO, 23.; CONGRESSO BRASILEIRO DE CIÊNCIA DO SOLO, 38., 2023, Florianópolis. Anais [...]. Florianópolis: Epagri, 2023. p. 949. Ref. ID 1339.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Solos. |
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| 25. | | AZEVEDO, C. F.; NASCIMENTO, M.; SILVA, F. F.; RESENDE, M. D. V. de; LOPES, P. S.; GUIMARÃES, S. E. F.; GLÓRIA, L. S. Comparison of dimensionality reduction methods to predict genomic breeding values for carcass traits in pigs. Genetics and Molecular Research, Ribeirão Preto, v. 14, n. 4, p. 12217-12227, 2015.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Florestas. |
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| 26. | | COSTA, J. A. da; AZEVEDO, C. F.; NASCIMENTO, M.; SILVA, F. F. e; RESENDE, M. D. V. de; NASCIMENTO, A. C. C. A comparison of regression methods based on dimensional reduction for genomic prediction. Genetics and Molecular Research, v. 20, n. 2, p. 1-15, 2021.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Café. |
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| 27. | | 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.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 4 |
| Biblioteca(s): Embrapa Florestas. |
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| 30. | | SUELA, M. M.; AZEVEDO, C. F.; NASCIMENTO, A. C. C.; MOMEN, M.; OLIVEIRA, A. C. B. de; CAIXETA, E. T.; MOROTA, G.; NASCIMENTO, M. Genome-wide association study for morphological, physiological, and productive traits in Coffea arabica using structural equation models. Tree Genetics & Genomes, v. 19, n. 3, 2023. 17 p.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Café. |
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| 31. | | GOIS, I. B.; BORÉM, A.; CRISTOFANI-YALY, M.; RESENDE, M. D. V. de; AZEVEDO, C. F.; BASTIANEL, M.; NOVELLI, V. M.; MACHADO, M. A. Genome wide selection in citrus breeding. Genetics and Molecular Research, v. 15, n. 4, gmr15048863, Oct. 2016.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Florestas. |
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| 32. | | SANTOS, V. S.; MARTINS FILHO, S.; RESENDE, M. D. V. de; AZEVEDO, C. F.; LOPES, P. S.; GUIMARÃES, S. E. F.; SILVA, F. F. Genomic prediction for additive and dominance effects of censored traits in pigs. Genetics and Molecular Research, v. 15, n. 4, gmr15048764, Oct. 2016.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Florestas. |
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| 34. | | ESTOPA, R. A.; PALUDETO, J. G. Z.; MÜLLER, B. S. F.; OLIVEIRA, R. A. de; AZEVEDO, C. F.; RESENDE, M. D. V. de; TAMBARUSSI, E. V.; GRATTAPAGLIA, D. Genomic prediction of growth and wood quality traits in Eucalyptus benthamii using different genomic models and variable SNP genotyping density. New Forests, 54, 2023.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Café; Embrapa Recursos Genéticos e Biotecnologia. |
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| 35. | | SANTOS, V. S.; MARTINS FILHO, S.; RESENDE, M. D. V. de; AZEVEDO, C. F.; LOPES, P. S.; GUIMARAES, S. E. F.; GLORIA, L. S.; SILVA, F. F. Genomic selection for slaughter age in pigs using the Cox frailty model. Genetics and Molecular Research, Ribeirão Preto, v. 14, n. 4, p. 12616-12627, 2015.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Florestas. |
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| 36. | | COSTA, J. A. da; AZEVEDO, C. F.; NASCIMENTO, M.; SILVA, F. F.; RESENDE, M. D. V. de; NASCIMENTO, A. C. C. Determination of optimal number of independent components in yield traits in rice. Scientia Agricola, v. 79, n. 6, p. 1-8, 2022.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Café. |
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| 37. | | AZEVEDO, C. F.; CARVALHO, I. R.; NASCIMENTO, M.; SILVA, J. A. G. da; NASCIMENTO, A, C. C.; CRUZ, C. D.; HUTH, C.; ALMEIDA, H. C. F. de. Informative prior distribution applied to linseed for the estimation of genetic parameters using a small sample size. Pesquisa Agropecuária Brasileira, v. 57, e02793, 2022. Título em português: Distribuição a priori informativa aplicada à linhaça para estimação de parâmetros genéticos com uso de tamanho amostral reduzido.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 38. | | ANDRADE, L. R. B. de; SOUSA, M. B. e; WOLFE, M.; JANNINK, J. L.; RESENDE, M. D. V. de; AZEVEDO, C. F.; OLIVEIRA, E. J. de. Increasing cassava root yield: additive-dominant genetic models for selection of parents and clones. Frontiers in Plant Science, v. 13, article 1071156, 2022.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Café. |
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| 39. | | COSTA, E. V.; DINIZ, D. B.; VERONEZE, R.; RESENDE, M. D. V. de; AZEVEDO, C. F.; GUIMARÃES, S. E. F.; SILVA, F. F.; LOPES, P. S. Estimating additive and dominance variances for complex traits in pigs combining genomic and pedigree information. Genetics and Molecular Research, v. 14, n. 2, p. 6303-6311, June 2015.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Florestas. |
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| 40. | | AZEVEDO, C. F.; RESENDE, M. D. V. de; SILVA, F. F. e; NASCIMENTO, M.; VIANA, J. M. S.; VALENTE, M. S. F. Population structure correction for genomic selection through eigenvector covariates. Crop Breeding and Applied Biotechnology, Viçosa, v. 17, n. 4, p.350-358, Oct./Dec. 2017.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Florestas. |
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| Registros recuperados : 77 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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