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| Registros recuperados : 25 | |
| 2. |  | 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.| Biblioteca(s): Embrapa Florestas. |
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| 3. | | BETTINI, S. H. P.; JOSEFOVICH, M. P. P. de M.; MUÑOZ, P. A. R.; LOTTI, C.; MATTOSO, L. H. C. Effect of lubricant on mechanical and rheological properties of compatibilized PP/sawdust composites. Carbohydrate Polymers, Barking, v. 94, n. 2, p. 800-806, 2013.| Biblioteca(s): Embrapa Instrumentação. |
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| 4. | | 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.| Biblioteca(s): Embrapa Florestas. |
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| 5. | | RESENDE JUNIOR, M. F. R.; MUÑOZ, P.; ACOSTA, J. J.; PETER, G. F.; DAVIS, J. M.; GRATTAPAGLIA, D.; RESENDE, M. D. V. de; KIRST, M. Accelerating the domestication of trees using genomic selection: accuracy of prediction models across ages and environments. New Phytologist, v. 193, p. 617-624, 2012.| Biblioteca(s): Embrapa Florestas; Embrapa Recursos Genéticos e Biotecnologia. |
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| 6. | | ALMEIDA FILHO, J. E. de; GUIMARÃES, J. F. R.; SILVA, F. F. e; RESENDE, M. D. V. de; MUÑOZ, P.; KIRST, M.; RESENDE JUNIOR, M. F. R. The contribution of dominance to phenotype prediction in a pine breeding and simulated population. Heredity, v. 117, p. 33-41, July 2016.| Biblioteca(s): Embrapa Florestas. |
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| 7. | | RESENDE JUNIOR, M.; RESENDE, M. D. V. de; MUNOZ, P. R.; TAKAHASHI, E. K.; PETROLI, C.; SANSALONI, C.; KIRST, M.; GRATTAPAGLIA, D. Increase in efficiency of genomic selection sing epistatic interactions and detection of candidate genes for rust resistance in Eucalyptus. In: INTERNATIONAL PLANT & ANIMAL GENOME, 21., 2013, San Diego. Abstracts... Jersey City: Scherago International, 2013. W287.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 8. | | RESENDE JUNIOR, M.; RESENDE, M. D. V. de; MUNOZ, P. R.; TAKAHASHI, E. K.; PETROLI, C.; SANSALONI, C.; KIRST, M.; GRATTAPAGLIA, D. Increase in efficiency of genomic selection sing epistatic interactions and detection of candidate genes for rust resistance in Eucalyptus. In: INTERNATIONAL PLANT & ANIMAL GENOME, 21., 2013, San Diego. Abstracts... Jersey City: Scherago International, 2013. W287.| Biblioteca(s): Embrapa Florestas. |
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| 9. | | ALMEIDA FILHO, J. E. de A.; RODRIGUES, J. F. G.; SILVA, F. F. e; RESENDE, M. D. V. de; RESENDE JÚNIOR, M.; MUÑOZ, P.; KIRST, M. Genomic prediction of assitive and non-additive effects using genetic markers and pedigrees in pines breeding. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 8., 2015, Goiânia. O melhoramento de plantas, o futuro da agricultura e a soberania nacional: anais. Goiânia: SBMP: UFG, 2015. Resumo.| Biblioteca(s): Embrapa Florestas. |
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| 10. | | MÜLLER, B. S. F.; NEVES, L. G.; RESENDE JÚNIOR, M. F. R.; MUÑOZ, P. R.; KIRST, M.; SANTOS, P. E. T. dos; PALUDZYSZYN FILHO, E.; GRATTAPAGLIA, D. Genomic selection for growth traits in Eucalyptus benthamii and E. pellita populations using a genome-wide Eucalyptus 60K SNPs chip. In: IUFRO TREE BIOTECHNOLOGY CONFERENCE, 2015, Florence. Forests: the importance to the planet and society. [S.l.]: IBBR: ICCOM, 2015.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 11. | | MÜLLER, B. S. F.; NEVES, L. G.; RESENDE JÚNIOR, M. F. R.; MUÑOZ, P. R.; KIRST, M.; SANTOS, P. E. T. dos; PALUDZYSZYN FILHO, E.; GRATTAPAGLIA, D. Genomic selection for growth traits in Eucalyptus benthamii and E. pellita populations using a genome-wide Eucalyptus 60K SNPs chip. In: IUFRO TREE BIOTECHNOLOGY CONFERENCE, 2015, Florence. Forests: the importance to the planet and society. [S.l.]: IBBR: ICCOM, 2015. Pen-drive.| Biblioteca(s): Embrapa Florestas. |
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| 12. | | FIGUEIREDO, U. J. de; BERCHEMBROCK, Y. V.; VALLE, C. B. do; BARRIOS, S. C. L.; QUESENBERRY, K. H.; MUÑOZ, P. R.; NUNES, J. A. R. Evaluating early selection in perennial tropical forages. Crop Breeding and Applied Biotechnology, v. 19, n. 3, p. 291-299, 2019.| Biblioteca(s): Embrapa Gado de Corte. |
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| 13. | | GUIMARÃES, J. F. R.; ALMEIDA FILHO, J. E.; RESENDE JÚNIOR, M. F.; RESENDE, M. D. V. de; SILVA, F. F. e; MUÑOZ, P.; KIRST, M. Predictive ability behavior across sites after discard of SNPS with unstable effects. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 8., 2015, Goiânia. O melhoramento de plantas, o futuro da agricultura e a soberania nacional: anais. Goiânia: SBMP: UFG, 2015. Resumo.| Biblioteca(s): Embrapa Florestas. |
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| 14. | | MUÑOZ, P. R.; RESENDE JUNIOR, M. F. R.; GEZAN, S. A.; RESENDE, M. D. V. de; CAMPOS, G. de los; KIRST, M.; HUBER, D.; PETER, G. F. Unraveling additive from nonadditive effects using genomic relationship matrices. Genetics, v. 198, p. 1759-1768, Dec. 2014.| Biblioteca(s): Embrapa Florestas. |
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| 15. | | AZEVEDO, C. F.; FERRÃO, L. F. V.; BENEVENUTO, J.; RESENDE, M. D. V. de; NASCIMENTO, M.; NASCIMENTO, A. C. C.; MUNOZ, P. R. Using visual scores for genomic prediction of complex traits in breeding programs. Theoretical and Applied Genetics, v. 137, n. 1, 2024. 16 p.| Biblioteca(s): Embrapa Café. |
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| 16. | | AZEVEDO, C. F.; RESENDE, M. D. V. de; SILVA, F. F. e; VIANA, J. M. S.; VALENTE, M. S. F.; RESENDE JUNIOR, M. F. R.; MUÑOZ, P. Ridge, Lasso and Bayesian additive dominance genomic models. BMC Genetics, v. 16, art. 105, Aug. 2015. 13 p.| Biblioteca(s): Embrapa Florestas. |
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| 17. | | RESENDE JUNIOR, M. F. R.; MUÑOZ, P.; RESENDE, M. D. V. de; GARRICK, D. J.; FERNANDO, R. L.; DAVIS, J. M.; JOKELA, E. J.; MARTIN, T. A.; PETER, G. F.; KIRST, M. Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.) Genetics, v. 190, p. 1503-1510, April 2012.| Biblioteca(s): Embrapa Florestas. |
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| 18. | | ALMEIDA FILHO, J. E. de A.; GUIMARÃES, J. F. R.; SILVA, F. F. e; RESENDE, M. D. V. de; MUÑOZ, P.; KIRST, M.; RESENDE JÚNIOR, M. F. R. de. Genomic prediction of additive and non-additive effects using genetic markers and pedigrees. G3: Genes, Genomes, Genetics, v. 9, p. 2739-2748, Aug. 2019.| Biblioteca(s): Embrapa Florestas. |
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| 19. | | MÜLLER, B. S. F.; NEVES, L. G.; ALMEIDA FILHO, J. E. de; RESENDE JUNIOR, M. F. R.; MUÑOZ, P. R.; SANTOS, P. E. T. dos; PALUDZYSZYN FILHO, E.; KIRST, M.; GRATTAPAGLIA, D. Genomic prediction in contrast to a genome-wide association study in explaining heritable variation of complex growth traits in breeding populations of Eucalyptus. BMC Genomics, v. 18, article 524, 2017. 17 p.| Biblioteca(s): Embrapa Florestas; Embrapa Recursos Genéticos e Biotecnologia. |
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| 20. | | RIOS, E. F.; ANDRADE, M. H. M. L.; RESENDE JR, M. F. R.; KIRST, M.; RESENDE, M. D. V. de; ALMEIDA FILHO, J. O. E. de; GEZAN, S. A.; MUNOZ, P. Genomic prediction in family bulks using different traits and cross-validations in pine. G3: Genes, Genomes, Genetics, v. 11, n. 9, p. 1-12, 2021.| Biblioteca(s): Embrapa Café. |
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| Registros recuperados : 25 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
08/12/2023 |
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Data da última atualização: |
08/12/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 4 |
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Autoria: |
ADUNOLA, P.; FERRÃO, M. A. G.; FERRÃO, R. G.; FONSECA, A. F. A. da; VOLPI, P. S.; COMÉRIO, M.; VERDIN FILHO, A. C.; MUNOZ, P. R.; FERRÃO, L. F. V. |
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Afiliação: |
PAUL ADUNOLA, UNIVERSITY OF FLORIDA; MARIA AMÉLIA G FERRÃO, CNPCa; ROMÁRIO G FERRÃO, INSTITUTO CAPIXABA DE PESQUISA, ASSISTÊNCIA TÉCNICA E EXTENSÃO RURAL; AYMBIRE F A DA FONSECA, INSTITUTO CAPIXABA DE PESQUISA, ASSISTÊNCIA TÉCNICA E EXTENSÃO RURAL; PAULO S VOLPI, INSTITUTO CAPIXABA DE PESQUISA, ASSISTÊNCIA TÉCNICA E EXTENSÃO RURAL; MARCONE COMÉRIO, INSTITUTO CAPIXABA DE PESQUISA, ASSISTÊNCIA TÉCNICA E EXTENSÃO RURAL; ABRAÃO C VERDIN FILHO, INSTITUTO CAPIXABA DE PESQUISA, ASSISTÊNCIA TÉCNICA E EXTENSÃO RURAL; PATRICIO R MUNOZ, UNIVERSITY OF FLORIDA; LUÍS FELIPE V FERRÃO, UNIVERSITY OF FLORIDA. |
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Título: |
Genomic selection for genotype performance and environmental stability in Coffea canéfora. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
G3: Genes, Genomes, Genetics, v. 13, n. 6, p. 1-13, 2023. |
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DOI: |
https://doi.org/10.1093/g3journal/jkad062 |
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Idioma: |
Inglês |
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Conteúdo: |
Coffee is one of the most important beverages and trade products in the world. Among the multiple research initiatives focused on coffee sustainability, plant breeding provides the best means to increase phenotypic performance and release cultivars that could meet market demands. Since coffee is well adapted to a diversity of tropical environments, an important question for those confronting the problem of evaluating phenotypic performance is the relevance of genotype-by-environment interaction. As a perennial crop with a long juvenile phase, coffee is subjected to significant temporal and spatial variations. Such facts not only hinder the selection of promising materials but also cause a majority of complaints among growers. In this study, we hypothesized that trait stability in coffee is genetically controlled and therefore is predictable using molecular information. To test it, we used genome-based methods to predict stability metrics computed with the primary goal of selecting coffee genotypes that combine high phenotypic performance and stability for target environments. Using 2 populations of Coffea canephora, evaluated across multiple years and locations, our contribution is 3-fold: (1) first, we demonstrated that the number of harvest evaluations may be reduced leading to accelerated implementation of molecular breeding; (2) we showed that stability metrics are predictable; and finally, (3) both stable and high-performance genotypes can be simultaneously predicted and selected. While this research was carried out on representative environments for coffee production with substantial crossover in genotypic ranking, we anticipate that genomic prediction can be an efficient tool to select coffee genotypes that combine high performance and stability across years and the target locations here evaluated. MenosCoffee is one of the most important beverages and trade products in the world. Among the multiple research initiatives focused on coffee sustainability, plant breeding provides the best means to increase phenotypic performance and release cultivars that could meet market demands. Since coffee is well adapted to a diversity of tropical environments, an important question for those confronting the problem of evaluating phenotypic performance is the relevance of genotype-by-environment interaction. As a perennial crop with a long juvenile phase, coffee is subjected to significant temporal and spatial variations. Such facts not only hinder the selection of promising materials but also cause a majority of complaints among growers. In this study, we hypothesized that trait stability in coffee is genetically controlled and therefore is predictable using molecular information. To test it, we used genome-based methods to predict stability metrics computed with the primary goal of selecting coffee genotypes that combine high phenotypic performance and stability for target environments. Using 2 populations of Coffea canephora, evaluated across multiple years and locations, our contribution is 3-fold: (1) first, we demonstrated that the number of harvest evaluations may be reduced leading to accelerated implementation of molecular breeding; (2) we showed that stability metrics are predictable; and finally, (3) both stable and high-performance genotypes can be simultaneously predicted an... Mostrar Tudo |
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Thesagro: |
Coffea Canephora. |
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Thesaurus NAL: |
Genomics; Genotype; Plant breeding; Prediction. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1159395/1/Genomic-selection-for-genotype.pdf
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Marc: |
LEADER 02692naa a2200289 a 4500
001 2159395
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008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1093/g3journal/jkad062$2DOI
100 1 $aADUNOLA, P.
245 $aGenomic selection for genotype performance and environmental stability in Coffea canéfora.$h[electronic resource]
260 $c2023
520 $aCoffee is one of the most important beverages and trade products in the world. Among the multiple research initiatives focused on coffee sustainability, plant breeding provides the best means to increase phenotypic performance and release cultivars that could meet market demands. Since coffee is well adapted to a diversity of tropical environments, an important question for those confronting the problem of evaluating phenotypic performance is the relevance of genotype-by-environment interaction. As a perennial crop with a long juvenile phase, coffee is subjected to significant temporal and spatial variations. Such facts not only hinder the selection of promising materials but also cause a majority of complaints among growers. In this study, we hypothesized that trait stability in coffee is genetically controlled and therefore is predictable using molecular information. To test it, we used genome-based methods to predict stability metrics computed with the primary goal of selecting coffee genotypes that combine high phenotypic performance and stability for target environments. Using 2 populations of Coffea canephora, evaluated across multiple years and locations, our contribution is 3-fold: (1) first, we demonstrated that the number of harvest evaluations may be reduced leading to accelerated implementation of molecular breeding; (2) we showed that stability metrics are predictable; and finally, (3) both stable and high-performance genotypes can be simultaneously predicted and selected. While this research was carried out on representative environments for coffee production with substantial crossover in genotypic ranking, we anticipate that genomic prediction can be an efficient tool to select coffee genotypes that combine high performance and stability across years and the target locations here evaluated.
650 $aGenomics
650 $aGenotype
650 $aPlant breeding
650 $aPrediction
650 $aCoffea Canephora
700 1 $aFERRÃO, M. A. G.
700 1 $aFERRÃO, R. G.
700 1 $aFONSECA, A. F. A. da
700 1 $aVOLPI, P. S.
700 1 $aCOMÉRIO, M.
700 1 $aVERDIN FILHO, A. C.
700 1 $aMUNOZ, P. R.
700 1 $aFERRÃO, L. F. V.
773 $tG3: Genes, Genomes, Genetics$gv. 13, n. 6, p. 1-13, 2023.
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Embrapa Café (CNPCa) |
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