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Registro Completo |
Biblioteca(s): |
Embrapa Florestas. |
Data corrente: |
16/12/2019 |
Data da última atualização: |
16/12/2019 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
SILVEIRA, L. S.; MARTINS FILHO, S.; AZEVEDO, C. F.; BARBOSA, E. C.; RESENDE, M. D. V. de; TAKAHASHI, E. K. |
Afiliação: |
L. S. Silveira, UFV; S. Martins Filho, UFV; C. F. Azevedo, UFV; E. C. Barbosa, UFV; MARCOS DEON VILELA DE RESENDE, CNPF; E. K. Takahashi, CENIBRA. |
Título: |
Bayesian models applied to genomic selection for categorical traits. |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
Genetics and Molecular Research, v. 18, n. 4: gmr18490, 2019. 10 p. |
DOI: |
10.4238/gmr18490 |
Idioma: |
Inglês |
Conteúdo: |
We compared two statistical methodologies applied to genetic and genomic analyses of categorical traits. The first one consists of a Bayesian approach to the Bayesian Linear Mixed Model (BLMM), which addresses the statistical problems of genomic prediction. The second methodology, called Bayesian Generalized Linear Mixed Model (BGLMM) is similar, but it is used when the distribution of the response variable is not Gaussian, as in the case of disease resistance phenotype categories. These models were compared according to predictive ability, bias, computational time and cross validation error rate (CVER). Additionally, an alternative classification method for the BLMM was proposed, which allowed us to obtain the CVER for this model. Estimates of the genetic parameters were obtained using BLASSO (Bayesian Least Absolute Shrinkage and Selection Operator) and Bayesian G-BLUP (Genomic Best Linear Unbiased Prediction) estimation methods applied to BLMM and BGLMM. The models were applied in two scenarios, with two and four classes for the phenotype of resistance to rust disease caused by the pathogen Puccinia psidii and classified as reaction types (two classes) and infection levels (four classes) recorded for 559 trees of Eucalyptus urophylla with 24,806 SNP markers. Modeling this trait through SNPs allow the next generation of plants to be selected early, reducing time and costs. We found the same predictive ability for both models and a bias value closer to the ideal for BLMM (GBLUP). The BGLMM had the best CVER (0.29 against 0.32 and 0.47 against 0.51 for 2 and 4 categories, respectively), BLMM had a three times shorter computational time, and though BLMM is not the most appropriate model for handling categorical data, this model presented similar responses to BGLMM. Thus, we consider it as an appropriate alternative for categorical data modeling. MenosWe compared two statistical methodologies applied to genetic and genomic analyses of categorical traits. The first one consists of a Bayesian approach to the Bayesian Linear Mixed Model (BLMM), which addresses the statistical problems of genomic prediction. The second methodology, called Bayesian Generalized Linear Mixed Model (BGLMM) is similar, but it is used when the distribution of the response variable is not Gaussian, as in the case of disease resistance phenotype categories. These models were compared according to predictive ability, bias, computational time and cross validation error rate (CVER). Additionally, an alternative classification method for the BLMM was proposed, which allowed us to obtain the CVER for this model. Estimates of the genetic parameters were obtained using BLASSO (Bayesian Least Absolute Shrinkage and Selection Operator) and Bayesian G-BLUP (Genomic Best Linear Unbiased Prediction) estimation methods applied to BLMM and BGLMM. The models were applied in two scenarios, with two and four classes for the phenotype of resistance to rust disease caused by the pathogen Puccinia psidii and classified as reaction types (two classes) and infection levels (four classes) recorded for 559 trees of Eucalyptus urophylla with 24,806 SNP markers. Modeling this trait through SNPs allow the next generation of plants to be selected early, reducing time and costs. We found the same predictive ability for both models and a bias value closer to the ideal for BLMM (G... Mostrar Tudo |
Palavras-Chave: |
Bayesian inference; Statistical methods. |
Thesagro: |
Melhoramento Genético Vegetal. |
Thesaurus Nal: |
Genetic improvement; Plant breeding. |
Categoria do assunto: |
G Melhoramento Genético |
Marc: |
LEADER 02649naa a2200253 a 4500 001 2116962 005 2019-12-16 008 2019 bl uuuu u00u1 u #d 024 7 $a10.4238/gmr18490$2DOI 100 1 $aSILVEIRA, L. S. 245 $aBayesian models applied to genomic selection for categorical traits.$h[electronic resource] 260 $c2019 520 $aWe compared two statistical methodologies applied to genetic and genomic analyses of categorical traits. The first one consists of a Bayesian approach to the Bayesian Linear Mixed Model (BLMM), which addresses the statistical problems of genomic prediction. The second methodology, called Bayesian Generalized Linear Mixed Model (BGLMM) is similar, but it is used when the distribution of the response variable is not Gaussian, as in the case of disease resistance phenotype categories. These models were compared according to predictive ability, bias, computational time and cross validation error rate (CVER). Additionally, an alternative classification method for the BLMM was proposed, which allowed us to obtain the CVER for this model. Estimates of the genetic parameters were obtained using BLASSO (Bayesian Least Absolute Shrinkage and Selection Operator) and Bayesian G-BLUP (Genomic Best Linear Unbiased Prediction) estimation methods applied to BLMM and BGLMM. The models were applied in two scenarios, with two and four classes for the phenotype of resistance to rust disease caused by the pathogen Puccinia psidii and classified as reaction types (two classes) and infection levels (four classes) recorded for 559 trees of Eucalyptus urophylla with 24,806 SNP markers. Modeling this trait through SNPs allow the next generation of plants to be selected early, reducing time and costs. We found the same predictive ability for both models and a bias value closer to the ideal for BLMM (GBLUP). The BGLMM had the best CVER (0.29 against 0.32 and 0.47 against 0.51 for 2 and 4 categories, respectively), BLMM had a three times shorter computational time, and though BLMM is not the most appropriate model for handling categorical data, this model presented similar responses to BGLMM. Thus, we consider it as an appropriate alternative for categorical data modeling. 650 $aGenetic improvement 650 $aPlant breeding 650 $aMelhoramento Genético Vegetal 653 $aBayesian inference 653 $aStatistical methods 700 1 $aMARTINS FILHO, S. 700 1 $aAZEVEDO, C. F. 700 1 $aBARBOSA, E. C. 700 1 $aRESENDE, M. D. V. de 700 1 $aTAKAHASHI, E. K. 773 $tGenetics and Molecular Research$gv. 18, n. 4: gmr18490, 2019. 10 p.
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Embrapa Florestas (CNPF) |
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Registros recuperados : 33 | |
5. | | BUDZINSKI, I. G. F.; LEITE, T. F.; TAKAHASHI, E. K.; PEREIRA, L. F. P.; VIEIRA, L. G. E. Coffea expansin gene family and expansin expression during fruit maturation. In:INTERNATIONAL CONFERENCE ON COFFEE SCIENCE, 21., 2006, Montpellier, France. Table of contents... Montpellier, France: Association for Science and Information on Coffee, 2007. 1 CD-ROM.Tipo: Artigo em Anais de Congresso |
Biblioteca(s): Embrapa Café. |
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6. | | SANTOS, T. B.; MAGALHÃES, D. M.; TAKAHASHI, E. K.; MARUR, C. J.; PEREIRA, L. F. P.; VIEIRA, L. G. E. Galactinol synthase gene expression in Coffea arabica L. under water stress. In:INTERNATIONAL CONFERENCE ON COFFEE SCIENCE, 21., 2006, Montpellier, France. Table of contents... Montpellier, France: Association for Science and Information on Coffee, 2007. 1 CD-ROM.Tipo: Artigo em Anais de Congresso |
Biblioteca(s): Embrapa Café. |
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8. | | 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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9. | | CASTRO, C. A. de O.; SOUZA, G. A. de; SANTOS, G. A. dos; RESENDE, M. D. V. de; TAKAHASHI, E. K.; LEITE, F. P. Aceleração do florescimento em genótipos autofecundados e florescimento ultra-precoce de mudas jovens de eucalyptus por top graftings. Boletim Técnico Sif, v. 1, n. 4, p. 1-6, 2021.Tipo: Artigo em Periódico Indexado | Circulação/Nível: C - 0 |
Biblioteca(s): Embrapa Café. |
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10. | | CASTRO, C. A. de O.; SANTOS, G. A. dos; TAKAHASHI, E. K.; NUNES, A. C. P.; SOUZA, G. A.; RESENDE, M. D. V. de. Accelerating Eucalyptus breeding strategies through top grafting applied to young seedlings. Industrial Crops and Products, v. 171, n. 1, 113906, 2021.Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
Biblioteca(s): Embrapa Café. |
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12. | | NOGUEIRA, T. A. P. C.; NUNES, A. C. P.; SANTOS, G. A. dos; TAKAHASHI, E. K.; RESENDE, M. D. V. de; CORRADI, I. S. Estimativa de parâmetros genéticos em progênies de irmãos completos de eucalipto e otimização de seleção. Scientia Forestalis, v. 47, n. 123, p. 451-462, set. 2019.Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 1 |
Biblioteca(s): Embrapa Florestas. |
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13. | | GRATTAPAGLIA, D.; RESENDE, M. D. V. de; RESENDE, M. R.; SANSALONI, C. P.; PETROLI, C. D.; MISSIAGGIA, A. A.; TAKAHASHI, E. K.; ZAMPROGNO, K. C.; KILIAN, A. Genomic selection for growth traits in Eucalyptus: accuracy within and across breeding populations. In: IUFRO TREE BIOTECHNOLOGY CONFERENCE, 2011, Arraial d'Ajuda. From genomes do integration and delivery: extended abstracts proceedings. [S.l.]: Embrapa: Veracel: IUFRO, 2011.Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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14. | | GRATTAPAGLIA, D.; RESENDE, M. D. V. de; RESENDE, M. R.; SANSALONI, C. P.; PETROLI, C. D.; MISSIAGGIA, A. A.; TAKAHASHI, E. K.; ZAMPROGNO, K. C.; KILIAN, A. Genomic selection for growth traits in Eucalyptus: accuracy within and across breeding populations. In: IUFRO TREE BIOTECHNOLOGY CONFERENCE, 2011, Arraial d'Ajuda. From genomes do integration and delivery: extended abstracts proceedings. [S.l.]: Embrapa: Veracel: IUFRO, 2011. 1 CD-ROMTipo: Artigo em Anais de Congresso |
Biblioteca(s): Embrapa Florestas. |
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15. | | 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.Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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16. | | 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.Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Florestas. |
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17. | | GRATTAPAGLIA, D.; SANSALONI, C.; PETROLI, C.; RESENDE JÚNIOR, M. F.; FARIA, D.; MISSIAGGIA, A. A.; TAKAHASHI. E. K.; ZAMPROGNO, K.; KILIAN, A.; RESENDE, M. D. V. de. Realized accuracies of Genomic Selection for volume growth in tropical Eucalyptus: marker assisted selection coming to reality in forest trees. In: CONGRESSO BRASILEIRO DE GENÉTICA, 56., 2010, Guarujá. Resumos... [Curitiba]: UFPR, 2010. p. 192.Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Florestas. |
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18. | | RESENDE, R. T.; RESENDE, M. D. V. de; SILVA, F. F. S.; AZEVEDO, C. F. A.; TAKAHASHI, E. K. T.; SILVA JUNIOR, O. B. da; GRATTAPAGLIA, D. Regional heritability mapping and genome-wide association identify loci for complex growth, wood and disease resistance traits in Eucalyptus. New Phytologist, v. 213, p. 1287-1300, 2017.Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
Biblioteca(s): Embrapa Florestas; Embrapa Recursos Genéticos e Biotecnologia. |
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19. | | GRATTAPAGLIA, D.; RESENDE, M. D. V. de; RESENDE, M. F. R.; SANSALONI, C. P.; PETROLI, C. D.; MISSIAGGIA, A. A.; TAKAHASHI, E. K.; ZAMPROGNO, K. C.; KILIAN, A. High realized accuracies of genomic selection for volume growth and wood density in Eucalyptus breeding populations with contrasting effective sizes. In: PLANT & ANIMAL GENOMES CONFERENCE, 19., 2011, San Diego. Conference... [S.l.]: International Plant & Animal Genome, 2011. Abstract. W235: Forest Trees.Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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20. | | GRATTAPAGLIA, D.; RESENDE, M. D. V. de; RESENDE, M. F. R.; SANSALONI, C. P.; PETROLI, C. D.; MISSIAGGIA, A. A.; TAKAHASHI, E. K.; ZAMPROGNO, K. C.; KILIAN, A. High realized accuracies of genomic selection for volume growth and wood density in Eucalyptus breeding populations with contrasting effective sizes. In: PLANT & ANIMAL GENOMES CONFERENCE, 19., 2011, San Diego. Conference... [S.l.]: International Plant & Animal Genome, 2011. W235: Forest Trees.Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Florestas. |
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Registros recuperados : 33 | |
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Nenhum registro encontrado para a expressão de busca informada. |
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