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Registro Completo |
Biblioteca(s): |
Embrapa Florestas. |
Data corrente: |
03/12/2019 |
Data da última atualização: |
03/12/2019 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
ANDRADE, L. R. B. de; SOUSA, M. B. e; OLIVEIRA, E. J. de; RESENDE, M. D. V. de; AZEVEDO, C. F. |
Afiliação: |
Luciano Rogério Braatz de Andrade, UFV; Massaine Bandeira e Sousa, Universidade Federal do Recôncavo da Bahia; EDER JORGE DE OLIVEIRA, CNPMF; MARCOS DEON VILELA DE RESENDE, CNPF; Camila Ferreira Azevedo, UFV. |
Título: |
Cassava yield traits predicted by genomic selection methods. |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
PLoS One, v. 14, n. 11, e0224920, Nov. 2019. 22 p. |
DOI: |
10.1371/journal.pone.0224920 |
Idioma: |
Inglês |
Conteúdo: |
Genomic selection (GS) has been used to optimize genetic gains when phenotypic selection is considered costly and difficult to measure. The objective of this work was to evaluate the efficiency and consistency of GS prediction for cassava yield traits (Manihot esculenta Crantz) using different methods, taking into account the effect of population structure. BLUPs and deregressed BLUPs were obtained for 888 cassava accessions and evaluated for fresh root yield, dry root yield and dry matter content in roots in 21 trials conducted from 2011 to 2016. The deregressed BLUPs obtained for the accessions from a 48K single nucleotide polymorphism dataset were used for genomic predictions based on the BayesB, BLASSO, RR-BLUP, G-BLUP and RKHS methods. The accessions? BLUPs were used in the validation step using four cross-validation strategies, taking into account population structure and different GS methods. Similar estimates of predictive ability and bias were identified for the different genomic selection methods in the first cross-validation strategy. Lower predictive ability was observed for fresh root yield (0.4569 ?RR-BLUP to 0.4756?RKHS) and dry root yield (0.4689 ?G-BLUP to 0.4818?RKHS) in comparison with dry matter content (0.5655 ? BLASSO to 0.5670 ?RKHS). However, the RKHS method exhibited higher efficiency and consistency in most of the validation scenarios in terms of prediction ability for fresh root yield and dry root yield. The correlations of the genomic estimated breeding values between the genomic selection methods were quite high (0.99?1.00), resulting in high coincidence of clone selection regardless of the genomic selection method. The deviance analyses within and between the validation clusters formed by the discriminant analysis of principal components were significant for all traits. Therefore, this study indicated that i) the prediction of dry matter content was more accurate compared to that of yield traits, possibly as a result of the smaller influence of non-additive genetic effects; ii) the RKHS method resulted in high and stable prediction ability in most of the validation scenarios; and iii) some kinship between the validation and training populations is desirable in order for genomic selection to succeed due to the significant effect of population structure on genomic selection predictions. MenosGenomic selection (GS) has been used to optimize genetic gains when phenotypic selection is considered costly and difficult to measure. The objective of this work was to evaluate the efficiency and consistency of GS prediction for cassava yield traits (Manihot esculenta Crantz) using different methods, taking into account the effect of population structure. BLUPs and deregressed BLUPs were obtained for 888 cassava accessions and evaluated for fresh root yield, dry root yield and dry matter content in roots in 21 trials conducted from 2011 to 2016. The deregressed BLUPs obtained for the accessions from a 48K single nucleotide polymorphism dataset were used for genomic predictions based on the BayesB, BLASSO, RR-BLUP, G-BLUP and RKHS methods. The accessions? BLUPs were used in the validation step using four cross-validation strategies, taking into account population structure and different GS methods. Similar estimates of predictive ability and bias were identified for the different genomic selection methods in the first cross-validation strategy. Lower predictive ability was observed for fresh root yield (0.4569 ?RR-BLUP to 0.4756?RKHS) and dry root yield (0.4689 ?G-BLUP to 0.4818?RKHS) in comparison with dry matter content (0.5655 ? BLASSO to 0.5670 ?RKHS). However, the RKHS method exhibited higher efficiency and consistency in most of the validation scenarios in terms of prediction ability for fresh root yield and dry root yield. The correlations of the genomic estimated br... Mostrar Tudo |
Palavras-Chave: |
Genomic predictions; Heredity. |
Thesagro: |
Mandioca; Melhoramento Genético Vegetal. |
Thesaurus Nal: |
Cassava; Plant breeding. |
Categoria do assunto: |
G Melhoramento Genético |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/205981/1/2019-M.Deon-PO-Cassava.pdf
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Marc: |
LEADER 03091naa a2200253 a 4500 001 2115740 005 2019-12-03 008 2019 bl uuuu u00u1 u #d 024 7 $a10.1371/journal.pone.0224920$2DOI 100 1 $aANDRADE, L. R. B. de 245 $aCassava yield traits predicted by genomic selection methods.$h[electronic resource] 260 $c2019 520 $aGenomic selection (GS) has been used to optimize genetic gains when phenotypic selection is considered costly and difficult to measure. The objective of this work was to evaluate the efficiency and consistency of GS prediction for cassava yield traits (Manihot esculenta Crantz) using different methods, taking into account the effect of population structure. BLUPs and deregressed BLUPs were obtained for 888 cassava accessions and evaluated for fresh root yield, dry root yield and dry matter content in roots in 21 trials conducted from 2011 to 2016. The deregressed BLUPs obtained for the accessions from a 48K single nucleotide polymorphism dataset were used for genomic predictions based on the BayesB, BLASSO, RR-BLUP, G-BLUP and RKHS methods. The accessions? BLUPs were used in the validation step using four cross-validation strategies, taking into account population structure and different GS methods. Similar estimates of predictive ability and bias were identified for the different genomic selection methods in the first cross-validation strategy. Lower predictive ability was observed for fresh root yield (0.4569 ?RR-BLUP to 0.4756?RKHS) and dry root yield (0.4689 ?G-BLUP to 0.4818?RKHS) in comparison with dry matter content (0.5655 ? BLASSO to 0.5670 ?RKHS). However, the RKHS method exhibited higher efficiency and consistency in most of the validation scenarios in terms of prediction ability for fresh root yield and dry root yield. The correlations of the genomic estimated breeding values between the genomic selection methods were quite high (0.99?1.00), resulting in high coincidence of clone selection regardless of the genomic selection method. The deviance analyses within and between the validation clusters formed by the discriminant analysis of principal components were significant for all traits. Therefore, this study indicated that i) the prediction of dry matter content was more accurate compared to that of yield traits, possibly as a result of the smaller influence of non-additive genetic effects; ii) the RKHS method resulted in high and stable prediction ability in most of the validation scenarios; and iii) some kinship between the validation and training populations is desirable in order for genomic selection to succeed due to the significant effect of population structure on genomic selection predictions. 650 $aCassava 650 $aPlant breeding 650 $aMandioca 650 $aMelhoramento Genético Vegetal 653 $aGenomic predictions 653 $aHeredity 700 1 $aSOUSA, M. B. e 700 1 $aOLIVEIRA, E. J. de 700 1 $aRESENDE, M. D. V. de 700 1 $aAZEVEDO, C. F. 773 $tPLoS One$gv. 14, n. 11, e0224920, Nov. 2019. 22 p.
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Embrapa Florestas (CNPF) |
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Registro Completo
Biblioteca(s): |
Embrapa Hortaliças. |
Data corrente: |
17/03/2010 |
Data da última atualização: |
04/02/2020 |
Tipo da produção científica: |
Artigo em Anais de Congresso / Nota Técnica |
Autoria: |
ANDRADE, C. de; ALCÂNTARA, F. A. de; MADEIRA, N. R.; MACÊDO, R. H.; FERNANDES, R. |
Afiliação: |
CASSIANO DE ANDRADE, FACULDADE DA TERRA DE BRASÍLIA; FLAVIA APARECIDA DE ALCÂNTARA, CNPH; NUNO RODRIGO MADEIRA, CNPH; RAISSA HAMANDA MACÊDO, FACULDADE DA TERRA DE BRASÍLIA; RODRIGO FERNANDES, FACULDADE DA TERRA DE BRASÍLIA. |
Título: |
Erosão hídrica em um Latossolo Vermelho cultivado com hortaliças sob diferentes sistemas de manejo. |
Ano de publicação: |
2009 |
Fonte/Imprenta: |
In: CONGRESSO BRASILEIRO DE CIÊNCIA DO SOLO, 32., 2009, Fortaleza. O solo e a produção de bioenergia: perspectivas e desafios: resumos. [Viçosa, MG]: SBCS; Fortaleza: UFC, 2009. |
Idioma: |
Português |
Thesagro: |
Allium Cepa; Cebola; Chuva; Erosão Hídrica; Hortaliça; Manejo do Solo; Matéria Orgânica; Nutriente; Plantio Direto. |
Categoria do assunto: |
-- |
Marc: |
LEADER 00877nam a2200253 a 4500 001 1783028 005 2020-02-04 008 2009 bl uuuu u00u1 u #d 100 1 $aANDRADE, C. de 245 $aErosão hídrica em um Latossolo Vermelho cultivado com hortaliças sob diferentes sistemas de manejo.$h[electronic resource] 260 $aIn: CONGRESSO BRASILEIRO DE CIÊNCIA DO SOLO, 32., 2009, Fortaleza. O solo e a produção de bioenergia: perspectivas e desafios: resumos. [Viçosa, MG]: SBCS; Fortaleza: UFC$c2009 650 $aAllium Cepa 650 $aCebola 650 $aChuva 650 $aErosão Hídrica 650 $aHortaliça 650 $aManejo do Solo 650 $aMatéria Orgânica 650 $aNutriente 650 $aPlantio Direto 700 1 $aALCÂNTARA, F. A. de 700 1 $aMADEIRA, N. R. 700 1 $aMACÊDO, R. H. 700 1 $aFERNANDES, R.
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