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 | Acesso ao texto completo restrito à biblioteca da Embrapa Florestas. Para informações adicionais entre em contato com cnpf.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Café; Embrapa Florestas. |
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Data corrente: |
05/01/2021 |
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Data da última atualização: |
05/01/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SIMIQUELI; RESENDE, M. D. V. de. |
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Afiliação: |
Guilherme Ferreira Simiqueli, UFV; MARCOS DEON VILELA DE RESENDE, CNPF. |
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Título: |
Entropy and mutual information in genome-wide selection: the splitting of k-fold cross-validation sets and implications for tree breeding. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Tree Genetics & Genomes, v. 16, article number 37, 2020. 14 p. |
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DOI: |
https://doi.org/10.1007/s11295-020-01430-6 |
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Idioma: |
Inglês |
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Conteúdo: |
Random k-fold cross-validation in genome-wide selection (GWS) can help to estimate predictive ability (ryy^). Predictive ability tends to be higher when training, and validation sets present a high degree of kinship. However, many tree breeding populations are less genetically related to the training sets and have different levels of phenotypic diversity. Therefore, this study proposes methods of splitting k-fold cross-validation sets to optimize ryy^ estimates that are consistent with the breeding population and verify the impact of phenotypic and genotypic distribution on GWS. Using a simulated Eucalyptus trait (h2=0.5) and Pinus taeda L. data for diameter at breast height (h2=0.31), six methods were developed based on mutual information (I) and entropy (H) for measuring genetic similarity and phenotypic dissimilarity, respectively. All methods were evaluated for ryy^, bias, minimum squared error of prediction, and genomic heritability. The Pearson correlations of these parameters with the kinship coefficient, and I and H between and within training and validation sets were also estimated. Our results show that closer genetic similarity did not significantly increase ryy^ and that a lower H reduced ryy^ and overestimated genomic breeding values. Consequently, phenotypic diversity (high H) should be added to tree breeding populations to increase genetic gain and reduce bias. The new methods accurately fitted models according to the entropy of tree breeding populations and their genetic relationship to the training sets. Therefore, these methods provided usable estimates of genetic gain to produce consistent success of long-term tree breeding programs. MenosRandom k-fold cross-validation in genome-wide selection (GWS) can help to estimate predictive ability (ryy^). Predictive ability tends to be higher when training, and validation sets present a high degree of kinship. However, many tree breeding populations are less genetically related to the training sets and have different levels of phenotypic diversity. Therefore, this study proposes methods of splitting k-fold cross-validation sets to optimize ryy^ estimates that are consistent with the breeding population and verify the impact of phenotypic and genotypic distribution on GWS. Using a simulated Eucalyptus trait (h2=0.5) and Pinus taeda L. data for diameter at breast height (h2=0.31), six methods were developed based on mutual information (I) and entropy (H) for measuring genetic similarity and phenotypic dissimilarity, respectively. All methods were evaluated for ryy^, bias, minimum squared error of prediction, and genomic heritability. The Pearson correlations of these parameters with the kinship coefficient, and I and H between and within training and validation sets were also estimated. Our results show that closer genetic similarity did not significantly increase ryy^ and that a lower H reduced ryy^ and overestimated genomic breeding values. Consequently, phenotypic diversity (high H) should be added to tree breeding populations to increase genetic gain and reduce bias. The new methods accurately fitted models according to the entropy of tree breeding populations and t... Mostrar Tudo |
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Palavras-Chave: |
Genetic gain; Genome-wide selection; Mutual information. |
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Thesagro: |
Eucalipto. |
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Thesaurus Nal: |
Entropy; Eucalyptus; Pinus. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
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001 2128975
005 2021-01-05
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1007/s11295-020-01430-6$2DOI
100 1 $aSIMIQUELI
245 $aEntropy and mutual information in genome-wide selection$bthe splitting of k-fold cross-validation sets and implications for tree breeding.$h[electronic resource]
260 $c2020
520 $aRandom k-fold cross-validation in genome-wide selection (GWS) can help to estimate predictive ability (ryy^). Predictive ability tends to be higher when training, and validation sets present a high degree of kinship. However, many tree breeding populations are less genetically related to the training sets and have different levels of phenotypic diversity. Therefore, this study proposes methods of splitting k-fold cross-validation sets to optimize ryy^ estimates that are consistent with the breeding population and verify the impact of phenotypic and genotypic distribution on GWS. Using a simulated Eucalyptus trait (h2=0.5) and Pinus taeda L. data for diameter at breast height (h2=0.31), six methods were developed based on mutual information (I) and entropy (H) for measuring genetic similarity and phenotypic dissimilarity, respectively. All methods were evaluated for ryy^, bias, minimum squared error of prediction, and genomic heritability. The Pearson correlations of these parameters with the kinship coefficient, and I and H between and within training and validation sets were also estimated. Our results show that closer genetic similarity did not significantly increase ryy^ and that a lower H reduced ryy^ and overestimated genomic breeding values. Consequently, phenotypic diversity (high H) should be added to tree breeding populations to increase genetic gain and reduce bias. The new methods accurately fitted models according to the entropy of tree breeding populations and their genetic relationship to the training sets. Therefore, these methods provided usable estimates of genetic gain to produce consistent success of long-term tree breeding programs.
650 $aEntropy
650 $aEucalyptus
650 $aPinus
650 $aEucalipto
653 $aGenetic gain
653 $aGenome-wide selection
653 $aMutual information
700 1 $aRESENDE, M. D. V. de
773 $tTree Genetics & Genomes$gv. 16, article number 37, 2020. 14 p.
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Registro original: |
Embrapa Florestas (CNPF) |
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Biblioteca(s): |
Embrapa Gado de Corte. |
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Data corrente: |
20/11/2013 |
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Data da última atualização: |
20/11/2013 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
MARTINS, L. B.; BARRIOS, S. C. L.; VALLE, C. B. do; FIGUEIREDO, U. J. DE; FARIA, T. A. C. |
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Afiliação: |
LUCAS BEARARI MARTINS, Acadêmico de Agronomia da Universidade Católica Dom Bosco - UCDB; SANZIO CARVALHO LIMA BARRIOS, CNPGC; CACILDA BORGES DO VALLE, CNPGC; Doutorando do Programa de Pós-graduação em Genética e Melhoramento de Plantas – UFLA/Lavras.; Acadêmica de Agronomia da Universidade Estadual de Mato Grosso do Sul - UEMS. |
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Título: |
Avaliação da produção de sementes de híbridos de Brachiaria decumbens |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
In: JORNADA CIENTÍFICA EMBRAPA GADO DE CORTE, 9., 2013, Campo Grande, MS. [Anais da..]. Campo Grande, MS: Embrapa Gado de Corte, 2013. |
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Série: |
(Embrapa Gado de Corte. Documentos, 204). |
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Idioma: |
Português |
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Notas: |
Comissão organizadora: Denise Baptaglin Montagner, Grácia Maria Soares Rosinha, Rodrigo Carvalho Alva |
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Palavras-Chave: |
Brachiaria decumbens cv. Basilik. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/92805/1/Lucas-Bearari-Martins-DOC204-5.pdf
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Marc: |
LEADER 00780nam a2200181 a 4500
001 1971682
005 2013-11-20
008 2013 bl uuuu u00u1 u #d
100 1 $aMARTINS, L. B.
245 $aAvaliação da produção de sementes de híbridos de Brachiaria decumbens$h[electronic resource]
260 $aIn: JORNADA CIENTÍFICA EMBRAPA GADO DE CORTE, 9., 2013, Campo Grande, MS. [Anais da..]. Campo Grande, MS: Embrapa Gado de Corte$c2013
490 $a(Embrapa Gado de Corte. Documentos, 204).
500 $aComissão organizadora: Denise Baptaglin Montagner, Grácia Maria Soares Rosinha, Rodrigo Carvalho Alva
653 $aBrachiaria decumbens cv. Basilik
700 1 $aBARRIOS, S. C. L.
700 1 $aVALLE, C. B. do
700 1 $aFIGUEIREDO, U. J. DE
700 1 $aFARIA, T. A. C.
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