| Registro completo |
| Provedor de dados: |
Ciência Rural
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| País: |
Brazil
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| Título: |
Genome prediction accuracy of common bean via Bayesian models
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| Autores: |
Barili,Leiri Daiane
Vale,Naine Martins do
Silva,Fabyano Fonseca e
Carneiro,José Eustáquio de Souza
Oliveira,Hinayah Rojas de
Vianello,Rosana Pereira
Valdisser,Paula Arielle Mendes Ribeiro
Nascimento,Moyses
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| Data: |
2018-01-01
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| Ano: |
2018
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| Palavras-chave: |
Phaseolus vulgaris
SNP markers
Cross-validation
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| Resumo: |
ABSTRACT: We aimed to apply genomic information based on SNP (single nucleotide polymorphism) markers for the genetic evaluation of the traits “stay-green” (SG), plant architecture (PA), grain aspect (GA) and grain yield (GY) in common bean through Bayesian models. These models were compared in terms of prediction accuracy and ability for heritability estimation for each one of the mentioned traits. A total of 80 cultivars were genotyped for 377 SNP markers, whose effects were estimated by five different Bayesian models: Bayes A (BA), B (BB), C (BC), LASSO (BL) e Ridge regression (BRR). Although, prediction accuracies calculated by means of cross-validation have been similar within each trait, the BB model stood out for the trait SG, whereas the BRR was indicated for the remaining traits. The heritability estimates for the traits SG, PA, GA and GY were 0.61, 0.28, 0.32 and 0.29, respectively. In summary, the Bayesian methods applied here were effective and ease to be implemented. The used SNP markers can help in the early selection of promising genotypes, since incorporating genomic information increase the prediction accuracy of the estimated genetic merit.
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| Tipo: |
Info:eu-repo/semantics/article
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| Idioma: |
Inglês
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| Identificador: |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782018000800204
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| Editor: |
Universidade Federal de Santa Maria
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| Relação: |
10.1590/0103-8478cr20170497
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| Formato: |
text/html
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| Fonte: |
Ciência Rural v.48 n.8 2018
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| Direitos: |
info:eu-repo/semantics/openAccess
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