Data/hora: 17/06/2024 15:18:31

Provedor de dados: 	65	
País: 	Brazil	
Título: 	Genome prediction accuracy of common bean via Bayesian models	
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.	
Data: 	2018-01-01	
Ano: 	2018	
Palavras-chave: 	Phaseolus vulgaris; SNP markers; Cross-validation.	
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.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782018000800204	
Editor: 	Universidade Federal de Santa Maria	
Relação: 	10.1590/0103-8478cr20170497	
Formato: 	text/html	
Fonte: 	Ciência Rural  v.48 n.8 2018	
Fonte: 	info:eu-repo/semantics/openAccess