Data/hora: 10/06/2024 14:11:25

Provedor de dados: | 63
País: | Brazil
Título: | New insights into genomic selection through population-based non-parametric prediction methods
Autores: | Lima,Leísa Pires; Azevedo,Camila Ferreira; Resende,Marcos Deon Vilela de; Silva,Fabyano Fonseca e; Suela,Matheus Massariol; Nascimento,Moysés; Viana,José Marcelo Soriano.
Data: | 2019-07-01
Ano: | 2019
Palavras-chave: | Genomic prediction; Selection index; Genetic gain; Asian rice.
Resumo: | ABSTRACT: Genome-wide selection (GWS) is based on a large number of markers widely distributed throughout the genome. Genome-wide selection provides for the estimation of the effect of each molecular marker on the phenotype, thereby allowing for the capture of all genes affecting the quantitative traits of interest. The main statistical tools applied to GWS are based on random regression or dimensionality reduction methods. In this study a new non-parametric method, called Delta-p was proposed, which was then compared to the Genomic Best Linear Unbiased Predictor (G-BLUP) method. Furthermore, a new selection index combining the genetic values obtained by the G-BLUP and Delta-p, named Delta-p/G-BLUP methods, was proposed. The efficiency of the proposed methods was evaluated through both simulation and real studies. The simulated data consisted of eight scenarios comprising a combination of two levels of heritability, two genetic architectures and two dominance status (absence and complete dominance). Each scenario was simulated ten times. All methods were applied to a real dataset of Asian rice (Oryza sativa) aiming to increase the efficiency of a current breeding program. The methods were compared as regards accuracy of prediction (simulation data) or predictive ability (real dataset), bias and recovery of the true genomic heritability. The results indicated that the proposed Delta-p/G-BLUP index outperformed the other methods in both prediction accuracy and predictive ability.
Tipo: | Info:eu-repo/semantics/article
Idioma: | Inglês
Identificador: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162019001400290
Editor: | São Paulo - Escola Superior de Agricultura "Luiz de Queiroz"
Relação: | 10.1590/1678-992x-2017-0351
Formato: | text/html
Fonte: | Scientia Agricola  v.76 n.4 2019
Fonte: | info:eu-repo/semantics/openAccess