Data/hora: 09/06/2024 23:00:27

Biblioteca(s): 	Embrapa Café.	
Data corrente: 	26/01/2022	
Data da última atualização: 	26/01/2022	
Autoria: 	OLIVEIRA, G. F.; NASCIMENTO, A. C. C.; NASCIMENTO, M.; SANT'ANNA, I. de C.; ROMERO, J. V.; AZEVEDO, C. F.; BHERING, L. L.; CAIXETA, E. T.	
Afiliação: 	GABRIELA FRANÇA OLIVEIRA, UFV; ANA CAROLINA CAMPANA NASCIMENTO, UFV; MOYSÉS NASCIMENTO, UFV; ISABELA DE CASTRO SANT'ANNA, IAC; JUAN VICENTE ROMERO, AGROSAVIA; CAMILA FERREIRA AZEVEDO, UFV; LEONARDO LOPES BHERING, UFV; EVELINE TEIXEIRA CAIXETA MOURA, CNPCa.	
Título: 	Quantile regression in genomic selection for oligogenic traits in autogamous plants: a simulation study.	
Ano de publicação: 	2021	
Fonte/Imprenta: 	Plos One, v. 16, n. 1, e0243666, 2021.	
DOI: 	https://doi.org/10.1371/journal.pone.0243666	
Idioma: 	Inglês	
Conteúdo: 	This study assessed the efficiency of Genomic selection (GS) or genome&#8208;wide selection (GWS), based on Regularized Quantile Regression (RQR), in the selection of genotypes to breed autogamous plant populations with oligogenic traits. To this end, simulated data of an F2 population were used, with traits with different heritability levels (0.10, 0.20 and 0.40), controlled by four genes. The generations were advanced (up to F6) at two selection intensities (10% and 20%). The genomic genetic value was computed by RQR for different quantiles (0.10, 0.50 and 0.90), and by the traditional GWS methods, specifically RR-BLUP and BLASSO. A second objective was to find the statistical methodology that allows the fastest fixation of favorable alleles. In general, the results of the RQR model were better than or equal to those of traditional GWS methodologies, achieving the fixation of favorable alleles in most of the evaluated scenarios. At a heritability level of 0.40 and a selection intensity of 10%, RQR (0.50) was the only methodology that fixed the alleles quickly, i.e., in the fourth generation. Thus, it was concluded that the application of RQR in plant breeding, to simulated autogamous plant populations with oligogenic traits, could reduce time and consequently costs, due to the reduction of selfing generations to fix alleles in the evaluated scenarios.	
Thesagro: 	Regressão Linear; Seleção Genótipa.	
Thesaurus Nal: 	Genomics; Plant breeding; Plant selection guides.	
Categoria do assunto: 	--	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/230507/1/Quantile-regression-in-genomic.pdf	
Registro original: 	Embrapa Café (CNPCa)	
Exemplares: 	CNPCa - (1563-1) - UPC - AP - DD -  -  -  - DIS