Genomic selection to resistance to Stenocarpella maydis in maize lines using DArTseq markers

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorSantos, Jhonathan Pedroso Rigal dos-
Autor(es): dc.creatorPires, Luiz Paulo Miranda-
Autor(es): dc.creatorVasconcellos, Renato Coelho de Castro-
Autor(es): dc.creatorPereira, Gabriela Santos-
Autor(es): dc.creatorVon Pinho, Renzo Garcia-
Autor(es): dc.creatorBalestre, Marcio-
Data de aceite: dc.date.accessioned2026-02-09T12:35:36Z-
Data de disponibilização: dc.date.available2026-02-09T12:35:36Z-
Data de envio: dc.date.issued2019-02-05-
Data de envio: dc.date.issued2019-02-05-
Data de envio: dc.date.issued2016-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/32730-
Fonte completa do material: dc.identifierhttps://link.springer.com/article/10.1186/s12863-016-0392-3-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1164407-
Descrição: dc.descriptionBackground: The identification of lines resistant to ear diseases is of great importance in maize breeding because such diseases directly interfere with kernel quality and yield. Among these diseases, ear rot disease is widely relevant due to significant decrease in grain yield. Ear rot may be caused by the fungus Stenocarpella maydi; however, little information about genetic resistance to this pathogen is available in maize, mainly related to candidate genes in genome. In order to exploit this genome information we used 23.154 Dart-seq markers in 238 lines and apply genome-wide selection to select resistance genotypes. We divide the lines into clusters to identify groups related to resistance to Stenocarpella maydi and use Bayesian stochastic search variable approach and rr-BLUP methods to comparate their selection results. Results: Through a principal component analysis (PCA) and hierarchical clustering, it was observed that the three main genetic groups (Stiff Stalk Synthetic, Non-Stiff Stalk Synthetic and Tropical) were clustered in a consistent manner, and information on the resistance sources could be obtained according to the line of origin where populations derived from genetic subgroup Suwan presenting higher levels of resistance. The ridge regression best linear unbiased prediction (rr-BLUP) and Bayesian stochastic search variable (BSSV) models presented equivalent abilities regarding predictive processes. Conclusion: Our work showed that is possible to select maize lines presenting a high resistance to Stenocarpella maydis. This claim is based on the acceptable level of predictive accuracy obtained by Genome-wide Selection (GWS) using different models. Furthermore, the lines related to background Suwan present a higher level of resistance than lines related to other groups.-
Idioma: dc.languageen-
Publicador: dc.publisherSpringer-
Direitos: dc.rightsrestrictAccess-
???dc.source???: dc.sourceBMC Genetics-
Palavras-chave: dc.subjectEar rot-
Palavras-chave: dc.subjectGenetic groups-
Palavras-chave: dc.subjectRidge regression best linear unbiased prediction-
Palavras-chave: dc.subjectBayesian stochastic search variable-
Título: dc.titleGenomic selection to resistance to Stenocarpella maydis in maize lines using DArTseq markers-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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