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Single and multi-trait genomic prediction for agronomic traits in Euterpe edulis.

Guilherme Bravim CanalCynthia Aparecida Valiati BarretoFrancine Alves Nogueira de AlmeidaIasmine Ramos ZaidanDiego Pereira do CoutoCamila Ferreira AzevedoMoysés NascimentoMarcia Flores da Silva FerreiraAdésio Ferreira
Published in: PloS one (2023)
Popularly known as juçaizeiro, Euterpe edulis has been gaining prominence in the fruit growing sector and has demanded the development of superior genetic materials. Since it is a native species and still little studied, the application of more sophisticated techniques can result in higher gains with less time. Until now, there are no studies that apply genomic prediction for this crop, especially in multi-trait analysis. In this sense, this study aimed to apply new methods and breeding techniques for the juçaizeiro, to optimize this breeding program through the application of genomic prediction. This data consisted of 275 juçaizeiro genotypes from a population of Rio Novo do Sul-ES, Brazil. The genomic prediction was performed using the multi-trait (G-BLUP MT) and single-trait (G-BLUP ST) models and the selection of superior genotypes was based on a selection index. Similar results for predictive ability were observed for both models. However, the G-BLUP ST model provided greater selection gains when compared to the G-BLUP MT. For this reason, the genomic estimated breeding values (GEBVs) from the G-BLUP ST, were used to select the six superior genotypes (UFES.A.RN.390, UFES.A.RN.386, UFES.A.RN.080, UFES.A.RN.383, UFES.S.RN.098, and UFES.S.RN.093). This was intended to provide superior genetic materials for the development of seedlings and implantation of productive orchards, which will meet the demands of the productive, industrial and consumer market.
Keyphrases
  • genome wide
  • copy number
  • dna methylation
  • gene expression
  • electronic health record
  • climate change
  • quality improvement
  • machine learning
  • health insurance
  • risk assessment
  • genetic diversity