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

Author

Listed:
  • Guilherme Bravim Canal
  • Cynthia Aparecida Valiati Barreto
  • Francine Alves Nogueira de Almeida
  • Iasmine Ramos Zaidan
  • Diego Pereira do Couto
  • Camila Ferreira Azevedo
  • Moysés Nascimento
  • Marcia Flores da Silva Ferreira
  • Adésio Ferreira

Abstract

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.

Suggested Citation

  • Guilherme Bravim Canal & Cynthia Aparecida Valiati Barreto & Francine Alves Nogueira de Almeida & Iasmine Ramos Zaidan & Diego Pereira do Couto & Camila Ferreira Azevedo & Moysés Nascimento & Marcia F, 2023. "Single and multi-trait genomic prediction for agronomic traits in Euterpe edulis," PLOS ONE, Public Library of Science, vol. 18(4), pages 1-19, April.
  • Handle: RePEc:plo:pone00:0275407
    DOI: 10.1371/journal.pone.0275407
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    References listed on IDEAS

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    1. Giovanny Covarrubias-Pazaran, 2016. "Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-15, June.
    2. Carolina Sansaloni & Jorge Franco & Bruno Santos & Lawrence Percival-Alwyn & Sukhwinder Singh & Cesar Petroli & Jaime Campos & Kate Dreher & Thomas Payne & David Marshall & Benjamin Kilian & Iain Miln, 2020. "Diversity analysis of 80,000 wheat accessions reveals consequences and opportunities of selection footprints," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
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