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

PLoS One. 2023 Apr 7;18(4):e0275407. doi: 10.1371/journal.pone.0275407. eCollection 2023.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Euterpe*
  • Genome
  • Genomics / methods
  • Genotype
  • Models, Genetic
  • Phenotype
  • Plant Breeding
  • Polymorphism, Single Nucleotide

Grants and funding

We thank the Conselho Nacional de Pesquisa (CNPq, Brazil) (Researcher productivity fellowship AF and MFSF), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, Brazil) – Finance Code 001, and the Fundação de Amparo à Pesquisa do Espírito Santo (FAPES, Vitória – ES, Brazil) in partnership with VALE, for the financial support to this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.