PLoS ONEGeneticsPeer-reviewed journal article
Single and Multi-trait Genomic Prediction for agronomic traits in Euterpe edulis
Guilherme Bravim CanaliD, Cynthia Aparecida Valiati BarretoiD, Francine Alves Nogueira de AlmeidaiD, Iasmine Ramos ZaidaniD, Diego Pereira do Couto, Camila Ferreira AzevedoiD, Moysés NascimentoiD, Márcia Flores da Silva FerreiraiD, Adésio FerreiraiD
Abstract
Popularly known as jucaizeiro, Euterpe edulis has been gaining prominence in the fruit growing sector and has demanded the development of superior genetic materials. As 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 jucaizeiro, to optimize this breeding program through the application of genomic selection. This data consisted of 275 jucaizeiro 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 matrices was based on the selection index of Mulamba and Mock. 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), 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. Key messageIn the first genomic selection study for Euterpe edulis, substantial gains for multiple traits of fruit production was reported. This is a key factor for the sustainable use of the species in the Atlantic Forest.
- organism: E. coli
- assay: whole-genome sequencing
- research focus: variant calling
- approach: statistical model
- Citations
- 6
- FWCI
- 0.99
- Field percentile
- top 27%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Evaluating the accuracy of genomic prediction of growth and wood traits in two Eucalyptus species and their F1 hybrids
Biyue Tan, Dario G. Grattapaglia, … Pär K. Ingvarsson·BMC Plant BiologyPeer-reviewed·Jun 29, 2017
- Genomic Selection in Rubber Tree Breeding: A Comparison of Models and Methods for dealing with G x E
Livia Moura Souza, Felipe Roberto Francisco, … Anete Pereira de Souza·Frontiers in Plant SciencePeer-reviewed·Oct 25, 2019
- Bivariate genomic prediction of phenotypes by selecting epistatic interactions across years
Elaheh Vojgani, Torsten Pook, … Henner Simianer·bioRxiv·Nov 18, 2020
- Integrating genome-wide association mapping of additive and dominance genetic effects to improve genomic prediction accuracy in Eucalyptus
Biyue Tan, Pär K. Ingvarsson·The Plant GenomePeer-reviewed·Apr 20, 2022
- Genetic architecture and genomic prediction accuracy of apple quantitative traits across environments
Michaela Jung, Beat Keller, … Andrea Patocchi·Horticulture ResearchPeer-reviewed·Jan 1, 2022
- Enhancing grapevine breeding efficiency through genomic prediction and selection index
Charlotte Brault, Vincent Segura, … Loïc Le Cunff·G3 Genes Genomes GeneticsPeer-reviewed·Feb 24, 2024