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Article|01 Jan 2019|OPEN
Prediction of genetic value for sweet cherry fruit maturity among environments using a 6K SNP array
Craig M. Hardner1 , , Ben J. Hayes1 , Satish Kumar2 , Stijn Vanderzande3 , Lichun Cai4 , Julia Piaskowski3 , José Quero-Garcia5 , José Antonio Campoy5 , Teresa Barreneche5 , Daniela Giovannini6 , Alessandro Liverani6 , Gérard Charlot7 , Miguel Villamil-Castro1 , Nnadozie Oraguzie8 and Cameron P. Peace,3
1University of Queensland, Queensland Alliance for Agriculture and Food Innovation, Brisbane, QLD 4072, Australia
2The New Zealand Institute for Plant and Food Research Limited, Hawke’s Bay Research Centre, Hastings 4130, New Zealand
3Department of Horticulture, Washington State University, Pullman, WA 99164, USA
4Department of Horticulture, Michigan State University, East Lansing, MI 48824, USA
5UMR 1332 BFP, INRA, University of Bordeaux, 33140 Nouvelle-Aquitaine, France
6Council for Agricultural Research and Economics (CREA), Fruit Unit of Forlì, Via la Canapona, 1 bis, 47121 Emilia-Romagna, Italy
7Centre Technique Interprofessionnel des Fruits et Légumes (CTIFL), 751 Chemin de Balandran, 30127 Bellegarde, France
8Department of Horticulture, Washington State University, Irrigated Agriculture Research and Extension Center, 24106N Bunn Road, Prosser, WA 99350, USA
*Corresponding author. E-mail: craig.hardner@uq.edu.au

Horticulture Research 6,
Article number: 6 (2019)
doi: https://doi.org/10.1038/s41438-018-0081-7
Views: 951

Received: 12 Dec 2017
Revised: 08 Jun 2018
Accepted: 15 Jul 2018
Published online: 01 Jan 2019

Abstract

The timing of fruit maturity is an important trait in sweet cherry production and breeding. Phenotypic variation for phenology of fruit maturity in sweet cherry appears to be under strong genetic control, but that control might be complicated by phenotypic instability across environments. Although such genotype-by-environment interaction (G × E) is a common phenomenon in crop plants, knowledge about it is lacking for fruit maturity timing and other sweet cherry traits. In this study, 1673 genome-wide SNP markers were used to estimate genomic relationships among 597 weakly pedigree-connected individuals evaluated over two seasons at three locations in Europe and one location in the USA, thus sampling eight ‘environments’. The combined dataset enabled a single meta-analysis to investigate the environmental stability of genomic predictions. Linkage disequilibrium among marker loci declined rapidly with physical distance, and ordination of the relationship matrix suggested no strong structure among germplasm. The most parsimonious G × E model allowed heterogeneous genetic variance and pairwise covariances among environments. Narrow-sense genomic heritability was very high (0.60–0.83), as was accuracy of predicted breeding values (>0.62). Average correlation of additive effects among environments was high (0.96) and breeding values were highly correlated across locations. Results indicated that genomic models can be used in cherry to accurately predict date of fruit maturity for untested individuals in new environments. Limited G × E for this trait indicated that phenotypes of individuals will be stable across similar environments. Equivalent analyses for other sweet cherry traits, for which multiple years of data are commonly available among breeders and cultivar testers, would be informative for predicting performance of elite selections and cultivars in new environments.