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Article|01 Apr 2022|OPEN
Genetic architecture and genomic predictive ability of apple quantitative traits across environments
Michaela Jung1,2 , , Beat Keller1,2 , Morgane Roth1,3 , Maria José Aranzana4,5 , Annemarie Auwerkerken6 , Walter Guerra7 , Mehdi Al-Rifaï8 , Mariusz Lewandowski9 , Nadia Sanin7 , Marijn Rymenants6,10 , Frédérique Didelot11 , Christian Dujak5 and Carolina Font i Forcada4 , Andrea Knauf1,2 , François Laurens8 , Bruno Studer2 , Hélène Muranty8 , Andrea Patocchi,1
1Agroscope, Breeding Research Group, 8820 Wädenswil, Switzerland
2Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, 8092 Zurich, Switzerland
3GAFL, INRAE, 84140 Montfavet, France
4IRTA (Institut de Recerca i Tecnologia Agroalimentàries), 08140 Caldes de Montbui, Barcelona, Spain
5Centre for Research in Agricultural Genomics (CRAG) CSIC-IRTA-UAB-UB, Campus UAB, 08193 Bellaterra, Barcelona, Spain
6Better3fruit N.V., 3202 Rillaar, Belgium
7Research Centre Laimburg, 39040 Auer, Italy
8Univ Angers, Institut Agro, INRAE, IRHS, SFR QUASAV, F-49000 Angers, France
9The National Institute of Horticultural Research, Konstytucji 3 Maja 1/3, 96-100 Skierniewice, Poland
10Laboratory for Plant Genetics and Crop Improvement, KU Leuven, B-3001 Leuven, Belgium
11Unité expérimentale Horticole, INRAE, F-49000 Angers, France
*Corresponding author. E-mail: michaela.jung@usys.ethz.ch

Horticulture Research 9,
Article number: uhac028 (2022)
doi: https://doi.org/10.1093/hr/uhac028
Views: 357

Received: 25 Jun 2021
Revised: 10 Apr 2022
Accepted: 11 Jan 2022
Published online: 01 Apr 2022

Abstract

Implementation of genomic tools is desirable to increase the efficiency of apple breeding. Recently, the multi-environment apple reference population (apple REFPOP) proved useful for rediscovering loci, estimating genomic predictive ability, and studying genotype by environment interactions (G × E). So far, only two phenological traits were investigated using the apple REFPOP, although the population may be valuable when dissecting genetic architecture and reporting predictive abilities for additional key traits in apple breeding. Here we show contrasting genetic architecture and genomic predictive abilities for 30 quantitative traits across up to six European locations using the apple REFPOP. A total of 59 stable and 277 location-specific associations were found using GWAS, 69.2% of which are novel when compared with 41 reviewed publications. Average genomic predictive abilities of 0.18–0.88 were estimated using main-effect univariate, main-effect multivariate, multi-environment univariate, and multi-environment multivariate models. The G × E accounted for up to 24% of the phenotypic variability. This most comprehensive genomic study in apple in terms of trait-environment combinations provided knowledge of trait biology and prediction models that can be readily applied for marker-assisted or genomic selection, thus facilitating increased breeding efficiency.