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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., This work was partially supported by the project RIS3CAT (COTPA-FRUIT3CAT) financed by the European Regional Development Fund through the FEDER frame of Catalonia 2014-2020 and by the CERCA Program from Generalitat de Catalunya. We acknowledge financial support from the Spanish Ministry of Economy and Competitiveness through the “Severo Ochoa Programme for Centres of Excellence in R&D” 2016-2019 (SEV-20150533) and 2020-2023 (CEX2019-000902-S)., With funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000902-S)

Implementation of genomic tools is desirable to increase the efficiency of apple breeding. The apple reference population (apple REFPOP) proved useful for rediscovering loci, estimating genomic prediction accuracy, and studying genotype by environment interactions (G×E). Here we show contrasting genetic architecture and genomic prediction accuracies 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 prediction accuracies of 0.18–0.88 were estimated using single-environment univariate, single-environment 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.

In the original publication, the positions of the SNP markers from the 50K SNP array are given according toGDDH13 v1.0 version of the apple reference genome and not according to GDDH13 v1.1 version as stated in the original publication.

Breeding of apple is a long-term and costly process due to the time and space requirements for screening selection candidates. Genomics-assisted breeding utilizes genomic and phenotypic information to increase the selection efficiency in breeding programs, and measurements of phenotypes in different environments can facilitate the application of the approach under various climatic conditions. Here we present an apple reference population: the apple REFPOP, a large collection formed of 534 genotypes planted in six European countries, as a unique tool to accelerate apple breeding. The population consisted of 269 accessions and 265 progeny from 27 parental combinations, representing the diversity in cultivated apple and current European breeding material, respectively. A high-density genome-wide dataset of 303,239 SNPs was produced as a combined output of two SNP arrays of different densities using marker imputation with an imputation accuracy of 0.95. Based on the genotypic data, linkage disequilibrium was low and population structure was weak. Two well-studied phenological traits of horticultural importance were measured. We found marker–trait associations in several previously identified genomic regions and maximum predictive abilities of 0.57 and 0.75 for floral emergence and harvest date, respectively. With decreasing SNP density, the detection of significant marker–trait associations varied depending on trait architecture. Regardless of the trait, 10,000 SNPs sufficed to maximize genomic prediction ability. We confirm the suitability of the apple REFPOP design for genomics-assisted breeding, especially for breeding programs using related germplasm, and emphasize the advantages of a coordinated and multinational effort for customizing apple breeding methods in the genomics era., This work was partially supported by the project RIS3CAT (COTPA-FRUIT3CAT) financed by the European Regional Development Fund through the FEDER frame of Catalonia 2014–2020 and by the CERCA Program from Generalitat de Catalunya. We acknowledge financial support from the Spanish Ministry of Economy and Competitiveness through the “Severo Ochoa Program for Centres of Excellence in R&D” 2016–2019 (SEV‐20150533). This work has been partially funded by the EU seventh Framework Program, the FruitBreedomics project No. 265582: Integrated Approach for Increasing Breeding Efficiency in Fruit Tree Crops.

International audience; Apple scab, caused by Venturia inaequalis, is a major fungal disease worldwide. Cultivation of scab-resistant cultivars would reduce the chemical footprint of apple production. However, new apple cultivars carrying durable resistances should be developed to prevent or at least slow the breakdown of resistance against races of V. inaequalis. One way to achieve durable resistance is to pyramid multiple scab resistance genes in a cultivar. The choice of the resistance genes to be combined in the pyramids should take into account the frequency of resistance breakdown and the geographical distribution of apple scab isolates able to cause such breakdowns. In order to acquire this information and to make it available to apple breeders, the VINQUEST project (www.vinquest.ch) was initiated in 2009. Ten years after launching this project, 24 partners from 14 countries regularly contribute data. From 2009 to 2018 nearly 9000 data points have been collected. This information has been used to identify the most promising apple scab resistance genes for developing cultivars with durable resistance, which to date are: Rvi5, Rvi11, Rvi12, Rvi14 and Rvi15. As expected, Rvi1, together with Rvi3 and Rvi8, were often overcome, hence have little value for scab resistance breeding. Rvi10 may also belong to this group. On the other hand Rvi2, Rvi4, Rvi6, Rvi7, Rvi9, and Rvi13 are still useful for the breeding, but their use is recommended only in extended pyramids of (≥3) resistance genes.

Apple scab causes significant losses in the production of this fruit. A timely and more site-specific monitoring and spraying of the disease could reduce the number of applications of fungicides in the fruit industry. The aim of this leaf-scale study therefore lies in the early detection of apple scab infections in a non-invasive and non-destructive way. In order to attain this objective, fluorescence- and hyperspectral imaging techniques were used. An experiment was conducted under controlled environmental conditions, linking hyperspectral reflectance and fluorescence imaging measurements to scab infection symptoms in a susceptible apple cultivar (Malus x domestica Borkh. cv. Braeburn). Plant stress was induced by inoculation of the apple plants with scab spores. The quantum efficiency of Photosystem II (PSII) photochemistry was derived from fluorescence images of leaves under light adapted conditions. Leaves inoculated with scab spores were expected to have lower PSII quantum efficiency than control (mock) leaves. However, besides scab-induced, also immature leaves exhibited low PSII quantum efficiency. Therefore, this study recommends the simultaneous use of fluorescence imaging and hyperspectral techniques. A shortwave infrared narrow-waveband ratio index (R1480/R2135) is presented in this paper as a promising tool to identify scab stress before symptoms become visible to the naked eye. Low PSII quantum efficiency attended by low narrow waveband R1480/R2135 index values points out scab stress in an early stage. Apparent high PSII quantum efficiency together with high overall reflectance in VIS and SWIR spectral domains indicate a severe, well-developed scab infection.

International audience; The application of genomic selection in fruit tree crops is expected to enhance breeding efficiency by increasing prediction accuracy, increasing selection intensity and decreasing generation interval. The objectives of this study were to assess the accuracy of prediction and selection response in commercial apple breeding programmes for key traits. The training population comprised 977 individuals derived from 20 pedigreed full-sib families. Historic phenotypic data were available on 10 traits related to productivity and fruit external appearance and genotypic data for 7829 SNPs obtained with an Illumina 20K SNP array. From these data, a genome-wide prediction model was built and subsequently used to calculate genomic breeding values of five application full-sib families. The application families had genotypes at 364 SNPs from a dedicated 512 SNP array, and these genotypic data were extended to the high-density level by imputation. These five families were phenotyped for 1 year and their phenotypes were compared to the predicted breeding values. Accuracy of genomic prediction across the 10 traits reached a maximum value of 0.5 and had a median value of 0.19. The accuracies were strongly affected by the phenotypic distribution and heritability of traits. In the largest family, significant selection response was observed for traits with high heritability and symmetric phenotypic distribution. Traits that showed non-significant response often had reduced and skewed phenotypic variation or low heritability. Among the five application families the accuracies were uncorrelated to the degree of relatedness to the training population. The results underline the potential of genomic prediction to accelerate breeding progress in outbred fruit tree crops that still need to overcome long generation intervals and extensive phenotyping costs.