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Additional file 5. Cluster plot examples for classifications of incompatible SNPs from Table 3.

Additional file 7. Additional cluster plot examples.

Additional file 4. Cluster plot examples for classifications of compatible SNPs from Table 3.

International audience; Genotypic variations in fruit tree architectural and functional traits have been reported but their genetic bases and the existence of common geneticdeterminants have rarely been investigated in wide genetic diversity. We made use of innovative in-eld high-throughput phenotyping on anassociation panel of 241 genotypes to quantify architectural and functional traits on 4-years old apple trees. T-Lidar technology was used for estimatingarchitectural traits (number of branches, tree height, STAR…), airborne thermal and multispectral imagery for assessing canopy temperature (a proxyof transpiration rate) and vegetation indices (NDVI, MCARI2, GNDVI). This dataset was complemented with yield-related traits (number of fruits, averagefruit weight). We explored genome wide associations on 16 traits with high density (275K) genotypic data. GWAS was run with a multi-locus mixedmodel using genetic kinship matrix and assuming different thresholds for SNP signicance: (i) the Bonferroni correction (Bonfth, -logpval > 6.7), (ii) acorrection based on an estimated number of independent SNPs (Bonfcor, -logpval > 5.7) and (iii) value based on common practices (-logpval = 5).Signicant SNPs with -logpval > 5 were detected for most traits with a number of them displaying -logpval above Bonfcor and above Bonfth. One to foursignicant SNPs were identied by variable with a proportion of variance explained by each SNP ranging from 6% to 14% and the total proportion ofvariance explained by all signicant SNPs exceeding up to 30% for the number of branches, STAR, MCARI2, number of fruit and crop load. SNPscontrolling different traits were detected on LG9 (height, STAR, volume) and LG13 (volume, MCARI2, NDVI, GNDVI). Analyses of the LD between SNPsallowed determining possible colocations within regions. Notably, some signicant SNPs were localized in genomic regions previously reported as QTLsfor similar traits in bi-parental population. This suggests their robustness and encourages further investigations.

International audience; Although more than 10.000 apple cultivars have been documented worldwide, modern commercial apple production is dominated by only a fewcultivars. Broadening the genetic diversity used in breeding programs thus appears as a necessity in order to reduce the vulnerability resulting fromgenetic uniformity. In this context, the identication of genetic resources that contain favourable alleles absent or rare in elite material is of primaryimportance for breeders. Harnessing this genetic diversity will probably require several generations of crosses starting from genetic resources, so thatparents carrying the identied favourable alleles are ready to be used in breeding programs. In order to effciently transfer these alleles, we propose touse genomic selection, a breeding approach that aims to estimate the breeding value of selection candidates using only genetic markers information.To do so, apple genetic resources (i.e. old varieties), elite material and hybrids between them have been genotyped and phenotyped so that predictionequations can be developed in order to evaluate the potential of genetic resources. As a preliminary step, these equations were built using data fromeither elite material or genetic resources and prediction accuracies were assessed and compared. To further improve the choice of the individuals usedto build the model, various optimisation algorithms were also used before estimating these accuracies. Given the differences in allele frequencies andlinkage disequilibrium patterns between the two datasets, the predictive ability of these models is expected to differ. One way to account for the differences is to combine these datasets and to use models that allow the estimation of population-specic effects. We will discuss the assets of suchan approach and how it could be effective to evaluate selection candidates. The obtained results should help us identify breeding strategies intendedto effciently transfer interesting alleles from genetic resources into elite material.

Resumen del trabajo presentado a la 10th Rosaceae Genomics Conference (RGC), celebrada de forma virtual del 9 al 11 de diciembre de 2020.

Background: Apple (Malus x domestica Borkh.) is one of the most important fruit tree crops of temperate areas, with great economic and cultural value. Apple cultivars can be maintained for centuries in plant collections through grafting, and some are thought to date as far back as Roman times. Molecular markers provide a means to reconstruct pedigrees and thus shed light on the recent history of migration and trade of biological materials. The objective of the present study was to identify relationships within a set of over 1400 mostly old apple cultivars using whole-genome SNP data (~ 253 K SNPs) in order to reconstruct pedigrees.Results: Using simple exclusion tests, based on counting the number of Mendelian errors, more than one thousand parent-offspring relations and 295 complete parent-offspring families were identified. Additionally, a grandparent couple was identified for the missing parental side of 26 parent-offspring pairings. Among the 407 parent-offspring relations without a second identified parent, 327 could be oriented because one of the individuals was an offspring in a complete family or by using historical data on parentage or date of recording. Parents of emblematic cultivars such as 'Ribston Pippin', 'White Transparent' and 'Braeburn' were identified. The overall pedigree combining all the identified relationships encompassed seven generations and revealed a major impact of two Renaissance cultivars of French and English origin, namely 'Reinette Franche' and 'Margil', and one North-Eastern Europe cultivar from the 1700s, 'Alexander'. On the contrary, several older cultivars, from the Middle Ages or the Roman times, had no, or only single, identifiable offspring in the set of studied accessions. Frequent crosses between cultivars originating from different European regions were identified, especially from the nineteenth century onwards.Conclusions: The availability of over 1400 apple genotypes, previously filtered for genetic uniqueness and providing a broad representation of European germplasm, has been instrumental for the success of this large pedigree reconstruction. It enlightens the history of empirical selection and recent breeding of apple cultivars in Europe and provides insights to speed-up future breeding and selection.

Additional file 9: Figure S1. Pedigrees linking the founder ‘Calville Rouge’ to all its offspring, over three generations. Cultivar names are in their short version (see Additional file 1: Table 1). The coloring of the name bars indicates the level of information known for the individual(s) in the pedigree: blue, individuals with both parents known; cream, individuals with one parent known; orange, unknown individual with both parents known; dark green, founders. Relationships are represented by black lines as the mother and the father cannot be identified with our data. The figure was drawn using data extracted from Additional file 8 and the Pedimap software [57]

Additional file 4. List of sources used to identify date of origin, first description, introduction, recording or inclusion in collections, or parents according to preferred name.

Additional file 13. Additional points of discussion regarding the historical and heritage value of the results obtained

Despite the availability of whole genome sequences of apple and peach, there has been a considerable gap between genomics and breeding. To bridge the gap, the European Union funded the FruitBreedomics project (March 2011 to August 2015) involving 28 research institutes and private companies. Three complementary approaches were pursued: (i) tool and software development, (ii) deciphering genetic control of main horticultural traits taking into account allelic diversity and (iii) developing plant materials, tools and methodologies for breeders. Decisive breakthroughs were made including the making available of ready-to-go DNA diagnostic tests for Marker Assisted Breeding, development of new, dense SNP arrays in apple and peach, new phenotypic methods for some complex traits, software for gene/QTL discovery on breeding germplasm via Pedigree Based Analysis (PBA). This resulted in the discovery of highly predictive molecular markers for traits of horticultural interest via PBA and via Genome Wide Association Studies (GWAS) on several European genebank collections. FruitBreedomics also developed pre-breeding plant materials in which multiple sources of resistance were pyramided and software that can support breeders in their selection activities. Through FruitBreedomics, significant progresses were made in the field of apple and peach breeding, genetics, genomics and bioinformatics of which advantage will be made by breeders, germplasm curators and scientists. A major part of the data collected during the project has been stored in the FruitBreedomics database and has been made available to the public. This review covers the scientific discoveries made in this major endeavour, and perspective in the apple and peach breeding and genomics in Europe and beyond., This work has been funded under the EU seventh Framework Programme by the FruitBreedomics project No. 265582: Integrated Approach for increasing breeding efficiency in fruit tree crops (http://www.fruitbreedomics.com/).

International audience; Deciphering the genetic control of flowering and ripening periods in apple is essential for breeding cultivars adapted to their growing environments. We implemented a large Genome-Wide Association Study (GWAS) at the European level using an association panel of 1,168 different apple genotypes distributed over six locations and phenotyped for these phenological traits. The panel was genotyped at a high-density of SNPs using the Axiom®Apple 480 K SNP array. We ran GWAS with a multi-locus mixed model (MLMM), which handles the putatively confounding effect of significant SNPs elsewhere on the genome. Genomic regions were further investigated to reveal candidate genes responsible for the phenotypic variation. At the whole population level, GWAS retained two SNPs as cofactors on chromosome 9 for flowering period, and six for ripening period (four on chromosome 3, one on chromosome 10 and one on chromosome 16) which, together accounted for 8.9 and 17.2% of the phenotypic variance, respectively. For both traits, SNPs in weak linkage disequilibrium were detected nearby, thus suggesting the existence of allelic heterogeneity. The geographic origins and relationships of apple cultivars accounted for large parts of the phenotypic variation. Variation in genotypic frequency of the SNPs associated with the two traits was connected to the geographic origin of the genotypes (grouped as North+East, West and South Europe), and indicated differential selection in different growing environments. Genes encoding transcription factors containing either NAC or MADS domains were identified as major candidates within the small confidence intervals computed for the associated genomic regions. A strong microsynteny between apple and peach was revealed in all the four confidence interval regions. This study shows how association genetics can unravel the genetic control of important horticultural traits in apple, as well as reduce the confidence intervals of the associated regions identified by linkage mapping approaches. Our findings can be used for the improvement of apple through marker-assisted breeding strategies that take advantage of the accumulating additive effects of the identified SNPs.

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., Horticulture Research, 7 (1)

Deciphering the genetic control of flowering and ripening periods in apple is essential for breeding cultivars adapted to their growing environments. We implemented a large Genome-Wide Association Study (GWAS) at the European level using an association panel of 1,168 different apple genotypes distributed over six locations and phenotyped for these phenological traits. The panel was genotyped at a high-density of SNPs using the Axiom®Apple 480 K SNP array. We ran GWAS with a multi-locus mixed model (MLMM), which handles the putatively confounding effect of significant SNPs elsewhere on the genome. Genomic regions were further investigated to reveal candidate genes responsible for the phenotypic variation. At the whole population level, GWAS retained two SNPs as cofactors on chromosome 9 for flowering period, and six for ripening period (four on chromosome 3, one on chromosome 10 and one on chromosome 16) which, together accounted for 8.9 and 17.2% of the phenotypic variance, respectively. For both traits, SNPs in weak linkage disequilibrium were detected nearby, thus suggesting the existence of allelic heterogeneity. The geographic origins and relationships of apple cultivars accounted for large parts of the phenotypic variation. Variation in genotypic frequency of the SNPs associated with the two traits was connected to the geographic origin of the genotypes (grouped as North+East, West and South Europe), and indicated differential selection in different growing environments. Genes encoding transcription factors containing either NAC or MADS domains were identified as major candidates within the small confidence intervals computed for the associated genomic regions. A strong microsynteny between apple and peach was revealed in all the four confidence interval regions. This study shows how association genetics can unravel the genetic control of important horticultural traits in apple, as well as reduce the confidence intervals of the associated regions identified by linkage mapping approaches. Our findings can be used for the improvement of apple through marker-assisted breeding strategies that take advantage of the accumulating additive effects of the identified SNPs. JU has been partially supported by an Early Stage Research Fellowship of the Institute of Advanced Studies (University of Bologna).

International audience; Quantitative trait loci (QTL) mapping approaches rely on the correct ordering of molecular markers along the chromosomes, which can be obtained from genetic linkage maps or a reference genome sequence. For apple (Malus domestica Borkh), the genome sequence v1 and v2 could not meet this need; therefore, a novel approach was devised to develop a dense genetic linkage map, providing the most reliable marker-loci order for the highest possible number of markers. The approach was based on four strategies: (i) the use of multiple full-sib families, (ii) the reduction of missing information through the use of HaploBlocks and alternative calling procedures for single-nucleotide polymorphism (SNP) markers, (iii) the construction of a single backcross-type data set including all families, and (iv) a two-step map generation procedure based on the sequential inclusion of markers. The map comprises 15 417 SNP markers, clustered in 3 K HaploBlock markers spanning 1 267 cM, with an average distance between adjacent markers of 0.37 cM and a maximum distance of 3.29 cM. Moreover, chromosome 5 was oriented according to its homoeologous chromosome 10. This map was useful to improve the apple genome sequence, design the Axiom Apple 480 K SNP array and perform multifamily-based QTL studies. Its collinearity with the genome sequences v1 and v3 are reported. To our knowledge, this is the shortest published SNP map in apple, while including the largest number of markers, families and individuals. This result validates our methodology, proving its value for the construction of integrated linkage maps for any outbreeding species.