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Brown rot, caused by Monilinia spp., is one of the most important diseases on stone fruit worldwide. Severe yield loss can be caused by pre- and post-harvest fruit decay. Although some degree of tolerance has been reported in peach and almond, the genetic resistance in peach cultivars is still lacking. To date, only few genomic regions associated with brown rot response in fruit skin and flesh have been detected in peach. Previous studies suggested brown rot tolerance in peach being a polygenic quantitative trait. More information is needed to uncover the genetics behind brown rot tolerance in peach. To identify the genomic regions in peach associated with this trait, 26 cultivars and progeny from 9 crosses with ‘Bolinha’ sources of tolerance, were phenotyped across two seasons (2015 and 2016) for brown rot disease severity index in wounded and non-wounded fruits and genotyped using a newly developed 9+9K peach SNP array. Genome wide association study using single- and multi-locus methods by GAPIT version 3, mrMLM 4.0, GAPIT and G Model, revealed 14 reliable SNPs significantly associated with brown rot infection responses in peach skin (10) and flesh (4) across whole genome except for chromosome 3. Candidate gene analysis within the haplotype regions of the detected markers identified 25 predicted genes associated with pathogen infection response/resistance. Results presented here facilitate further understanding of genetics behind brown rot tolerance in peach and provide an important foundation for DNA-assisted breeding.

BackgroundEnvironmental adaptation and expanding harvest seasons are primary goals of most peach [Prunus persica(L.) Batsch] breeding programs. Breeding perennial crops is a challenging task due to their long breeding cycles and large tree size. Pedigree-based analysis using pedigreed families followed by haplotype construction creates a platform for QTL and marker identification, validation, and the use of marker-assisted selection in breeding programs.ResultsPhenotypic data of seven F1low to medium chill full-sib families were collected over 2 years at two locations and genotyped using the 9 K SNP Illumina array. Three QTLs were discovered for bloom date (BD) and mapped on linkage group 1 (LG1) (172–182 cM), LG4 (48–54 cM), and LG7 (62–70 cM), explaining 17–54%, 11–55%, and 11–18% of the phenotypic variance, respectively. The QTL for ripening date (RD) and fruit development period (FDP) on LG4 was co-localized at the central part of LG4 (40–46 cM) and explained between 40 and 75% of the phenotypic variance. Haplotype analyses revealed SNP haplotypes and predictive SNP marker(s) associated with desired QTL alleles and the presence of multiple functional alleles with different effects for a single locus for RD and FDP.ConclusionsA multiple pedigree-linked families approach validated major QTLs for the three key phenological traits which were reported in previous studies across diverse materials, geographical distributions, and QTL mapping methods. Haplotype characterization of these genomic regions differentiates this study from the previous QTL studies. Our results will provide the peach breeder with the haplotypes for three BD QTLs and one RD/FDP QTL to create predictive DNA-based molecular marker tests to select parents and/or seedlings that have desired QTL alleles and cull unwanted genotypes in early seedling stages.

[Background]: Highly polygenic traits such as fruit weight, sugar content and acidity strongly influence the agroeconomic value of peach varieties. Genomic Selection (GS) can accelerate peach yield and quality gain if predictions show higher levels of accuracy compared to phenotypic selection. The available IPSC 9K SNP array V1 allows standardized and highly reliable genotyping, preparing the ground for GS in peach., [Results]: A repeatability model (multiple records per individual plant) for genome-enabled predictions in eleven European peach populations is presented. The analysis included 1147 individuals derived from both commercial and non-commercial peach or peach-related accessions. Considered traits were average fruit weight (FW), sugar content (SC) and titratable acidity (TA). Plants were genotyped with the 9K IPSC array, grown in three countries (France, Italy, Spain) and phenotyped for 3–5 years. An analysis of imputation accuracy of missing genotypic data was conducted using the software Beagle, showing that two of the eleven populations were highly sensitive to increasing levels of missing data. The regression model produced, for each trait and each population, estimates of heritability (FW:0.35, SC:0.48, TA:0.53, on average) and repeatability (FW:0.56, SC:0.63, TA:0.62, on average). Predictive ability was estimated in a five-fold cross validation scheme within population as the correlation of true and predicted phenotypes. Results differed by populations and traits, but predictive abilities were in general high (FW:0.60, SC:0.72, TA:0.65, on average)., [Conclusions]: This study assessed the feasibility of Genomic Selection in peach for highly polygenic traits linked to yield and fruit quality. The accuracy of imputing missing genotypes was as high as 96%, and the genomic predictive ability was on average 0.65, but could be as high as 0.84 for fruit weight or 0.83 for titratable acidity. The estimated repeatability may prove very useful in the management of the typical long cycles involved in peach productions. All together, these results are very promising for the application of genomic selection to peach breeding programmes., This work was supported by the European Union-funded project “FruitBreedomics: Integrated approach for increasing breeding efficiency in fruit tree crops” (Grant #FP7-265582; http://fruitbreedomics.com/; http://ec.europa.eu/research/fp7/index_en.cfm). Work in Italy was partly supported also by “Ministero delle Politiche Agricole Alimentari e Forestali” (MiPAAF, http://www.politicheagricole.it) through the project “DRUPOMICS: Sequenziamento del genoma del pesco ed utilizzo della sequenza in programmi di miglioramento della qualità del frutto del pesco e della resistenza alle malattie” (Grant # DM14999/7303/08). DB received funds also from Italian private and public agencies within the project “MAS.PES: apricot and peach breeding by molecular-assisted selection”.

Brown rot, caused by Monilinia spp., is one of the most important diseases on stone fruit worldwide. Severe yield loss can be caused by pre- and post-harvest fruit decay. Although some degree of tolerance has been reported in peach and almond, the genetic resistance in peach cultivars is still lacking. To date, only few genomic regions associated with brown rot response in fruit skin and flesh have been detected in peach. Previous studies suggested brown rot tolerance in peach being a polygenic quantitative trait. More information is needed to uncover the genetics behind brown rot tolerance in peach. To identify the genomic regions in peach associated with this trait, 26 cultivars and progeny from 9 crosses with ‘Bolinha’ sources of tolerance, were phenotyped across two seasons (2015 and 2016) for brown rot disease severity index in wounded and non-wounded fruits and genotyped using a newly developed 9+9K peach SNP array. Genome wide association study using single- and multi-locus methods by GAPIT version 3, mrMLM 4.0, GAPIT and G Model, revealed 14 reliable SNPs significantly associated with brown rot infection responses in peach skin (10) and flesh (4) across whole genome except for chromosome 3. Candidate gene analysis within the haplotype regions of the detected markers identified 25 predicted genes associated with pathogen infection response/resistance. Results presented here facilitate further understanding of genetics behind brown rot tolerance in peach and provide an important foundation for DNA-assisted breeding.

The Rosaceae crop family (including almond, apple, apricot, blackberry, peach, pear, plum, raspberry, rose, strawberry, sweet cherry, and sour cherry) provides vital contributions to human well-being and is economically significant across the U.S. In 2003, industry stakeholder initiatives prioritized the utilization of genomics, genetics, and breeding to develop new cultivars exhibiting both disease resistance and superior horticultural quality. However, rosaceous crop breeders lacked certain knowledge and tools to fully implement DNA-informed breeding—a “chasm” existed between existing genomics and genetic information and the application of this knowledge in breeding. The RosBREED project (“Ros” signifying a Rosaceae genomics, genetics, and breeding community initiative, and “BREED”, indicating the core focus on breeding programs), addressed this challenge through a comprehensive and coordinated 10-year effort funded by the USDA-NIFA Specialty Crop Research Initiative. RosBREED was designed to enable the routine application of modern genomics and genetics technologies in U.S. rosaceous crop breeding programs, thereby enhancing their efficiency and effectiveness in delivering cultivars with producer-required disease resistances and market-essential horticultural quality. This review presents a synopsis of the approach, deliverables, and impacts of RosBREED, highlighting synergistic global collaborations and future needs. Enabling technologies and tools developed are described, including genome-wide scanning platforms and DNA diagnostic tests. Examples of DNA-informed breeding use by project participants are presented for all breeding stages, including pre-breeding for disease resistance, parental and seedling selection, and elite selection advancement. The chasm is now bridged, accelerating rosaceous crop genetic improvement.

Background: Fruit quality traits have a significant effect on consumer acceptance and subsequently on peach (Prunus persica (L.) Batsch) consumption. Determining the genetic bases of key fruit quality traits is essential for industry to improve fruit quality and increase consumption. A Bayesian approach embedded in the FlexQTL software increases the accuracy of QTL mapping and the probability of identifying new and validating known QTLs across a wide range of genetic backgrounds.Results: Phenotypic data of seven F1 low to medium chill full-sib families were collected over two years at two locations and genotyped using the 9K SNP Illumina array. One major QTL for fruit blush was found on linkage group 4 (LG4) at 40–46 cM that explained from 20 to 32% of the total phenotypic variance and showed three QTL alleles of different effects. For SSC, one QTL was mapped on LG5 at 60-72cM and explained from 17 to 39% of the phenotypic variance. A major QTL for TA that co-localized with the major locus for low-acid fruit (D-locus) was mapped at the proximal end of LG5 and explained 35 to 80% of the phenotypic variance. The new QTL for TA on the distal end of LG5 explained 14 to 22% of the phenotypic variance. This QTL co-localized with the QTL for SSC and affected TA only when the first QTL is homozygous for high acidity (epistasis). Haplotype analyses revealed SNP haplotypes and predictive SNP marker(s) associated with desired QTL alleles.Conclusions: A multi-family-based QTL discovery approach enhanced the ability to discover a new TA QTL and validated other QTLs which were reported in previous studies. Identified predictive SNPs and their original sources will facilitate the selection of parents and/or seedlings that have desired haplotype alleles. Our findings will help peach breeders develop new predictive, DNA-based molecular marker tests for routine use in marker-assisted breeding (MAB).

Genetic control and location of QTLs associated with phytochemical compounds and fruit quality in peach [Prunus persica (L.) Batsch] were evaluated using an F2 mapping population (ZC2) derived from cross between ‘Zin Dai’ × ‘Crimson Lady’. Antioxidant capacity, accumulation of phenolic compounds (total phenolics, flavonoids, and anthocyanins), and fruit quality traits (fruit diameter, fruit weight, fruit firmness, soluble solids concentration, titratable acidity, and ripening index) were evaluated for 2 years (2013–2014). Fourteen QTLs for phytochemical and fruit quality traits were identified in 5 LGs, with two QTL clusters (qPC.ZC_5.1_2014 and qPC.ZC_7.1) observed on LGs 5 and 7. The QTL cluster qPC.ZC_5.1_2014 was associated with antioxidant capacity, flavonoids, anthocyanin content, and SSC, while qPC.ZC_7.1 exhibited association only with flavonoids and fruit ripening index. QTL clusters associated with different fruit quality traits were observed on LGs 1 and 6. Candidate gene analyses of the QTL cluster on LG5 (qPC.ZC_5.1_2014) revealed 14 candidate genes in peach with functional annotation related to biosynthesis pathway of phytochemical compounds.

BackgroundFruit quality traits have a significant effect on consumer acceptance and subsequently on peach (Prunus persica(L.) Batsch) consumption. Determining the genetic bases of key fruit quality traits is essential for the industry to improve fruit quality and increase consumption. Pedigree-based analysis across multiple peach pedigrees can identify the genomic basis of complex traits for direct implementation in marker-assisted selection. This strategy provides breeders with better-informed decisions and improves selection efficiency and, subsequently, saves resources and time.ResultsPhenotypic data of seven F1low to medium chill full-sib families were collected over 2 years at two locations and genotyped using the 9 K SNP Illumina array. One major QTL for fruit blush was found on linkage group 4 (LG4) at 40–46 cM that explained from 20 to 32% of the total phenotypic variance and showed three QTL alleles of different effects. For soluble solids concentration (SSC), one QTL was mapped on LG5 at 60-72 cM and explained from 17 to 39% of the phenotypic variance. A major QTL for titratable acidity (TA) co-localized with the major locus for low-acid fruit (D-locus). It was mapped at the proximal end of LG5 and explained 35 to 80% of the phenotypic variance. The new QTL for TA on the distal end of LG5 explained 14 to 22% of the phenotypic variance. This QTL co-localized with the QTL for SSC and affected TA only when the first QTL is homozygous for high acidity (epistasis). Haplotype analyses revealed SNP haplotypes and predictive SNP marker(s) associated with desired QTL alleles.ConclusionsA multi-family-based QTL discovery approach enhanced the ability to discover a new TA QTL at the distal end of LG5 and validated other QTLs which were reported in previous studies. Haplotype characterization of the mapped QTLs distinguishes this work from the previous QTL studies. Identified predictive SNPs and their original sources will facilitate the selection of parents and/or seedlings that have desired QTL alleles. Our findings will help peach breeders develop new predictive, DNA-based molecular marker tests for routine use in marker-assisted breeding.

The aim of this study was to evaluate the diversity of yam genotypes concerning their agro-morphological traits based on the Ward-modified location model (Ward-MLM) procedure. 209 genotypes from the commercial production area of the Reconcavo region in the state of Bahia, Brazil were used. Three agronomic traits (length, width and weight of the rhizophore) and two morphological traits (rhizophore shape and skin color) were evaluated. A considerable agro-morphological diversity was detected in the data for the 209 yam genotypes. The Ward-MLM procedure showed that the optimal number of groups according to the criteria of pseudo F and pseudo t2 is four. The separation by genotype groups was associated with their origin from two regions with different soil and climatic conditions. The Ward-MLM procedure has shown its usefulness to detect diversity and cluster genotypes by simultaneous use of morphological and agronomic traits. Key words: Cluster analysis, discriminant analysis, Dioscorea species, Ward-modified location model (MLM).

High-quality genotypic data is a requirement for many genetic analyses. For any crop, errors in genotype calls, phasing of markers, linkage maps, pedigree records, and unnoticed variation in ploidy levels can lead to spurious marker-locus-trait associations and incorrect origin assignment of alleles to individuals. High-throughput genotyping requires automated scoring, as manual inspection of thousands of scored loci is too time-consuming. However, automated SNP scoring can result in errors that should be corrected to ensure recorded genotypic data are accurate and thereby ensure confidence in downstream genetic analyses. To enable quick identification of errors in a large genotypic data set, we have developed a comprehensive workflow. This multiple-step workflow is based on inheritance principles and on removal of markers and individuals that do not follow these principles, as demonstrated here for apple, peach, and sweet cherry. Genotypic data was obtained on pedigreed germplasm using 6-9K SNP arrays for each crop and a subset of well-performing SNPs was created using ASSIsT. Use of correct (and corrected) pedigree records readily identified violations of simple inheritance principles in the genotypic data, streamlined with FlexQTL™ software. Retained SNPs were grouped into haploblocks to increase the information content of single alleles and reduce computational power needed in downstream genetic analyses. Haploblock borders were defined by recombination locations detected in ancestral generations of cultivars and selections. Another round of inheritance-checking was conducted, for haploblock alleles (i.e., haplotypes). High-quality genotypic data sets were created using this workflow for pedigreed collections representing the U.S. breeding germplasm of apple, peach, and sweet cherry evaluated within the RosBREED project. These data sets contain 3855, 4005, and 1617 SNPs spread over 932, 103, and 196 haploblocks in apple, peach, and sweet cherry, respectively. The highly curated phased SNP and haplotype data sets, as well as the raw iScan data, of germplasm in the apple, peach, and sweet cherry Crop Reference Sets is available through the Genome Database for Rosaceae.

Fruit texture is a crucial quality factor influencing consumer preference and shelf life. Peach (P. persica L. Batsch) is a highly perishable fruit subjected to a rapid softening after harvest. Improvement of peach shelf life is an important breeding objective, stimulating the characterization and exploitation of texture-related traits. Variants of melting (M) texture have captured an increasing interest, following the economic success of “Big Top” nectarine, one of the most cultivated varieties worldwide. “Big Top” fruit maintains a crispy texture for an extended period before the onset of the melting phase, prolonging its shelf life. Genetic determinants regulating this complex trait, defined as slow softening (SwS), are still unknown, mainly because of limitations in phenotyping methods. In this work, a mechanical approach for measuring SwS fruit texture was used to phenotype offspring derived from a cross between “Rebus028” (SwS texture) and “Max10” (M texture). Mechanical parameters were used in linkage mapping, allowing the identification of a major QTL on chromosome 8 (qSwS8.1). The presence of this QTL was validated by a genome-wide association study (GWAS) in a panel of accessions phenotyped for mechanical properties. Less significant signals were also detected by GWAS in other genomic regions, suggesting that additional loci may regulate the SwS trait, possibly depending on the genetic background. The inheritance pattern of the SwS trait and the presence of additional loci are crucial aspects to be addressed in future studies, along with a better characterization of other important textural attributes.

Double flowers with supernumerary petals have been selected by humans for their attractive appearance and commercial value in several ornamental plants, including Prunus persica (peach), a recognized model for Rosaceae genetics and genomics. Despite the relevance of this trait, knowledge of the underlying genes is limited. Of two distinct loci controlling the double-flower phenotype in peach, we focused on the dominant Di2 locus. High-resolution linkage mapping in five segregating progenies delimited Di2 to an interval spanning 150 858 bp and 22 genes, including Prupe.6G242400 encoding an euAP2 transcription factor. Analyzing genomic resequencing data from single- and double-flower accessions, we identified a deletion spanning the binding site for miR172 in Prupe.6G242400 as a candidate variant for the double-flower trait, and we showed transcript expression for both wild-type and deleted alleles. Consistent with the proposed role in controlling petal number, Prupe.6G242400 is expressed in buds at critical times for floral development. The indelDi2 molecular marker designed on this sequence variant co-segregated with the phenotype in 621 progenies, accounting for the dominant inheritance of the Di2 locus. Further corroborating the results in peach, we identified a distinct but similar mutation in the ortholog of Prupe.6G242400 in double-flower roses. Phylogenetic analysis showed that these two genes belong to a TARGET OF EAT (TOE)-type clade not represented in Arabidopsis, indicating a divergence of gene functions between AP2-type and TOE-type factors in Arabidopsis and other species. The identification of orthologous candidate genes for the double-flower phenotype in two important Rosaceae species provides valuable information to understand the genetic control of this trait in other major ornamental plants.

Highly saturated genetic linkage maps are extremely helpful to breeders and are an essential prerequisite for many biological applications such as the identification of marker-trait associations, mapping quantitative trait loci (QTL), candidate gene identification, development of molecular markers for marker-assisted selection (MAS) and comparative genetic studies. Several high-density genetic maps, constructed using the 9K SNP peach array, are available for peach. However, each of these maps is based on a single mapping population and has limited use for QTL discovery and comparative studies. A consensus genetic linkage map developed from multiple populations provides not only a higher marker density and a greater genome coverage when compared to the individual maps, but also serves as a valuable tool for estimating genetic positions of unmapped markers. In this study, a previously developed linkage map from the cross between two peach cultivars ‘Zin Dai’ and ‘Crimson Lady’ (ZC2) was improved by genotyping additional progenies. In addition, a peach consensus map was developed based on the combination of the improved ZC2 genetic linkage map with three existing high-density genetic maps of peach and a reference map of Prunus. A total of 1,476 SNPs representing 351 unique marker positions were mapped across eight linkage groups on the ZC2 genetic map. The ZC2 linkage map spans 483.3 cM with an average distance between markers of 1.38 cM/marker. The MergeMap and LPmerge tools were used for the construction of a consensus map based on markers shared across five genetic linkage maps. The consensus linkage map contains a total of 3,092 molecular markers, consisting of 2,975 SNPs, 116 SSRs and 1 morphological marker associated with slow ripening in peach (SR). The consensus map provides valuable information on marker order and genetic position for QTL identification in peach and other genetic studies within Prunus and Rosaceae., This project was supported in part by the USDA-NIFA-Specialty Crop Research Initiative project, RosBREED: Enabling marker-assisted breeding in Rosaceae (2009-51181-05808) to KG, and RosBREED 2: Combining disease resistance with horticultural quality in new rosaceous cultivars (2014-51181-22378) to KG. The Spanish Ministry of Economy and Competitiveness (project RTA2015-00050-00-00, Severo Ochoa Program for Centres of Excellence in R&D 201-2019 (SEV-2015-0533) and CERCA Programme-Generalitat de Catalunya). This work was in part supported by the Ministero delle Politiche Agricole Alimentari e Forestali (MiPAAF, Italy) through the projects DRUPOMICS (grant DM14999/7303/08), and 'MAS.PES: apricot and peach breeding by molecular-assisted selection' a project funded by private and public agencies.

One of the applications of genomics is to identify genetic markers linked to loci responsible for variation in phenotypic traits, which could be used in breeding programs to select individuals with favorable alleles, particularly at the seedling stage. With this aim, in the framework of the European project FruitBreedomics, we selected five main peach fruit characters and a resistance trait, controlled by major genes with Mendelian inheritance: fruit flesh color Y, fruit skin pubescence G, fruit shape S, sub-acid fruit D, stone adhesion-flesh texture F-M, and resistance to green peach aphid Rm2. They were all previously mapped in Prunus. We then selected three F1 and three F2 progenies segregating for these characters and developed genetic maps of the linkage groups including the major genes, using the single nucleotide polymorphism (SNP) genome-wide scans obtained with the International Peach SNP Consortium (IPSC) 9K SNP array v1. We identified SNPs co-segregating with the characters in all cases. Their positions were in agreement with the known positions of the major genes. The number of SNPs linked to each of these, as well as the size of the physical regions encompassing them, varied depending on the maps. As a result, the number of useful SNPs for marker-assisted selection varied accordingly. As a whole, this study establishes a sound basis for further development of MAS on these characters. Additionally, we also discussed some limitations that were observed regarding the SNP array efficiency., This work has been funded under the EU seventh Framework program by the FruitBreedomics project (FP7-KBBE-2010-265582): Integrated Approach for increasing breeding efficiency in fruit tree crop.

Background Maturity date (MD) is a crucial factor for marketing of fresh fruit, especially those with limited shelf-life such as peach (Prunus persica L. Batsch): selection of several cultivars with differing MD would be advantageous to cover and extend the marketing season. Aims of this work were the fine mapping and identification of candidate genes for the major maturity date locus previously identified on peach linkage group 4. To improve genetic resolution of the target locus two F2 populations derived from the crosses Contender x Ambra (CxA, 306 individuals) and PI91459 (NJ Weeping) x Bounty (WxBy, 103 individuals) were genotyped with the Sequenom and 9K Illumina Peach Chip SNP platforms, respectively. Results Recombinant individuals from the WxBy F2 population allowed the localisation of maturity date locus to a 220 kb region of the peach genome. Among the 25 annotated genes within this interval, functional classification identified ppa007577m and ppa008301m as the most likely candidates, both encoding transcription factors of the NAC (NAM/ATAF1, 2/CUC2) family. Re-sequencing of the four parents and comparison with the reference genome sequence uncovered a deletion of 232 bp in the upstream region of ppa007577m that is homozygous in NJ Weeping and heterozygous in Ambra, Bounty and the WxBy F1 parent. However, this variation did not segregate in the CxA F2 population being the CxA F1 parent homozygous for the reference allele. The second gene was thus examined as a candidate for maturity date. Re-sequencing of ppa008301m, showed an in-frame insertion of 9 bp in the last exon that co-segregated with the maturity date locus in both CxA and WxBy F2 populations. Conclusions Using two different segregating populations, the map position of the maturity date locus was refined from 3.56 Mb to 220 kb. A sequence variant in the NAC gene ppa008301m was shown to co-segregate with the maturity date locus, suggesting this gene as a candidate controlling ripening time in peach. If confirmed on other genetic materials, this variant may be used for marker-assisted breeding of new cultivars with differing maturity date.

Fruit weight is a quantitative trait influenced by the combined action of several genes and environmental factors. Knowledge of the quantitative trait loci (QTLs) associated with fruit weight and size is a priority to support breeding programmes in peach (Prunus persica (L.) Batsch) because of commercial interest in larger fruits. To this end, we built a genetic map of an F-2 progeny of 117 individuals from the cross PI91459 ('NJ Weeping') x 'Bounty' using a single nucleotide polymorphism (SNP) genotyping array for peach (9K SNP array v1). Data for fruit weight, height, width, and depth were recorded for the progeny and both parents over 2 years (2011, 2012). Correlations between the traits fruit weight and size were positive and significant for both years. A SNP map was constructed comprising 1,148 markers distributed over eight linkage groups. The map spans 536.6 cM with an average distance between markers of 0.52 cM, covering 93.6 % of the physical length of the peach genome, thus representing an ideal basis for QTL mapping. QTL analysis led to the identification of a total of 28 QTLs for the considered traits, eleven of which remained stable in both years. We also observed clusters of QTLs, some of which were mapped for the first time, while others correspond to loci previously identified in different progenies and following different approaches.

Peach was domesticated in China more than four millennia ago and from there it spread world-wide. Since the middle of the last century, peach breeding programs have been very dynamic generating hundreds of new commercial varieties, however, in most cases such varieties derive from a limited collection of parental lines (founders). This is one reason for the observed low levels of variability of the commercial gene pool, implying that knowledge of the extent and distribution of genetic variability in peach is critical to allow the choice of adequate parents to confer enhanced productivity, adaptation and quality to improved varieties. With this aim we genotyped 1,580 peach accessions (including a few closely related Prunus species) maintained and phenotyped in five germplasm collections (four European and one Chinese) with the International Peach SNP Consortium 9K SNP peach array. The study of population structure revealed the subdivision of the panel in three main populations, one mainly made up of Occidental varieties from breeding programs (POP1OCB), one of Occidental landraces (POP2OCT) and the third of Oriental accessions (POP3OR). Analysis of linkage disequilibrium (LD) identified differential patterns of genome-wide LD blocks in each of the populations. Phenotypic data for seven monogenic traits were integrated in a genome-wide association study (GWAS). The significantly associated SNPs were always in the regions predicted by linkage analysis, forming haplotypes of markers. These diagnostic haplotypes could be used for marker-assisted selection (MAS) in modern breeding programs., This work has been funded by the EU seventh Framework Programme (http://ec.europa.eu/research/fp7/index_en.cfm) through the project “FruitBreedomics: Integrated Approach for increasing breeding efficiency in fruit tree crops” (Grant #FP7- 265582; http://fruitbreedomics.com/); by the Ministero delle Politiche Agricole Alimentari e Forestali -Italy (MiPAAF, http://www.politicheagricole.it) through the project ‘‘DRUPOMICS: Sequenziamento del genoma del pesco ed utilizzo della sequenza in programmi di miglioramento della qualita` del frutto del pesco e della resistenza alle malattie’’ (Grant # DM14999/7303/08) and “ESPLORA: Esplorazione della biodiversità vegetale ed animale alla ricerca di alleli superiori da inserire nei programmi avanzati di miglioramento genetico a sostegno dell’agricoltura nazionale” (Grant #DM 14658/7303/10); by the Spanish Ministry of Science and Innovation (http://www.micinn.es/) through the project AGL2012-40228-C02-01 (uso de la secuencia genomica para la caracterizacion de la variabilidad intraclonal e interespecifica en Melocotonero y almendro) and by the INIA (http://www.inia.es/) through the Project RF2012-00024-C04-04 (“conservación y caracterización de germoplasma introducido”).