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Abstract Genomic regions associated with ripening time (RPT) and soluble solids concentration (SSC) were mapped using a pedigreed population including multiple F1 and F2 families from the Clemson University peach breeding program (CUPBP). RPT and SSC QTLs were consistently identified in two seasons (2011 and 2012) and the average datasets (average of two seasons). A target region spanning 10,981,971–11,298,736 bp on chromosome 4 of peach reference genome used for haplotype analysis revealed four haplotypes with significant differences in trait values among different diplotype combinations. Favorable alleles at the target region for both RPT and SSC were determined and a DNA test for predicting RPT and SSC was developed. Two Kompetitive Allele Specific PCR (KASP) assays were validated on 84 peach cultivars and 163 seedlings from the CUPBP, with only one assay (Ppe.RPT/SSC-1) needed to predict between early and late-season ripening cultivars and low and high SSC. These results advance our understanding of the genetic basis of RPT and SSC and facilitate selection of new peach cultivars with the desired RPT and SSC.

Abstract Chilling requirement (CR) is an important agronomic trait controlling the floral bud break for proper flowering in peach. Even though it has been widely researched and several peach CR quantitative trait loci (QTLs) have been identified, no diagnostic DNA tests validated in the U.S. peach breeding germplasm are available for this trait. Breeders and growers need a simple DNA test to predict the CR of peach cultivars for their particular environment. Therefore, we developed a quick and reliable Kompetitive Allele Specific PCR (KASP) DNA test using haplotype information from 9K IPSC genotype data of the U.S. peach germplasm integrating four CR-associated SNP markers from the previously reported CR QTL region on linkage group 1. Four KASP assays (Ppe.CR.1-1 to -4) were developed and validated on 77 peach cultivars, and nine accessions from two F2 populations, with 96 and 74% accuracy in determining expected CR genotype (compared to SNP array) and predicting phenotype, respectively. Furthermore, the Ppe.CR.1 showed 80% accuracy in predicting the precise CR phenotype in the Clemson University peach breeding material. Only one Ppe.CR.1 KASP assay (Ppe.CR.1-1) is needed to distinguish between haplotypes with CR lower and higher than 800 chilling hours, and two Ppe.CR.1 assays (Pp.CR.1-1 and -4), are capable of distinguishing low, moderate, and high CR alleles. Coupled with the crude DNA extraction, the Ppe.CR.1 DNA test provides a low-cost option for breeders and growers to predict CR in peach material with more than 70% accuracy.

Armillaria root rot (ARR), caused by Armillaria species and Desarmillaria tabescens, is a severe disease that affects stone fruit trees in the United States. One strategy to mitigate the impact of this disease is to develop ARR-resistant rootstocks. However, current techniques to screen Prunus species for resistance to ARR are time-consuming, labor-intensive, and may not fully replicate field conditions. To address these limitations, we developed a new rapid in vitro screening assay, which uses roots of 2-year-old Prunus rootstock genotypes. We screened 12 Prunus genotypes against Armillaria mellea, Armillaria solidipes, and Desarmillaria tabescens in vitro. Freshly excavated root segments were placed next to or on top of fungal cultures. After 21 days, the circumferential percentage and horizontal length of the fungal colonization and the ability of the fungus to enter through root periderm were evaluated. The root tissue surrounding the infection was also evaluated to assess any response reactions against the ARR pathogens. Our results showed that inoculated root tissues displayed signs of fungal infection, and infection and host responses varied among the Prunus genotypes. Host responses similar to those observed in the field, such as compartmentalization of infected tissue with barrier zones, necrophylactic periderm formation, and callus formation on root surfaces, were observed and were more evident in less susceptible genotypes. In conclusion, our newly developed assay, which uses freshly excavated roots from 2-year-old rootstocks, can rapidly screen Prunus genotypes for resistance to ARR.

Climate change is affecting the production of temperate fruit crops. Freeze damage, particularly in spring, has resulted in significant economic losses in peach production in the southeastern United States. Research efforts in peach and other Prunus species have primarily focused on dormancy-related traits associated with bloom time, such as chill and heat requirement, with fruitlet freeze tolerance not equally represented. This study reports fruitlet freeze tolerance in 75 peach and nectarine accessions at six freezing temperatures (0 to −10 °C) using electrolyte leakage method over two seasons (2022–2023). Fruitlet freeze tolerance ranged from −3.9 to −10.2 °C with an estimated freeze damage ranging from 16–48% of fruitlet tissue with the majority of the accessions showing tolerance to cold temperatures in the −4 to −6 °C and 25–35% range. Variability in tolerance was noted across years, including some inconsistencies between tolerance group assignments. Grouping based on the estimated damage showed better stability and some accessions changed their grouping from the extremes to an intermediate tolerance group. Interestingly, nectarine accessions were among the most tolerant in both seasons. Broad-sense heritability of 0.52 and 0.85, estimated for freeze tolerance and % tissue damage, respectively, suggested genetic control of this trait with a potential for improvement via breeding.

Armillaria root rot (ARR) poses a significant threat to the long-term productivity of stone-fruit and nut crops in the predominant production area of the United States. To mitigate this issue, the development of ARR-resistant and horticulturally-acceptable rootstocks is a crucial step towards the maintenance of production sustainability. To date, genetic resistance to ARR has been found in exotic plum germplasm and a peach/plum hybrid rootstock, ’MP-29‘. However, the widely-used peach rootstock Guardian® is susceptible to the pathogen. To understand the molecular defense mechanisms involved in ARR resistance in Prunus rootstocks, transcriptomic analyses of one susceptible and two resistant Prunus spp. were performed using two causal agents of ARR, including Armillaria mellea and Desarmillaria tabescens. The results of in vitro co-culture experiments revealed that the two resistant genotypes showed different temporal response dynamics and fungus-specific responses, as seen in the genetic response. Gene expression analysis over time indicated an enrichment of defense-related ontologies, including glucosyltransferase activity, monooxygenase activity, glutathione transferase activity, and peroxidase activity. Differential gene expression and co-expression network analysis highlighted key hub genes involved in the sensing and enzymatic degradation of chitin, GSTs, oxidoreductases, transcription factors, and biochemical pathways likely involved in Armillaria resistance. These data provide valuable resources for the improvement of ARR resistance in Prunus rootstocks through breeding.

Brown rot, caused by Monilinia spp., is one of the most important postharvest diseases of stone fruits worldwide. Brown rot resistance in peach is a polygenic trait controlled by multiple genes with a small effect. In this study, we assessed the feasibility of genomic prediction (GP) for brown rot resistance in peach using eight contrasting methods (GBLUP, rrBLUP, BayesA, BayesB, BayesC, Bayesian Ridge Regression, Bayesian Lasso and RKHS). A testing panel of 38 cultivars/advanced selections and 288 F1 individuals from 27 pedigree-related breeding families with 'Bolinha' and/or 'Contender' or almond source of resistance was phenotyped over six seasons (2015 to 2020). GP models outperformed MAS models under five-fold cross validation, and low to moderate predictive accuracy (PA) was achieved by fitting GP model for wounded (W) (0.092−0.449) and low PA for non-wounded (NW) disease severity index (0.129−0.295). An alternative cross validation approach using disease severity index recorded in lab to predict field disease incidence (FDI) in unphenotyped accessions revealed moderate correlation (0.548−0.553). Genomic predicted breeding value distinguished accessions with low FDI from those with high FDI. The results presented here demonstrated feasibility of incorporating GP in peach breeding.

Genotype-by-environment interaction (G × E) is a common phenomenon influencing genetic improvement in plants, and a good understanding of this phenomenon is important for breeding and cultivar deployment strategies. However, there is little information on G × E in horticultural tree crops, mostly due to evaluation costs, leading to a focus on the development and deployment of locally adapted germplasm. Using sweetness (measured as soluble solids content, SSC) in peach/nectarine assessed at four trials from three US peach-breeding programs as a case study, we evaluated the hypotheses that (i) complex data from multiple breeding programs can be connected using GBLUP models to improve the knowledge of G × E for breeding and deployment and (ii) accounting for a known large-effect quantitative trait locus (QTL) improves the prediction accuracy. Following a structured strategy using univariate and multivariate models containing additive and dominance genomic effects on SSC, a model that included a previously detected QTL and background genomic effects was a significantly better fit than a genome-wide model with completely anonymous markers. Estimates of an individual’s narrow-sense and broad-sense heritability for SSC were high (0.57–0.73 and 0.66–0.80, respectively), with 19–32% of total genomic variance explained by the QTL. Genome-wide dominance effects and QTL effects were stable across environments. Significant G × E was detected for background genome effects, mostly due to the low correlation of these effects across seasons within a particular trial. The expected prediction accuracy, estimated from the linear model, was higher than the realised prediction accuracy estimated by cross-validation, suggesting that these two parameters measure different qualities of the prediction models. While prediction accuracy was improved in some cases by combining data across trials, particularly when phenotypic data for untested individuals were available from other trials, this improvement was not consistent. This study confirms that complex data can be combined into a single analysis using GBLUP methods to improve understanding of G × E and also incorporate known QTL effects. In addition, the study generated baseline information to account for population structure in genomic prediction models in horticultural crop improvement.

Abstract Background Environmental 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. Results Phenotypic data of seven F1 low 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. Conclusions A 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.

U.S. peach (Prunus persica) growers are challenged by the need to protect their orchards from economically damaging diseases and deliver fruit with the quality expectations of the supply chain. This study focuses on the U.S. southeastern peach sector, including North Carolina, South Carolina, Alabama, Virginia, and Georgia. This region offers a useful case to analyze growers’ preferences for both fruit quality and disease resistance. We collected primary data from peach operations in 2016 and 2018. In both surveys, a discrete choice experiment was used to advance the understanding of how peach growers in the southeastern United States value fruit quality (i.e., fruit size and external color) vs. disease resistance [i.e., brown rot (Monilinia fructicola)]. The sample of growers surveyed in 2016 growers placed a greater importance on the fruit quality attribute that would imply higher returns, that is, fruit size (expressed as fruit diameter) compared with improvements in brown rot resistance and external fruit color. Meanwhile, the sample of growers surveyed in 2018 placed a higher importance to brown rot resistance and external fruit color compared with fruit size. Findings consistent for the 2 years are that growers are willing to pay for larger rather than smaller improvements in brown rot resistance, and that a large improvement in brown rot resistance is more important than external fruit color.

Abstract 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 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. Results Phenotypic data of seven F1 low 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. Conclusions A 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.

Bud break timing in peach [Prunus persica (L.) Batsch] is determined by the sequential fulfillment of a chilling requirement (CR) and a heat requirement (HR) for development. Genotypic variation in CR has been well characterized in peach. Adapting peaches to low chilling environment through reduced CR can make them susceptible to crop destroying spring frosts, if bloom occurs too early. Potential variation in HR between accessions has received less attention due to the methodological difficulty in assessing HR independently of CR. HR could vary in the magnitude of growing degree hours (GDHs) and/or the base temperature at which GDH accumulation begins. Characterizing HR traits in peach accessions could allow improved bloom time modeling and selection of phenotypes with improved spring frost avoidance through delayed bloom. We estimated GDH and apparent base temperature for floral bud break by observing time to floral bud break at several constant forcing temperatures. We evaluated 54 peach accessions (representing a range of CR) in which chilling had been saturated after >1,700 h at 3°C. Accessions differed widely in both the GDH requirement (2,015 to 11,191°C⋅h) and apparent base temperature (−1.85 to 8.69°C) for GDH accumulation. GDH and apparent base temperature were negatively correlated. A simulation exercise was performed to assess relative importance of varying base temperature vs. GDH for delaying bloom at different chilling accumulations at three locations in the southeastern United States using 30 years of historical weather data. The aim of this study was to determine whether there may be unrecognized diversity in peach germplasm for two HR traits (base temperature and thermal time) to enable breeding efforts to delay floral bud break and reduce the frost exposure risk of developing flowers and fruits. Our results suggest that selecting cultivars for increased GDH would be a safer, more reliable strategy for delaying bloom than increasing base temperature for GDH accumulation.

Bacterial spot, caused by Xanthomonas arboricola pv. pruni (Xap), is a serious peach disease with symptoms that traverse severe defoliation and black surface pitting, cracking or blemishes on peach fruit with global economic impacts. A management option for control and meeting consumer demand for chemical-free, environmentally friendly fruit production is the development of resistant or tolerant cultivars. We developed simple, accurate, and efficient DNA assays (Ppe.XapF) based on SNP genotyping with KASP technology to quickly test for bacterial spot resistance alleles in peach fruit that allows breeders to cull seedlings at the greenhouse stage. The objective of this research was to validate newly developed DNA tests that target the two major QTLs for fruit resistance in peach with diagnostic utility in predicting fruit response to bacterial spot infection. Our study confirms that with only two Ppe.XapF DNA tests, Ppe.XapF1-1 and Ppe.XapF6-2, individuals carrying susceptible alleles can be identified. Use of these efficient and accurate Ppe.XapF KASP tests resulted in 44% reduction in seedling planting rate in the Clemson University peach breeding program.

A fruitful genomic resource Detailed genomic maps from the fruit-bearing trees of the Prunus genus should greatly accelerate the breeding of superior cultivars. These plants produce a variety of popular fruits, but until relatively recently, breeders had only limited genetic information with which to work. Pere Arús of Spain’s Institute of Agrifood Research and Technology and colleagues have now reviewed the rapid advances in Prunus genomics that have taken place since 2010, when researchers completed the first genome assembly for this genus. In the ensuing decade, increasingly high-quality genomes from the peach, Japanese apricot, and cherry have allowed scientists to home in on chromosomal regions associated with key traits such as fruit quality and disease resistance. These data also offer valuable genetic markers that agronomists can use to guide the production of healthier trees and more commercially desirable fruits.

Bud dormancy is a genotype-dependent mechanism observed in Prunus species in which bud growth is inhibited, and the accumulation of a specific amount of chilling (endodormancy) and heat (ecodormancy) is necessary to resume growth and reach flowering. We analyzed publicly available transcriptome data from fifteen cultivars of four Prunus species (almond, apricot, peach, and sweet cherry) sampled at endo- and ecodormancy points to identify conserved genes and pathways associated with dormancy control in the genus. A total of 13,018 genes were differentially expressed during dormancy transitions, of which 139 and 223 were of interest because their expression profiles correlated with endo- and ecodormancy, respectively, in at least one cultivar of each species. The endodormancy-related genes comprised transcripts mainly overexpressed during chilling accumulation and were associated with abiotic stresses, cell wall modifications, and hormone regulation. The ecodormancy-related genes, upregulated after chilling fulfillment, were primarily involved in the genetic control of carbohydrate regulation, hormone biosynthesis, and pollen development. Additionally, the integrated co-expression network of differentially expressed genes in the four species showed clusters of co-expressed genes correlated to dormancy stages and genes of breeding interest overlapping with quantitative trait loci for bloom time and chilling and heat requirements.

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.

Peach is one of the most important fruit crops in the world, with the global annual production about 24.6 million tons. The United States is the fourth-largest producer after China, Spain, and Italy. Peach consumption has decreased over the last decade, most likely due to inconsistent quality of the fruit on the market. Thus, marker-assisted selection for fruit quality traits is highly desired in fresh market peach breeding programs and one of the major goals of the RosBREED project. The ability to use DNA information to select for desirable traits would enable peach breeders to efficiently plan crosses and select seedlings with desired quality traits early in the selection process before fruiting. Therefore, we assembled a multi-locus genome wide association study (GWAS) of 620 individuals from three public fresh market peach breeding programs (Arkansas, Texas, and South Carolina). The material was genotyped using 9K SNP array and the traits were phenotyped for three phenological (bloom date, ripening date, and days after bloom) and 11 fruit quality-related traits (blush, fruit diameter, fruit weight, adherence, fruit firmness, redness around pit, fruit texture, pit weight, soluble solid concentration, titratable acidity, and pH) over three seasons (2010, 2011, and 2012). Multi-locus association analyses, carried out using mrMLM 4.0 and FarmCPU R packages, revealed a total of 967 and 180 quantitative trait nucleotides (QTNs), respectively. Among the 88 consistently reliable QTNs detected using multiple multi-locus GWAS methods and/or at least two seasons, 44 were detected for the first time. Fruit quality hotspots were identified on chromosomes 1, 3, 4, 5, 6, and 8. Out of 566 candidate genes detected in the genomic regions harboring the QTN clusters, 435 were functionally annotated. Gene enrichment analyses revealed 68 different gene ontology (GO) terms associated with fruit quality traits. Data reported here advance our understanding of genetic mechanisms underlying important fruit quality traits and further support the development of DNA tools for breeding.

Bloom date (BD) in peach is determined by the dynamic relationship between chilling (CR) and heat requirement (HR) fulfilment during dormancy. Understanding these thermal requirements would enable breeders to adapt new cultivars to variable climates. Among the three traits, HR is the least investigated, with the genetic variability in peach germplasm and interaction between HR, CR and BD still mostly unknown. Therefore, we investigated the HR of 136 peach cultivars over 8 growing seasons (2014–2021) by calculating the growing degree hours (GDH) from the moment their CR was satisfied until full bloom. The HR ranged from 1362 to 10,348 GDH across years and cultivars, with cultivar HR eight-year having the best linear unbiased prediction (BLUP) values from 4808 to 7721 GDH. In addition, a high positive correlation between BD and CR, a negative correlation between CR and HR and a seasonal effect on the correlation between BD and HR were observed. Moreover, simulating HR with different threshold base temperatures (Tb) revealed different trends of GDH accumulation, suggesting that genotype-specific Tb should be determined to allow precise discrimination of this requirement. Peach germplasm showed high variation in HR that could be used in breeding for bloom delay to adapt to different environments and climate change.

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.

It has recently been described that the Japanese plum “Santa Rosa” bud sport series contains variations in ripening pattern: climacteric, suppressed-climacteric and non-climacteric types. This provides an interesting model to study the role of ethylene and other key mechanisms governing fruit ripening, softening and senescence. The aim of the current study was to investigate such differences at the genomic level, using this series of plum bud sports, with special reference to genes involved in ethylene biosynthesis, signal transduction, and sugar metabolism. Genomic DNA, isolated from leaf samples of six Japanese plum cultivars (“Santa Rosa”, “July Santa Rosa”, “Late Santa Rosa”, “Sweet Miriam”, “Roysum”, and “Casselman”), was used to construct paired-end standard Illumina libraries. Sequences were aligned to the Prunus persica genome, and genomic variations (SNPs, INDELS, and CNV's) were investigated. Results determined 12 potential candidate genes with significant copy number variation (CNV), being associated with ethylene perception and signal transduction components. Additionally, the Maximum Likelihood (ML) phylogenetic tree showed two sorbitol dehydrogenase genes grouping into a distinct clade, indicating that this natural group is well-defined and presents high sequence identity among its members. In contrast, the ethylene group, which includes ACO1, ACS1, ACS4, ACS5, CTR1, ERF1, ERF3, and ethylene-receptor genes, was widely distributed and clustered into 10 different groups. Thus, ACS, ERF, and sorbitol dehydrogenase proteins potentially share a common ancestor for different plant genomes, while the expansion rate may be related to ancestral expansion rather than species-specific events. Based on the distribution of the clades, we suggest that gene function diversification for the ripening pathway occurred prior to family extension. We herein report all the frameshift mutations in genes involved in sugar transport and ethylene biosynthesis detected as well as the gene CNV implicated in ripening differences.

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.

A total of 34 apple ( × Borkh.) cDNA libraries were constructed from root, leaf, bud, shoot, flower, and fruit tissues, at various developmental stages and/or under biotic or abiotic stress conditions, and of several genotypes. From these libraries, 190,425 clones were partially sequenced from the 5′ end and 42,619 clones were sequenced from the 3′ end, and a total of 182,241 high-quality expressed sequence tags (ESTs) were obtained. These coalesced into 23,442 tentative contigs and 9843 singletons, for a total of 33,825 apple unigenes. Functional annotation of this unigene set revealed an even distribution of apple sequences among the three main gene ontology categories. Of ∼33,000 apple unigenes, 8437 (25%) had no detectable homologs ( >0.1) in the genome. When the entire apple unigene set was compared with the entire citrus [ (L.) Osbeck] unigene set and the poplar ( Torr. & Gray) predicted proteome, both members of the core eudicot and rosids clade, 13,521 of apple unigenes matched one or more sequences in citrus, while 25,817 had counterparts in the poplar protein database. Apple––citrus–poplar comparisons revealed closer evolutionary relationships between apple and poplar than with the other two species. Genes involved in basic metabolic pathways appear to be largely conserved among apple, citrus, poplar, and .

Linkage maps are valuable tools in genetic and genomic studies. For sweet cherry, linkage maps have been constructed using mainly microsatellite markers (SSRs) and, recently, using single nucleotide polymorphism markers (SNPs) from a cherry 6K SNP array. Genotyping-by-sequencing (GBS), a new methodology based on high-throughput sequencing, holds great promise for identification of high number of SNPs and construction of high density linkage maps. In this study, GBS was used to identify SNPs from an intra-specific sweet cherry cross. A total of 8,476 high quality SNPs were selected for mapping. The physical position for each SNP was determined using the peach genome, Peach v1.0, as reference, and a homogeneous distribution of markers along the eight peach scaffolds was obtained. On average, 65.6% of the SNPs were present in genic regions and 49.8% were located in exonic regions. In addition to the SNPs, a group of SSRs was also used for construction of linkage maps. Parental and consensus high density maps were constructed by genotyping 166 siblings from a 'Rainier' x 'Rivedel' (Ra x Ri) cross. Using Ra x Ri population, 462, 489 and 985 markers were mapped into eight linkage groups in 'Rainier', 'Rivedel' and the Ra x Ri map, respectively, with 80% of mapped SNPs located in genic regions. Obtained maps spanned 549.5, 582.6 and 731.3 cM for 'Rainier', 'Rivedel' and consensus maps, respectively, with an average distance of 1.2 cM between adjacent markers for both 'Rainier' and 'Rivedel' maps and of 0.7 cM for Ra x Ri map. High synteny and co-linearity was observed between obtained maps and with Peach v1.0. These new high density linkage maps provide valuable information on the sweet cherry genome, and serve as the basis for identification of QTLs and genes relevant for the breeding of the species.

Low-cost, high throughput genotyping methods are crucial to marker discovery and marker-assisted breeding efforts, but have not been available for many 'specialty crops' such as fruit and nut trees. Here we apply the Genotyping-By-Sequencing (GBS) method developed for cereals to the discovery of single nucleotide polymorphisms (SNPs) in a peach F2 mapping population. Peach is a genetic and genomic model within the Rosaceae and will provide a template for the use of this method with other members of this family. Our F2 mapping population of 57 genotypes segregates for bloom time (BD) and chilling requirement (CR) and we have extensively phenotyped this population. The population derives from a selfed F1 progeny of a cross between 'Hakuho' (high CR) and 'UFGold' (low CR). We were able to successfully employ GBS and the TASSEL GBS pipeline without modification of the original methodology using the ApeKI restriction enzyme and multiplexing at an equivalent of 96 samples per Illumina HiSeq 2000 lane. We obtained hundreds of SNP markers which were then used to construct a genetic linkage map and identify quantitative trait loci (QTL) for BD and CR.

Although a large number of single nucleotide polymorphism (SNP) markers covering the entire genome are needed to enable molecular breeding efforts such as genome wide association studies, fine mapping, genomic selection and marker-assisted selection in peach [Prunus persica (L.) Batsch] and related Prunus species, only a limited number of genetic markers, including simple sequence repeats (SSRs), have been available to date. To address this need, an international consortium (The International Peach SNP Consortium; IPSC) has pursued a coordinated effort to perform genome-scale SNP discovery in peach using next generation sequencing platforms to develop and characterize a high-throughput Illumina Infinium® SNP genotyping array platform. We performed whole genome re-sequencing of 56 peach breeding accessions using the Illumina and Roche/454 sequencing technologies. Polymorphism detection algorithms identified a total of 1,022,354 SNPs. Validation with the Illumina GoldenGate® assay was performed on a subset of the predicted SNPs, verifying ∼75% of genic (exonic and intronic) SNPs, whereas only about a third of intergenic SNPs were verified. Conservative filtering was applied to arrive at a set of 8,144 SNPs that were included on the IPSC peach SNP array v1, distributed over all eight peach chromosomes with an average spacing of 26.7 kb between SNPs. Use of this platform to screen a total of 709 accessions of peach in two separate evaluation panels identified a total of 6,869 (84.3%) polymorphic SNPs.The almost 7,000 SNPs verified as polymorphic through extensive empirical evaluation represent an excellent source of markers for future studies in genetic relatedness, genetic mapping, and dissecting the genetic architecture of complex agricultural traits. The IPSC peach SNP array v1 is commercially available and we expect that it will be used worldwide for genetic studies in peach and related stone fruit and nut species.