15 years of GDR: New data and functionality in the Genome Database for Rosaceae.

The Genome Database for Rosaceae (GDR, https://www.rosaceae.org) is an integrated web-based community database resource providing access to publicly available genomics, genetics and breeding data and data-mining tools to facilitate basic, translational and applied research in Rosaceae. The volume of data in GDR has increased greatly over the last 5 years. The GDR now houses multiple versions of whole genome assembly and annotation data from 14 species, made available by recent advances in sequencing technology. Annotated and searchable reference transcriptomes, RefTrans, combining peer-reviewed published RNA-Seq as well as EST datasets, are newly available for major crop species. Significantly more quantitative trait loci, genetic maps and markers are available in MapViewer, a new visualization tool that better integrates with other pages in GDR. Pathways can be accessed through the new GDR Cyc Pathways databases, and synteny among the newest genome assemblies from eight species can be viewed through the new synteny browser, SynView. Collated single-nucleotide polymorphism diversity data and phenotypic data from publicly available breeding datasets are integrated with other relevant data. Also, the new Breeding Information Management System allows breeders to upload, manage and analyze their private breeding data within the secure GDR server with an option to release data publicly.

Genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits.

BACKGROUND: Sweet cherry is consumed widely across the world and provides substantial economic benefits in regions where it is grown. While cherry breeding has been conducted in the Pacific Northwest for over half a century, little is known about the genetic architecture of important traits. We used a genome-enabled mixed model to predict the genetic performance of 505 individuals for 32 phenological, disease response and fruit quality traits evaluated in the RosBREED sweet cherry crop data set. Genome-wide predictions were estimated using a repeated measures model for phenotypic data across 3 years, incorporating additive, dominance and epistatic variance components. Genomic relationship matrices were constructed with high-density SNP data and were used to estimate relatedness and account for incomplete replication across years. RESULTS: High broad-sense heritabilities of 0.83, 0.77, and 0.76 were observed for days to maturity, firmness, and fruit weight, respectively. Epistatic variance exceeded 40% of the total genetic variance for maturing timing, firmness and powdery mildew response. Dominance variance was the largest for fruit weight and fruit size at 34% and 27%, respectively. Omission of non-additive sources of genetic variance from the genetic model resulted in inflation of narrow-sense heritability but minimally influenced prediction accuracy of genetic values in validation. Predicted genetic rankings of individuals from single-year models were inconsistent across years, likely due to incomplete sampling of the population genetic variance. CONCLUSIONS: Predicted breeding values and genetic values revealed many high-performing individuals for use as parents and the most promising selections to advance for cultivar release consideration, respectively. This study highlights the importance of using the appropriate genetic model for calculating breeding values to avoid inflation of expected parental contribution to genetic gain. The genomic predictions obtained will enable breeders to efficiently leverage the genetic potential of North American sweet cherry germplasm by identifying high quality individuals more rapidly than with phenotypic data alone.

The Genome Database for Rosaceae (GDR): year 10 update.

The Genome Database for Rosaceae (GDR, http:/www.rosaceae.org), the long-standing central repository and data mining resource for Rosaceae research, has been enhanced with new genomic, genetic and breeding data, and improved functionality. Whole genome sequences of apple, peach and strawberry are available to browse or download with a range of annotations, including gene model predictions, aligned transcripts, repetitive elements, polymorphisms, mapped genetic markers, mapped NCBI Rosaceae genes, gene homologs and association of InterPro protein domains, GO terms and Kyoto Encyclopedia of Genes and Genomes pathway terms. Annotated sequences can be queried using search interfaces and visualized using GBrowse. New expressed sequence tag unigene sets are available for major genera, and Pathway data are available through FragariaCyc, AppleCyc and PeachCyc databases. Synteny among the three sequenced genomes can be viewed using GBrowse_Syn. New markers, genetic maps and extensively curated qualitative/Mendelian and quantitative trait loci are available. Phenotype and genotype data from breeding projects and genetic diversity projects are also included. Improved search pages are available for marker, trait locus, genetic diversity and publication data. New search tools for breeders enable selection comparison and assistance with breeding decision making.

Development and preliminary evaluation of a 90 K Axiom® SNP array for the allo-octoploid cultivated strawberry Fragaria × ananassa.

BACKGROUND: A high-throughput genotyping platform is needed to enable marker-assisted breeding in the allo-octoploid cultivated strawberry Fragaria × ananassa. Short-read sequences from one diploid and 19 octoploid accessions were aligned to the diploid Fragaria vesca 'Hawaii 4' reference genome to identify single nucleotide polymorphisms (SNPs) and indels for incorporation into a 90 K Affymetrix® Axiom® array. We report the development and preliminary evaluation of this array. RESULTS: About 36 million sequence variants were identified in a 19 member, octoploid germplasm panel. Strategies and filtering pipelines were developed to identify and incorporate markers of several types: di-allelic SNPs (66.6%), multi-allelic SNPs (1.8%), indels (10.1%), and ploidy-reducing "haploSNPs" (11.7%). The remaining SNPs included those discovered in the diploid progenitor F. iinumae (3.9%), and speculative "codon-based" SNPs (5.9%). In genotyping 306 octoploid accessions, SNPs were assigned to six classes with Affymetrix's "SNPolisher" R package. The highest quality classes, PolyHigh Resolution (PHR), No Minor Homozygote (NMH), and Off-Target Variant (OTV) comprised 25%, 38%, and 1% of array markers, respectively. These markers were suitable for genetic studies as demonstrated in the full-sib family 'Holiday' × 'Korona' with the generation of a genetic linkage map consisting of 6,594 PHR SNPs evenly distributed across 28 chromosomes with an average density of approximately one marker per 0.5 cM, thus exceeding our goal of one marker per cM. CONCLUSIONS: The Affymetrix IStraw90 Axiom array is the first high-throughput genotyping platform for cultivated strawberry and is commercially available to the worldwide scientific community. The array's high success rate is likely driven by the presence of naturally occurring variation in ploidy level within the nominally octoploid genome, and by effectiveness of the employed array design and ploidy-reducing strategies. This array enables genetic analyses including generation of high-density linkage maps, identification of quantitative trait loci for economically important traits, and genome-wide association studies, thus providing a basis for marker-assisted breeding in this high value crop.

A candidate gene based approach validates Md-PG1 as the main responsible for a QTL impacting fruit texture in apple (Malus x domestica Borkh).

BACKGROUND: Apple is a widely cultivated fruit crop for its quality properties and extended storability. Among the several quality factors, texture is the most important and appreciated, and within the apple variety panorama the cortex texture shows a broad range of variability. Anatomically these variations depend on degradation events occurring in both fruit primary cell wall and middle lamella. This physiological process is regulated by an enzymatic network generally encoded by large gene families, among which polygalacturonase is devoted to the depolymerization of pectin. In apple, Md-PG1, a key gene belonging to the polygalacturonase gene family, was mapped on chromosome 10 and co-localized within the statistical interval of a major hot spot QTL associated to several fruit texture sub-phenotypes. RESULTS: In this work, a QTL corresponding to the position of Md-PG1 was validated and new functional alleles associated to the fruit texture properties in 77 apple cultivars were discovered. 38 SNPs genotyped by gene full length resequencing and 2 SSR markers ad hoc targeted in the gene metacontig were employed. Out of this SNP set, eleven were used to define three significant haplotypes statistically associated to several texture components. The impact of Md-PG1 in the fruit cell wall disassembly was further confirmed by the cortex structure electron microscope scanning in two apple varieties characterized by opposite texture performance, such as 'Golden Delicious' and 'Granny Smith'. CONCLUSIONS: The results here presented step forward into the genetic dissection of fruit texture in apple. This new set of haplotypes, and microsatellite alleles, can represent a valuable toolbox for a more efficient parental selection as well as the identification of new apple accessions distinguished by superior fruit quality features.

Deducing genotypes for loci of interest from SNP array data via haplotype sharing, demonstrated for apple and cherry.

Breeders, collection curators, and other germplasm users require genetic information, both genome-wide and locus-specific, to effectively manage their genetically diverse plant material. SNP arrays have become the preferred platform to provide genome-wide genetic profiles for elite germplasm and could also provide locus-specific genotypic information. However, genotypic information for loci of interest such as those within PCR-based DNA fingerprinting panels and trait-predictive DNA tests is not readily extracted from SNP array data, thus creating a disconnect between historic and new data sets. This study aimed to establish a method for deducing genotypes at loci of interest from their associated SNP haplotypes, demonstrated for two fruit crops and three locus types: quantitative trait loci Ma and Ma3 for acidity in apple, apple fingerprinting microsatellite marker GD12, and Mendelian trait locus Rf for sweet cherry fruit color. Using phased data from an apple 8K SNP array and sweet cherry 6K SNP array, unique haplotypes spanning each target locus were associated with alleles of important breeding parents. These haplotypes were compared via identity-by-descent (IBD) or identity-by-state (IBS) to haplotypes present in germplasm important to U.S. apple and cherry breeding programs to deduce target locus alleles in this germplasm. While IBD segments were confidently tracked through pedigrees, confidence in allele identity among IBS segments used a shared length threshold. At least one allele per locus was deduced for 64-93% of the 181 individuals. Successful validation compared deduced Rf and GD12 genotypes with reported and newly obtained genotypes. Our approach can efficiently merge and expand genotypic data sets, deducing missing data and identifying errors, and is appropriate for any crop with SNP array data and historic genotypic data sets, especially where linkage disequilibrium is high. Locus-specific genotypic information extracted from genome-wide SNP data is expected to enhance confidence in management of genetic resources.

Detection of Breeding-Relevant Fruit Cracking and Fruit Firmness Quantitative Trait Loci in Sweet Cherry via Pedigree-Based and Genome-Wide Association Approaches.

Breeding for decreased fruit cracking incidence and increased fruit firmness in sweet cherry creates an attractive alternative to variable results from cultural management practices. DNA-informed breeding increases its efficiency, yet upstream research is needed to identify the genomic regions associated with the trait variation of a breeding-relevant magnitude, as well as to identify the parental sources of favorable alleles. The objectives of this research were to identify the quantitative trait loci (QTLs) associated with fruit cracking incidence and firmness, estimate the effects of single nucleotide polymorphism (SNP) haplotypes at the detected QTLs, and identify the ancestral source(s) of functional haplotypes. Fruit cracking incidence and firmness were evaluated for multiple years on 259 unselected seedlings representing 22 important breeding parents. Phenotypic data, in conjunction with genome-wide genotypic data from the RosBREED cherry 6K SNP array, were used in the QTL analysis performed via Pedigree-Based Analysis using the FlexQTL™ software, supplemented by a Genome-Wide Association Study using the BLINK software. Haplotype analysis was conducted on the QTLs to identify the functional SNP haplotypes and estimate their phenotypic effects, and the haplotypes were tracked through the pedigree. Four QTLs (two per trait) were consistent across the years and/or both analysis methods and validated the previously reported QTLs. qCrack-LG1.1m (the label given to a consistent QTL for cracking incidence on chromosome 1) explained 2-15.1% of the phenotypic variance, while qCrack-LG5.1m, qFirm-LG1.2m, and qFirm-LG3.2m explained 7.6-13.8, 8.8-21.8, and 1.7-10.1% of the phenotypic variance, respectively. At each QTL, at least two SNP haplotypes had significant effects and were considered putative functional SNP haplotypes. Putative low-cracking SNP haplotypes were tracked to an unnamed parent of 'Emperor Francis' and 'Schmidt' and unnamed parents of 'Napoleon' and 'Hedelfingen,' among others, and putative high-firmness haplotypes were tracked to an unnamed parent of 'Emperor Francis' and 'Schmidt,' an unnamed grandparent of 'Black Republican,' 'Rube,' and an unknown parent of 'Napoleon.' These four stable QTLs can now be targeted for DNA test development, with the goal of translating information discovered here into usable tools to aid in breeding decisions.

As It Stands: The Palouse Wild Cider Apple Breeding Program.

Providing hands-on education for the next generation of plant breeders would help maximize effectiveness of future breeding efforts. Such education should include training in introgression of crop wild relative alleles, which can increase genetic diversity while providing cultivar attributes that meet industry and consumer demands in a crop such as cider apple. Incorporation of DNA information in breeding decisions has become more common and is another skill future plant breeders need. The Palouse Wild Cider apple breeding program (PWCabp) was established at Washington State University in early 2014 as a student-run experiential learning opportunity. The objectives of this study were to describe the PWCabp's approaches, outcomes, and student involvement to date that has relied on a systematic operational structure, utilization of wild relatives, and incorporation of DNA information. Students chose the crop (cider apple) and initial target market and stakeholders (backyard growers and hobbyists of the Palouse region). Twelve target attributes were defined including high phenolics and red flesh. Phase one and two field trials were established. Two promising high-bitterness selections were identified and propagated. By running the PWCabp, more than 20 undergraduate and graduate students gained experience in the decisions and operations of a fruit breeding program. PWCabp activities have produced desirable new germplasm via utilization of highly diverse Malus germplasm and trained new plant breeding professionals via experiential learning.

DNA profiling with the 20K apple SNP array reveals Malus domestica hybridization and admixture in M. sieversii, M. orientalis, and M. sylvestris genebank accessions.

The USDA-ARS National Plant Germplasm System (NPGS) apple collection in Geneva, NY, USA maintains accessions of the primary Malus domestica (Suckow) Borkh. progenitor species M. sieversii (Ledeb.) M. Roem., M. orientalis Uglitzk., and M. sylvestris (L.) Mill. Many of these accessions originated from seeds that were collected from wild populations in the species' centers of diversity. Some of these accessions have fruit phenotypes that suggest recent M. domestica hybridization, which if true would represent crop contamination of wild species populations and mislabeled species status of NPGS accessions. Pedigree connections and admixture between M. domestica and its progenitor species can be readily identified with apple SNP array data, despite such arrays not being designed for these purposes. To investigate species purity, most (463 accessions) of the NPGS accessions labeled as these three progenitor species were genotyped using the 20K apple SNP array. DNA profiles obtained were compared with a dataset of more than 5000 unique M. domestica apple cultivars. Only 212 accessions (151 M. sieversii, 26 M. orientalis, and 35 M. sylvestris) were identified as "pure" species representatives because their DNA profiles did not exhibit genotypic signatures of recent hybridization with M. domestica. Twenty-one accessions (17 M. sieversii, 1 M. orientalis, and 3 M. sylvestris) previously labeled as wild species were instead fully M. domestica. Previously unrealized hybridization and admixture between wild species and M. domestica was identified in 230 accessions (215 M. sieversii, 9 M. orientalis, and 6 M. sylvestris). Among these species-mislabeled accessions, 'Alexander', 'Gold Reinette', 'Charlamoff', 'Rosmarina Bianca', and 'King of the Pippins' were the most frequently detected M. domestica parents or grandparents. These results have implications for collection management, including germplasm distribution, and might affect conclusions of previous research focused on these three progenitor species in the NPGS apple collection. Specifically, accessions received from the NPGS for breeding and genomics, genetics, and evolutionary biology research might not be truly representative of their previously assigned species.

Multi-environment genomic prediction for soluble solids content in peach (Prunus persica).

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.

Fire blight QTL analysis in a multi-family apple population identifies a reduced-susceptibility allele in 'Honeycrisp'.

Breeding apple cultivars with resistance offers a potential solution to fire blight, a damaging bacterial disease caused by Erwinia amylovora. Most resistance alleles at quantitative trait loci (QTLs) were previously characterized in diverse Malus germplasm with poor fruit quality, which reduces breeding utility. This study utilized a pedigree-based QTL analysis approach to elucidate the genetic basis of resistance/susceptibility to fire blight from multiple genetic sources in germplasm relevant to U.S. apple breeding programs. Twenty-seven important breeding parents (IBPs) were represented by 314 offspring from 32 full-sib families, with 'Honeycrisp' being the most highly represented IBP. Analyzing resistance/susceptibility data from a two-year replicated field inoculation study and previously curated genome-wide single nucleotide polymorphism data, QTLs were consistently mapped on chromosomes (Chrs.) 6, 7, and 15. These QTLs together explained ~28% of phenotypic variation. The Chr. 6 and Chr. 15 QTLs colocalized with previously reported QTLs, while the Chr. 7 QTL is possibly novel. 'Honeycrisp' inherited a rare reduced-susceptibility allele at the Chr. 6 QTL from its grandparent 'Frostbite'. The highly resistant IBP 'Enterprise' had at least one putative reduced-susceptibility allele at all three QTLs. In general, lower susceptibility was observed for individuals with higher numbers of reduced-susceptibility alleles across QTLs. This study highlighted QTL mapping and allele characterization of resistance/susceptibility to fire blight in complex pedigree-connected apple breeding germplasm. Knowledge gained will enable more informed parental selection and development of trait-predictive DNA tests for pyramiding favorable alleles and selection of superior apple cultivars with resistance to fire blight.

The use of shared haplotype length information for pedigree reconstruction in asexually propagated outbreeding crops, demonstrated for apple and sweet cherry.

Pedigree information is of fundamental importance in breeding programs and related genetics efforts. However, many individuals have unknown pedigrees. While methods to identify and confirm direct parent-offspring relationships are routine, those for other types of close relationships have yet to be effectively and widely implemented with plants, due to complications such as asexual propagation and extensive inbreeding. The objective of this study was to develop and demonstrate methods that support complex pedigree reconstruction via the total length of identical by state haplotypes (referred to in this study as "summed potential lengths of shared haplotypes", SPLoSH). A custom Python script, HapShared, was developed to generate SPLoSH data in apple and sweet cherry. HapShared was used to establish empirical distributions of SPLoSH data for known relationships in these crops. These distributions were then used to estimate previously unknown relationships. Case studies in each crop demonstrated various pedigree reconstruction scenarios using SPLoSH data. For cherry, a full-sib relationship was deduced for 'Emperor Francis, and 'Schmidt', a half-sib relationship for 'Van' and 'Windsor', and the paternal grandparents of 'Stella' were confirmed. For apple, 29 cultivars were found to share an unknown parent, the pedigree of the unknown parent of 'Cox's Pomona' was reconstructed, and 'Fameuse' was deduced to be a likely grandparent of 'McIntosh'. Key genetic resources that enabled this empirical study were large genome-wide SNP array datasets, integrated genetic maps, and previously identified pedigree relationships. Crops with similar resources are also expected to benefit from using HapShared for empowering pedigree reconstruction.

QTL dynamics for fruit firmness and softening around an ethylene-dependent polygalacturonase gene in apple (Malus x domestica Borkh.).

Apple fruit are well known for their storage life, although a wide range of flesh softening occurs among cultivars. Loss of firmness is genetically coordinated by the action of several cell wall enzymes, including polygalacturonase (PG) which depolymerizes cell wall pectin. By the analysis of 'Fuji' (Fj) and 'Mondial Gala' (MG), two apple cultivars characterized by a distinctive ripening behaviour, the involvement of Md-PG1 in the fruit softening process was confirmed to be ethylene dependent by its transcript being down-regulated by 1-methylcyclopropene treatment in MG and in the low ethylene-producing cultivar Fj. Comparing the PG sequence of MG and Fj, a single nucleotide polymorphism (SNP) was discovered. Segregation of the Md-PG1(SNP) marker within a full-sib population, obtained by crossing Fj and MG, positioned Md-PG1 in the linkage group 10 of MG, co-located with a quantitative trait locus (QTL) identified for fruit firmness in post-harvest ripening. Fruit firmness and softening analysed in different stages, from harvest to post-storage, determined a shift of the QTL from the top of this linkage group to the bottom, where Md-ACO1, a gene involved in ethylene biosynthesis in apple, is mapped. This PG-ethylene-related gene has beeen positioned in the apple genome on chromosome 10, which contains several QTLs controlling fruit firmness and softening, and the interplay among the allelotypes of the linked loci should be considered in the design of a marker-assisted selection breeding scheme for apple texture.

The cherry 6+9K SNP array: a cost-effective improvement to the cherry 6K SNP array for genetic studies.

Cherry breeding and genetic studies can benefit from genome-wide genetic marker assays. Currently, a 6K SNP array enables genome scans in cherry; however, only a third of these SNPs are informative, with low coverage in many genomic regions. Adding previously detected SNPs to this array could provide a cost-efficient upgrade with increased genomic coverage across the 670 cM/352.9 Mb cherry whole genome sequence. For sweet cherry, new SNPs were chosen following a focal point strategy, grouping six to eight SNPs within 10-kb windows with an average of 0.6 cM (627 kb) between focal points. Additional SNPs were chosen to represent important regions. Sweet cherry, the fruticosa subgenome of sour cherry, and cherry organellar genomes were targeted with 6942, 2020, and 38 new SNPs, respectively. The +9K add-on provided 2128, 1091, and 70 new reliable, polymorphic SNPs for sweet cherry and the avium and the fruticosa subgenomes of sour cherry, respectively. For sweet cherry, 1241 reliable polymorphic SNPs formed 237 informative focal points, with another 2504 SNPs in-between. The +9K SNPs increased genetic resolution and genome coverage of the original cherry SNP array and will help increase understanding of the genetic control of key traits and relationships among individuals in cherry.

A Rosaceae Family-Level Approach To Identify Loci Influencing Soluble Solids Content in Blackberry for DNA-Informed Breeding.

A Rosaceae family-level candidate gene approach was used to identify genes associated with sugar content in blackberry (Rubus subgenus Rubus). Three regions conserved among apple (Malus × domestica), peach (Prunus persica), and alpine strawberry (Fragaria vesca) were identified that contained previously detected sweetness-related quantitative trait loci (QTL) in at least two of the crops. Sugar related genes from these conserved regions and 789 sugar-associated apple genes were used to identify 279 Rubus candidate transcripts. A Hyb-Seq approach was used in conjunction with PacBio sequencing to generate haplotype level sequence information of sugar-related genes for 40 cultivars with high and low soluble solids content from the University of Arkansas and USDA blackberry breeding programs. Polymorphisms were identified relative to the 'Hillquist' blackberry (R. argutus) and ORUS 4115-3 black raspberry (R. occidentalis) genomes and tested for their association with soluble solids content (SSC). A total of 173 alleles were identified that were significantly (α = 0.05) associated with SSC. KASP genotyping was conducted for 92 of these alleles on a validation set of blackberries from each breeding program and 48 markers were identified that were significantly associated with SSC. One QTL, qSSC-Ruh-ch1.1, identified in both breeding programs accounted for an increase of 1.5 °Brix and the polymorphisms were detected in the intron space of a sucrose synthase gene. This discovery represents the first environmentally stable sweetness QTL identified in blackberry. The approach demonstrated in this study can be used to develop breeding tools for other crops that have not yet benefited directly from the genomics revolution.

RosBREED: bridging the chasm between discovery and application to enable DNA-informed breeding in rosaceous crops.

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.

A fruit quality gene map of Prunus.

BACKGROUND: Prunus fruit development, growth, ripening, and senescence includes major biochemical and sensory changes in texture, color, and flavor. The genetic dissection of these complex processes has important applications in crop improvement, to facilitate maximizing and maintaining stone fruit quality from production and processing through to marketing and consumption. Here we present an integrated fruit quality gene map of Prunus containing 133 genes putatively involved in the determination of fruit texture, pigmentation, flavor, and chilling injury resistance. RESULTS: A genetic linkage map of 211 markers was constructed for an intraspecific peach (Prunus persica) progeny population, Pop-DG, derived from a canning peach cultivar 'Dr. Davis' and a fresh market cultivar 'Georgia Belle'. The Pop-DG map covered 818 cM of the peach genome and included three morphological markers, 11 ripening candidate genes, 13 cold-responsive genes, 21 novel EST-SSRs from the ChillPeach database, 58 previously reported SSRs, 40 RAFs, 23 SRAPs, 14 IMAs, and 28 accessory markers from candidate gene amplification. The Pop-DG map was co-linear with the Prunus reference T x E map, with 39 SSR markers in common to align the maps. A further 158 markers were bin-mapped to the reference map: 59 ripening candidate genes, 50 cold-responsive genes, and 50 novel EST-SSRs from ChillPeach, with deduced locations in Pop-DG via comparative mapping. Several candidate genes and EST-SSRs co-located with previously reported major trait loci and quantitative trait loci for chilling injury symptoms in Pop-DG. CONCLUSION: The candidate gene approach combined with bin-mapping and availability of a community-recognized reference genetic map provides an efficient means of locating genes of interest in a target genome. We highlight the co-localization of fruit quality candidate genes with previously reported fruit quality QTLs. The fruit quality gene map developed here is a valuable tool for dissecting the genetic architecture of fruit quality traits in Prunus crops.

Validation of SNP markers for fruit quality and disease resistance loci in apple (Malus × domestica Borkh.) using the OpenArray® platform.

Genome mapping has promised much to tree fruit breeding during the last 10 years. Nevertheless, one of the greatest challenges remaining to tree fruit geneticists is the translation of trait loci and whole genome sequences into diagnostic genetic markers that are efficient and cost-effective for use by breeders, who must select genetically optimal parents and subsequently select genetically superior individuals among their progeny. To take this translational step, we designed the apple International RosBREED SNP Consortium OpenArray v1.0 (IRSCOA v1.0) assay using a set of 128 apple single nucleotide polymorphisms (SNPs) linked to fruit quality and pest and disease resistance trait loci. The Thermo Fisher Scientific OpenArray® technology enables multiplexed screening of SNP markers using a real-time PCR instrument with fluorescent probe-based Taqman® assays. We validated the apple IRSCOA v1.0 multi-trait assay by screening 240 phenotyped individuals from the Plant & Food Research apple cultivar breeding programme. This set of individuals comprised commercial and heritage cultivars, elite selections, and families segregating for traits of importance to breeders. In total, 33 SNP markers of the IRSCOA v1.0 were validated for use in marker-assisted selection (MAS) for the scab resistances Rvi2/Vh2, Rvi4/Vh4, Rvi6/Vf, fire blight resistance MR5/RLP1, powdery mildew resistance Pl2, fruit firmness, skin colour, flavour intensity, and acidity. The availability of this set of validated trait-associated SNP markers, which can be used individually on multiple genotyping platforms available to various apple breeding programmes or re-designed using the flanking sequences, represents a large translational genetics step from genomics to crop improvement of apple.

Prunus genetics and applications after de novo genome sequencing: achievements and prospects.

Prior to the availability of whole-genome sequences, our understanding of the structural and functional aspects of Prunus tree genomes was limited mostly to molecular genetic mapping of important traits and development of EST resources. With public release of the peach genome and others that followed, significant advances in our knowledge of Prunus genomes and the genetic underpinnings of important traits ensued. In this review, we highlight key achievements in Prunus genetics and breeding driven by the availability of these whole-genome sequences. Within the structural and evolutionary contexts, we summarize: (1) the current status of Prunus whole-genome sequences; (2) preliminary and ongoing work on the sequence structure and diversity of the genomes; (3) the analyses of Prunus genome evolution driven by natural and man-made selection; and (4) provide insight into haploblocking genomes as a means to define genome-scale patterns of evolution that can be leveraged for trait selection in pedigree-based Prunus tree breeding programs worldwide. Functionally, we summarize recent and ongoing work that leverages whole-genome sequences to identify and characterize genes controlling 22 agronomically important Prunus traits. These include phenology, fruit quality, allergens, disease resistance, tree architecture, and self-incompatibility. Translationally, we explore the application of sequence-based marker-assisted breeding technologies and other sequence-guided biotechnological approaches for Prunus crop improvement. Finally, we present the current status of publically available Prunus genomics and genetics data housed mainly in the Genome Database for Rosaceae (GDR) and its updated functionalities for future bioinformatics-based Prunus genetics and genomics inquiry.

Prediction of genetic value for sweet cherry fruit maturity among environments using a 6K SNP array.

The timing of fruit maturity is an important trait in sweet cherry production and breeding. Phenotypic variation for phenology of fruit maturity in sweet cherry appears to be under strong genetic control, but that control might be complicated by phenotypic instability across environments. Although such genotype-by-environment interaction (G × E) is a common phenomenon in crop plants, knowledge about it is lacking for fruit maturity timing and other sweet cherry traits. In this study, 1673 genome-wide SNP markers were used to estimate genomic relationships among 597 weakly pedigree-connected individuals evaluated over two seasons at three locations in Europe and one location in the USA, thus sampling eight 'environments'. The combined dataset enabled a single meta-analysis to investigate the environmental stability of genomic predictions. Linkage disequilibrium among marker loci declined rapidly with physical distance, and ordination of the relationship matrix suggested no strong structure among germplasm. The most parsimonious G × E model allowed heterogeneous genetic variance and pairwise covariances among environments. Narrow-sense genomic heritability was very high (0.60-0.83), as was accuracy of predicted breeding values (>0.62). Average correlation of additive effects among environments was high (0.96) and breeding values were highly correlated across locations. Results indicated that genomic models can be used in cherry to accurately predict date of fruit maturity for untested individuals in new environments. Limited G × E for this trait indicated that phenotypes of individuals will be stable across similar environments. Equivalent analyses for other sweet cherry traits, for which multiple years of data are commonly available among breeders and cultivar testers, would be informative for predicting performance of elite selections and cultivars in new environments.