Genetic factors acting prior to dormancy in sour cherry influence bloom time the following spring.

Understanding the process of Prunus species floral development is crucial for developing strategies to manipulate bloom time and prevent crop loss due to climate change. Here, we present a detailed examination of flower development from initiation until bloom for early- and late-blooming sour cherries (Prunus cerasus) from a population segregating for a major bloom time QTL on chromosome 4. Using a new staging system, we show floral buds from early-blooming trees were persistently more advanced than those from late-blooming siblings. A gDNA coverage analysis revealed the late-blooming haplotype of this QTL, k, is located on a subgenome originating from the late-blooming P. fruticosa progenitor. Transcriptome analyses identified many genes within this QTL as differentially expressed between early- and late-blooming trees during the vegetative-to-floral transition. From these, we identified candidate genes for the late bloom phenotype, including multiple transcription factors homologous to REproductive Meristem (REM) B3 domain-containing proteins. Additionally, we determined the basis of k in sour cherry is likely separate from candidate genes found in sweet cherry - suggesting several major regulators of bloom time are located on Prunus chromosome 4.

Genome of tetraploid sour cherry (Prunus cerasus L.) 'Montmorency' identifies three distinct ancestral Prunus genomes.

Sour cherry (Prunus cerasus L.) is a valuable fruit crop in the Rosaceae family and a hybrid between progenitors closely related to extant Prunus fruticosa (ground cherry) and Prunus avium (sweet cherry). Here we report a chromosome-scale genome assembly for sour cherry cultivar Montmorency, the predominant cultivar grown in the USA. We also generated a draft assembly of P. fruticosa to use alongside a published P. avium sequence for syntelog-based subgenome assignments for 'Montmorency' and provide compelling evidence P. fruticosa is also an allotetraploid. Using hierarchal k-mer clustering and phylogenomics, we show 'Montmorency' is trigenomic, containing two distinct subgenomes inherited from a P. fruticosa-like ancestor (A and A') and two copies of the same subgenome inherited from a P. avium-like ancestor (BB). The genome composition of 'Montmorency' is AA'BB and little-to-no recombination has occurred between progenitor subgenomes (A/A' and B). In Prunus, two known classes of genes are important to breeding strategies: the self-incompatibility loci (S-alleles), which determine compatible crosses, successful fertilization, and fruit set, and the Dormancy Associated MADS-box genes (DAMs), which strongly affect dormancy transitions and flowering time. The S-alleles and DAMs in 'Montmorency' and P. fruticosa were manually annotated and support subgenome assignments. Lastly, the hybridization event 'Montmorency' is descended from was estimated to have occurred less than 1.61 million years ago, making sour cherry a relatively recent allotetraploid. The 'Montmorency' genome highlights the evolutionary complexity of the genus Prunus and will inform future breeding strategies for sour cherry, comparative genomics in the Rosaceae, and questions regarding neopolyploidy.

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 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.

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 draft genome of sweet cherry (Prunus avium L.) reveals genome-wide and local effects of domestication.

Sweet cherry (Prunus avium L.) trees are both economically important fruit crops but also important components of natural forest ecosystems in Europe, Asia and Africa. Wild and domesticated trees currently coexist in the same geographic areas with important questions arising on their historical relationships. Little is known about the effects of the domestication process on the evolution of the sweet cherry genome. We assembled and annotated the genome of the cultivated variety "Big Star*" and assessed the genetic diversity among 97 sweet cherry accessions representing three different stages in the domestication and breeding process (wild trees, landraces and modern varieties). The genetic diversity analysis revealed significant genome-wide losses of variation among the three stages and supports a clear distinction between wild and domesticated trees, with only limited gene flow being detected between wild trees and domesticated landraces. We identified 11 domestication sweeps and five breeding sweeps covering, respectively, 11.0 and 2.4 Mb of the P. avium genome. A considerable fraction of the domestication sweeps overlaps with those detected in the related species, Prunus persica (peach), indicating that artificial selection during domestication may have acted independently on the same regions and genes in the two species. We detected 104 candidate genes in sweep regions involved in different processes, such as the determination of fruit texture, the regulation of flowering and fruit ripening and the resistance to pathogens. The signatures of selection identified will enable future evolutionary studies and provide a valuable resource for genetic improvement and conservation programs in sweet cherry.

High-quality, genome-wide SNP genotypic data for pedigreed germplasm of the diploid outbreeding species apple, peach, and sweet cherry through a common workflow.

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.

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.

A fruit firmness QTL identified on linkage group 4 in sweet cherry (Prunus avium L.) is associated with domesticated and bred germplasm.

Fruit firmness is an important market driven trait in sweet cherry (Prunus avium L.) where the desirable increase in fruit firmness is associated with landrace and bred cultivars. The aim of this work was to investigate the genetic basis of fruit firmness using plant materials that include wild cherry (syn. mazzard), landrace and bred sweet cherry germplasm. A major QTL for fruit firmness, named qP-FF4.1, that had not previously been reported, was identified in three sweet cherry populations. Thirteen haplotypes (alleles) associated with either soft or firm fruit were identified for qP-FF4.1 in the sweet cherry germplasm, and the "soft" alleles were dominant over the "firm" alleles. The finding that sweet cherry individuals that are homozygous for the "soft" alleles for qP-FF4.1 are exclusively mazzards and that the vast majority of the bred cultivars are homozygous for "firm" alleles suggests that this locus is a signature of selection. Candidate genes related to plant cell wall modification and various plant hormone signaling pathways were identified, with an expansin gene being the most promising candidate. These results advance our understanding of the genetic basis of fruit firmness and will help to enable the use of DNA informed breeding for this trait in sweet cherry breeding programs.

Genetic Dissection of Bloom Time in Low Chilling Sweet Cherry (Prunus avium L.) Using a Multi-Family QTL Approach.

Bloom time in sweet cherry (Prunus avium L.) is a highly heritable trait that varies between genotypes and depends on the environmental conditions. Bud-break occurs after chill and heat requirements of each genotype are fulfilled, and dormancy is released. Bloom time is a critical trait for fruit production as matching cultivar adaptation to the growing area is essential for adequate fruit set. Additionally, low chilling cultivars are of interest to extend sweet cherry production to warmer regions, and for the crop adaptation to increasing winter and spring temperatures. The aim of this work is to investigate the genetic control of this trait by analyzing multiple families derived from the low chilling and extra-early flowering local Spanish cultivar 'Cristobalina' and other cultivars with higher chilling requirements and medium to late bloom times. Bloom time evaluation in six related sweet cherry populations confirmed a high heritability of this trait, and skewed distribution toward late flowering, revealing possible dominance of the late bloom alleles. SNP genotyping of the six populations (n = 406) resulted in a consensus map of 1269 SNPs. Quantitative trait loci (QTL) analysis using the Bayesian approach implemented by FlexQTL™ software revealed two major QTLs on linkage groups 1 and 2 (qP-BT1.1m and qP-BT2.1m) that explained 47.6% of the phenotypic variation. The QTL on linkage group 1 was mapped to a 0.26 Mbp region that overlaps with the DORMANCY ASSOCIATED MADS-BOX (DAM) genes. This finding is consistent with peach results that indicate that these genes are major determinants of chilling requirement in Prunus. Haplotype analysis of the linkage group 1 and 2 QTL regions showed that 'Cristobalina' was the only cultivar tested that contributed early bloom time alleles for these two QTLs. This work contributes to knowledge of the genetic control of chilling requirement and bloom date and will enable marker-assisted selection for low chilling in sweet cherry breeding programs.

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.

Inferences on specificity recognition at the Malus×domestica gametophytic self-incompatibility system.

In Malus × domestica (Rosaceae) the product of each SFBB gene (the pollen component of the gametophytic self-incompatibility (GSI) system) of a S-haplotype (the combination of pistil and pollen genes that are linked) interacts with a sub-set of non-self S-RNases (the pistil component), but not with the self S-RNase. To understand how the Malus GSI system works, we identified 24 SFBB genes expressed in anthers, and determined their gene sequence in nine M. domestica cultivars. Expression of these SFBBs was not detected in the petal, sepal, filament, receptacle, style, stigma, ovary or young leaf. For all SFBBs (except SFBB15), identical sequences were obtained only in cultivars having the same S-RNase. Linkage with a particular S-RNase was further established using the progeny of three crosses. Such data is needed to understand how other genes not involved in GSI are affected by the S-locus region. To classify SFBBs specificity, the amino acids under positive selection obtained when performing intra-haplotypic analyses were used. Using this information and the previously identified S-RNase positively selected amino acid sites, inferences are made on the S-RNase amino acid properties (hydrophobicity, aromatic, aliphatic, polarity, and size), at these positions, that are critical features for GSI specificity determination.

Convergent evolution at the gametophytic self-incompatibility system in Malus and Prunus.

S-RNase-based gametophytic self-incompatibility (GSI) has evolved once before the split of the Asteridae and Rosidae. This conclusion is based on the phylogenetic history of the S-RNase that determines pistil specificity. In Rosaceae, molecular characterizations of Prunus species, and species from the tribe Pyreae (i.e., Malus, Pyrus, Sorbus) revealed different numbers of genes determining S-pollen specificity. In Prunus only one pistil and pollen gene determine GSI, while in Pyreae there is one pistil but multiple pollen genes, implying different specificity recognition mechanisms. It is thus conceivable that within Rosaceae the genes involved in GSI in the two lineages are not orthologous but possibly paralogous. To address this hypothesis we characterised the S-RNase lineage and S-pollen lineage genes present in the genomes of five Rosaceae species from three genera: M. × domestica (apple, self-incompatible (SI); tribe Pyreae), P. persica (peach, self-compatible (SC); Amygdaleae), P. mume (mei, SI; Amygdaleae), Fragaria vesca (strawberry, SC; Potentilleae), and F. nipponica (mori-ichigo, SI; Potentilleae). Phylogenetic analyses revealed that the Malus and Prunus S-RNase and S-pollen genes belong to distinct gene lineages, and that only Prunus S-RNase and SFB-lineage genes are present in Fragaria. Thus, S-RNase based GSI system of Malus evolved independently from the ancestral system of Rosaceae. Using expression patterns based on RNA-seq data, the ancestral S-RNase lineage gene is inferred to be expressed in pistils only, while the ancestral S-pollen lineage gene is inferred to be expressed in tissues other than pollen.

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.

Construction and comparative analyses of highly dense linkage maps of two sweet cherry intra-specific progenies of commercial cultivars.

Despite the agronomical importance and high synteny with other Prunus species, breeding improvements for cherry have been slow compared to other temperate fruits, such as apple or peach. However, the recent release of the peach genome v1.0 by the International Peach Genome Initiative and the sequencing of cherry accessions to identify Single Nucleotide Polymorphisms (SNPs) provide an excellent basis for the advancement of cherry genetic and genomic studies. The availability of dense genetic linkage maps in phenotyped segregating progenies would be a valuable tool for breeders and geneticists. Using two sweet cherry (Prunus avium L.) intra-specific progenies derived from crosses between 'Black Tartarian' × 'Kordia' (BT×K) and 'Regina' × 'Lapins'(R×L), high-density genetic maps of the four parental lines and the two segregating populations were constructed. For BT×K and R×L, 89 and 121 F(1) plants were used for linkage mapping, respectively. A total of 5,696 SNP markers were tested in each progeny. As a result of these analyses, 723 and 687 markers were mapped into eight linkage groups (LGs) in BT×K and R×L, respectively. The resulting maps spanned 752.9 and 639.9 cM with an average distance of 1.1 and 0.9 cM between adjacent markers in BT×K and R×L, respectively. The maps displayed high synteny and co-linearity between each other, with the Prunus bin map, and with the peach genome v1.0 for all eight LGs (LG1-LG8). These maps provide a useful tool for investigating traits of interest in sweet cherry and represent a qualitative advance in the understanding of the cherry genome and its synteny with other members of the Rosaceae family.

Development and evaluation of a 9K SNP array for peach by internationally coordinated SNP detection and validation in breeding germplasm.

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.

Genome-wide SNP detection, validation, and development of an 8K SNP array for apple.

As high-throughput genetic marker screening systems are essential for a range of genetics studies and plant breeding applications, the International RosBREED SNP Consortium (IRSC) has utilized the Illumina Infinium® II system to develop a medium- to high-throughput SNP screening tool for genome-wide evaluation of allelic variation in apple (Malus×domestica) breeding germplasm. For genome-wide SNP discovery, 27 apple cultivars were chosen to represent worldwide breeding germplasm and re-sequenced at low coverage with the Illumina Genome Analyzer II. Following alignment of these sequences to the whole genome sequence of 'Golden Delicious', SNPs were identified using SoapSNP. A total of 2,113,120 SNPs were detected, corresponding to one SNP to every 288 bp of the genome. The Illumina GoldenGate® assay was then used to validate a subset of 144 SNPs with a range of characteristics, using a set of 160 apple accessions. This validation assay enabled fine-tuning of the final subset of SNPs for the Illumina Infinium® II system. The set of stringent filtering criteria developed allowed choice of a set of SNPs that not only exhibited an even distribution across the apple genome and a range of minor allele frequencies to ensure utility across germplasm, but also were located in putative exonic regions to maximize genotyping success rate. A total of 7867 apple SNPs was established for the IRSC apple 8K SNP array v1, of which 5554 were polymorphic after evaluation in segregating families and a germplasm collection. This publicly available genomics resource will provide an unprecedented resolution of SNP haplotypes, which will enable marker-locus-trait association discovery, description of the genetic architecture of quantitative traits, investigation of genetic variation (neutral and functional), and genomic selection in apple.

Development and evaluation of a genome-wide 6K SNP array for diploid sweet cherry and tetraploid sour cherry.

High-throughput genome scans are important tools for genetic studies and breeding applications. Here, a 6K SNP array for use with the Illumina Infinium® system was developed for diploid sweet cherry (Prunus avium) and allotetraploid sour cherry (P. cerasus). This effort was led by RosBREED, a community initiative to enable marker-assisted breeding for rosaceous crops. Next-generation sequencing in diverse breeding germplasm provided 25 billion basepairs (Gb) of cherry DNA sequence from which were identified genome-wide SNPs for sweet cherry and for the two sour cherry subgenomes derived from sweet cherry (avium subgenome) and P. fruticosa (fruticosa subgenome). Anchoring to the peach genome sequence, recently released by the International Peach Genome Initiative, predicted relative physical locations of the 1.9 million putative SNPs detected, preliminarily filtered to 368,943 SNPs. Further filtering was guided by results of a 144-SNP subset examined with the Illumina GoldenGate® assay on 160 accessions. A 6K Infinium® II array was designed with SNPs evenly spaced genetically across the sweet and sour cherry genomes. SNPs were developed for each sour cherry subgenome by using minor allele frequency in the sour cherry detection panel to enrich for subgenome-specific SNPs followed by targeting to either subgenome according to alleles observed in sweet cherry. The array was evaluated using panels of sweet (n = 269) and sour (n = 330) cherry breeding germplasm. Approximately one third of array SNPs were informative for each crop. A total of 1825 polymorphic SNPs were verified in sweet cherry, 13% of these originally developed for sour cherry. Allele dosage was resolved for 2058 polymorphic SNPs in sour cherry, one third of these being originally developed for sweet cherry. This publicly available genomics resource represents a significant advance in cherry genome-scanning capability that will accelerate marker-locus-trait association discovery, genome structure investigation, and genetic diversity assessment in this diploid-tetraploid crop group.

Comparative analysis of rosaceous genomes and the reconstruction of a putative ancestral genome for the family.

BACKGROUND: Comparative genome mapping studies in Rosaceae have been conducted until now by aligning genetic maps within the same genus, or closely related genera and using a limited number of common markers. The growing body of genomics resources and sequence data for both Prunus and Fragaria permits detailed comparisons between these genera and the recently released Malus × domestica genome sequence. RESULTS: We generated a comparative analysis using 806 molecular markers that are anchored genetically to the Prunus and/or Fragaria reference maps, and physically to the Malus genome sequence. Markers in common for Malus and Prunus, and Malus and Fragaria, respectively were 784 and 148. The correspondence between marker positions was high and conserved syntenic blocks were identified among the three genera in the Rosaceae. We reconstructed a proposed ancestral genome for the Rosaceae. CONCLUSIONS: A genome containing nine chromosomes is the most likely candidate for the ancestral Rosaceae progenitor. The number of chromosomal translocations observed between the three genera investigated was low. However, the number of inversions identified among Malus and Prunus was much higher than any reported genome comparisons in plants, suggesting that small inversions have played an important role in the evolution of these two genera or of the Rosaceae.

Comparative analyses reveal distinct sets of lineage-specific genes within Arabidopsis thaliana.

BACKGROUND: The availability of genome and transcriptome sequences for a number of species permits the identification and characterization of conserved as well as divergent genes such as lineage-specific genes which have no detectable sequence similarity to genes from other lineages. While genes conserved among taxa provide insight into the core processes among species, lineage-specific genes provide insights into evolutionary processes and biological functions that are likely clade or species specific. RESULTS: Comparative analyses using the Arabidopsis thaliana genome and sequences from 178 other species within the Plant Kingdom enabled the identification of 24,624 A. thaliana genes (91.7%) that were termed Evolutionary Conserved (EC) as defined by sequence similarity to a database entry as well as two sets of lineage-specific genes within A. thaliana. One of the A. thaliana lineage-specific gene sets share sequence similarity only to sequences from species within the Brassicaceae family and are termed Conserved Brassicaceae-Specific Genes (914, 3.4%, CBSG). The other set of A. thaliana lineage-specific genes, the Arabidopsis Lineage-Specific Genes (1,324, 4.9%, ALSG), lack sequence similarity to any sequence outside A. thaliana. While many CBSGs (76.7%) and ALSGs (52.9%) are transcribed, the majority of the CBSGs (76.1%) and ALSGs (94.4%) have no annotated function. Co-expression analysis indicated significant enrichment of the CBSGs and ALSGs in multiple functional categories suggesting their involvement in a wide range of biological functions. Subcellular localization prediction revealed that the CBSGs were significantly enriched in proteins targeted to the secretory pathway (412, 45.1%). Among the 107 putatively secreted CBSGs with known functions, 67 encode a putative pollen coat protein or cysteine-rich protein with sequence similarity to the S-locus cysteine-rich protein that is the pollen determinant controlling allele specific pollen rejection in self-incompatible Brassicaceae species. Overall, the ALSGs and CBSGs were more highly methylated in floral tissue compared to the ECs. Single Nucleotide Polymorphism (SNP) analysis showed an elevated ratio of non-synonymous to synonymous SNPs within the ALSGs (1.99) and CBSGs (1.65) relative to the EC set (0.92), mainly caused by an elevated number of non-synonymous SNPs, indicating that they are fast-evolving at the protein sequence level. CONCLUSIONS: Our analyses suggest that while a significant fraction of the A. thaliana proteome is conserved within the Plant Kingdom, evolutionarily distinct sets of genes that may function in defining biological processes unique to these lineages have arisen within the Brassicaceae and A. thaliana.