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

Genotype-by-environment and QTL-by-environment interactions in sweet cherry (Prunus avium L.) for flowering date

In sweet cherry (Prunus avium L.), flowering date is strongly dependent on the environment conditions and, therefore, is a trait of major interest for adaptation to climate change. Such trait can be influenced by genotype-by-environment interaction (G×E), that refers to differences in the response of genotypes to different environments. If not taken into account, G×E can reduce selection accuracy and overall genetic gain. However, little is known about G×E in fruit tree species. Flowering date is a highly heritable and polygenic trait for which many quantitative trait loci (QTLs) have been identified. As for the overall genetic performance, differential expression of QTLs in response to environment (QTL-by-environment interaction, QTL×E) can occur. The present study is based on the analysis of a multi-environment trial (MET) suitable for the study of G×E and QTL×E in sweet cherry. It consists of a sweet cherry F₁ full-sib family (n = 121) derived from the cross between cultivars 'Regina' and 'Lapins' and planted in two copies in five locations across four European countries (France, Italy, Slovenia and Spain) covering a large range of climatic conditions. The aim of this work was to study the effect of the environment on flowering date and estimate G×E, to carry QTL detection in different environments in order to study the QTL stability across environments and to estimate QTL×E. A strong effect of the environment on flowering date and its genetic control was highlighted. Two large-effect and environment-specific QTLs with significant QTL×E were identified on linkage groups (LGs) 1 and 4. This work gives new insights into the effect of the environment on a trait of main importance in one of the most economically important fruit crops in temperate regions. Moreover, molecular markers were developed for flowering date and a strategy consisting in using specific markers for warm or cold regions was proposed to optimize marker-assisted selection (MAS) in sweet cherry breeding programs.

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.

Development of a 135K SNP genotyping array for Actinidia arguta and its applications for genetic mapping and QTL analysis in kiwifruit

Kiwifruit (Actinidia spp) is a woody, perennial and deciduous vine. In this genus, there are multiple ploidy levels but the main cultivated cultivars are polyploid. Despite the availability of many genomic resources in kiwifruit, SNP genotyping is still a challenge given these different levels of polyploidy. Recent advances in SNP array technologies have offered a high-throughput genotyping platform for genome-wide DNA polymorphisms. In this study, we developed a high-density SNP genotyping array to facilitate genetic studies and breeding applications in kiwifruit. SNP discovery was performed by genome-wide DNA sequencing of 40 kiwifruit genotypes. The identified SNPs were stringently filtered for sequence quality, predicted conversion performance and distribution over the available Actinidia chinensis genome. A total of 134 729 unique SNPs were put on the array. The array was evaluated by genotyping 400 kiwifruit individuals. We performed a multidimensional scaling analysis to assess the diversity of kiwifruit germplasm, showing that the array was effective to distinguish kiwifruit accessions. Using a tetraploid F1 population, we constructed an integrated linkage map covering 3060.9 cM across 29 linkage groups and performed QTL analysis for the sex locus that has been identified on Linkage Group 3 (LG3) in Actinidia arguta. Finally, our dataset presented evidence of tetrasomic inheritance with partial preferential pairing in A. arguta. In conclusion, we developed and evaluated a 135K SNP genotyping array for kiwifruit. It has the advantage of a comprehensive design that can be an effective tool in genetic studies and breeding applications in this high-value crop.

The Role of Italy in the Use of Advanced Plant Genomic Techniques on Fruit Trees: State of the Art and Future Perspectives

Climate change is deeply impacting the food chain production, lowering quality and yield. In this context, the international scientific community has dedicated many efforts to enhancing resilience and sustainability in agriculture. Italy is among the main European producers of several fruit trees; therefore, national research centers and universities undertook several initiatives to maintain the specificity of the 'Made in Italy' label. Despite their importance, fruit crops are suffering from difficulties associated with the conventional breeding approaches, especially in terms of financial commitment, land resources availability, and long generation times. The 'new genomic techniques' (NGTs), renamed in Italy as 'technologies for assisted evolution' (TEAs), reduce the time required to obtain genetically improved cultivars while precisely targeting specific DNA sequences. This review aims to illustrate the role of the Italian scientific community in the use of NGTs, with a specific focus on Citrus, grapevine, apple, pear, chestnut, strawberry, peach, and kiwifruit. For each crop, the key genes and traits on which the scientific community is working, as well as the technological improvements and advancements on the regeneration of local varieties, are presented. Lastly, a focus is placed on the legal aspects in the European and in Italian contexts.

A high-density integrated map for grapevine based on three mapping populations genotyped by the Vitis18K SNP chip

We present a high-density integrated map for grapevine, allowing refinement and improved understanding of the grapevine genome, while demonstrating the applicability of the Vitis18K SNP chip for linkage mapping. The improvement of grapevine through biotechnology requires identification of the molecular bases of target traits by studying marker-trait associations. The Vitis18K SNP chip provides a useful genotyping tool for genome-wide marker analysis. Most linkage maps are based on single mapping populations, but an integrated map can increase marker density and show order conservation. Here we present an integrated map based on three mapping populations. The parents consist of the well-known wine cultivars 'Cabernet Sauvignon', 'Corvina' and 'Rhine Riesling', the lesser-known wine variety 'Deckrot', and a table grape selection, G1-7720. Three high-density population maps with an average inter-locus gap ranging from 0.74 to 0.99 cM were developed. These maps show high correlations (0.9965-0.9971) with the reference assembly, containing only 93 markers with large order discrepancies compared to expected physical positions, of which a third is consistent across multiple populations. Moreover, the genetic data aid the further refinement of the grapevine genome assembly, by anchoring 104 yet unanchored scaffolds. From these population maps, an integrated map was constructed which includes 6697 molecular markers and reduces the inter-locus gap distance to 0.60 cM, resulting in the densest integrated map for grapevine thus far. A small number of discrepancies, mainly of short distance, involve 88 markers that remain conflictual across maps. The integrated map shows similar collinearity to the reference assembly (0.9974) as the single maps. This high-density map increases our understanding of the grapevine genome and provides a useful tool for its further characterization and the dissection of complex traits.

QTLs Identification for Iron Chlorosis in a Segregating Peach-Almond Progeny Through Double-Digest Sequence-Based Genotyping (SBG)

Linkage maps are highly appreciated tools for cultivar and rootstock breeding programs because they are suitable for genetic and genomic studies. In this study, we report on using sequence-based genotyping (SBG) approach to simultaneously discover and genotype SNPs from two peach-based rootstocks ("Adafuel" and "Flordaguard") and their progeny (n = 118): from a initial mapping population composed of 131 seedlings. The plant material was developed at the EEAD-CSIC Prunus rootstocks breeding program, aiming to obtain a segregating progeny for a range of characters of agronomical interest to rootstock breeding (iron-chlorosis and root-asphyxia tolerance, nematode resistance, vigor traits, and other effects on scion cultivars). Sequence reads obtained from double-digest SBG were aligned to the P. persica reference genome (Peach v2.0). While eight linkage groups were constructed for "Adafuel," only four linkage groups were constructed for "Flordaguard," given the low heterozygosity of this last genotype. High synteny and co-linearity were observed between obtained maps and Peach v2.0. On the other hand, this work aimed to elucidate the genetic basis of leaf chlorosis tolerance using the phenotypic segregation of the progeny to iron-chlorosis tolerance, along with the QTLs responsible for leaf chlorosis. The F1 mapping population, composed initially of 131 seedlings, was growing in four field trials established on calcareous soils at the experimental field of the EEAD-CSIC in Zaragoza, Spain. From the initial mapping population, 131 individuals were selected for their phenotypical characterization with SPAD measurements of plants grown in the field, exhibiting a great variability. Significant QTLs associated with tolerance to iron chlorosis were found in LG1, LG5, LG7, and LG8. The significant QTLs detected in LG5 and LG7 have not been associated with this abiotic stress before in Prunus. Several candidate genes such as Prupe.1G541100, predicted as glutamyl-tRNA reductase 1, Prupe.1G468200, encoding a 2-oxoglutarate (2OG), and Fe(II)-dependent oxygenase superfamily protein or Prupe.1G577000 (ppa011050.m), a NIFU-like protein 2 (NIFU2) were detected. The exact biological function of some of these genes should be verified for the future development of marker-assisted selection for peach iron chlorosis tolerance.

Applications of Genomic Tools in Plant Breeding: Crop Biofortification

Crop breeding has mainly been focused on increasing productivity, either directly or by decreasing the losses caused by biotic and abiotic stresses (that is, incorporating resistance to diseases and enhancing tolerance to adverse conditions, respectively). Quite the opposite, little attention has been paid to improve the nutritional value of crops. It has not been until recently that crop biofortification has become an objective within breeding programs, through either conventional methods or genetic engineering. There are many steps along this long path, from the initial evaluation of germplasm for the content of nutrients and health-promoting compounds to the development of biofortified varieties, with the available and future genomic tools assisting scientists and breeders in reaching their objectives as well as speeding up the process. This review offers a compendium of the genomic technologies used to explore and create biodiversity, to associate the traits of interest to the genome, and to transfer the genomic regions responsible for the desirable characteristics into potential new varieties. Finally, a glimpse of future perspectives and challenges in this emerging area is offered by taking the present scenario and the slow progress of the regulatory framework as the starting point.

New insights into flowering date in Prunus: fine mapping of a major QTL in sweet cherry

Flowering date is an important trait in Prunus fruit species, especially for their adaptation in a global warming context. Numerous quantitative trait loci (QTLs) have been identified and a major one was previously located on LG4. The objectives of this study were to fine-map this QTL in sweet cherry, to identify robust candidate genes by using the new sweet cherry genome sequence of the cultivar 'Regina' and to define markers usable in marker-assisted selection (MAS). We performed QTL analyses on two populations derived from crosses using cultivars 'Regina' and 'Garnet' as parents. The first one (n = 117) was phenotyped over ten years, while the second one (n = 1386) was evaluated during three years. Kompetitive allele specific PCR (KASP) markers located within the QTL region on LG4 were developed and mapped within this region, consisting in the first fine mapping in sweet cherry. The QTL interval was narrowed from 380 kb to 68 kb and candidate genes were identified by using the genome sequence of 'Regina'. Their expression was analyzed from bud dormancy period to flowering in cultivars 'Regina' and 'Garnet'. Several genes, such as PavBOI-E3, PavSR45a and PavSAUR71, were differentially expressed in these two cultivars and could be then considered as promising candidate genes. Two KASP markers were validated using a population derived from a cross between cultivars 'Regina' and 'Lapins' and two collections, including landraces and modern cultivars. Thanks to the high synteny within the Prunus genus, these results give new insights into the control of flowering date in Prunus species and pave the way for the development of molecular breeding strategies.

Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing

Forest tree breeding efforts have focused mainly on improving traits of economic importance, selecting trees suited to new environments or generating trees that are more resilient to biotic and abiotic stressors. This review describes various methods of forest tree selection assisted by genomics and the main technological challenges and achievements in research at the genomic level. Due to the long rotation time of a forest plantation and the resulting long generation times necessary to complete a breeding cycle, the use of advanced techniques with traditional breeding have been necessary, allowing the use of more precise methods for determining the genetic architecture of traits of interest, such as genome-wide association studies (GWASs) and genomic selection (GS). In this sense, main factors that determine the accuracy of genomic prediction models are also addressed. In turn, the introduction of genome editing opens the door to new possibilities in forest trees and especially clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9). It is a highly efficient and effective genome editing technique that has been used to effectively implement targetable changes at specific places in the genome of a forest tree. In this sense, forest trees still lack a transformation method and an inefficient number of genotypes for CRISPR/Cas9. This challenge could be addressed with the use of the newly developing technique GRF-GIF with speed breeding.

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.

Multi-year analyses on three populations reveal the first stable QTLs for tolerance to rain-induced fruit cracking in sweet cherry (Prunus avium L.)

Rain-induced fruit cracking is a major problem in sweet cherry cultivation. Basic research has been conducted to disentangle the physiological and mechanistic bases of this complex phenomenon, whereas genetic studies have lagged behind. The objective of this work was to disentangle the genetic determinism of rain-induced fruit cracking. We hypothesized that a large genetic variation would be revealed, by visual field observations conducted on mapping populations derived from well-contrasted cultivars for cracking tolerance. Three populations were evaluated over 7-8 years by estimating the proportion of cracked fruits for each genotype at maturity, at three different areas of the sweet cherry fruit: pistillar end, stem end, and fruit side. An original approach was adopted to integrate, within simple linear models, covariates potentially related to cracking, such as rainfall accumulation before harvest, fruit weight, and firmness. We found the first stable quantitative trait loci (QTLs) for cherry fruit cracking, explaining percentages of phenotypic variance above 20%, for each of these three types of cracking tolerance, in different linkage groups, confirming the high complexity of this trait. For these and other QTLs, further analyses suggested the existence of at least two-linked QTLs in each linkage group, some of which showed confidence intervals close to 5 cM. These promising results open the possibility of developing marker-assisted selection strategies to select cracking-tolerant sweet cherry cultivars. Further studies are needed to confirm the stability of the reported QTLs over different genetic backgrounds and environments and to narrow down the QTL confidence intervals, allowing the exploration of underlying candidate genes.

Autochthonous Austrian Varieties of Prunus avium L. Represent a Regional Gene Pool, Assessed Using SSR and AFLP Markers

Sweet cherry production faces new challenges that necessitate the exploitation of genetic resources such as varietal collections and landraces in breeding programs. A harmonized approach to characterization is key for an optimal utilization of germplasm in breeding. This study reports the genotyping of 63 sweet cherry accessions using a harmonized set of 11 simple sequence repeat (SSR) markers optimized in two multiplexed PCR reactions. Thirty-eight distinct allelic profiles were identified. The set of SSR markers chosen proved highly informative in these germplasm; an average of 6.3 alleles per locus, a PIC value of 0.59 and above-average expected and observed heterozygosity levels were detected. Additionally, 223 amplified fragment length polymorphism (AFLP) markers derived from eight selective primer combinations were employed to further differentiate 17 closely related accessions, confirming the SSR analysis. Genetic relationships between internationally known old cultivars were revealed: SSR fingerprints of “Schneiders Späte Knorpelkirsche” and “Germersdorfer” were found to be identical to those of the standard cultivar “Noire de Meched”, among others, whereas four accessions known as “Hedelfinger Riesenkirsche” and four known as “Große Schwarze Knorpelkirsche” showed allelic differences at various loci. The genetic diversity of locally-grown cultivars worldwide might be currently underestimated. Several autochthonous Austrian sweet cherry germplasm accessions were genotyped for the first time and their genetic relationships analyzed and discussed. Interestingly, seven Austrian sweet cherry landraces were shown to be clearly genetically separated from international and modern varieties, indicating that Austrian germplasm could include valuable genetic resources for future breeding efforts.

Recent Large-Scale Genotyping and Phenotyping of Plant Genetic Resources of Vegetatively Propagated Crops

Several recent national and international projects have focused on large-scale genotyping of plant genetic resources in vegetatively propagated crops like fruit and berries, potatoes and woody ornamentals. The primary goal is usually to identify true-to-type plant material, detect possible synonyms, and investigate genetic diversity and relatedness among accessions. A secondary goal may be to create sustainable databases that can be utilized in research and breeding for several years ahead. Commonly applied DNA markers (like microsatellite DNA and SNPs) and next-generation sequencing each have their pros and cons for these purposes. Methods for large-scale phenotyping have lagged behind, which is unfortunate since many commercially important traits (yield, growth habit, storability, and disease resistance) are difficult to score. Nevertheless, the analysis of gene action and development of robust DNA markers depends on environmentally controlled screening of very large sets of plant material. Although more time-consuming, co-operative projects with broad-scale data collection are likely to produce more reliable results. In this review, we will describe some of the approaches taken in genotyping and/or phenotyping projects concerning a wide variety of vegetatively propagated crops.

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.

Use of Targeted Amplicon Sequencing in Peanut to Generate Allele Information on Allotetraploid Sub-Genomes

The use of molecular markers in plant breeding has become a routine practice, but the cost per accession can be a hindrance to the routine use of Quantitative Trait Loci (QTL) identification in breeding programs. In this study, we demonstrate the use of targeted re-sequencing as a proof of concept of a cost-effective approach to retrieve highly informative allele information, as well as develop a bioinformatics strategy to capture the genome-specific information of a polyploid species. SNPs were identified from alignment of raw transcriptome reads (2 × 50 bp) to a synthetic tetraploid genome using BWA followed by a GATK pipeline. Regions containing high polymorphic SNPs in both A genome and B genomes were selected as targets for the resequencing study. Targets were amplified using multiplex PCR followed by sequencing on an Illumina HiSeq. Eighty-one percent of the SNP calls in diploids and 68% of the SNP calls in tetraploids were confirmed. These results were also confirmed by KASP validation. Based on this study, we find that targeted resequencing technologies have potential for obtaining maximum allele information in allopolyploids at reduced cost.

A de novo assembly of the sweet cherry (Prunus avium cv. Tieton) genome using linked-read sequencing technology

The sweet cherry (Prunus avium) is one of the most economically important fruit species in the world. However, there is a limited amount of genetic information available for this species, which hinders breeding efforts at a molecular level. We were able to describe a high-quality reference genome assembly and annotation of the diploid sweet cherry (2n = 2x = 16) cv. Tieton using linked-read sequencing technology. We generated over 750 million clean reads, representing 112.63 GB of raw sequencing data. The Supernova assembler produced a more highly-ordered and continuous genome sequence than the current P. avium draft genome, with a contig N50 of 63.65 KB and a scaffold N50 of 2.48 MB. The final scaffold assembly was 280.33 MB in length, representing 82.12% of the estimated Tieton genome. Eight chromosome-scale pseudomolecules were constructed, completing a 214 MB sequence of the final scaffold assembly. De novo, homology-based, and RNA-seq methods were used together to predict 30,975 protein-coding loci. 98.39% of core eukaryotic genes and 97.43% of single copy orthologues were identified in the embryo plant, indicating the completeness of the assembly. Linked-read sequencing technology was effective in constructing a high-quality reference genome of the sweet cherry, which will benefit the molecular breeding and cultivar identification in this species.

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.

Whole genome re-sequencing of sweet cherry (Prunus avium L.) yields insights into genomic diversity of a fruit species

Sweet cherries, Prunus avium L. (Rosaceae), are gaining importance due to their perenniallity and nutritional attributes beneficial for human health. Interestingly, sweet cherry cultivars exhibit a wide range of phenotypic diversity in important agronomic traits, such as flowering time and defense reactions against pathogens. In this study, whole-genome resequencing (WGRS) was employed to characterize genetic variation, population structure and allelic variants in a panel of 20 sweet cherry and one wild cherry genotypes, embodying the majority of cultivated Greek germplasm and a representative of a local wild cherry elite phenotype. The 21 genotypes were sequenced in an average depth of coverage of 33.91×. and effective mapping depth, to the genomic reference sequence of 'Satonishiki' cultivar, between 22.21× to 36.62×. Discriminant analysis of principal components (DAPC) with SNPs revealed two clusters of genotypes. There was a rapid linkage disequilibrium decay, as the majority of SNP pairs with r2 in near complete disequilibrium (>0.8) were found at physical distances less than 10 kb. Functional analysis of the variants showed that the genomic ratio of non-synonymous/synonymous (dN/dS) changes was 1.78. The higher dN frequency in the Greek cohort of sweet cherry could be the result of artificial selection pressure imposed by breeding, in combination with the vegetative propagation of domesticated cultivars through grafting. The majority of SNPs with high impact (e.g., stop codon gaining, frameshift), were identified in genes involved in flowering time, dormancy and defense reactions against pathogens, providing promising resources for future breeding programs. Our study has established the foundation for further large scale characterization of sweet cherry germplasm, enabling breeders to incorporate diverse germplasm and allelic variants to fine tune flowering and maturity time and disease resistance in sweet cherry cultivars.

Genome-wide SNP identification in Prunus rootstocks germplasm collections using Genotyping-by-Sequencing: phylogenetic analysis, distribution of SNPs and prediction of their effect on gene function

Genotyping-by-Sequencing (GBS) was applied in a set of 53 diploid Prunus rootstocks and five scion cultivars from three subgenera (Amygdalus, Prunus and Cerasus) for genome-wide SNP identification and to assess genetic diversity of both Chilean and Spanish germplasm collections. A group of 45,382 high quality SNPs (MAF >0.05; missing data <5%) were selected for analysis of this group of 58 accessions. These SNPs were distributed in genic and intergenic regions in the eight pseudomolecules of the peach genome (Peach v2.0), with an average of 53% located in exonic regions. The genetic diversity detected among the studied accessions divided them in three groups, which are in agreement with their current taxonomic classification. SNPs were classified based on their putative effect on annotated genes and KOG analysis was carried out to provide a deeper understanding of the function of 119 genes affected by high-impact SNPs. Results demonstrate the high utility for Prunus rootstocks identification and studies of diversity in Prunus species. Also, given the high number of SNPs identified in exonic regions, this strategy represents an important tool for finding candidate genes underlying traits of interest and potential functional markers for use in marker-assisted selection.

Development of an integrated 200K SNP genotyping array and application for genetic mapping, genome assembly improvement and genome wide association studies in pear (Pyrus)

Pear (Pyrus; 2n = 34), the third most important temperate fruit crop, has great nutritional and economic value. Despite the availability of many genomic resources in pear, it is challenging to genotype novel germplasm resources and breeding progeny in a timely and cost-effective manner. Genotyping arrays can provide fast, efficient and high-throughput genetic characterization of diverse germplasm, genetic mapping and breeding populations. We present here 200K AXIOM^® PyrSNP, a large-scale single nucleotide polymorphism (SNP) genotyping array to facilitate genotyping of Pyrus species. A diverse panel of 113 re-sequenced pear genotypes was used to discover SNPs to promote increased adoption of the array. A set of 188 diverse accessions and an F₁ population of 98 individuals from 'Cuiguan' × 'Starkrimson' was genotyped with the array to assess its effectiveness. A large majority of SNPs (166 335 or 83%) are of high quality. The high density and uniform distribution of the array SNPs facilitated prediction of centromeric regions on 17 pear chromosomes, and significantly improved the genome assembly from 75.5% to 81.4% based on genetic mapping. Identification of a gene associated with flowering time and candidate genes linked to size of fruit core via genome wide association studies showed the usefulness of the array in pear genetic research. The newly developed high-density SNP array presents an important tool for rapid and high-throughput genotyping in pear for genetic map construction, QTL identification and genomic selection.

Development of EST-based SSR and SNP markers in Gastrodia elata (herbal medicine) by sequencing, de novo assembly and annotation of the transcriptome

Tianma (Gastrodia elata Blume) has unique biological characteristics and high medicinal value. The wild resource of G. elata is being overutilized and should be conserved as it is already included in the list of endangered species in China. The population size of cultivated G. elata is small because of domestication bottleneck. Therefore, it is of utmost importance to evolve high-quality varieties and conserve wild resources of G. elata. In this study, we sequenced tuber transcriptomes of three major cultivated sub-species of Gastrodia elata, namely G. elata BI. f. elata, G. elata Bl. f. glauca S. Chow, and G. elata Bl. f. Viridis, and obtained about 7.8G clean data. The assembled high-quality reads of three sub-species were clustered into 56,884 unigenes. Of these, 31,224 (54.89%), 25,733 (45.24%), 22,629 (39.78%), and 11,856 (20.84%) unigenes were annotated by Nr, Swiss-Port, Eukaryotic Ortholog Groups (KOG), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, respectively. Here, a total of 3766 EST-SSRs and 128,921 SNPs were identified from the unigenes. The results not only offer huge number of genes that were responsible for the growth, development, and metabolism of bioactive components, but also a large number of molecular markers were detected for future studies on the conservation genetics and molecular breeding of G. elata.

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.

Edit at will: Genotype independent plant transformation in the era of advanced genomics and genome editing

The combination of advanced genomics, genome editing and plant transformation biology presents a powerful platform for basic plant research and crop improvement. Together these advances provide the tools to identify genes as targets for direct editing as single base pair changes, deletions, insertions and site specific homologous recombination. Recent breakthrough technologies using morphogenic regulators in plant transformation creates the ability to introduce reagents specific toward their identified targets and recover stably transformed and/or edited plants which are genotype independent. These technologies enable the possibility to alter a trait in any variety, without genetic disruption which would require subsequent extensive breeding, but rather to deliver the same variety with one trait changed. Regulatory issues regarding this technology will predicate how broadly these technologies will be implemented. In addition, education will play a crucial role for positive public acceptance. Taken together these technologies comprise a platform for advanced breeding which is an imperative for future world food security.

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.

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.

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.

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.

Tools for Genetic Studies in Experimental Populations of Polyploids

Polyploid organisms carry more than two copies of each chromosome, a condition rarely tolerated in animals but which occurs relatively frequently in the plant kingdom. One of the principal challenges faced by polyploid organisms is to evolve stable meiotic mechanisms to faithfully transmit genetic information to the next generation upon which the study of inheritance is based. In this review we look at the tools available to the research community to better understand polyploid inheritance, many of which have only recently been developed. Most of these tools are intended for experimental populations (rather than natural populations), facilitating genomics-assisted crop improvement and plant breeding. This is hardly surprising given that a large proportion of domesticated plant species are polyploid. We focus on three main areas: (1) polyploid genotyping; (2) genetic and physical mapping; and (3) quantitative trait analysis and genomic selection. We also briefly review some miscellaneous topics such as the mode of inheritance and the availability of polyploid simulation software. The current polyploid analytic toolbox includes software for assigning marker genotypes (and in particular, estimating the dosage of marker alleles in the heterozygous condition), establishing chromosome-scale linkage phase among marker alleles, constructing (short-range) haplotypes, generating linkage maps, performing genome-wide association studies (GWAS) and quantitative trait locus (QTL) analyses, and simulating polyploid populations. These tools can also help elucidate the mode of inheritance (disomic, polysomic or a mixture of both as in segmental allopolyploids) or reveal whether double reduction and multivalent chromosomal pairing occur. An increasing number of polyploids (or associated diploids) are being sequenced, leading to publicly available reference genome assemblies. Much work remains in order to keep pace with developments in genomic technologies. However, such technologies also offer the promise of understanding polyploid genomes at a level which hitherto has remained elusive.

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.

High-density genetic mapping of a major QTL for resistance to multiple races of loose smut in a tetraploid wheat cross

Loose smut, caused by Ustilago tritici (Pers.) Rostr., is a systemic disease of tetraploid durum wheat (Triticum turgidum L.). Loose smut can be economically controlled by growing resistant varieties, making it important to find and deploy new sources of resistance. Blackbird, a variety of T. turgidum L. subsp. carthlicum (Nevski) A. Love & D. Love, carries a high level of resistance to loose smut. Blackbird was crossed with the loose smut susceptible durum cultivar Strongfield to produce a doubled haploid (DH) mapping population. The parents and progenies were inoculated with U. tritici races T26, T32 and T33 individually and as a mixture at Swift Current, Canada in 2011 and 2012 and loose smut incidence (LSI) was assessed. Genotyping of the DH population and parents using an Infinium iSelect 90K single nucleotide polymorphism (SNP) array identified 12,952 polymorphic SNPs. The SNPs and 426 SSRs (previously genotyped in the same population) were mapped to 16 linkage groups spanning 3008.4 cM at an average inter-marker space of 0.2 cM in a high-density genetic map. Composite interval mapping analysis revealed three significant quantitative trait loci (QTL) for loose smut resistance on chromosomes 3A, 6B and 7A. The loose smut resistance QTL on 6B (QUt.spa-6B.2) and 7A (QUt.spa-7A.2) were derived from Blackbird. Strongfield contributed the minor QTL on 3A (QUt.spa-3A.2). The resistance on 6B was a stable major QTL effective against all individual races and the mixture of the three races; it explained up to 74% of the phenotypic variation. This study is the first attempt in durum wheat to identify and map loose smut resistance QTL using a high-density genetic map. The QTL QUt.spa-6B.2 would be an effective source for breeding resistance to multiple races of the loose smut pathogen because it provides near-complete broad resistance to the predominant virulence on the Canadian prairies.

Revolution in Genotyping Platforms for Crop Improvement

In the past decade, the application of high-throughput sequencing to crop genotyping has given rise to novel platforms capable of genotyping tens of thousands of genome-wide DNA markers. Coupled with the decreasing costs of sequencing, this rapid increase in markers allows accelerated and highly accurate genotyping of entire crop populations and diversity sets using single nucleotide polymorphisms (SNPs). These revolutionary advances accelerate crop improvement by facilitating a more precise connection of phenotype to genotype through association studies, linkage mapping and diversity analysis. The platforms driving the advances in genotyping are array technologies and genotyping by sequencing (GBS) methods, which include both low-coverage whole genome resequencing (skim sequencing) and reduced representation sequencing (RRS) approaches. Here, we outline and compare these genotyping platforms and provide a perspective on the promising future of crop genotyping. While SNP arrays provide high quality, simple handling, and unchallenging analysis, the lower cost of RRS and the greater data volume produced by skim sequencing suggest that use of GBS will become more prevalent in crop genomics as sequencing costs decrease and data analysis becomes more streamlined. Graphical Abstract.

The genome sequence of sweet cherry (Prunus avium) for use in genomics-assisted breeding

We determined the genome sequence of sweet cherry (Prunus avium) using next-generation sequencing technology. The total length of the assembled sequences was 272.4 Mb, consisting of 10,148 scaffold sequences with an N50 length of 219.6 kb. The sequences covered 77.8% of the 352.9 Mb sweet cherry genome, as estimated by k-mer analysis, and included >96.0% of the core eukaryotic genes. We predicted 43,349 complete and partial protein-encoding genes. A high-density consensus map with 2,382 loci was constructed using double-digest restriction site–associated DNA sequencing. Comparing the genetic maps of sweet cherry and peach revealed high synteny between the two genomes; thus the scaffolds were integrated into pseudomolecules using map- and synteny-based strategies. Whole-genome resequencing of six modern cultivars found 1,016,866 SNPs and 162,402 insertions/deletions, out of which 0.7% were deleterious. The sequence variants, as well as simple sequence repeats, can be used as DNA markers. The genomic information helps us to identify agronomically important genes and will accelerate genetic studies and breeding programs for sweet cherries. Further information on the genomic sequences and DNA markers is available in DBcherry (http://cherry.kazusa.or.jp (8 May 2017, date last accessed)).

Crop Breeding Chips and Genotyping Platforms: Progress, Challenges, and Perspectives

There is a rapidly rising trend in the development and application of molecular marker assays for gene mapping and discovery in field crops and trees. Thus far, more than 50 SNP arrays and 15 different types of genotyping-by-sequencing (GBS) platforms have been developed in over 25 crop species and perennial trees. However, much less effort has been made on developing ultra-high-throughput and cost-effective genotyping platforms for applied breeding programs. In this review, we discuss the scientific bottlenecks in existing SNP arrays and GBS technologies and the strategies to develop targeted platforms for crop molecular breeding. We propose that future practical breeding platforms should adopt automated genotyping technologies, either array or sequencing based, target functional polymorphisms underpinning economic traits, and provide desirable prediction accuracy for quantitative traits, with universal applications under wide genetic backgrounds in crops. The development of such platforms faces serious challenges at both the technological level due to cost ineffectiveness, and the knowledge level due to large genotype-phenotype gaps in crop plants. It is expected that such genotyping platforms will be achieved in the next ten years in major crops in consideration of (a) rapid development in gene discovery of important traits, (b) deepened understanding of quantitative traits through new analytical models and population designs, (c) integration of multi-layer -omics data leading to identification of genes and pathways responsible for important breeding traits, and (d) improvement in cost effectiveness of large-scale genotyping. Crop breeding chips and genotyping platforms will provide unprecedented opportunities to accelerate the development of cultivars with desired yield potential, quality, and enhanced adaptation to mitigate the effects of climate change.

Evaluation of multiple approaches to identify genome-wide polymorphisms in closely related genotypes of sweet cherry (Prunus avium L.)

Identification of genetic polymorphisms and subsequent development of molecular markers is important for marker assisted breeding of superior cultivars of economically important species. Sweet cherry (Prunus avium L.) is an economically important non-climacteric tree fruit crop in the Rosaceae family and has undergone a genetic bottleneck due to breeding, resulting in limited genetic diversity in the germplasm that is utilized for breeding new cultivars. Therefore, it is critical to recognize the best platforms for identifying genome-wide polymorphisms that can help identify, and consequently preserve, the diversity in a genetically constrained species. For the identification of polymorphisms in five closely related genotypes of sweet cherry, a gel-based approach (TRAP), reduced representation sequencing (TRAPseq), a 6k cherry SNParray, and whole genome sequencing (WGS) approaches were evaluated in the identification of genome-wide polymorphisms in sweet cherry cultivars. All platforms facilitated detection of polymorphisms among the genotypes with variable efficiency. In assessing multiple SNP detection platforms, this study has demonstrated that a combination of appropriate approaches is necessary for efficient polymorphism identification, especially between closely related cultivars of a species. The information generated in this study provides a valuable resource for future genetic and genomic studies in sweet cherry, and the insights gained from the evaluation of multiple approaches can be utilized for other closely related species with limited genetic diversity in the breeding germplasm.

The Peach v2.0 release: high-resolution linkage mapping and deep resequencing improve chromosome-scale assembly and contiguity

BACKGROUND

The availability of the peach genome sequence has fostered relevant research in peach and related Prunus species enabling the identification of genes underlying important horticultural traits as well as the development of advanced tools for genetic and genomic analyses. The first release of the peach genome (Peach v1.0) represented a high-quality WGS (Whole Genome Shotgun) chromosome-scale assembly with high contiguity (contig L50 214.2 kb), large portions of mapped sequences (96%) and high base accuracy (99.96%). The aim of this work was to improve the quality of the first assembly by increasing the portion of mapped and oriented sequences, correcting misassemblies and improving the contiguity and base accuracy using high-throughput linkage mapping and deep resequencing approaches.

RESULTS

Four linkage maps with 3,576 molecular markers were used to improve the portion of mapped and oriented sequences (from 96.0% and 85.6% of Peach v1.0 to 99.2% and 98.2% of v2.0, respectively) and enabled a more detailed identification of discernible misassemblies (10.4 Mb in total). The deep resequencing approach fixed 859 homozygous SNPs (Single Nucleotide Polymorphisms) and 1347 homozygous indels. Moreover, the assembled NGS contigs enabled the closing of 212 gaps with an improvement in the contig L50 of 19.2%.

CONCLUSIONS

The improved high quality peach genome assembly (Peach v2.0) represents a valuable tool for the analysis of the genetic diversity, domestication, and as a vehicle for genetic improvement of peach and related Prunus species. Moreover, the important phylogenetic position of peach and the absence of recent whole genome duplication (WGD) events make peach a pivotal species for comparative genomics studies aiming at elucidating plant speciation and diversification processes.

The Peach v2.0 release: high-resolution linkage mapping and deep resequencing improve chromosome-scale assembly and contiguity

BACKGROUND

The availability of the peach genome sequence has fostered relevant research in peach and related Prunus species enabling the identification of genes underlying important horticultural traits as well as the development of advanced tools for genetic and genomic analyses. The first release of the peach genome (Peach v1.0) represented a high-quality WGS (Whole Genome Shotgun) chromosome-scale assembly with high contiguity (contig L50 214.2 kb), large portions of mapped sequences (96%) and high base accuracy (99.96%). The aim of this work was to improve the quality of the first assembly by increasing the portion of mapped and oriented sequences, correcting misassemblies and improving the contiguity and base accuracy using high-throughput linkage mapping and deep resequencing approaches.

RESULTS

Four linkage maps with 3,576 molecular markers were used to improve the portion of mapped and oriented sequences (from 96.0% and 85.6% of Peach v1.0 to 99.2% and 98.2% of v2.0, respectively) and enabled a more detailed identification of discernible misassemblies (10.4 Mb in total). The deep resequencing approach fixed 859 homozygous SNPs (Single Nucleotide Polymorphisms) and 1347 homozygous indels. Moreover, the assembled NGS contigs enabled the closing of 212 gaps with an improvement in the contig L50 of 19.2%.

CONCLUSIONS

The improved high quality peach genome assembly (Peach v2.0) represents a valuable tool for the analysis of the genetic diversity, domestication, and as a vehicle for genetic improvement of peach and related Prunus species. Moreover, the important phylogenetic position of peach and the absence of recent whole genome duplication (WGD) events make peach a pivotal species for comparative genomics studies aiming at elucidating plant speciation and diversification processes.

DNA-informed breeding of rosaceous crops: promises, progress and prospects

Crops of the Rosaceae family provide valuable contributions to rural economies and human health and enjoyment. Sustained solutions to production challenges and market demands can be met with genetically improved new cultivars. Traditional rosaceous crop breeding is expensive and time-consuming and would benefit from improvements in efficiency and accuracy. Use of DNA information is becoming conventional in rosaceous crop breeding, contributing to many decisions and operations, but only after past decades of solved challenges and generation of sufficient resources. Successes in deployment of DNA-based knowledge and tools have arisen when the 'chasm' between genomics discoveries and practical application is bridged systematically. Key steps are establishing breeder desire for use of DNA information, adapting tools to local breeding utility, identifying efficient application schemes, accessing effective services in DNA-based diagnostics and gaining experience in integrating DNA information into breeding operations and decisions. DNA-informed germplasm characterization for revealing identity and relatedness has benefitted many programs and provides a compelling entry point to reaping benefits of genomics research. DNA-informed germplasm evaluation for predicting trait performance has enabled effective reallocation of breeding resources when applied in pioneering programs. DNA-based diagnostics is now expanding from specific loci to genome-wide considerations. Realizing the full potential of this expansion will require improved accuracy of predictions, multi-trait DNA profiling capabilities, streamlined breeding information management systems, strategies that overcome plant-based features that limit breeding progress and widespread training of current and future breeding personnel and allied scientists.

Genomic dissection of a 'Fuji' apple cultivar: re-sequencing, SNP marker development, definition of haplotypes, and QTL detection

'Fuji' is one of the most popular and highly-produced apple cultivars worldwide, and has been frequently used in breeding programs. The development of genotypic markers for the preferable phenotypes of 'Fuji' is required. Here, we aimed to define the haplotypes of 'Fuji' and find associations between haplotypes and phenotypes of five traits (harvest day, fruit weight, acidity, degree of watercore, and flesh mealiness) by using 115 accessions related to 'Fuji'. Through the re-sequencing of 'Fuji' genome, total of 2,820,759 variants, including single nucleotide polymorphisms (SNPs) and insertions or deletions (indels) were detected between 'Fuji' and 'Golden Delicious' reference genome. We selected mapping-validated 1,014 SNPs, most of which were heterozygous in 'Fuji' and capable of distinguishing alleles inherited from the parents of 'Fuji' (i.e., 'Ralls Janet' and 'Delicious'). We used these SNPs to define the haplotypes of 'Fuji' and trace their inheritance in relatives, which were shown to have an average of 27% of 'Fuji' genome. Analysis of variance (ANOVA) based on 'Fuji' haplotypes identified one quantitative trait loci (QTL) each for harvest time, acidity, degree of watercore, and mealiness. A haplotype from 'Delicious' chr14 was considered to dominantly cause watercore, and one from 'Ralls Janet' chr1 was related to low-mealiness.

New resources for genetic studies in Populus nigra: genome-wide SNP discovery and development of a 12k Infinium array

Whole genome resequencing of 51 Populus nigra (L.) individuals from across Western Europe was performed using Illumina platforms. A total number of 1 878 727 SNPs distributed along the P. nigra reference sequence were identified. The SNP calling accuracy was validated with Sanger sequencing. SNPs were selected within 14 previously identified QTL regions, 2916 expressional candidate genes related to rust resistance, wood properties, water-use efficiency and bud phenology and 1732 genes randomly spread across the genome. Over 10 000 SNPs were selected for the construction of a 12k Infinium Bead-Chip array dedicated to association mapping. The SNP genotyping assay was performed with 888 P. nigra individuals. The genotyping success rate was 91%. Our high success rate was due to the discovery panel design and the stringent parameters applied for SNP calling and selection. In the same set of P. nigra genotypes, linkage disequilibrium throughout the genome decayed on average within 5-7 kb to half of its maximum value. As an application test, ADMIXTURE analysis was performed with a selection of 600 SNPs spread throughout the genome and 706 individuals collected along 12 river basins. The admixture pattern was consistent with genetic diversity revealed by neutral markers and the geographical distribution of the populations. These newly developed SNP resources and genotyping array provide a valuable tool for population genetic studies and identification of QTLs through natural-population based genetic association studies in P. nigra.

Genetic diversity, linkage disequilibrium, population structure and construction of a core collection of Prunus avium L. landraces and bred cultivars

BACKGROUND

Depiction of the genetic diversity, linkage disequilibrium (LD) and population structure is essential for the efficient organization and exploitation of genetic resources. The objectives of this study were to (i) to evaluate the genetic diversity and to detect the patterns of LD, (ii) to estimate the levels of population structure and (iii) to identify a 'core collection' suitable for association genetic studies in sweet cherry.

RESULTS

A total of 210 genotypes including modern cultivars and landraces from 16 countries were genotyped using the RosBREED cherry 6 K SNP array v1. Two groups, mainly bred cultivars and landraces, respectively, were first detected using STRUCTURE software and confirmed by Principal Coordinate Analysis (PCoA). Further analyses identified nine subgroups using STRUCTURE and Discriminant Analysis of Principal Components (DAPC). Several sub-groups correspond to different eco-geographic regions of landraces distribution. Linkage disequilibrium was evaluated showing lower values than in peach, the reference Prunus species. A 'core collection' containing 156 accessions was selected using the maximum length sub tree method.

CONCLUSION

The present study constitutes the first population genetics analysis in cultivated sweet cherry using a medium-density SNP (single nucleotide polymorphism) marker array. We provided estimations of linkage disequilibrium, genetic structure and the definition of a first INRA's Sweet Cherry core collection useful for breeding programs, germplasm management and association genetics studies.

Genomics of pear and other Rosaceae fruit trees

The family Rosaceae includes many economically important fruit trees, such as pear, apple, peach, cherry, quince, apricot, plum, raspberry, and loquat. Over the past few years, whole-genome sequences have been released for Chinese pear, European pear, apple, peach, Japanese apricot, and strawberry. These sequences help us to conduct functional and comparative genomics studies and to develop new cultivars with desirable traits by marker-assisted selection in breeding programs. These genomics resources also allow identification of evolutionary relationships in Rosaceae, development of genome-wide SNP and SSR markers, and construction of reference genetic linkage maps, which are available through the Genome Database for the Rosaceae website. Here, we review the recent advances in genomics studies and their practical applications for Rosaceae fruit trees, particularly pear, apple, peach, and cherry.

Mapping of Candidate Genes Involved in Bud Dormancy and Flowering Time in Sweet Cherry (Prunus avium)

The timing of flowering in perennial plants is crucial for their survival in temperate climates and is regulated by the duration of bud dormancy. Bud dormancy release and bud break depend on the perception of cumulative chilling during endodormancy and heat during the bud development. The objectives of this work were to identify candidate genes involved in dormancy and flowering processes in sweet cherry, their mapping in two mapping progenies ‘Regina’ × ‘Garnet’ and ‘Regina’ × ‘Lapins’, and to select those candidate genes which co-localized with quantitative trait loci (QTLs) associated with temperature requirements for bud dormancy release and flowering. Based on available data on flowering processes in various species, a list of 79 candidate genes was established. The peach and sweet cherry orthologs were identified and primers were designed to amplify sweet cherry candidate gene fragments. Based on the amplified sequences of the three parents of the mapping progenies, SNPs segregations in the progenies were identified. Thirty five candidate genes were genetically mapped in at least one of the two progenies and all were in silico mapped. Co-localization between candidate genes and QTLs associated with temperature requirements and flowering date were identified for the first time in sweet cherry. The allelic composition of the candidate genes located in the major QTL for heat requirements and flowering date located on linkage group 4 have a significant effect on these two traits indicating their potential use for breeding programs in sweet cherry to select new varieties adapted to putative future climatic conditions.

Evaluating the Influence of the Microsatellite Marker Set on the Genetic Structure Inferred in Pyrus communis L

Fingerprinting information can be used to elucidate in a robust manner the genetic structure of germplasm collections, allowing a more rational and fine assessment of genetic resources. Bayesian model-based approaches are nowadays majorly preferred to infer genetic structure, but it is still largely unresolved how marker sets should be built in order to obtain a robust inference. The objective was to evaluate, in Pyrus germplasm collections, the influence of the SSR marker set size on the genetic structure inferred, also evaluating the influence of the criterion used to select those markers. Inferences were performed considering an increasing number of SSR markers that ranged from just two up to 25, incorporated one at a time into the analysis. The influence of the number of SSR markers used was evaluated comparing the number of populations and the strength of the signal detected, and also the similarity of the genotype assignments to populations between analyses. In order to test if those results were influenced by the criterion used to select the SSRs, several choosing scenarios based on the discrimination power or the fixation index values of the SSRs were tested. Our results indicate that population structure could be inferred accurately once a certain SSR number threshold was reached, which depended on the underlying structure within the genotypes, but the method used to select the markers included on each set appeared not to be very relevant. The minimum number of SSRs required to provide robust structure inferences and adequate measurements of the differentiation, even when low differentiation levels exist within populations, was proved similar to that of the complete list of recommended markers for fingerprinting. When a SSR set size similar to the minimum marker sets recommended for fingerprinting it is used, only major divisions or moderate (FST>0.05) differentiation of the germplasm are detected.

High density linkage mapping of genomic and transcriptomic SNPs for synteny analysis and anchoring the genome sequence of chickpea

This study presents genome-wide discovery of SNPs through next generation sequencing of the genome of Cicer reticulatum. Mapping of the C. reticulatum sequenced reads onto the draft genome assembly of C. arietinum (desi chickpea) resulted in identification of 842,104 genomic SNPs which were utilized along with an additional 36,446 genic SNPs identified from transcriptome sequences of the aforementioned varieties. Two new chickpea Oligo Pool All (OPAs) each having 3,072 SNPs were designed and utilized for SNP genotyping of 129 Recombinant Inbred Lines (RILs). Using Illumina GoldenGate Technology genotyping data of 5,041 SNPs were generated and combined with the 1,673 marker data from previously published studies, to generate a high resolution linkage map. The map comprised of 6698 markers distributed on eight linkage groups spanning 1083.93 cM with an average inter-marker distance of 0.16 cM. Utility of the present map was demonstrated for improving the anchoring of the earlier reported draft genome sequence of desi chickpea by ~30% and that of kabuli chickpea by 18%. The genetic map reported in this study represents the most dense linkage map of chickpea , with the potential to facilitate efficient anchoring of the draft genome sequences of desi as well as kabuli chickpea varieties.

Mining microsatellites in the peach genome: development of new long-core SSR markers for genetic analyses in five Prunus species

A wide inventory of molecular markers is nowadays available for individual fingerprinting. Microsatellites, or simple sequence repeats (SSRs), play a relevant role due to their relatively ease of use, their abundance in the plant genomes, and their co-dominant nature, together with the availability of primer sequences in many important agricultural crops. Microsatellites with long-core motifs are more easily scored and were adopted long ago in human genetics but they were developed only in few crops, and Prunus species are not among them. In the present work the peach whole-genome sequence was used to select 216 SSRs containing long-core motifs with tri-, tetra- and penta-nucleotide repeats. Microsatellite primer pairs were designed and tested for polymorphism in the five diploid Prunus species of economic relevance (almond, apricot, Japanese plum, peach and sweet cherry). A set of 26 microsatellite markers covering all the eight chromosomes, was also selected and used in the molecular characterization, population genetics and structure analyses of a representative sample of the five diploid Prunus species, assessing their transportability and effectiveness. The combined probability of identity between two random individuals for the whole set of 26 SSRs was quite low, ranging from 2.30 × 10⁻⁷ in peach to 9.48 × 10⁻¹⁰ in almond, confirming the usefulness of the proposed set for fingerprinting analyses in Prunus species.

Identification of Genetic Loci Associated with Quality Traits in Almond via Association Mapping

To design an appropriate association study, we need to understand population structure and the structure of linkage disequilibrium within and among populations as well as in different regions of the genome in an organism. In this study, we have used a total of 98 almond accessions, from five continents located and maintained at the Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA; Spain), and 40 microsatellite markers. Population structure analysis performed in 'Structure' grouped the accessions into two principal groups; the Mediterranean (Western-Europe) and the non-Mediterranean, with K = 3, being the best fit for our data. There was a strong subpopulation structure with linkage disequilibrium decaying with increasing genetic distance resulting in lower levels of linkage disequilibrium between more distant markers. A significant impact of population structure on linkage disequilibrium in the almond cultivar groups was observed. The mean r2 value for all intra-chromosomal loci pairs was 0.040, whereas, the r2 for the inter-chromosomal loci pairs was 0.036. For analysis of association between the markers and phenotypic traits, five models comprising both general linear models and mixed linear models were selected to test the marker trait associations. The mixed linear model (MLM) approach using co-ancestry values from population structure and kinship estimates (K model) as covariates identified a maximum of 16 significant associations for chemical traits and 12 for physical traits. This study reports for the first time the use of association mapping for determining marker-locus trait associations in a world-wide almond germplasm collection. It is likely that association mapping will have the most immediate and largest impact on the tier of crops such as almond with the greatest economic value.

Prunus transcription factors: breeding perspectives

Many plant processes depend on differential gene expression, which is generally controlled by complex proteins called transcription factors (TFs). In peach, 1533 TFs have been identified, accounting for about 5.5% of the 27,852 protein-coding genes. These TFs are the reference for the rest of the Prunus species. TF studies in Prunus have been performed on the gene expression analysis of different agronomic traits, including control of the flowering process, fruit quality, and biotic and abiotic stress resistance. These studies, using quantitative RT-PCR, have mainly been performed in peach, and to a lesser extent in other species, including almond, apricot, black cherry, Fuji cherry, Japanese apricot, plum, and sour and sweet cherry. Other tools have also been used in TF studies, including cDNA-AFLP, LC-ESI-MS, RNA, and DNA blotting or mapping. More recently, new tools assayed include microarray and high-throughput DNA sequencing (DNA-Seq) and RNA sequencing (RNA-Seq). New functional genomics opportunities include genome resequencing and the well-known synteny among Prunus genomes and transcriptomes. These new functional studies should be applied in breeding programs in the development of molecular markers. With the genome sequences available, some strategies that have been used in model systems (such as SNP genotyping assays and genotyping-by-sequencing) may be applicable in the functional analysis of Prunus TFs as well. In addition, the knowledge of the gene functions and position in the peach reference genome of the TFs represents an additional advantage. These facts could greatly facilitate the isolation of genes via QTL (quantitative trait loci) map-based cloning in the different Prunus species, following the association of these TFs with the identified QTLs using the peach reference genome.

Single Nucleotide Polymorphism Identification in Polyploids: A Review, Example, and Recommendations

Understanding the relationship between genotype and phenotype is a major biological question and being able to predict phenotypes based on molecular genotypes is integral to molecular breeding. Whole-genome duplications have shaped the history of all flowering plants and present challenges to elucidating the relationship between genotype and phenotype, especially in neopolyploid species. Although single nucleotide polymorphisms (SNPs) have become popular tools for genetic mapping, discovery and application of SNPs in polyploids has been difficult. Here, we summarize common experimental approaches to SNP calling, highlighting recent polyploid successes. To examine the impact of software choice on these analyses, we called SNPs among five peanut genotypes using different alignment programs (BWA-mem and Bowtie 2) and variant callers (SAMtools, GATK, and Freebayes). Alignments produced by Bowtie 2 and BWA-mem and analyzed in SAMtools shared 24.5% concordant SNPs, and SAMtools, GATK, and Freebayes shared 1.4% concordant SNPs. A subsequent analysis of simulated Brassica napus chromosome 1A and 1C genotypes demonstrated that, of the three software programs, SAMtools performed with the highest sensitivity and specificity on Bowtie 2 alignments. These results, however, are likely to vary among species, and we therefore propose a series of best practices for SNP calling in polyploids.

Construction of High Density Sweet Cherry (Prunus avium L.) Linkage Maps Using Microsatellite Markers and SNPs Detected by Genotyping-by-Sequencing (GBS)

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.

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.