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

A haplotype-phased genome characterizes the genomic architecture and causal variants for RXf1 conferring resistance to Xanthomonas fragariae in strawberry (F. × ananassa)

BACKGROUND

Cultivated octoploid strawberry (Fragaria × ananassa) is one of the most economically important fruits worldwide due to its flavor, texture, and health benefits. However, bacterial angular leaf spot (ALS) causes economic losses in fruit production and plant nurseries. All commercial strawberry varieties are susceptible to ALS. A major resistance locus, RXf1, has been reported, but the genomic structure and candidate genes underlying this resistance remain known.

RESULTS

Fine-mapping was performed using three segregating populations containing 663 individuals that were genotyped with subgenome specific seven high-resolution melting (HRM) markers to narrow the RXf1 region to a 486-kb interval on chromosome 6C. We assembled a haplotype-phased chromosome-scale genome of ALS-resistant breeding selection FL17.68-110 using highly accurate long-read sequencing and trio-binning with parental short reads. The 1.62 Gbp genome containing two haplotypes, 56 chromosomes and 193,072 annotated genes. Transcriptome analysis in response to the ALS pathogen identified a candidate gene, Resistance gene analogue 3 (RGA3), associated with the RXf1 resistance. The gene structure and sequence variations within FaRGA3 were identified between resistant and susceptible genotypes.

CONCLUSIONS

Our results narrowed the RXf1 region, identified structural variations within this locus and pointed to FaRGA3 as a promising candidate gene. This information will be useful for breeders toward developing ALS-resistant strawberry varieties, and the high-quality genome will be a valuable resource for further genomics research in octoploid strawberry.

Improvement of crop production in controlled environment agriculture through breeding

Controlled environment agriculture (CEA) represents one of the fastest-growing sectors of horticulture. Production in controlled environments ranges from highly controlled indoor environments with 100% artificial lighting (vertical farms or plant factories) to high-tech greenhouses with or without supplemental lighting, to simpler greenhouses and high tunnels. Although food production occurs in the soil inside high tunnels, most CEA operations use various hydroponic systems to meet crop irrigation and fertility needs. The expansion of CEA offers promise as a tool for increasing food production in and near urban systems as these systems do not rely on arable agricultural land. In addition, CEA offers resilience to climate instability by growing inside protective structures. Products harvested from CEA systems tend to be of high quality, both internal and external, and are sought after by consumers. Currently, CEA producers rely on cultivars bred for production in open-field agriculture. Because of high energy and other production costs in CEA, only a limited number of food crops have proven themselves to be profitable to produce. One factor contributing to this situation may be a lack of optimized cultivars. Indoor growing operations offer opportunities for breeding cultivars that are ideal for these systems. To facilitate breeding these specialized cultivars, a wide range of tools are available for plant breeders to help speed this process and increase its efficiency. This review aims to cover breeding opportunities and needs for a wide range of horticultural crops either already being produced in CEA systems or with potential for CEA production. It also reviews many of the tools available to breeders including genomics-informed breeding, marker-assisted selection, precision breeding, high-throughput phenotyping, and potential sources of germplasm suitable for CEA breeding. The availability of published genomes and trait-linked molecular markers should enable rapid progress in the breeding of CEA-specific food crops that will help drive the growth of this industry.

How to handle high subgenome sequence similarity in allopolyploid Fragaria x ananassa: linkage disequilibrium based variant filtering

BACKGROUND

The allo-octoploid Fragaria x ananassa follows disomic inheritance, yet the high sequence similarity among its subgenomes can lead to misalignment of short sequencing reads (150 bp). This misalignment results in an increased number of erroneous variants during variant calling. To accurately associate traits with the appropriate subgenome, it is essential to filter out these erroneous variants. By classifying variants into correct (type 1) and erroneous types (homoeologous variants-type 2, and multi-locus variants-type 3), we can improve the reliability of downstream analyses.

RESULTS

Our analysis reveals that while erroneous variant types often display skewed average allele balances (AAB) for heterozygous calls, this measure alone is insufficient. To mitigate the erroneous variants further, we employed a Linkage Disequilibrium (LD) based filtering method that correlates highly (99%) with an approach that utilizes a genetic map from a biparental population. This combined filtering strategy-using both LD-based and average allele balance methods-resulted in the lowest switch error rate (0.037). Notably, our best filtering approach decreased phasing switch error rates by 44% and preserved 72% of the original dataset.

CONCLUSIONS

The results indicate that identifying erroneous variants due to subgenome similarity can be effectively achieved without extensive genotyping of mapping populations. By implementing the LD-based filtering method, the phasing accuracy improved which improves the tracability of important alleles in the germplasm, paving the way for better understanding of trait associations in F. x ananassa.

Development of a next generation SNP genotyping array for wheat

High-throughput genotyping arrays have provided a cost-effective, reliable and interoperable system for genotyping hexaploid wheat and its relatives. Existing, highly cited arrays including our 35K Wheat Breeder's array and the Illumina 90K array were designed based on a limited amount of varietal sequence diversity and with imperfect knowledge of SNP positions. Recent progress in wheat sequencing has given us access to a vast pool of SNP diversity, whilst technological improvements have allowed us to fit significantly more probes onto a 384-well format Axiom array than previously possible. Here we describe a novel Axiom genotyping array, the 'Triticum aestivum Next Generation' array (TaNG), largely derived from whole genome skim sequencing of 204 elite wheat lines and 111 wheat landraces taken from the Watkins 'Core Collection'. We used a novel haplotype optimization approach to select SNPs with the highest combined varietal discrimination and a design iteration step to test and replace SNPs which failed to convert to reliable markers. The final design with 43 372 SNPs contains a combination of haplotype-optimized novel SNPs and legacy cross-platform markers. We show that this design has an improved distribution of SNPs compared to previous arrays and can be used to generate genetic maps with a significantly higher number of distinct bins than our previous array. We also demonstrate the improved performance of TaNGv1.1 for Genome-wide association studies (GWAS) and its utility for Copy Number Variation (CNV) analysis. The array is commercially available with supporting marker annotations and initial genotyping results freely available.

Genetic loci associated with tissue-specific resistance to powdery mildew in octoploid strawberry (Fragaria × ananassa)

Powdery mildew is one of the most problematic diseases in strawberry production. To date, few commercial strawberry cultivars are deemed to have complete resistance and as such, an extensive spray programme must be implemented to control the pathogen. Here, a large-scale field experiment was used to determine the powdery mildew resistance status of leaf and fruit tissues across a diverse panel of strawberry genotypes. This phenotypic data was used to identify Quantitative Trait Nucleotides (QTN) associated with tissue-specific powdery mildew resistance. In total, six stable QTN were found to be associated with foliar resistance, with one QTN on chromosome 7D associated with a 61% increase in resistance. In contrast to the foliage results, there were no QTN associated with fruit disease resistance and there was a high level of resistance observed on strawberry fruit, with no genetic correlation observed between fruit and foliar symptoms, indicating a tissue-specific response. Beyond the identification of genetic loci, we also demonstrate that genomic selection can lead to rapid gains in foliar resistance across genotypes, with the potential to capture >50% of the genetic foliage resistance present in the population. To date, breeding of robust powdery mildew resistance in strawberry has been impeded by the quantitative nature of natural resistance and a lack of knowledge relating to the genetic control of the trait. These results address this shortfall, through providing the community with a wealth of information that could be utilized for genomic informed breeding, implementation of which could deliver a natural resistance strategy for combatting powdery mildew.

Advances in genomics and genome editing for improving strawberry (Fragaria ×ananassa)

The cultivated strawberry, Fragaria ×ananassa, is a recently domesticated fruit species of economic interest worldwide. As such, there is significant interest in continuous varietal improvement. Genomics-assisted improvement, including the use of DNA markers and genomic selection have facilitated significant improvements of numerous key traits during strawberry breeding. CRISPR/Cas-mediated genome editing allows targeted mutations and precision nucleotide substitutions in the target genome, revolutionizing functional genomics and crop improvement. Genome editing is beginning to gain traction in the more challenging polyploid crops, including allo-octoploid strawberry. The release of high-quality reference genomes and comprehensive subgenome-specific genotyping and gene expression profiling data in octoploid strawberry will lead to a surge in trait discovery and modification by using CRISPR/Cas. Genome editing has already been successfully applied for modification of several strawberry genes, including anthocyanin content, fruit firmness and tolerance to post-harvest disease. However, reports on many other important breeding characteristics associated with fruit quality and production are still lacking, indicating a need for streamlined genome editing approaches and tools in Fragaria ×ananassa. In this review, we present an overview of the latest advancements in knowledge and breeding efforts involving CRISPR/Cas genome editing for the enhancement of strawberry varieties. Furthermore, we explore potential applications of this technology for improving other Rosaceous plant species.

Accelerating genetic gains for quantitative resistance to verticillium wilt through predictive breeding in strawberry

Verticillium wilt (VW), a devastating vascular wilt disease of strawberry (Fragaria × $\times$ ananassa), has caused economic losses for nearly a century. This disease is caused by the soil-borne pathogen Verticillium dahliae, which occurs nearly worldwide and causes disease in numerous agriculturally important plants. The development of VW-resistant cultivars is critically important for the sustainability of strawberry production. We previously showed that a preponderance of the genetic resources (asexually propagated hybrid individuals) preserved in public germplasm collections were moderately to highly susceptible and that genetic gains for increased resistance to VW have been negligible over the last 60 years. To more fully understand the challenges associated with breeding for increased quantitative resistance to this pathogen, we developed and phenotyped a training population of hybrids (n = 564 $n = 564$ ) among elite parents with a wide range of resistance phenotypes. When these data were combined with training data from a population of elite and exotic hybrids (n = 386 $n = 386$ ), genomic prediction accuracies of 0.47-0.48 were achieved and were predicted to explain 70%-75% of the additive genetic variance for resistance. We concluded that breeding values for resistance to VW can be predicted with sufficient accuracy for effective genomic selection with routine updating of training populations.

Development and Assessment of SNP Genotyping Arrays for Citrus and Its Close Relatives

Rapid advancements in technologies provide various tools to analyze fruit crop genomes to better understand genetic diversity and relationships and aid in breeding. Genome-wide single nucleotide polymorphism (SNP) genotyping arrays offer highly multiplexed assays at a relatively low cost per data point. We report the development and validation of 1.4M SNP Axiom® Citrus HD Genotyping Array (Citrus 15AX 1 and Citrus 15AX 2) and 58K SNP Axiom® Citrus Genotyping Arrays for Citrus and close relatives. SNPs represented were chosen from a citrus variant discovery panel consisting of 41 diverse whole-genome re-sequenced accessions of Citrus and close relatives, including eight progenitor citrus species. SNPs chosen mainly target putative genic regions of the genome and are accurately called in both Citrus and its closely related genera while providing good coverage of the nuclear and chloroplast genomes. Reproducibility of the arrays was nearly 100%, with a large majority of the SNPs classified as the most stringent class of markers, "PolyHighResolution" (PHR) polymorphisms. Concordance between SNP calls in sequence data and array data average 98%. Phylogenies generated with array data were similar to those with comparable sequence data and little affected by 3 to 5% genotyping error. Both arrays are publicly available.

Strawberry soluble solids QTL with inverse effects on yield

Sugars are the main drivers of strawberry sweetness, and understanding their genetic control is of critical importance for breeding. Large-scale genome-wide association studies were performed in two populations totaling 3399 individuals evaluated for soluble solids content (SSC) and fruit yield. Two stable quantitative trait loci (QTL) on chromosome 3B and 6A for SSC were identified. Favorable haplotypes at both QTL for SSC decreased yield, though optimal allelic combinations were identified with reduced impacts on yield. Metabolites in the starch and sucrose metabolism pathway were characterized and quantified for 23 contrasting genotypes in leaves, white fruit, and red fruit. Variations in sucrose concentrations/efflux indicated genetic variation underlying sucrose accumulation and transportation during fruit ripening. Integration of genome-wide association studies and expression quantitative locus mapping identified starch synthase 4 (FxaC_10g00830) and sugar transporter 2-like candidate genes (FxaC_21g51570) within the respective QTL intervals. These results will enable immediate applications in genomics-assisted breeding for flavor and further study of candidate genes underlying genetic variation of sugar accumulation in strawberry fruit.

Transgressive segregation, hopeful monsters, and phenotypic selection drove rapid genetic gains and breakthroughs in predictive breeding for quantitative resistance to Macrophomina in strawberry

Two decades have passed since the strawberry (Fragaria x ananassa) disease caused by Macrophomina phaseolina, a necrotrophic soilborne fungal pathogen, began surfacing in California, Florida, and elsewhere. This disease has since become one of the most common causes of plant death and yield losses in strawberry. The Macrophomina problem emerged and expanded in the wake of the global phase-out of soil fumigation with methyl bromide and appears to have been aggravated by an increase in climate change-associated abiotic stresses. Here we show that sources of resistance to this pathogen are rare in gene banks and that the favorable alleles they carry are phenotypically unobvious. The latter were exposed by transgressive segregation and selection in populations phenotyped for resistance to Macrophomina under heat and drought stress. The genetic gains were immediate and dramatic. The frequency of highly resistant individuals increased from 1% in selection cycle 0 to 74% in selection cycle 2. Using GWAS and survival analysis, we found that phenotypic selection had increased the frequencies of favorable alleles among 10 loci associated with resistance and that favorable alleles had to be accumulated among four or more of these loci for an individual to acquire resistance. An unexpectedly straightforward solution to the Macrophomina disease resistance breeding problem emerged from our studies, which showed that highly resistant cultivars can be developed by genomic selection per se or marker-assisted stacking of favorable alleles among a comparatively small number of large-effect loci.

A medium-density genotyping platform for cultivated strawberry using DArTag technology

Genomic prediction in breeding populations containing hundreds to thousands of parents and seedlings is prohibitively expensive with current high-density genetic marker platforms designed for strawberry. We developed mid-density panels of molecular inversion probes (MIPs) to be deployed with the "DArTag" marker platform to provide a low-cost, high-throughput genotyping solution for strawberry genomic prediction. In total, 7742 target single nucleotide polymorphism (SNP) regions were used to generate MIP assays that were tested with a screening panel of 376 octoploid Fragaria accessions. We evaluated the performance of DArTag assays based on genotype segregation, amplicon coverage, and their ability to produce subgenome-specific amplicon alignments to the FaRR1 assembly and subsequent alignment-based variant calls with strong concordance to DArT's alignment-free, count-based genotype reports. We used a combination of marker performance metrics and physical distribution in the FaRR1 assembly to select 3K and 5K production panels for genotyping of large strawberry populations. We show that the 3K and 5K DArTag panels are able to target and amplify homologous alleles within subgenomic sequences with low-amplification bias between reference and alternate alleles, supporting accurate genotype calling while producing marker genotypes that can be treated as functionally diploid for quantitative genetic analysis. The 3K and 5K target SNPs show high levels of polymorphism in diverse F. × ananassa germplasm and UC Davis cultivars, with mean pairwise diversity (π) estimates of 0.40 and 0.32 and mean heterozygous genotype frequencies of 0.35 and 0.33, respectively.

Deciphering the genetic architecture of fruit color in strawberry

Fruits of Fragaria species usually have an appealing bright red color due to the accumulation of anthocyanins, water-soluble flavonoid pigments. Octoploid cultivated strawberry (Fragaria × ananassa) is a major horticultural crop for which fruit color and associated nutritional value are main breeding targets. Great diversity in fruit color intensity and pattern is observed not only in cultivated strawberry but also in wild relatives such as its octoploid progenitor F. chiloensis or the diploid woodland strawberry F. vesca, a model for fruit species in the Rosaceae. This review examines our understanding of fruit color formation in strawberry and how ongoing developments will advance it. Natural variations of fruit color as well as color changes during fruit development or in response to several cues have been used to explore the anthocyanin biosynthetic pathway and its regulation. So far, the successful identification of causal genetic variants has been largely driven by the availability of high-throughput genotyping tools and high-quality reference genomes of F. vesca and F. × ananassa. The current completion of haplotype-resolved genomes of F. × ananassa combined with QTL mapping will accelerate the exploitation of the untapped genetic diversity of fruit color and help translate the findings into strawberry improvement.

Molecular bases of strawberry fruit quality traits: Advances, challenges, and opportunities

The strawberry is one of the world's most popular fruits, providing humans with vitamins, fibers, and antioxidants. Cultivated strawberry (Fragaria × ananassa) is an allo-octoploid and highly heterozygous, making it a challenge for breeding, quantitative trait locus (QTL) mapping, and gene discovery. Some wild strawberry relatives, such as Fragaria vesca, have diploid genomes and are becoming laboratory models for the cultivated strawberry. Recent advances in genome sequencing and CRISPR-mediated genome editing have greatly improved the understanding of various aspects of strawberry growth and development in both cultivated and wild strawberries. This review focuses on fruit quality traits that are most relevant to the consumers, including fruit aroma, sweetness, color, firmness, and shape. Recently available phased-haplotype genomes, single nucleotide polymorphism (SNP) arrays, extensive fruit transcriptomes, and other big data have made it possible to locate key genomic regions or pinpoint specific genes that underlie volatile synthesis, anthocyanin accumulation for fruit color, and sweetness intensity or perception. These new advances will greatly facilitate marker-assisted breeding, the introgression of missing genes into modern varieties, and precise genome editing of selected genes and pathways. Strawberries are poised to benefit from these recent advances, providing consumers with fruit that is tastier, longer-lasting, healthier, and more beautiful.

Genomic selection strategies for clonally propagated crops

For genomic selection in clonally propagated crops with diploid (-like) meiotic behavior to be effective, crossing parents should be selected based on genomic predicted cross-performance unless dominance is negligible. For genomic selection (GS) in clonal breeding programs to be effective, parents should be selected based on genomic predicted cross-performance unless dominance is negligible. Genomic prediction of cross-performance enables efficient exploitation of the additive and dominance value simultaneously. Here, we compared different GS strategies for clonally propagated crops with diploid (-like) meiotic behavior, using strawberry as an example. We used stochastic simulation to evaluate six combinations of three breeding programs and two parent selection methods. The three breeding programs included (1) a breeding program that introduced GS in the first clonal stage, and (2) two variations of a two-part breeding program with one and three crossing cycles per year, respectively. The two parent selection methods were (1) parent selection based on genomic estimated breeding values (GEBVs) and (2) parent selection based on genomic predicted cross-performance (GPCP). Selection of parents based on GPCP produced faster genetic gain than selection of parents based on GEBVs because it reduced inbreeding when the dominance degree increased. The two-part breeding programs with one and three crossing cycles per year using GPCP always produced the most genetic gain unless dominance was negligible. We conclude that (1) in clonal breeding programs with GS, parents should be selected based on GPCP, and (2) a two-part breeding program with parent selection based on GPCP to rapidly drive population improvement has great potential to improve breeding clonally propagated crops.

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.

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.

A multi-omics framework reveals strawberry flavor genes and their regulatory elements

Flavor is essential to consumer preference of foods and is an increasing focus of plant breeding programs. In fruit crops, identifying genes underlying volatile organic compounds has great promise to accelerate flavor improvement, but polyploidy and heterozygosity in many species have slowed progress. Here we use octoploid cultivated strawberry to demonstrate how genomic heterozygosity, transcriptomic intricacy and fruit metabolomic diversity can be treated as strengths and leveraged to uncover fruit flavor genes and their regulatory elements. Multi-omics datasets were generated including an expression quantitative trait loci map with 196 diverse breeding lines, haplotype-phased genomes of a highly-flavored breeding selection, a genome-wide structural variant map using five haplotypes, and volatile genome-wide association study (GWAS) with > 300 individuals. Overlaying regulatory elements, structural variants and GWAS-linked allele-specific expression of numerous genes to variation in volatile compounds important to flavor. In one example, the functional role of anthranilate synthase alpha subunit 1 in methyl anthranilate biosynthesis was supported via fruit transient gene expression assays. These results demonstrate a framework for flavor gene discovery in fruit crops and a pathway to molecular breeding of cultivars with complex and desirable flavor.

Quantitative evaluation of nonlinear methods for population structure visualization and inference

Population structure (also called genetic structure and population stratification) is the presence of a systematic difference in allele frequencies between subpopulations in a population as a result of nonrandom mating between individuals. It can be informative of genetic ancestry, and in the context of medical genetics, it is an important confounding variable in genome-wide association studies. Recently, many nonlinear dimensionality reduction techniques have been proposed for the population structure visualization task. However, an objective comparison of these techniques has so far been missing from the literature. In this article, we discuss the previously proposed nonlinear techniques and some of their potential weaknesses. We then propose a novel quantitative evaluation methodology for comparing these nonlinear techniques, based on populations for which pedigree is known a priori either through artificial selection or simulation. Based on this evaluation metric, we find graph-based algorithms such as t-SNE and UMAP to be superior to principal component analysis, while neural network-based methods fall behind.

Inheritance of esters and other volatile compounds responsible for the fruity aroma in strawberry

Cultivated strawberry, Fragaria  ×  ananassa, has a complex aroma due to the presence of more than 350 volatile organic compounds (VOCs). However, a mixture of only 19 compounds, called Key Volatile Compounds (KVC), can impart the main strawberry aroma. The octoploid nature of the cultivated strawberry species (2n = 8x = 56) adds complexity to the heritance of the accumulation of the volatiles responsible for aroma. An F1 population cross between two breeding parental lines, FC50 and FD54, was phenotyped for aroma by SPME GCMS during six harvests. A total of 58 compounds were identified: 33 esters, nine terpenes, seven aldehydes, four lactones, two furans, one acid, one alkane and one alcohol, of which 16 were KVCs. A total of 179 QTLs were found, and 85 of these were detected in at least three harvests, of which 50 QTLs were considered major (LOD > 4.0) and detected in five or six analyzed harvests. Several clusters of ester QTLs associated with fruity aroma were discovered, such as QTLs for esters that share hexanoate group that were mapped in LG4A (Hexanoate_4A), those that share acetate and octyl groups in LG6A (Acetate_6A and Octyl_6A) or those with the same methyl group in LG7B (Methyl_7B). Different terpene QTLs associated with floral aroma appear grouped in a cluster in LG3C (Terpene_3C). Some of these clusters of QTLs were validated in a second F2 population, a cross of "Camarosa" and "Dover," that was also phenotyped for three years. Selected SNPs from floral and fruity aroma QTLs were tested in a third population, which will most likely be useful for marker-assisted breeding (MAB).

Novel Fusarium wilt resistance genes uncovered in natural and cultivated strawberry populations are found on three non-homoeologous chromosomes

Several Fusarium wilt resistance genes were discovered, genetically and physically mapped, and rapidly deployed via marker-assisted selection to develop cultivars resistant to Fusarium oxysporum f. sp. fragariae, a devastating soil-borne pathogen of strawberry. Fusarium wilt, a soilborne disease caused by Fusarium oxysporum f. sp. fragariae, poses a significant threat to strawberry (Fragaria [Formula: see text] ananassa) production in many parts of the world. This pathogen causes wilting, collapse, and death in susceptible genotypes. We previously identified a dominant gene (FW1) on chromosome 2B that confers resistance to race 1 of the pathogen, and hypothesized that gene-for-gene resistance to Fusarium wilt was widespread in strawberry. To explore this, a genetically diverse collection of heirloom and modern cultivars and octoploid ecotypes were screened for resistance to Fusarium wilt races 1 and 2. Here, we show that resistance to both races is widespread in natural and domesticated populations and that resistance to race 1 is conferred by partially to completely dominant alleles among loci (FW1, FW2, FW3, FW4, and FW5) found on three non-homoeologous chromosomes (1A, 2B, and 6B). The underlying genes have not yet been cloned and functionally characterized; however, plausible candidates were identified that encode pattern recognition receptors or other proteins known to confer gene-for-gene resistance in plants. High-throughput genotyping assays for SNPs in linkage disequilibrium with FW1-FW5 were developed to facilitate marker-assisted selection and accelerate the development of race 1 resistant cultivars. This study laid the foundation for identifying the genes encoded by FW1-FW5, in addition to exploring the genetics of resistance to race 2 and other races of the pathogen, as a precaution to averting a Fusarium wilt pandemic.

Exploring the diversity and genetic structure of the U.S. National Cultivated Strawberry Collection

The cultivated strawberry (Fragaria ×ananassa) arose through a hybridization of two wild American octoploid strawberry species in a French garden in the 1750s. Since then, breeders have developed improved cultivars adapted to different growing regions. Diverse germplasm is crucial to meet the challenges strawberry breeders will continue to address. The USDA-ARS National Clonal Germplasm Repository (NCGR) in Corvallis, Oregon maintains the U.S. strawberry collection. Recent developments in high-throughput genotyping for strawberry can provide new insights about the diversity and structure of the collection, germplasm management, and future breeding strategies. Genotyping was conducted on 539 F. ×ananassa accessions using either the iStraw35 or FanaSNP 50 K Axiom array. Data for markers shared by the two arrays were curated for call quality, missing data, and minor allele frequency resulting in 4033 markers for structure assessment, diversity analysis, pedigree confirmation, core collection development, and the identification of haplotypes associated with desirable traits. The F. ×ananassa collection was equally diverse across the different geographic regions represented. K-means clustering, sNMF, and UPGMA hierarchal clustering revealed seven to nine sub-populations associated with different geographic breeding centers. Two 100 accession core collections were created. Pedigree linkages within the collection were confirmed. Finally, accessions containing disease resistance-associated haplotypes for FaRCa1, FaRCg1, FaRMp1, and FaRPc2 were identified. These new core collections will allow breeders and researchers to more efficiently utilize the F. ×ananassa collection. The core collections and other accessions of interest can be requested for research from the USDA-ARS NCGR via the Germplasm Resources Information Network (https://www.ars-grin.gov/).

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.

High Resolution Quantitative Trait Locus Mapping and Whole Genome Sequencing Enable the Design of an Anthocyanidin Reductase-Specific Homoeo-Allelic Marker for Fruit Colour Improvement in Octoploid Strawberry (Fragaria × ananassa)

Fruit colour is central to the sensorial and nutritional quality of strawberry fruit and is therefore a major target in breeding programmes of the octoploid cultivated strawberry (Fragaria × ananassa). The red colour of the fruit is caused by the accumulation of anthocyanins, which are water-soluble flavonoids. To facilitate molecular breeding, here we have mapped with high resolution fruit colour quantitative trait loci (QTLs) (COLOUR, scored visually as in selection programmes) and associated flavonoid metabolic QTLs (5 anthocyanins compounds together with 8 flavonols and flavan-3-ols) to specific subgenomes of cultivated strawberry. Two main colour-related QTLs were located on the LG3A linkage group (Fragaria vesca subgenome). Genetic mapping, transcriptome analysis and whole genome sequencing enabled the detection of a homoeo-allelic variant of ANTHOCYANIDIN REDUCTASE (ANR) underlying the major male M3A COLOUR and pelargonidin-3-glucoside (PgGs) QTLs (up to ∼20% of explained variance). Consistent with previously published functional studies, ANR transcript abundance was inversely related with PgGs content in contrasted progeny individuals. Genetic segregation analyses further indicated that a molecular marker designed using an 18 bp deletion found in the 5'UTR of the candidate ANR homoeo-allelic variant is effective in identifying genotypes with intense red fruit colour. Our study provides insights into the genetic and molecular control of colour-related traits in strawberry and further defines a genetic marker for marker-assisted selection of new strawberry varieties with improved colour. The QTLs detected and the underlying candidate genes are different from those described to date, emphasising the importance of screening a wide diversity of genetic resources in strawberry.

Utilization of a Sugarcane100K Single Nucleotide Polymorphisms Microarray-Derived High-Density Genetic Map in Quantitative Trait Loci Mapping and Function Role Prediction of Genes Related to Chlorophyll Content in Sugarcane

Chlorophyll is the most important pigment for plant photosynthesis that plays an important role in crop growth and production. In this study, the chlorophyll content trait was explored to improve sugarcane yield. Two hundred and eighty-five F₁ progenies from the cross YT93-159 × ROC22 with significantly different chlorophyll contents were included as test materials. The chlorophyll content of the +1 leaves during elongation phase was measured using a SPAD-502 meter through a three-crop cycle (plant cane, first ratoon, and second ratoon). Linkage analysis was conducted on a high-density genetic map constructed based on the sugarcane 100K SNP chip. In addition, Fv/Fm, plant height, stalk diameter, brix data were collected on plant cane during the elongation and maturation phases. The results showed that the +1 leaf SPAD values, which can be used as an important reference to evaluate the growth potential of sugarcane, were significantly and positively correlated with the Fv/Fm during elongation phase, as well as with plant height, stalk diameter, and brix during maturity phase (P < 0.01). The broad sense heritability (H ²) of the chlorophyll content trait was 0.66 for plant cane crop, 0.67 for first ratoon crop, and 0.73 for second ratoon crop, respectively, indicating that this trait was mainly controlled by genetic factors. Thirty-one quantitative trait loci (QTL) were detected by QTL mapping. Among them, a major QTL, qCC-R1, could account for 12.95% of phenotypic variation explained (PVE), and the other 30 minor QTLs explained 2.37-7.99% PVE. Twenty candidate genes related to chlorophyll content were identified in the QTLs plus a 200-Kb extension region within either sides, of which four were homologous genes involved in the chlorophyll synthesis process and the remaining 16 played a certain role in chlorophyll catabolic pathway, chloroplast organization, or photosynthesis. These results provide a theoretical reference for analyzing the genetic mechanism of chlorophyll synthesis and subsequent improvement of photosynthetic characteristics in sugarcane.

Shape, firmness and fruit quality QTLs shared in two non-related strawberry populations

The cultivated strawberry (Fragaria x ananassa) is an octoploid species (2n = 8x = 56), appreciated widely for its fruit. There have been very few studies on fruit quality traits, which are known to be mostly polygenic and environmentally dependent. To identify higher genetic variability, two non-related populations were genotyped: an F1 population cross between 'FC50' and 'FD54' and an F2 population cross between 'Camarosa' and 'Dover', hybridizing both with IStraw35k and IStraw90k SNP arrays, respectively. The F1 genetic map was constructed with 14595 SNPs and the F2 map with 7977 SNPs. High collinearity was observed when comparing one genetic map with the other and on comparing both with the octoploid genome. To assess fruit variability, both populations were phenotyped for shape, firmness, taste and other fruit traits over the 2016-2019 period. With QTL analyses, 33 stable QTLs were mapped in the 'FC50xFD54' population, and three hotspot regions were found for shape traits in LG3A, LG4D and LG6D. In the '21AF' population, only eight stable QTLs were detected. Despite that, two major and stable QTLs were mapped in the same interval of confidence for both populations. A shared fruit shape ratio QTL which explained around 25 % of trait variance was mapped in LG3A, and a shared firmness QTL explaining 26.9 % of trait variance in LG7C. For the first time, two QTLs were discovered in LG3A and LG4A for a phenotype neck without achenes. When analysing two different mapping populations, in addition to finding specific QTL regions for the studied traits, a narrowing down of the interval of confidence for the shared QTLs is achieved. As a result of this study, a new set of SNPs for fruit firmness and shape is now available for use in MAS in strawberry breeding programs.

Fur colour in the Arctic fox: genetic architecture and consequences for fitness

Genome-wide association studies provide good opportunities for studying the genetic basis of adaptive traits in wild populations. Yet, previous studies often failed to identify major effect genes. In this study, we used high-density single nucleotide polymorphism and individual fitness data from a wild non-model species. Using a whole-genome approach, we identified the MC1R gene as the sole causal gene underlying Arctic fox Vulpes lagopus fur colour. Further, we showed the adaptive importance of fur colour genotypes through measures of fitness that link ecological and evolutionary processes. We found a tendency for blue foxes that are heterozygous at the fur colour locus to have higher fitness than homozygous white foxes. The effect of genotype on fitness was independent of winter duration but varied with prey availability, with the strongest effect in years of increasing rodent populations. MC1R is located in a genomic region with high gene density, and we discuss the potential for indirect selection through linkage and pleiotropy. Our study shows that whole-genome analyses can be successfully applied to wild species and identify major effect genes underlying adaptive traits. Furthermore, we show how this approach can be used to identify knowledge gaps in our understanding of interactions between ecology and evolution.

Comparative Transcriptome Analysis to Identify Candidate Genes for FaRCg1 Conferring Resistance Against Colletotrichum gloeosporioides in Cultivated Strawberry (Fragaria × ananassa)

Colletotrichum crown rot (CCR) caused by Colletotrichum gloeosporioides is a serious threat to the cultivated strawberry (Fragaria × ananassa). Our previous study reported that a major locus, FaRCg1, increases resistance. However, the genomic structure of FaRCg1 and potential candidate genes associated with the resistance remained unknown. Here, we performed comparative transcriptome analyses of resistant 'Florida Elyana' and susceptible 'Strawberry Festival' after infection and identified candidate genes potentially involved in resistance. In 'Florida Elyana', 6,099 genes were differentially expressed in response to C. gloeosporioides. Gene ontology analysis showed that the most upregulated genes were functionally associated with signaling pathways of plant defense responses. Three genes in the genomic region of FaRCg1 were highly upregulated: a von Willebrand Factor A domain-containing protein, a subtilisin-like protease, and a TIFY 11A-like protein. Subgenome-specific markers developed for the candidate genes were tested with a diverse panel of 219 accessions from University of Florida and North Carolina State University breeding programs. Significant and positive associations were found between the high-resolution melting (HRM) marker genotypes and CCR phenotypes. These newly developed subgenome-specific functional markers for FaRCg1 can facilitate development of resistant varieties through marker-assisted selection.

Unraveling the Complex Hybrid Ancestry and Domestication History of Cultivated Strawberry

Cultivated strawberry (Fragaria × ananassa) is one of our youngest domesticates, originating in early eighteenth-century Europe from spontaneous hybrids between wild allo-octoploid species (Fragaria chiloensis and Fragaria virginiana). The improvement of horticultural traits by 300 years of breeding has enabled the global expansion of strawberry production. Here, we describe the genomic history of strawberry domestication from the earliest hybrids to modern cultivars. We observed a significant increase in heterozygosity among interspecific hybrids and a decrease in heterozygosity among domesticated descendants of those hybrids. Selective sweeps were found across the genome in early and modern phases of domestication—59–76% of the selectively swept genes originated in the three less dominant ancestral subgenomes. Contrary to the tenet that genetic diversity is limited in cultivated strawberry, we found that the octoploid species harbor massive allelic diversity and that F. × ananassa harbors as much allelic diversity as either wild founder. We identified 41.8 M subgenome-specific DNA variants among resequenced wild and domesticated individuals. Strikingly, 98% of common alleles and 73% of total alleles were shared between wild and domesticated populations. Moreover, genome-wide estimates of nucleotide diversity were virtually identical in F. chiloensis,F. virginiana, and F. × ananassa (π = 0.0059–0.0060). We found, however, that nucleotide diversity and heterozygosity were significantly lower in modern F. × ananassa populations that have experienced significant genetic gains and have produced numerous agriculturally important cultivars.

Social network analysis of the genealogy of strawberry: retracing the wild roots of heirloom and modern cultivars

The widely recounted story of the origin of cultivated strawberry (Fragaria × ananassa) oversimplifies the complex interspecific hybrid ancestry of the highly admixed populations from which heirloom and modern cultivars have emerged. To develop deeper insights into the three-century-long domestication history of strawberry, we reconstructed the genealogy as deeply as possible—pedigree records were assembled for 8,851 individuals, including 2,656 cultivars developed since 1775. The parents of individuals with unverified or missing pedigree records were accurately identified by applying an exclusion analysis to array-genotyped single-nucleotide polymorphisms. We identified 187 wild octoploid and 1,171 F. × ananassa founders in the genealogy, from the earliest hybrids to modern cultivars. The pedigree networks for cultivated strawberry are exceedingly complex labyrinths of ancestral interconnections formed by diverse hybrid ancestry, directional selection, migration, admixture, bottlenecks, overlapping generations, and recurrent hybridization with common ancestors that have unequally contributed allelic diversity to heirloom and modern cultivars. Fifteen to 333 ancestors were predicted to have transmitted 90% of the alleles found in country-, region-, and continent-specific populations. Using parent–offspring edges in the global pedigree network, we found that selection cycle lengths over the past 200 years of breeding have been extraordinarily long (16.0-16.9 years/generation), but decreased to a present-day range of 6.0-10.0 years/generation. Our analyses uncovered conspicuous differences in the ancestry and structure of North American and European populations, and shed light on forces that have shaped phenotypic diversity in F. × ananassa.

Genetic Analysis of Methyl Anthranilate, Mesifurane, Linalool, and Other Flavor Compounds in Cultivated Strawberry (Fragaria × ananassa)

The cultivated strawberry (Fragaria × ananassa) is an economically important fruit crop that is intensively bred for improved sensory qualities. The diversity of fruit flavors and aromas in strawberry results mainly from the interactions of sugars, acids, and volatile organic compounds (VOCs) that are derived from diverse biochemical pathways influenced by the expression of many genes. This study integrates multiomic analyses to identify QTL and candidate genes for multiple aroma compounds in a complex strawberry breeding population. Novel fruit volatile QTL was discovered for methyl anthranilate, methyl 2-hexenoate, methyl 2-methylbutyrate, mesifurane, and a shared QTL on Chr 3 was found for nine monoterpene and sesquiterpene compounds, including linalool, 3-carene, β-phellandrene, α-limonene, linalool oxide, nerolidol, α-caryophellene, α-farnesene, and β-farnesene. Fruit transcriptomes from a subset of 64 individuals were used to support candidate gene identification. For methyl esters including the grape-like methyl anthranilate, a novel ANTHANILIC ACID METHYL TRANSFERASE-like gene was identified. Two mesifurane QTL correspond with the known biosynthesis gene O-METHYL TRANSFERASE 1 and a novel FURANEOL GLUCOSYLTRANSFERASE. The shared terpene QTL contains multiple fruit-expressed terpenoid pathway-related genes including NEROLIDOL SYNTHASE 1 (FanNES1). The abundance of linalool and other monoterpenes is partially governed by a co-segregating expression-QTL (eQTL) for FanNES1 transcript variation, and there is additional evidence for quantitative effects from other terpenoid-pathway genes in this narrow genomic region. These QTLs present new opportunities in breeding for improved flavor in commercial strawberry.

Genetic Analysis of Methyl Anthranilate, Mesifurane, Linalool, and Other Flavor Compounds in Cultivated Strawberry (Fragaria × ananassa)

The cultivated strawberry (Fragaria × ananassa) is an economically important fruit crop that is intensively bred for improved sensory qualities. The diversity of fruit flavors and aromas in strawberry results mainly from the interactions of sugars, acids, and volatile organic compounds (VOCs) that are derived from diverse biochemical pathways influenced by the expression of many genes. This study integrates multiomic analyses to identify QTL and candidate genes for multiple aroma compounds in a complex strawberry breeding population. Novel fruit volatile QTL was discovered for methyl anthranilate, methyl 2-hexenoate, methyl 2-methylbutyrate, mesifurane, and a shared QTL on Chr 3 was found for nine monoterpene and sesquiterpene compounds, including linalool, 3-carene, β-phellandrene, α-limonene, linalool oxide, nerolidol, α-caryophellene, α-farnesene, and β-farnesene. Fruit transcriptomes from a subset of 64 individuals were used to support candidate gene identification. For methyl esters including the grape-like methyl anthranilate, a novel ANTHANILIC ACID METHYL TRANSFERASE-like gene was identified. Two mesifurane QTL correspond with the known biosynthesis gene O-METHYL TRANSFERASE 1 and a novel FURANEOL GLUCOSYLTRANSFERASE. The shared terpene QTL contains multiple fruit-expressed terpenoid pathway-related genes including NEROLIDOL SYNTHASE 1 (FanNES1). The abundance of linalool and other monoterpenes is partially governed by a co-segregating expression-QTL (eQTL) for FanNES1 transcript variation, and there is additional evidence for quantitative effects from other terpenoid-pathway genes in this narrow genomic region. These QTLs present new opportunities in breeding for improved flavor in commercial strawberry.

Genomic Characterization of the Fruity Aroma Gene, FaFAD1, Reveals a Gene Dosage Effect on γ-Decalactone Production in Strawberry (Fragaria × ananassa)

Strawberries produce numerous volatile compounds that contribute to the unique flavors of fruits. Among the many volatiles, γ-decalactone (γ-D) has the greatest contribution to the characteristic fruity aroma in strawberry fruit. The presence or absence of γ-D is controlled by a single locus, FaFAD1. However, this locus has not yet been systematically characterized in the octoploid strawberry genome. It has also been reported that the volatile content greatly varies among the strawberry varieties possessing FaFAD1, suggesting that another genetic factor could be responsible for the different levels of γ-D in fruit. In this study, we explored the genomic structure of FaFAD1 and determined the allele dosage of FaFAD1 that regulates variations of γ-D production in cultivated octoploid strawberry. The genome-wide association studies confirmed the major locus FaFAD1 that regulates the γ-D production in cultivated strawberry. With the hybrid capture-based next-generation sequencing analysis, a major presence-absence variation of FaFAD1 was discovered among γ-D producers and non-producers. To explore the genomic structure of FaFAD1 in the octoploid strawberry, three bacterial artificial chromosome (BAC) libraries were developed. A deletion of 8,262 bp was consistently found in the FaFAD1 region of γ-D non-producing varieties. With the newly developed InDel-based codominant marker genotyping, along with γ-D metabolite profiling data, we revealed the impact of gene dosage effect for the production of γ-D in the octoploid strawberry varieties. Altogether, this study provides systematic information of the prominent role of FaFAD1 presence and absence polymorphism in producing γ-D and proposes that both alleles of FaFAD1 are required to produce the highest content of fruity aroma in strawberry fruit.

Integration of Infinium and Axiom SNP array data in the outcrossing species Malus × domestica and causes for seemingly incompatible calls

Background

Single nucleotide polymorphism (SNP) array technology has been increasingly used to generate large quantities of SNP data for use in genetic studies. As new arrays are developed to take advantage of new technology and of improved probe design using new genome sequence and panel data, a need to integrate data from different arrays and array platforms has arisen. This study was undertaken in view of our need for an integrated high-quality dataset of Illumina Infinium® 20 K and Affymetrix Axiom® 480 K SNP array data in apple (Malus × domestica). In this study, we qualify and quantify the compatibility of SNP calling, defined as SNP calls that are both accurate and concordant, across both arrays by two approaches. First, the concordance of SNP calls was evaluated using a set of 417 duplicate individuals genotyped on both arrays starting from a set of 10,295 robust SNPs on the Infinium array. Next, the accuracy of the SNP calls was evaluated on additional germplasm (n = 3141) from both arrays using Mendelian inconsistent and consistent errors across thousands of pedigree links. While performing this work, we took the opportunity to evaluate reasons for probe failure and observed discordant SNP calls.

Results

Concordance among the duplicate individuals was on average of 97.1% across 10,295 SNPs. Of these SNPs, 35% had discordant call(s) that were further curated, leading to a final set of 8412 (81.7%) SNPs that were deemed compatible. Compatibility was highly influenced by the presence of alternate probe binding locations and secondary polymorphisms. The impact of the latter was highly influenced by their number and proximity to the 3′ end of the probe.

Conclusions

The Infinium and Axiom SNP array data were mostly compatible. However, data integration required intense data filtering and curation. This work resulted in a workflow and information that may be of use in other data integration efforts. Such an in-depth analysis of array concordance and accuracy as ours has not been previously described in the literature and will be useful in future work on SNP array data integration and interpretation, and in probe/platform development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07565-7.

Strawberry fruit shape: quantification by image analysis and QTL detection by genome-wide association analysis

Fruit shape of cultivated strawberry (Fragaria × ananassa Duch.) is an important breeding target. To detect genomic regions associated with this trait, its quantitative evaluation is needed. Previously we created a multi-parent advanced-generation inter-cross (MAGIC) strawberry population derived from six founder parents. In this study, we used this population to quantify fruit shape. Elliptic Fourier descriptors (EFDs) were generated from 2 969 two-dimensional binarized fruit images, and principal component (PC) scores were calculated on the basis of the EFD coefficients. PC1-PC3 explained 96% of variation in shape and thus adequately quantified it. In genome-wide association study, the PC scores were used as phenotypes. Genome wide association study using mixed linear models revealed 2 quantitative trait loci (QTLs) for fruit shape. Our results provide a novel and effective method to analyze strawberry fruit morphology; the detected QTLs and presented method can support marker-assisted selection in practical breeding programs to improve fruit shape.

Discovery of three loci increasing resistance to charcoal rot caused by Macrophomina phaseolina in octoploid strawberry

Charcoal rot caused by Macrophomina phaseolinais an increasing economic problem in annualized strawberry production systems around the world. Currently there are no effective postfumigation chemical controls for managing charcoal rot, and no information is available on the genetic architecture of resistance to M. phaseolina in strawberry (Fragaria ×ananassa). In this study, three multiparental discovery populations and two validation populations were inoculated at planting and evaluated for mortality in three consecutive growing seasons. Genome-wide SNP genotyping and pedigree-based analysis with FlexQTL™ software were performed. Two large-effect quantitative trait loci (QTL) increasing charcoal rot resistance were discovered and validated in cultivated germplasm. FaRMp1 was located on linkage group 2A in the interval 20.4to 24.9 cM, while FaRMp2 was located on linkage group 4B in the interval 41.1to 61.2 cM. Together these QTLs explained 27% and 17% of the phenotypic variance in two discovery populations consisting of elite breeding germplasm. For both QTLs, the resistant allele showed some evidence of partial dominance, but no significant interaction was detected between the two loci. As the dosage of resistant alleles increased from 0 to 4 across the two QTLs, mortality decreased regardless of the combination of alleles.A third locus, FaRMp3 on 4D, was discovered in FVC 11-58, a reconstituted F.×ananassa originating from diverse F. virginiana and F. chiloensis accessions. This locus accounted for 44% of phenotypic variation in four segregating crosses. These findings will form the basis for DNA-informed breeding for resistance to charcoal rot in cultivated strawberry.

Genomic Selection for F1 Hybrid Breeding in Strawberry (Fragaria × ananassa)

Cultivated strawberry is the most widely consumed fruit crop in the world, and therefore, many breeding programs are underway to improve its agronomic traits such as fruit quality. Strawberry cultivars were vegetatively propagated through runners and carried a high risk of infection with viruses and insects. To solve this problem, the development of F₁ hybrid seeds has been proposed as an alternative breeding strategy in strawberry. In this study, we conducted a potential assessment of genomic selection (GS) in strawberry F₁ hybrid breeding. A total of 105 inbred lines were developed as candidate parents of strawberry F₁ hybrids. In addition, 275 parental combinations were randomly selected from the 105 inbred lines and crossed to develop test F₁ hybrids for GS model training. These populations were phenotyped for petiole length, leaf area, Brix, fruit hardness, and pericarp color. Whole-genome shotgun sequencing of the 105 inbred lines detected 20,811 single nucleotide polymorphism sites that were provided for subsequent GS analyses. In a GS model construction, inclusion of dominant effects showed a slight advantage in GS accuracy. In the across population prediction analysis, GS models using the inbred lines showed predictability for the test F₁ hybrids and vice versa, except for Brix. Finally, the GS models were used for phenotype prediction of 5,460 possible F₁ hybrids from 105 inbred lines to select F₁ hybrids with high fruit hardness or high pericarp color. These F₁ hybrids were developed and phenotyped to evaluate the efficacy of the GS. As expected, F₁ hybrids that were predicted to have high fruit hardness or high pericarp color expressed higher observed phenotypic values than the F₁ hybrids that were selected for other objectives. Through the analyses in this study, we demonstrated that GS can be applied for strawberry F₁ hybrid breeding.

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.

Independent Validation of Genomic Prediction in Strawberry Over Multiple Cycles

The University of Florida strawberry (Fragaria × ananassa) breeding program has implemented genomic prediction (GP) as a tool for choosing outstanding parents for crosses over the last five seasons. This has allowed the use of some parents 1 year earlier than with traditional methods, thus reducing the duration of the breeding cycle. However, as the number of breeding cycles increases over time, greater knowledge is needed on how multiple cycles can be used in the practical implementation of GP in strawberry breeding. Advanced selections and cultivars totaling 1,558 unique individuals were tested in field trials for yield and fruit quality traits over five consecutive years and genotyped for 9,908 SNP markers. Prediction of breeding values was carried out using Bayes B models. Independent validation was carried out using separate trials/years as training (TRN) and testing (TST) populations. Single-trial predictive abilities for five polygenic traits averaged 0.35, which was reduced to 0.24 when individuals common across trials were excluded, emphasizing the importance of relatedness among training and testing populations. Training populations including up to four previous breeding cycles increased predictive abilities, likely due to increases in both training population size and relatedness. Predictive ability was also strongly influenced by heritability, but less so by changes in linkage disequilibrium and effective population size. Genotype by year interactions were minimal. A strategy for practical implementation of GP in strawberry breeding is outlined that uses multiple cycles to predict parental performance and accounts for traits not included in GP models when constructing crosses. Given the importance of relatedness to the success of GP in strawberry, future work could focus on the optimization of relatedness in the design of TRN and TST populations to increase predictive ability in the short-term without compromising long-term genetic gains.

Chromosome Level Assembly of Homozygous Inbred Line 'Wongyo 3115' Facilitates the Construction of a High-Density Linkage Map and Identification of QTLs Associated With Fruit Firmness in Octoploid Strawberry (Fragaria × ananassa)

Strawberry is an allo-octoploid crop with high genome heterozygosity and complexity, which hinders the sequencing and the assembly of the genome. However, in the present study, we have generated a chromosome level assembly of octoploid strawberry sourced from a highly homozygous inbred line 'Wongyo 3115', using long- and short-read sequencing technologies. The assembly of 'Wongyo 3115' produced 805.6 Mb of the genome with 323 contigs scaffolded into 208 scaffolds with an N50 of 27.3 Mb after further gap filling. The whole genome annotation resulted in 151,892 genes with a gene density of 188.52 (genes/Mb) and validation of a genome, using BUSCO analysis resulted in 94.10% complete BUSCOs. Firmness is one of the vital traits in strawberry, which facilitate the postharvest shelf-life qualities. The molecular and genetic mechanisms that contribute the firmness in strawberry remain unclear. We have constructed a high-density genetic map based on the 'Wongyo 3115' reference genome to identify loci associated with firmness in the present study. For the quantitative trait locus (QTL) identification, the 'BS F₂' populations developed from two inbred lines were genotyped, using an Axiom 35K strawberry chip, and marker positions were analyzed based on the 'Wongyo 3115' genome. Genetic maps were constructed with 1,049 bin markers, spanning the 3,861 cM. Using firmness data of 'BS F₂' obtained from 2 consecutive years, five QTLs were identified on chromosomes 3-3, 5-1, 6-1, and 6-4. Furthermore, we predicted the candidate genes associated with firmness in strawberries by utilizing transcriptome data and QTL information. Overall, we present the chromosome-level assembly and annotation of a homozygous octoploid strawberry inbred line and a linkage map constructed to identify QTLs associated with fruit firmness.

Genomic Informed Breeding Strategies for Strawberry Yield and Fruit Quality Traits

Over the last two centuries, breeders have drastically modified the fruit quality of strawberries through artificial selection. However, there remains significant variation in quality across germplasm with scope for further improvements to be made. We reported extensive phenotyping of fruit quality and yield traits in a multi-parental strawberry population to allow genomic prediction and quantitative trait nucleotide (QTN) identification, thereby enabling the description of genetic architecture to inform the efficacy of implementing advanced breeding strategies. A negative relationship (r = -0.21) between total soluble sugar content and class one yield was identified, indicating a trade-off between these two essential traits. This result highlighted an established dilemma for strawberry breeders and a need to uncouple the relationship, particularly under June-bearing, protected production systems comparable to this study. A large effect of quantitative trait nucleotide was associated with perceived acidity and pH whereas multiple loci were associated with firmness. Therefore, we recommended the implementation of both marker assisted selection (MAS) and genomic prediction to capture the observed variation respectively. Furthermore, we identified a large effect locus associated with a 10% increase in the number of class one fruit and a further 10 QTN which, when combined, are associated with a 27% increase in the number of marketable strawberries. Ultimately, our results suggested that the best method to improve strawberry yield is through selecting parental lines based upon the number of marketable fruits produced per plant. Not only were strawberry number metrics less influenced by environmental fluctuations, but they had a larger additive genetic component when compared with mass traits. As such, selecting using "number" traits should lead to faster genetic gain.

Development of a highly efficient 50K single nucleotide polymorphism genotyping array for the large and complex genome of Norway spruce (Picea abies L. Karst) by whole genome resequencing and its transferability to other spruce species

Norway spruce (Picea abies L. Karst) is one of the most important forest tree species with significant economic and ecological impact in Europe. For decades, genomic and genetic studies on Norway spruce have been challenging due to the large and repetitive genome (19.6 Gb with more than 70% being repetitive). To accelerate genomic studies, including population genetics, genome‐wide association studies (GWAS) and genomic selection (GS), in Norway spruce and related species, we here report on the design and performance of a 50K single nucleotide polymorphism (SNP) genotyping array for Norway spruce. The array is developed based on whole genome resequencing (WGS), making it the first WGS‐based SNP array in any conifer species so far. After identifying SNPs using genome resequencing data from 29 trees collected in northern Europe, we adopted a two‐step approach to design the array. First, we built a 450K screening array and used this to genotype a population of 480 trees sampled from both natural and breeding populations across the Norway spruce distribution range. These samples were then used to select high‐confidence probes that were put on the final 50K array. The SNPs selected are distributed over 45,552 scaffolds from the P. abies version 1.0 genome assembly and target 19,954 unique gene models with an even coverage of the 12 linkage groups in Norway spruce. We show that the array has a 99.5% probe specificity, >98% Mendelian allelic inheritance concordance, an average sample call rate of 96.30% and an SNP call rate of 98.90% in family trios and haploid tissues. We also observed that 23,797 probes (50%) could be identified with high confidence in three other spruce species (white spruce [Picea glauca], black spruce [P. mariana] and Sitka spruce [P. sitchensis]). The high‐quality genotyping array will be a valuable resource for genetic and genomic studies in Norway spruce as well as in other conifer species of the same genus.

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.

ddRAD-seq derived genome-wide SNPs, high density linkage map and QTLs for fruit quality traits in strawberry (Fragaria x ananassa)

Understanding the genetic determinants are essential for improving the fruit quality traits of strawberry. In this study, we focused on mapping the loci for fruit-length (FL), -diameter (FD), -weight (FW) and -soluble solid content (SSC) using the genome-wide single nucleotide polymorphisms (SNPs) identified via ddRAD-sequencing of the F₁ population raised from Maehyang (♀) X Festival (♂). A total of 12,698 high quality SNPs were identified of which 1554 SNPs that showed significant Mendelian segregation (p < 0.05) were mapped to 53 linkage groups (LG) spanning a total of 2937.93 cM with an average marker density of 2.14 cM/locus. Six QTLs for FL and four QTLs for each of FD, FW and SSC were identified that explained 24–35%, 21–42%, 24–54% and 23–50% of overall phenotypic variations, respectively. The genes that lie within these QTL regions were extracted and discussed thoroughly. In addition, a high resolution melting marker (MF154) were designed based on the SNP A1⁷²³G of the UDP-glucose 4-epimerase GEPI48-like gene FAN_iscf00021287. The marker detected the high vs low sugar containing F₁ plants and commercial cultivars with 81.39% and 86.95% detection accuracy, respectively. These SNPs, linkage map, QTLs and candidate genes will be helpful in understanding and improving the fruit quality traits of strawberry.

Metabolite Quantitative Trait Loci for Flavonoids Provide New Insights into the Genetic Architecture of Strawberry (Fragaria × ananassa) Fruit Quality

Flavonoids are products from specialized metabolism that contribute to fruit sensorial (color) and nutritional (antioxidant properties) quality. Here, using a pseudo full-sibling F₁ progeny previously studied for fruit sensorial quality of cultivated strawberry (Fragaria × ananassa), we explored over two successive years the genetic architecture of flavonoid-related traits using liquid chromatography electrospray ionization tandem mass spectrometry (13 compounds including anthocyanins, flavonols, and flavan-3-ols) and colorimetric assays (anthocyanins, flavonoids, phenolics, and total antioxidant capacity (ferric reducing antioxidant power and Trolox equivalent antioxidant capacity)). Network correlation analysis highlighted the high connectivity of flavonoid compounds within each chemical class and low correlation with colorimetric traits except for anthocyanins. Mapping onto the female and male linkage maps of 152 flavonoid metabolic quantitative trait loci (mQTLs) and of 26 colorimetric QTLs indicated colocalization on few linkage groups of major flavonoid- and taste-related QTLs previously uncovered. These results pave the way for the discovery of genetic variations underlying flavonoid mQTLs and for marker-assisted selection of strawberry varieties with improved sensorial and nutritional quality.

Role of NGS and SNP genotyping methods in sugarcane improvement programs

Sugarcane (Saccharum spp.) is one of the most economically significant crops because of its high sucrose content and it is a promising biomass feedstock for biofuel production. Sugarcane genome sequencing and analysis is a difficult task due to its heterozygosity and polyploidy. Long sequence read technologies, PacBio Single-Molecule Real-Time (SMRT) sequencing, the Illumina TruSeq, and the Oxford Nanopore sequencing could solve the problem of genome assembly. On the applications side, next generation sequencing (NGS) technologies played a major role in the discovery of single nucleotide polymorphism (SNP) and the development of low to high throughput genotyping platforms. The two mainstream high throughput genotyping platforms are the SNP microarray and genotyping by sequencing (GBS). This paper reviews the NGS in sugarcane genomics, genotyping methodologies, and the choice of these methods. Array-based SNP genotyping is robust, provides consistent SNPs, and relatively easier downstream data analysis. The GBS method identifies large scale SNPs across the germplasm. A combination of targeted GBS and array-based genotyping methods should be used to increase the accuracy of genomic selection and marker-assisted breeding.

A pentaploid-based linkage map of the ancestral octoploid strawberry Fragaria virginiana reveals instances of sporadic hyper-recombination

The first high-resolution genetic linkage map of the ancestral octoploid (2n = 8x = 56) strawberry species, Fragaria virginiana, was constructed using segregation data obtained from a pentaploid progeny population. This novel mapping population of size 178 was generated by crossing highly heterozygous F. virginiana hybrid "LB48" as a paternal parent with diploid (2n = 2x = 14) Fragaria vesca "Hawaii 4". The LB48 linkage map comprises 6055 markers genotyped on the Axiom® IStraw90 strawberry SNP array. The map consists of 28 linkage groups (LGs) organized into seven homoeology groups of four LGs each, and excludes a small 29th LG of undefined homoeology. One member of each homoeology group was assignable to an "A" subgenome associated with ancestral diploid Fragaria vesca, while no other subgenomes were defined. Despite an intriguing discrepancy within homoeology group VI, synteny comparisons with the previously published Fragaria ×ananassa DA × MO linkage map revealed substantial agreement. Following initial map construction, examination of crossover distributions revealed that six of the total 5162 (=29 chromosomes/individual × 178 individuals) chromosomes making up the data set exhibited abnormally high crossover counts, ranging from 15 to 48 crossovers per chromosome, as compared with the overall mean of 0.66 crossovers per chromosome. Each of these six hyper-recombinant (HypR) chromosomes occurred in a different LG and in a different individual. When calculated upon exclusion of the six HypR chromosomes, the canonical (i.e., broadly representative) LB48 map had 1851 loci distributed over a total map length of 1873 cM, while their inclusion increased the number of loci by 130, and the overall map length by 91 cM. Discovery of these hyper-recombinant chromosomes points to the existence of a sporadically acting mechanism that, if identified and manipulable, could be usefully harnessed for multiple purposes by geneticists and breeders.

A roadmap for research in octoploid strawberry

The cultivated strawberry (Fragaria × ananassa) is an allo-octoploid species, originating nearly 300 years ago from wild progenitors from the Americas. Since that time the strawberry has become the most widely cultivated fruit crop in the world, universally appealing due to its sensory qualities and health benefits. The recent publication of the first high-quality chromosome-scale octoploid strawberry genome (cv. Camarosa) is enabling rapid advances in genetics, stimulating scientific debate and provoking new research questions. In this forward-looking review we propose avenues of research toward new biological insights and applications to agriculture. Among these are the origins of the genome, characterization of genetic variants, and big data approaches to breeding. Key areas of research in molecular biology will include the control of flowering, fruit development, fruit quality, and plant-pathogen interactions. In order to realize this potential as a global community, investments in genome resources must be continually augmented.

Genome Synteny Has Been Conserved Among the Octoploid Progenitors of Cultivated Strawberry Over Millions of Years of Evolution

Allo-octoploid cultivated strawberry (Fragaria × ananassa) originated through a combination of polyploid and homoploid hybridization, domestication of an interspecific hybrid lineage, and continued admixture of wild species over the last 300 years. While genes appear to flow freely between the octoploid progenitors, the genome structures and diversity of the octoploid species remain poorly understood. The complexity and absence of an octoploid genome frustrated early efforts to study chromosome evolution, resolve subgenomic structure, and develop a single coherent linkage group nomenclature. Here, we show that octoploid Fragaria species harbor millions of subgenome-specific DNA variants. Their diversity was sufficient to distinguish duplicated (homoeologous and paralogous) DNA sequences and develop 50K and 850K SNP genotyping arrays populated with co-dominant, disomic SNP markers distributed throughout the octoploid genome. Whole-genome shotgun genotyping of an interspecific segregating population yielded 1.9M genetically mapped subgenome variants in 5,521 haploblocks spanning 3,394 cM in F. chiloensis subsp. lucida, and 1.6M genetically mapped subgenome variants in 3,179 haploblocks spanning 2,017 cM in F. × ananassa. These studies provide a dense genomic framework of subgenome-specific DNA markers for seamlessly cross-referencing genetic and physical mapping information and unifying existing chromosome nomenclatures. Using comparative genomics, we show that geographically diverse wild octoploids are effectively diploidized, nearly completely collinear, and retain strong macro-synteny with diploid progenitor species. The preservation of genome structure among allo-octoploid taxa is a critical factor in the unique history of garden strawberry, where unimpeded gene flow supported its origin and domestication through repeated cycles of interspecific hybridization.

Exploring Deep Learning for Complex Trait Genomic Prediction in Polyploid Outcrossing Species

Genomic prediction (GP) is the procedure whereby the genetic merits of untested candidates are predicted using genome wide marker information. Although numerous examples of GP exist in plants and animals, applications to polyploid organisms are still scarce, partly due to limited genome resources and the complexity of this system. Deep learning (DL) techniques comprise a heterogeneous collection of machine learning algorithms that have excelled at many prediction tasks. A potential advantage of DL for GP over standard linear model methods is that DL can potentially take into account all genetic interactions, including dominance and epistasis, which are expected to be of special relevance in most polyploids. In this study, we evaluated the predictive accuracy of linear and DL techniques in two important small fruits or berries: strawberry and blueberry. The two datasets contained a total of 1,358 allopolyploid strawberry (2n=8x=112) and 1,802 autopolyploid blueberry (2n=4x=48) individuals, genotyped for 9,908 and 73,045 single nucleotide polymorphism (SNP) markers, respectively, and phenotyped for five agronomic traits each. DL depends on numerous parameters that influence performance and optimizing hyperparameter values can be a critical step. Here we show that interactions between hyperparameter combinations should be expected and that the number of convolutional filters and regularization in the first layers can have an important effect on model performance. In terms of genomic prediction, we did not find an advantage of DL over linear model methods, except when the epistasis component was important. Linear Bayesian models were better than convolutional neural networks for the full additive architecture, whereas the opposite was observed under strong epistasis. However, by using a parameterization capable of taking into account these non-linear effects, Bayesian linear models can match or exceed the predictive accuracy of DL. A semiautomatic implementation of the DL pipeline is available at https://github.com/lauzingaretti/deepGP/.