High-throughput genotyping for species identification and diversity assessment in germplasm collections

Genetic Diversity and Population Structure of a Large USDA Sesame Collection

Sesame, Sesamum indicum L., is one of the oldest domesticated crops used for its oil and protein in many parts of the world. To build genomic resources for sesame that could be used to improve sesame productivity and responses to stresses, a USDA sesame germplasm collection of 501 accessions originating from 36 countries was used in this study. The panel was genotyped using genotyping-by-sequencing (GBS) technology to explore its genetic diversity and population structure and the relatedness among its accessions. A total of 24,735 high-quality single-nucleotide polymorphism (SNP) markers were identified over the 13 chromosomes. The marker density was 1900 SNP per chromosome, with an average polymorphism information content (PIC) value of 0.267. The marker polymorphisms and heterozygosity estimators indicated the usefulness of the identified SNPs to be used in future genetic studies and breeding activities. The population structure, principal components analysis (PCA), and unrooted neighbor-joining phylogenetic tree analyses classified two distinct subpopulations, indicating a wide genetic diversity within the USDA sesame collection. Analysis of molecular variance (AMOVA) revealed that 29.5% of the variation in this population was due to subpopulations, while 57.5% of the variation was due to variation among the accessions within the subpopulations. These results showed the degree of differentiation between the two subpopulations as well as within each subpopulation. The high fixation index (FST) between the distinguished subpopulations indicates a wide genetic diversity and high genetic differentiation among and within the identified subpopulations. The linkage disequilibrium (LD) pattern averaged 161 Kbp for the whole sesame genome, while the LD decay ranged from 168 Kbp at chromosome LG09 to 123 Kbp in chromosome LG05. These findings could explain the complications of linkage drag among the traits during selections. The selected accessions and genotyped SNPs provide tools to enhance genetic gain in sesame breeding programs through molecular approaches.

Genome composition in Brassica interspecific hybrids affects chromosome inheritance and viability of progeny

Interspecific hybridization is widespread in nature and can result in the formation of new hybrid species as well as the transfer of traits between species. However, the fate of newly formed hybrid lineages is relatively understudied. We undertook pairwise crossing between multiple genotypes of three Brassica allotetraploid species Brassica juncea (2n = AABB), Brassica carinata (2n = BBCC), and Brassica napus (2n = AACC) to generate AABC, BBAC, and CCAB interspecific hybrids and investigated chromosome inheritance and fertility in these hybrids and their self-pollinated progeny. Surprisingly, despite the presence of a complete diploid genome in all hybrids, hybrid fertility was very low. AABC and BBAC first generation (F1) hybrids both averaged ~16% pollen viability compared to 3.5% in CCAB hybrids: most CCAB hybrid flowers were male-sterile. AABC and CCAB F1 hybrid plants averaged 5.5 and 0.5 seeds per plant, respectively, and BBAC F1 hybrids ~56 seeds/plant. In the second generation (S1), all confirmed self-pollinated progeny resulting from CCAB hybrids were sterile, producing no self-pollinated seeds. Three AABC S1 hybrids putatively resulting from unreduced gametes produced 3, 14, and 182 seeds each, while other AABC S1 hybrids averaged 1.5 seeds/plant (0-8). BBAC S1 hybrids averaged 44 seeds/plant (range 0-403). We also observed strong bias towards retention rather than loss of the haploid genomes, suggesting that the subgenomes in the Brassica allotetraploids are already highly interdependent, such that loss of one subgenome is detrimental to fertility and viability. Our results suggest that relationships between subgenomes determine hybridization outcomes in these species.

Genetic factors inherited from both diploid parents interact to affect genome stability and fertility in resynthesized allotetraploid Brassica napus

Established allopolyploids are known to be genomically stable and fertile. However, in contrast, most newly resynthesized allopolyploids are infertile and meiotically unstable. Identifying the genetic factors responsible for genome stability in newly formed allopolyploid is key to understanding how 2 genomes come together to form a species. One hypothesis is that established allopolyploids may have inherited specific alleles from their diploid progenitors which conferred meiotic stability. Resynthesized Brassica napus lines are often unstable and infertile, unlike B. napus cultivars. We tested this hypothesis by characterizing 41 resynthesized B. napus lines produced by crosses between 8 Brassica rapa and 8 Brassica oleracea lines for copy number variation resulting from nonhomologous recombination events and fertility. We resequenced 8 B. rapa and 5 B. oleracea parent accessions and analyzed 19 resynthesized lines for allelic variation in a list of meiosis gene homologs. SNP genotyping was performed using the Illumina Infinium Brassica 60K array for 3 individuals per line. Self-pollinated seed set and genome stability (number of copy number variants) were significantly affected by the interaction between both B. rapa and B. oleracea parental genotypes. We identified 13 putative meiosis gene candidates which were significantly associated with frequency of copy number variants and which contained putatively harmful mutations in meiosis gene haplotypes for further investigation. Our results support the hypothesis that allelic variants inherited from parental genotypes affect genome stability and fertility in resynthesized rapeseed.

Application of crop wild relatives in modern breeding: An overview of resources, experimental and computational methodologies

Global agricultural industries are under pressure to meet the future food demand; however, the existing crop genetic diversity might not be sufficient to meet this expectation. Advances in genome sequencing technologies and availability of reference genomes for over 300 plant species reveals the hidden genetic diversity in crop wild relatives (CWRs), which could have significant impacts in crop improvement. There are many ex-situ and in-situ resources around the world holding rare and valuable wild species, of which many carry agronomically important traits and it is crucial for users to be aware of their availability. Here we aim to explore the available ex-/in- situ resources such as genebanks, botanical gardens, national parks, conservation hotspots and inventories holding CWR accessions. In addition we highlight the advances in availability and use of CWR genomic resources, such as their contribution in pangenome construction and introducing novel genes into crops. We also discuss the potential and challenges of modern breeding experimental approaches (e.g. de novo domestication, genome editing and speed breeding) used in CWRs and the use of computational (e.g. machine learning) approaches that could speed up utilization of CWR species in breeding programs towards crop adaptability and yield improvement.

Pangenomics and Crop Genome Adaptation in a Changing Climate

During crop domestication and breeding, wild plant species have been shaped into modern high-yield crops and adapted to the main agro-ecological regions. However, climate change will impact crop productivity in these regions, and agriculture needs to adapt to support future food production. On a global scale, crop wild relatives grow in more diverse environments than crop species, and so may host genes that could support the adaptation of crops to new and variable environments. Through identification of individuals with increased climate resilience we may gain a greater understanding of the genomic basis for this resilience and transfer this to crops. Pangenome analysis can help to identify the genes underlying stress responses in individuals harbouring untapped genomic diversity in crop wild relatives. The information gained from the analysis of these pangenomes can then be applied towards breeding climate resilience into existing crops or to re-domesticating crops, combining environmental adaptation traits with crop productivity.

Identification of superior parents with high fiber quality using molecular markers and phenotypes based on a core collection of upland cotton (Gossypium hirsutum L.)

The combination of molecular markers and phenotypes to select superior parents has become the goal of modern breeders. In this study, 491 upland cotton (Gossypium hirsutum L.) accessions were genotyped using the CottonSNP80K array and then a core collection (CC) was constructed. Superior parents with high fiber quality were identified using molecular markers and phenotypes based on the CC. The Nei diversity index, Shannon's diversity index, and polymorphism information content among chromosomes for 491 accessions ranged from 0.307 to 0.402, 0.467 to 0.587, and 0.246 to 0.316, with mean values of 0.365, 0.542, and 0.291, respectively. A CC containing 122 accessions was established and was categorized into eight clusters based on the K2P genetic distances. From the CC, 36 superior parents (including duplicates) were selected, which contained the elite alleles of markers and ranked in the top 10% of phenotypic values for each fiber quality trait. Among the 36 materials, eight were for fiber length, four were for fiber strength, nine were for fiber micronaire, five were for fiber uniformity, and ten were for fiber elongation. In particular, the nine materials, 348 (Xinluzhong34), 319 (Xinluzhong3), 325 (Xinluzhong9), 397 (L1-14), 205 (XianIII9704), 258 (9D208), 464 (DP201), 467 (DP150), and 465 (DP208), possessed the elite alleles of markers for at least two traits and could be given priority in breeding applications for a more synchronous improvement of fiber quality. The work provides an efficient method for superior parent selection and will facilitate the application of molecular design breeding to cotton fiber quality.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01300-0.

Supporting in situ conservation of the genetic diversity of crop wild relatives using genomic technologies

The last decade has witnessed huge technological advances in genomics, particularly in DNA sequencing. Here, we review the actual and potential application of genomics in supporting in situ conservation of crop wild relatives (CWRs). In addition to helping in prioritization of protection of CWR taxa and in situ conservation sites, genome analysis is allowing the identification of novel alleles that need to be prioritized for conservation. Genomics is enabling the identification of potential sources of important adaptive traits that can guide the establishment or enrichment of in situ genetic reserves. Genomic tools also have the potential for developing a robust framework for monitoring and reporting genome‐based indicators of genetic diversity changes associated with factors such as land use or climate change. These tools have been demonstrated to have an important role in managing the conservation of populations, supporting sustainable access and utilization of CWR diversity, enhancing accelerated domestication of new crops and forensic genomics thus preventing misappropriation of genetic resources. Despite this great potential, many policy makers and conservation managers have failed to recognize and appreciate the need to accelerate the application of genomics to support the conservation and management of biodiversity in CWRs to underpin global food security. Funding and inadequate genomic expertise among conservation practitioners also remain major hindrances to the widespread application of genomics in conservation.

Genomic background selection to reduce the mutation load after random mutagenesis

Random mutagenesis is a standard procedure to increase allelic variation in a crop species, especially in countries where the use of genetically modified crops is limited due to legal constraints. The chemical mutagen EMS is used in many species to induce random mutations throughout the genome with high mutation density. The major drawback for functional analysis is a high background mutation load in a single plant that must be eliminated by subsequent backcrossing, a time and resource-intensive activity. Here, we demonstrate that genomic background selection combined with marker-assisted selection is an efficient way to select individuals with reduced background mutations within a short period. We identified BC1 plants with a significantly higher share of the recurrent parent genome, thus saving one backcross generation. Furthermore, spring rapeseed as the recurrent parent in a backcrossing program could accelerate breeding by reducing the generation cycle. Our study depicts the potential for reducing the background mutation load while accelerating the generation cycle in EMS-induced winter oilseed rape populations by integrating genomic background selection.

Development and validation of diagnostic SNP markers for quality control genotyping in a collection of four rice (Oryza) species

Morphological identification of closely related rice species, particularly those in the Oryza AA genome group, presents major challenges and often results in cases of misidentification. Recent work by this group identified diagnostic single nucleotide polymorphic (SNP) markers specific for several rice species and subspecies based on DArTseq next-generation sequencing technology ("DArTseq"). These SNPs can be used for quality control (QC) analysis in rice breeding and germplasm maintenance programs. Here, we present the DArTseq-based diagnostic SNPs converted into Kompetitive allele-specific PCR (KASPar or KASP) assays and validation data for a subset of them; these can be used for low-cost routine genotyping quality control (QC) analysis. Of the 224 species/subspecies' diagnostic SNPs tested, 158 of them produced working KASP assays, a conversion success rate of 70%. Two validation experiments were run with 87 of the 158 SNP markers to ensure that the assays amplified, were polymorphic, and distinguished the five species/subspecies tested. Based on these validation test results, we recommend a panel of 36 SNP markers that clearly delineate O. barthii, O. glaberrima, O. longistaminata, O. sativa spp. indica and japonica. The KASP assays provide a flexible, rapid turnaround and cost-effective tool to facilitate germplasm curation and management of these four Oryza AA genome species across multiple genebanks.

Modeling first order additive × additive epistasis improves accuracy of genomic prediction for sclerotinia stem rot resistance in canola

The fungus Sclerotinia sclerotiorum infects hundreds of plant species including many crops. Resistance to this pathogen in canola (Brassica napus L. subsp. napus) is controlled by numerous quantitative trait loci (QTL). For such polygenic traits, genomic prediction may be useful for breeding as it can capture many QTL at once while also considering nonadditive genetic effects. Here, we test application of common regression models to genomic prediction of S. sclerotiorum resistance in canola in a diverse panel of 218 plants genotyped at 24,634 loci. Disease resistance was scored by infection with an aggressive isolate and monitoring over 3 wk. We found that including first-order additive × additive epistasis in linear mixed models (LMMs) improved accuracy of breeding value estimation between 3 and 40%, depending on method of assessment, and correlation between phenotypes and predicted total genetic values by 14%. Bayesian models performed similarly to or worse than genomic relationship matrix-based models for estimating breeding values or overall phenotypes from genetic values. Bayesian ridge regression, which is most similar to the genomic relationship matrix-based approach in the amount of shrinkage it applies to marker effects, was the most accurate of this family of models. This confirms several studies indicating the highly polygenic nature of sclerotinia stem rot resistance. Overall, our results highlight the use of simple epistasis terms for prediction of breeding values and total genetic values for a complex disease resistance phenotype in canola.

Opening the Treasure Chest: The Current Status of Research on Brassica oleracea and B. rapa Vegetables From ex situ Germplasm Collections

Germplasm collections reflect the genetic variability in crops and their wild relatives. Hence, those genetic resources are tremendously valuable for breeders and researchers, especially in light of climatic change and stagnant crop production rates. In order to achieve improvements in crop production and end-use quality, favorable traits and donor alleles present in germplasm collections need to be identified and utilized. This review covers recent reports on the utilization of germplasm material to isolate genotypes of Brassica oleracea and B. rapa vegetables, focusing on high nutrient use efficiency, accumulation of biologically active metabolites, pest resistance, and favorable phenotypic appearance. We discuss the current state of Brassica vegetable collections in genebanks and summarize studies directed to the molecular characterization of those collections.

The History of Lentil (Lens culinaris subsp. culinaris) Domestication and Spread as Revealed by Genotyping-by-Sequencing of Wild and Landrace Accessions

Protein-rich legumes accompanied carbohydrate-rich cereals since the beginning of agriculture and yet their domestication history is not as well understood. Lentil (Lens culinaris Medik. subsp. culinaris) was first cultivated in Southwest Asia (SWA) 8000-10,000 years ago but archeological evidence is unclear as to how many times it may have been independently domesticated, in which SWA region(s) this may have happened, and whether wild species within the Lens genus have contributed to the cultivated gene pool. In this study, we combined genotyping-by-sequencing (GBS) of 190 accessions from wild (67) and domesticated (123) lentils from the Old World with archeological information to explore the evolutionary history, domestication, and diffusion of lentils to different environments. GBS led to the discovery of 87,647 single-nucleotide polymorphisms (SNPs), which allowed us to infer the phylogeny of genus Lens. We confirmed previous studies proposing four groups within it. The only gene flow detected was between cultivated varieties and their progenitor (L. culinaris subsp. orientalis) albeit at very low levels. Nevertheless, a few putative hybrids or naturalized cultivars were identified. Within cultivated lentil, we found three geographic groups. Phylogenetics, population structure, and archeological data coincide in a scenario of protracted domestication of lentils, with two domesticated gene pools emerging in SWA. Admixed varieties are found throughout their range, suggesting a relaxed selection process. A small number of alleles involved in domestication and adaptation to climatic variables were identified. Both novel mutation and selection on standing variation are presumed to have played a role in adaptation of lentils to different environments. The results presented have implications for understanding the process of plant domestication (past), the distribution of genetic diversity in germplasm collections (present), and targeting genes in breeding programs (future).

Development of a minimal KASP marker panel for distinguishing genotypes in apple collections

Accurate identification of named accessions in germplasm collections is extremely important, especially for vegetatively propagated crops which are expensive to maintain. Thus, an inexpensive, reliable, and rapid genotyping method is essential because it avoids the need for laborious and time-consuming morphological comparisons. Single Nucleotide Polymorphism (SNP) marker panels containing large numbers of SNPs have been developed for many crop species, but such panels are much too large for basic cultivar identification. Here, we have identified a minimum set of SNP markers sufficient to distinguish apple cultivars held in the English and Welsh national collections providing a cheaper and automatable alternative to the markers currently used by the community. We show that SNP genotyping with a small set of well selected markers is equally efficient as microsatellites for the identification of apple cultivars and has the added advantage of automation and reduced cost when screening large numbers of samples.

Understanding Host-Pathogen Interactions in Brassica napus in the Omics Era

Brassica napus (canola/oilseed rape/rapeseed) is an economically important crop, mostly found in temperate and sub-tropical regions, that is cultivated widely for its edible oil. Major diseases of Brassica crops such as Blackleg, Clubroot, Sclerotinia Stem Rot, Downy Mildew, Alternaria Leaf Spot and White Rust have caused significant yield and economic losses in rapeseed-producing countries worldwide, exacerbated by global climate change, and, if not remedied effectively, will threaten global food security. To gain further insights into the host-pathogen interactions in relation to Brassica diseases, it is critical that we review current knowledge in this area and discuss how omics technologies can offer promising results and help to push boundaries in our understanding of the resistance mechanisms. Omics technologies, such as genomics, proteomics, transcriptomics and metabolomics approaches, allow us to understand the host and pathogen, as well as the interaction between the two species at a deeper level. With these integrated data in multi-omics and systems biology, we are able to breed high-quality disease-resistant Brassica crops in a more holistic, targeted and accurate way.

Comparisons of sampling methods for assessing intra- and inter-accession genetic diversity in three rice species using genotyping by sequencing

To minimize the cost of sample preparation and genotyping, most genebank genomics studies in self-pollinating species are conducted on a single individual to represent an accession, which may be heterogeneous with larger than expected intra-accession genetic variation. Here, we compared various population genetics parameters among six DNA (leaf) sampling methods on 90 accessions representing a wild species (O. barthii), cultivated and landraces (O. glaberrima, O. sativa), and improved varieties derived through interspecific hybridizations. A total of 1,527 DNA samples were genotyped with 46,818 polymorphic single nucleotide polymorphisms (SNPs) using DArTseq. Various statistical analyses were performed on eleven datasets corresponding to 5 plants per accession individually and in a bulk (two sets), 10 plants individually and in a bulk (two sets), all 15 plants individually (one set), and a randomly sampled individual repeated six times (six sets). Overall, we arrived at broadly similar conclusions across 11 datasets in terms of SNP polymorphism, heterozygosity/heterogeneity, diversity indices, concordance among genetic dissimilarity matrices, population structure, and genetic differentiation; there were, however, a few discrepancies between some pairs of datasets. Detailed results of each sampling method, the concordance in their outputs, and the technical and cost implications of each method were discussed.

Development of diagnostic SNP markers for quality assurance and control in sweetpotato [Ipomoea batatas (L.) Lam.] breeding programs

Quality assurance and control (QA/QC) is an essential element of a breeding program's optimization efforts towards increased genetic gains. Due to auto-hexaploid genome complexity, a low-cost marker platform for routine QA/QC in sweetpotato breeding programs is still unavailable. We used 662 parents of the International Potato Center (CIP)'s global breeding program spanning Peru, Uganda, Mozambique and Ghana, to develop a low-density highly informative single nucleotide polymorphism (SNP) marker set to be deployed for routine QA/QC. Segregation of the selected 30 SNPs (two SNPs per base chromosome) in a recombined breeding population was evaluated using 282 progeny from some of the parents above. The progeny were replicated from in-vitro, screenhouse and field, and the selected SNP-set was confirmed to identify relatively similar mislabeling error rates as a high density SNP-set of 10,159 markers. Six additional trait-specific markers were added to the selected SNP set from previous quantitative trait loci mapping studies. The 36-SNP set will be deployed for QA/QC in breeding pipelines and in fingerprinting of advanced clones or released varieties to monitor genetic gains in famers' fields. The study also enabled evaluation of CIP's global breeding population structure and the effect of some of the most devastating stresses like sweetpotato virus disease on genetic variation management. These results will inform future deployment of genomic selection in sweetpotato.

Genotyping-by-Sequencing Derived Single Nucleotide Polymorphisms Provide the First Well-Resolved Phylogeny for the Genus Triticum (Poaceae)

Wheat (Triticum spp.) has been an important staple food crop for mankind since the beginning of agriculture. The genus Triticum L. is composed of diploid, tetraploid, and hexaploid species, majority of which have not yet been discriminated clearly, and hence their phylogeny and classification remain unresolved. Genotyping-by-sequencing (GBS) is an easy and affordable method that allows us to generate genome-wide single nucleotide polymorphism (SNP) markers. In this study, we used GBS to obtain SNPs covering all seven chromosomes from 283 accessions of Triticum-related genera. After filtering low-quality and redundant SNPs based on haplotype information, the GBS assay provided 14,188 high-quality SNPs that were distributed across the A (71%), B (26%), and D (2.4%) genomes. Cluster analysis and discriminant analysis of principal components (DAPC) allowed us to distinguish six distinct groups that matched well with Triticum species complexity. We constructed a Bayesian phylogenetic tree using 14,188 SNPs, in which 17 Triticum species and subspecies were discriminated. Dendrogram analysis revealed that the polyploid wheat species could be divided into groups according to the presence of A, B, D, and G genomes with strong nodal support and provided new insight into the evolution of spelt wheat. A total of 2,692 species-specific SNPs were identified to discriminate the common (T. aestivum) and durum (T. turgidum) wheat cultivar and landraces. In principal component analysis grouping, the two wheat species formed individual clusters and the SNPs were able to distinguish up to nine groups of 10 subspecies. This study demonstrated that GBS-derived SNPs could be used efficiently in genebank management to classify Triticum species and subspecies that are very difficult to distinguish by their morphological characters.

Single Primer Enrichment Technology (SPET) for High-Throughput Genotyping in Tomato and Eggplant Germplasm

Single primer enrichment technology (SPET) is a new, robust, and customizable solution for targeted genotyping. Unlike genotyping by sequencing (GBS), and like DNA chips, SPET is a targeted genotyping technology, relying on the sequencing of a region flanking a primer. Its reliance on single primers, rather than on primer pairs, greatly simplifies panel design, and allows higher levels of multiplexing than PCR-based genotyping. Thanks to the sequencing of the regions surrounding the target SNP, SPET allows the discovery of thousands of closely linked, novel SNPs. In order to assess the potential of SPET for high-throughput genotyping in plants, a panel comprising 5k target SNPs, designed both on coding regions and introns/UTRs, was developed for tomato and eggplant. Genotyping of two panels composed of 400 tomato and 422 eggplant accessions, comprising both domesticated material and wild relatives, generated a total of 12,002 and 30,731 high confidence SNPs, respectively, which comprised both target and novel SNPs in an approximate ratio of 1:1.6, and 1:5.5 in tomato and eggplant, respectively. The vast majority of the markers was transferrable to related species that diverged up to 3.4 million years ago (Solanum pennellii for tomato and S. macrocarpon for eggplant). Maximum Likelihood phylogenetic trees and PCA outputs obtained from the whole dataset highlighted genetic relationships among accessions and species which were congruent with what was previously reported in literature. Better discrimination among domesticated accessions was achieved by using the target SNPs, while better discrimination among wild species was achieved using the whole SNP dataset. Our results reveal that SPET genotyping is a robust, high-throughput technology for genetic fingerprinting, with a high degree of cross-transferability between crops and their cultivated and wild relatives, and allows identification of duplicates and mislabeled accessions in genebanks.

CropSNPdb: a database of SNP array data for Brassica crops and hexaploid bread wheat

Advances in sequencing technology have led to a rapid rise in the genomic data available for plants, driving new insights into the evolution, domestication and improvement of crops. Single nucleotide polymorphisms (SNPs) are a major component of crop genomic diversity, and are invaluable as genetic markers in research and breeding programs. High-throughput SNP arrays, or 'SNP chips', can generate reproducible sets of informative SNP markers and have been broadly adopted. Although there are many public repositories for sequencing data, which are routinely uploaded, there are no formal repositories for crop SNP array data. To make SNP array data more easily accessible, we have developed CropSNPdb (http://snpdb.appliedbioinformatics.com.au), a database for SNP array data produced by the Illumina Infinium™ hexaploid bread wheat (Triticum aestivum) 90K and Brassica 60K arrays. We currently host SNPs from datasets covering 526 Brassica lines and 309 bread wheat lines, and provide search, download and upload utilities for users. CropSNPdb provides a useful repository for these data, which can be applied for a range of genomics and molecular crop-breeding activities.

Comparisons of molecular diversity indices, selective sweeps and population structure of African rice with its wild progenitor and Asian rice

The extent of molecular diversity parameters across three rice species was compared using large germplasm collection genotyped with genomewide SNPs and SNPs that fell within selective sweep regions. Previous studies conducted on limited number of accessions have reported very low genetic variation in African rice (Oryza glaberrima Steud.) as compared to its wild progenitor (O. barthii A. Chev.) and to Asian rice (O. sativa L.). Here, we characterized a large collection of African rice and compared its molecular diversity indices and population structure with the two other species using genomewide single nucleotide polymorphisms (SNPs) and SNPs that mapped within selective sweeps. A total of 3245 samples representing African rice (2358), Asian rice (772) and O. barthii (115) were genotyped with 26,073 physically mapped SNPs. Using all SNPs, the level of marker polymorphism, average genetic distance and nucleotide diversity in African rice accounted for 59.1%, 63.2% and 37.1% of that of O. barthii, respectively. SNP polymorphism and overall nucleotide diversity of the African rice accounted for 20.1-32.1 and 16.3-37.3% of that of the Asian rice, respectively. We identified 780 SNPs that fell within 37 candidate selective sweeps in African rice, which were distributed across all 12 rice chromosomes. Nucleotide diversity of the African rice estimated from the 780 SNPs was 8.3 × 10^-4, which is not only 20-fold smaller than the value estimated from all genomewide SNPs (π = 1.6 × 10^-2), but also accounted for just 4.1%, 0.9% and 2.1% of that of O. barthii, lowland Asian rice and upland Asian rice, respectively. The genotype data generated for a large collection of rice accessions conserved at the AfricaRice genebank will be highly useful for the global rice community and promote germplasm use.

A genome-wide association study of early-maturation traits in upland cotton based on the CottonSNP80K array

Genome-wide association studies (GWASs) efficiently identify genetic loci controlling traits at a relatively high resolution. In this study, variations in major early-maturation traits, including seedling period (SP), bud period (BP), flower and boll period (FBP), and growth period (GP), of 169 upland cotton accessions were investigated, and a GWAS of early maturation was performed based on a CottonSNP80K array. A total of 49,650 high-quality single-nucleotide polymorphisms (SNPs) were screened, and 29 significant SNPs located on chromosomes A6, A7, A8, D1, D2, and D9, were repeatedly identified as associated with early-maturation traits, in at least two environments or two algorithms. Of these 29 significant SNPs, 1, 12, 11, and 5 were related to SP, BP, FBP, and GP, respectively. Six peak SNPs, TM47967, TM13732, TM20937, TM28428, TM50283, and TM72552, exhibited phenotypic contributions of approximately 10%, which could allow them to be used for marker-assisted selection. One of these, TM72552, as well as four other SNPs, TM72554, TM72555, TM72558, and TM72559, corresponded to the quantitative trait loci previously reported. In total, 274 candidate genes were identified from the genome sequences of upland cotton and were categorized based on their functional annotations. Finally, our studies identified Gh_D01G0340 and Gh_D01G0341 as potential candidate genes for improving cotton early maturity.

Detecting de Novo Homoeologous Recombination Events in Cultivated Brassica napus Using a Genome-Wide SNP Array

The heavy selection pressure due to intensive breeding of Brassica napus has created a narrow gene pool, limiting the ability to produce improved varieties through crosses between B. napus cultivars. One mechanism that has contributed to the adaptation of important agronomic traits in the allotetraploid B. napus has been chromosomal rearrangements resulting from homoeologous recombination between the constituent A and C diploid genomes. Determining the rate and distribution of such events in natural B. napus will assist efforts to understand and potentially manipulate this phenomenon. The Brassica high-density 60K SNP array, which provides genome-wide coverage for assessment of recombination events, was used to assay 254 individuals derived from 11 diverse cultivated spring type B. napus These analyses identified reciprocal allele gain and loss between the A and C genomes and allowed visualization of de novo homoeologous recombination events across the B. napus genome. The events ranged from loss/gain of 0.09 Mb to entire chromosomes, with almost 5% aneuploidy observed across all gametes. There was a bias toward sub-telomeric exchanges leading to genome homogenization at chromosome termini. The A genome replaced the C genome in 66% of events, and also featured more dominantly in gain of whole chromosomes. These analyses indicate de novo homoeologous recombination is a continuous source of variation in established Brassica napus and the rate of observed events appears to vary with genetic background. The Brassica 60K SNP array will be a useful tool in further study and manipulation of this phenomenon.

Unlocking the diversity of genebanks: whole-genome marker analysis of Swiss bread wheat and spelt

High-throughput genotyping of Swiss bread wheat and spelt accessions revealed differences in their gene pools and identified bread wheat landraces that were not used in breeding. Genebanks play a pivotal role in preserving the genetic diversity present among old landraces and wild progenitors of modern crops and they represent sources of agriculturally important genes that were lost during domestication and in modern breeding. However, undesirable genes that negatively affect crop performance are often co-introduced when landraces and wild crop progenitors are crossed with elite cultivars, which often limit the use of genebank material in modern breeding programs. A detailed genetic characterization is an important prerequisite to solve this problem and to make genebank material more accessible to breeding. Here, we genotyped 502 bread wheat and 293 spelt accessions held in the Swiss National Genebank using a 15K wheat SNP array. The material included both spring and winter wheats and consisted of old landraces and modern cultivars. Genome- and sub-genome-wide analyses revealed that spelt and bread wheat form two distinct gene pools. In addition, we identified bread wheat landraces that were genetically distinct from modern cultivars. Such accessions were possibly missed in the early Swiss wheat breeding program and are promising targets for the identification of novel genes. The genetic information obtained in this study is appropriate to perform genome-wide association studies, which will facilitate the identification and transfer of agriculturally important genes from the genebank into modern cultivars through marker-assisted selection.

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.

Development of species diagnostic SNP markers for quality control genotyping in four rice (Oryza L.) species

Species misclassification (misidentification) and handling errors have been frequently reported in various plant species conserved at diverse gene banks, which could restrict use of germplasm for correct purpose. The objectives of the present study were to (i) determine the extent of genotyping error (reproducibility) on DArTseq-based single-nucleotide polymorphisms (SNPs); (ii) determine the proportion of misclassified accessions across 3134 samples representing three African rice species complex (Oryza glaberrima, O. barthii, and O. longistaminata) and an Asian rice (O. sativa), which are conserved at the AfricaRice gene bank; and (iii) develop species- and sub-species (ecotype)-specific diagnostic SNP markers for rapid and low-cost quality control (QC) analysis. Genotyping error estimated from 15 accessions, each replicated from 2 to 16 times, varied from 0.2 to 3.1%, with an overall average of 0.8%. Using a total of 3134 accessions genotyped with 31,739 SNPs, the proportion of misclassified samples was 3.1% (97 of the 3134 accessions). Excluding the 97 misclassified accessions, we identified a total of 332 diagnostic SNPs that clearly discriminated the three indigenous African species complex from Asian rice (156 SNPs), O. longistaminata accessions from both O. barthii and O. glaberrima (131 SNPs), and O. sativa spp. indica from O. sativa spp. japonica (45 SNPs). Using chromosomal position, minor allele frequency, and polymorphic information content as selection criteria, we recommended a subset of 24 to 36 of the 332 diagnostic SNPs for routine QC genotyping, which would be highly useful in determining the genetic identity of each species and correct human errors during routine gene bank operations.

Usefulness of a New Large Set of High Throughput EST-SNP Markers as a Tool for Olive Germplasm Collection Management

Germplasm collections are basic tools for conservation, characterization, and efficient use of olive genetic resources. The identification of the olive cultivars maintained in the collections is an important ongoing task which has been performed by both, morphological and molecular markers. In the present study, based on the sequencing results of previous genomic projects, a new set of 1,043 EST-SNP markers has been identified. In order to evaluate its discrimination capacity and utility in diversity studies, this set of markers was used in a representative number of accessions from 20 different olive growing countries and maintained at the World Olive Germplasm Collection of IFAPA Centre 'Alameda del Obispo' (Córdoba, Spain), one of the world's largest olive germplasm bank. Thus, the cultivated material included: cultivars belonging to previously defined core collections by means of SSR markers and agronomical traits, well known homonymy cases, possible redundancies previously identified in the collection, and recently introduced accessions. Marker stability was tested in repeated analyses of a selected number of accessions, as well as in different trees and accessions belonging to the same cultivar. In addition, 15 genotypes from a cross 'Picual' × 'Arbequina' cultivars from the IFAPA olive breeding program and a set of 89 wild genotypes were also included in the study. Our results indicate that, despite their relatively wide variability, the new set of EST-SNPs displayed lower levels of genetic diversity than SSRs in the set of olive core collections tested. However, the EST-SNP markers displayed consistent and reliable results from different plant material sources and plant propagation events. The EST-SNPs revealed a clear cut off between inter- and intra-cultivar variation in olive. Besides, they were able to reliably discriminate among different accessions, to detect possible homonymy cases as well as efficiently ascertain the presence of redundant germplasm in the collection. Additionally, these markers were highly transferable to the wild genotypes. These results, together with the low genotyping error rates and the easy and fully automated procedure used to get the genotyping data, validate the new set of EST-SNPs as possible markers of choice for olive cultivar identification.

Copy number variation and disease resistance in plants

Plant genome diversity varies from single nucleotide polymorphisms to large-scale deletions, insertions, duplications, or re-arrangements. These re-arrangements of sequences resulting from duplication, gains or losses of DNA segments are termed copy number variations (CNVs). During the last decade, numerous studies have emphasized the importance of CNVs as a factor affecting human phenotype; in particular, CNVs have been associated with risks for several severe diseases. In plants, the exploration of the extent and role of CNVs in resistance against pathogens and pests is just beginning. Since CNVs are likely to be associated with disease resistance in plants, an understanding of the distribution of CNVs could assist in the identification of novel plant disease-resistance genes. In this paper, we review existing information about CNVs; their importance, role and function, as well as their association with disease resistance in plants.

Insights into the genetic relationships among plants of Beta section Beta using SNP markers

Using a much higher number of SNP markers and larger sample sizes than all the previous studies, we characterized the genetic relationships among wild and cultivated plants of section Beta. We analyzed the genetic variation of Beta section Beta, which includes wild taxa (Beta macrocarpa, B. patula, B. vulgaris subsp. adanensis and B. vulgaris subsp. maritima) and cultivars (fodder beet, sugar beet, garden beet, leaf beet, and swiss chards), using 9724 single nucleotide polymorphism markers. The analyses conducted at the individual level without a priori groups confirmed the strong differentiation of B. macrocarpa and B. vulgaris subsp. adanensis from the other taxa. B. vulgaris subsp. maritima showed a complex genetic structure partly following a geographical pattern, which confounded the differences between this taxon and the cultivated varieties. Cultivated varieties were structured into three main groups: garden beets, fodder and sugar beets, and leaf beets and swiss chards. The genetic structure described here will be helpful to correctly estimate linkage disequilibrium and to test for statistical associations between genetic markers and environmental variables.

A multiplex PCR for rapid identification of Brassica species in the triangle of U

BACKGROUND

Within the Brassicaceae, six species from the genus Brassica are widely cultivated throughout the world as oilseed, condiment, fodder or vegetable crops. The genetic relationships among the six Brassica species are described by U's triangle model. Extensive shared traits and diverse morphotypes among Brassica species make identification and classification based on phenotypic data alone challenging and unreliable, especially when dealing with large germplasm collections. Consequently, a major issue for genebank collections is ensuring the correct identification of species. Molecular genotyping based on simple sequence repeat (SSR) marker sequencing or the Illumina Infinium Brassica napus 60K single nucleotide polymorphism (SNP) array has been used to identify species and assess genetic diversity of Brassica collections. However, these methods are technically challenging, expensive and time-consuming, making them unsuitable for routine or rapid screening of Brassica accessions for germplasm management. A cheaper, faster and simpler method for Brassica species identification is described here.

RESULTS

A multiplex polymerase chain reaction (MPCR) consisting of new and existing primers specific to the Brassica A, B and C genomes was able to reliably distinguish all six Brassica species in the triangle of U with 16 control samples of known species identity. Further validation against 120 Brassica accessions previously genotyped showed that the MPCR is highly accurate and comparable to more advanced techniques such as SSR marker sequencing or the Illumina Infinium B. napus 60K SNP array. In addition, the MPCR was sensitive enough to detect seed contaminations in pooled seed samples of Brassica accessions.

CONCLUSION

A cheap and fast multiplex PCR assay for identification of Brassica species in the triangle of U was developed and validated in this study. The MPCR assay can be readily implemented in any basic molecular laboratory and should prove useful for the management of Brassica germplasm collections in genebanks.

A user guide to the Brassica 60K Illumina Infinium™ SNP genotyping array

The Brassica napus 60K Illumina Infinium™ SNP array has had huge international uptake in the rapeseed community due to the revolutionary speed of acquisition and ease of analysis of this high-throughput genotyping data, particularly when coupled with the newly available reference genome sequence. However, further utilization of this valuable resource can be optimized by better understanding the promises and pitfalls of SNP arrays. We outline how best to analyze Brassica SNP marker array data for diverse applications, including linkage and association mapping, genetic diversity and genomic introgression studies. We present data on which SNPs are locus-specific in winter, semi-winter and spring B. napus germplasm pools, rather than amplifying both an A-genome and a C-genome locus or multiple loci. Common issues that arise when analyzing array data will be discussed, particularly those unique to SNP markers and how to deal with these for practical applications in Brassica breeding applications.

Diversity analysis of cotton (Gossypium hirsutum L.) germplasm using the CottonSNP63K Array

BACKGROUND

Cotton germplasm resources contain beneficial alleles that can be exploited to develop germplasm adapted to emerging environmental and climate conditions. Accessions and lines have traditionally been characterized based on phenotypes, but phenotypic profiles are limited by the cost, time, and space required to make visual observations and measurements. With advances in molecular genetic methods, genotypic profiles are increasingly able to identify differences among accessions due to the larger number of genetic markers that can be measured. A combination of both methods would greatly enhance our ability to characterize germplasm resources. Recent efforts have culminated in the identification of sufficient SNP markers to establish high-throughput genotyping systems, such as the CottonSNP63K array, which enables a researcher to efficiently analyze large numbers of SNP markers and obtain highly repeatable results. In the current investigation, we have utilized the SNP array for analyzing genetic diversity primarily among cotton cultivars, making comparisons to SSR-based phylogenetic analyses, and identifying loci associated with seed nutritional traits.

RESULTS

The SNP markers distinctly separated G. hirsutum from other Gossypium species and distinguished the wild from cultivated types of G. hirsutum. The markers also efficiently discerned differences among cultivars, which was the primary goal when designing the CottonSNP63K array. Population structure within the genus compared favorably with previous results obtained using SSR markers, and an association study identified loci linked to factors that affect cottonseed protein content.

CONCLUSIONS

Our results provide a large genome-wide variation data set for primarily cultivated cotton. Thousands of SNPs in representative cotton genotypes provide an opportunity to finely discriminate among cultivated cotton from around the world. The SNPs will be relevant as dense markers of genome variation for association mapping approaches aimed at correlating molecular polymorphisms with variation in phenotypic traits, as well as for molecular breeding approaches in cotton.

Deletion of a Stay-Green Gene Associates with Adaptive Selection in Brassica napus

Chlorophyll levels provide important information about plant growth and physiological plasticity in response to changing environments. The stay-green gene NON-YELLOWING 1 (NYE1) is believed to regulate chlorophyll degradation during senescence, concomitantly affecting the disassembly of the light-harvesting complex and hence indirectly influencing photosynthesis. We identified Brassica napus accessions carrying an NYE1 deletion associated with increased chlorophyll content, and with upregulated expression of light-harvesting complex and photosynthetic reaction center (PSI and PSII) genes. Comparative analysis of the seed oil content of accessions with related genetic backgrounds revealed that the B. napus NYE1 gene deletion (bnnye1) affected oil accumulation, and linkage disequilibrium signatures suggested that the locus has been subject to artificial selection by breeding in oilseed B. napus forms. Comparative analysis of haplotype diversity groups (haplogroups) between three different ecotypes of the allopolyploid B. napus and its A-subgenome diploid progenitor, Brassica rapa, indicated that introgression of the bnnye1 deletion from Asian B. rapa into winter-type B. napus may have simultaneously improved its adaptation to cooler environments experienced by autumn-sown rapeseed.

Oilseed rape: learning about ancient and recent polyploid evolution from a recent crop species

Oilseed rape (Brassica napus) is one of our youngest crop species, arising several times under cultivation in the last few thousand years and completely unknown in the wild. Oilseed rape originated from hybridisation events between progenitor diploid species B. rapa and B. oleracea, both important vegetable species. The diploid progenitors are also ancient polyploids, with remnants of two previous polyploidisation events evident in the triplicated genome structure. This history of polyploid evolution and human agricultural selection makes B. napus an excellent model with which to investigate processes of genomic evolution and selection in polyploid crops. The ease of de novo interspecific hybridisation, responsiveness to tissue culture, and the close relationship of oilseed rape to the model plant Arabidopsis thaliana, coupled with the recent availability of reference genome sequences and suites of molecular cytogenetic and high-throughput genotyping tools, allow detailed dissection of genetic, genomic and phenotypic interactions in this crop. In this review we discuss the past and present uses of B. napus as a model for polyploid speciation and evolution in crop species, along with current and developing analysis tools and resources. We further outline unanswered questions that may now be tractable to investigation.

Identification of Putative Candidate Genes for Water Stress Tolerance in Canola (Brassica napus)

Drought stress can directly inhibit seedling establishment in canola (Brassica napus), resulting in lower plant densities and reduced yields. To dissect this complex trait, 140 B. napus accessions were phenotyped under normal (0.0 MPa, S0) and water-stressed conditions simulated by polyethylene glycol (PEG) 6000 (-0.5 MPa, S5) in a hydroponic system. Phenotypic variation and heritability indicated that the root to shoot length ratio was a reliable indicator for water stress tolerance. Thereafter, 66 accessions (16 water stress tolerant, 34 moderate and 16 sensitive lines) were genotyped using 25,495 Brassica single nucleotide polymorphisms (SNPs). Genome-wide association studies (GWAS) identified 16 loci significantly associated with water stress response. Two B. napus accessions were used for RNA sequencing, with differentially-expressed genes under normal and water-stressed conditions examined. By combining differentially-expressed genes detected by RNA sequencing with significantly associated loci from GWAS, 79 candidate genes were identified, of which eight were putatively associated with drought tolerance based on gene ontology of Arabidopsis. Functional validation of these genes may confirm key drought-related genes for selection and breeding in B. napus. Our results provide insight into the genetic basis of water stress tolerance in canola.