SNP genotyping in melons: genetic variation, population structure, and linkage disequilibrium

Novel sequencing technologies were recently used to generate sequences from multiple melon (Cucumis melo L.) genotypes, enabling the in silico identification of large single nucleotide polymorphism (SNP) collections. In order to optimize the use of these markers, SNP validation and large-scale genotyping are necessary. In this paper, we present the first validated design for a genotyping array with 768 SNPs that are evenly distributed throughout the melon genome. This customized Illumina GoldenGate assay was used to genotype a collection of 74 accessions, representing most of the botanical groups of the species. Of the assayed loci, 91 % were successfully genotyped. The array provided a large number of polymorphic SNPs within and across accessions. This set of SNPs detected high levels of variation in accessions from this crop’s center of origin as well as from several other areas of melon diversification. Allele distribution throughout the genome revealed regions that distinguished between the two main groups of cultivated accessions (inodorus and cantalupensis). Population structure analysis showed a subdivision into five subpopulations, reflecting the history of the crop. A considerably low level of LD was detected, which decayed rapidly within a few kilobases. Our results show that the GoldenGate assay can be used successfully for high-throughput SNP genotyping in melon. Since many of the genotyped accessions are currently being used as the parents of breeding populations in various programs, this set of mapped markers could be used for future mapping and breeding efforts.     

SNP marker diversity in common bean (<Emphasis Type="Italic">Phaseolus vulgaris</Emphasis> L.)

Single nucleotide polymorphism (SNP) markers have become a genetic technology of choice because of their automation and high precision of allele calls. In this study, our goal was to develop 94 SNPs and test them across well-chosen common bean (Phaseolus vulgaris L.) germplasm. We validated and accessed SNP diversity at 84 gene-based and 10 non-genic loci using KASPar technology in a panel of 70 genotypes that have been used as parents of mapping populations and have been previously evaluated for SSRs. SNPs exhibited high levels of genetic diversity, an excess of middle frequency polymorphism, and a within-genepool mismatch distribution as expected for populations affected by sudden demographic expansions after domestication bottlenecks. This set of markers was useful for distinguishing Andean and Mesoamerican genotypes but less useful for distinguishing within each gene pool. In summary, slightly greater polymorphism and race structure was found within the Andean gene pool than within the Mesoamerican gene pool but polymorphism rate between genotypes was consistent with genepool and race identity. Our survey results represent a baseline for the choice of SNP markers for future applications because gene-associated SNPs could themselves be causative SNPs for traits. Finally, we discuss that the ideal genetic marker combination with which to carry out diversity, mapping and association studies in common bean should consider a mix of both SNP and SSR markers.     

SNP discovery by amplicon sequencing and multiplex SNP genotyping in the allopolyploid species Brassica napus

Oilseed rape (Brassica napus) is an allotetraploid species consisting of two genomes, derived from B. rapa (A genome) and B. oleracea (C genome). The presence of these two genomes makes single nucleotide polymorphism (SNP) marker identification and SNP analysis more challenging than in diploid species, as for a given locus usually two versions of a DNA sequence (based on the two ancestral genomes) have to be analyzed simultaneously during SNP identification and analysis. One hundred amplicons derived from expressed sequence tag (ESTs) were analyzed to identify SNPs in a panel of oilseed rape varieties and within two sister species representing the ancestral genomes. A total of 604 SNPs were identified, averaging one SNP in every 42 bp. It was possible to clearly discriminate SNPs that are polymorphic between different plant varieties from SNPs differentiating the two ancestral genomes. To validate the identified SNPs for their use in genetic analysis, we have developed Illumina GoldenGate assays for some of the identified SNPs. Through the analysis of a number of oilseed rape varieties and mapping populations with GoldenGate assays, we were able to identify a number of different segregation patterns in allotetraploid oilseed rape. The majority of the identified SNP markers can be readily used for genetic mapping, showing that amplicon sequencing and Illumina GoldenGate assays can be used to reliably identify SNP markers in tetraploid oilseed rape and to convert them into successful SNP assays that can be used for genetic analysis.     

Genome-Wide Association Studies Using Single Nucleotide Polymorphism Markers Developed by Re-Sequencing of the Genomes of Cultivated Tomato

With the aim of understanding relationship between genetic and phenotypic variations in cultivated tomato, single nucleotide polymorphism (SNP) markers covering the whole genome of cultivated tomato were developed and genome-wide association studies (GWAS) were performed. The whole genomes of six tomato lines were sequenced with the ABI-5500xl SOLiD sequencer. Sequence reads covering ∼13.7× of the genome for each line were obtained, and mapped onto tomato reference genomes (SL2.40) to detect ∼1.5 million SNP candidates. Of the identified SNPs, 1.5% were considered to confer gene functions. In the subsequent Illumina GoldenGate assay for 1536 SNPs, 1293 SNPs were successfully genotyped, and 1248 showed polymorphisms among 663 tomato accessions. The whole-genome linkage disequilibrium (LD) analysis detected highly biased LD decays between euchromatic (58 kb) and heterochromatic regions (13.8 Mb). Subsequent GWAS identified SNPs that were significantly associated with agronomical traits, with SNP loci located near genes that were previously reported as candidates for these traits. This study demonstrates that attractive loci can be identified by performing GWAS with a large number of SNPs obtained from re-sequencing analysis.     

High-throughput genotyping with the GoldenGate assay in the complex genome of soybean

Large numbers of single nucleotide polymorphism (SNP) markers are now available for a number of crop species. However, the high-throughput methods for multiplexing SNP assays are untested in complex genomes, such as soybean, that have a high proportion of paralogous genes. The Illumina GoldenGate assay is capable of multiplexing from 96 to 1,536 SNPs in a single reaction over a 3-day period. We tested the GoldenGate assay in soybean to determine the success rate of converting verified SNPs into working assays. A custom 384-SNP GoldenGate assay was designed using SNPs that had been discovered through the resequencing of five diverse accessions that are the parents of three recombinant inbred line (RIL) mapping populations. The 384 SNPs that were selected for this custom assay were predicted to segregate in one or more of the RIL mapping populations. Allelic data were successfully generated for 89% of the SNP loci (342 of the 384) when it was used in the three RIL mapping populations, indicating that the complex nature of the soybean genome had little impact on conversion of the discovered SNPs into usable assays. In addition, 80% of the 342 mapped SNPs had a minor allele frequency >10% when this assay was used on a diverse sample of Asian landrace germplasm accessions. The high success rate of the GoldenGate assay makes this a useful technique for quickly creating high density genetic maps in species where SNP markers are rapidly becoming available. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. Mention of a trade name, proprietary product, or specific equipment does not constitute a guarantee or warranty by the USDA and does not imply approval of a product to the exclusion of others that may be suitable.     

SNPs in stress-responsive rice genes: validation, genotyping, functional relevance and population structure

ABSTRACT: BACKGROUND: Single nucleotide polymorphism (SNP) validation and large-scale genotyping are required to maximize the use of DNA sequence variation and determine the functional relevance of candidate genes for complex stress tolerance traits through genetic association in rice. We used the bead array platform-based Illumina GoldenGate assay to validate and genotype SNPs in a select set of stress-responsive genes to understand their functional relevance and study the population structure in rice. RESULTS: Of the 384 putative SNPs assayed, we successfully validated and genotyped 362 (94.3%). Of these 325 (84.6%) showed polymorphism among the 91 rice genotypes examined. Physical distribution, degree of allele sharing, admixtures and introgression, and amino acid replacement of SNPs in 263 abiotic and 62 biotic stress-responsive genes provided clues for identification and targeted mapping of trait-associated genomic regions. We assessed the functional and adaptive significance of validated SNPs in a set of contrasting drought tolerant upland and sensitive lowland rice genotypes by correlating their allelic variation with amino acid sequence alterations in catalytic domains and three-dimensional secondary protein structure encoded by stress-responsive genes. We found a strong genetic association among SNPs in the nine stress-responsive genes with upland and lowland ecological adaptation. Higher nucleotide diversity was observed in indica accessions compared with other rice sub-populations based on different population genetic parameters. The inferred ancestry of 16% among rice genotypes was derived from admixed populations with the maximum between upland aus and wild Oryza species. CONCLUSIONS: SNPs validated in biotic and abiotic stress-responsive rice genes can be used in association analyses to identify candidate genes and develop functional markers for stress tolerance in rice.     

A pipeline for high throughput detection and mapping of SNPs from EST databases

Single nucleotide polymorphisms (SNPs) represent the most abundant type of genetic variation that can be used as molecular markers. The SNPs that are hidden in sequence databases can be unlocked using bioinformatic tools. For efficient application of these SNPs, the sequence set should be error-free as much as possible, targeting single loci and suitable for the SNP scoring platform of choice. We have developed a pipeline to effectively mine SNPs from public EST databases with or without quality information using QualitySNP software, select reliable SNP and prepare the loci for analysis on the Illumina GoldenGate genotyping platform. The applicability of the pipeline was demonstrated using publicly available potato EST data, genotyping individuals from two diploid mapping populations and subsequently mapping the SNP markers (putative genes) in both populations. Over 7000 reliable SNPs were identified that met the criteria for genotyping on the GoldenGate platform. Of the 384 SNPs on the SNP array approximately 12% dropped out. For the two potato mapping populations 165 and 185 SNPs segregating SNP loci could be mapped on the respective genetic maps, illustrating the effectiveness of our pipeline for SNP selection and validation.     

Genome-wide single nucleotide polymorphism and Insertion-Deletion discovery through next-generation sequencing of reduced representation libraries in common bean

Single nucleotide polymorphisms (SNPs) and insertions-deletions (InDels) are valuable molecular markers for genomics and genetics studies and molecular breeding. The advent of next-generation sequencing techniques has enabled researchers to approach high-throughput and cost-effective SNP and InDel discovery on a genomic scale. In this report, 36 common bean genotypes grown in Canada were used to construct reduced representation libraries for next-generation sequencing. Using 76 million sequence reads generated by the Illumina HiSeq 2000 Sequencing System, we identified a total of 43,698 putative SNPs and 1,267 putative InDels. Of the SNPs, 43,504 were bi-allelic and 194 were tri-allelic, and the InDels comprised 574 insertions and 693 deletions. The putative bi-allelic SNPs were distributed across all 11 chromosomes with the highest number of SNPs observed in chromosome 2 (4,788), and the lowest in chromosome 10 (2,941). With the aid of the recent release of the first chromosome-scale version of Phaseolus vulgaris, 24,907 bi-allelic SNPs, 79 tri-allelic SNPs, 315 insertions, and 377 deletions were located in 8,758, 77, 273, and 364 genes, respectively. Among these 24,907 bi-allelic SNPs, 7,168 nonsynonymous bi-allelic SNPs were identified within 36 common bean genotypes that were located in 4,303 genes. A total of 113 putative SNPs were randomly chosen for validation using high-resolution melt analysis. Of the 113 candidate SNPs, 105 (92.9 %) contained the predicted SNPs.     

LSGermOPA,a custom OPA of 384 EST-derived SNPs for high-throughput lettuce (<Emphasis Type="Italic">Lactuca sativa</Emphasis> L.) germplasm fingerprinting

To deploy a high-throughput genotyping platform in germplasm management, we designed and tested a custom OPA (Oligo Pool All), LSGermOPA, for assessing the genetic diversity and population structure of the USDA cultivated lettuce (Lactuca sativa L.) germplasm collection using Illumina’s GoldenGate assay. This OPA contains 384 EST (expressed sequence tag)-derived SNP (single nucleotide polymorphism) markers selected from a large set of SNP markers experimentally validated and mapped by the Compositae Genome Project. Used for genotyping were DNA samples prepared from bulked leaves of five randomly-selected seedlings from each of 380 lettuce accessions. High-quality genotype data were obtained from 354 of the 384 SNPs. The reproducibility of automatic genotype calls was 99.8% as calculated from the four pairs of duplicated DNA samples in the assay. An unexpectedly high percentage of heterozygous genotypes at the polymorphic loci for most accessions indicated a high level of heterogeneity within accessions. Only 148 homogenous accessions, collectively comprising all five horticultural types, were used in subsequent analyses to demonstrate the usefulness of LSGermOPA. The results of phylogenetic relationship, population structure and genetic differentiation analyses were consistent with previous reports using other marker systems. This suggests that LSGermOPA is capable of revealing sufficient levels of polymorphism among lettuce cultivars and is appropriate for rapid assessment of genetic diversity and population structure in the lettuce germplasm collection. Challenges and strategies for effective genotyping and managing lettuce germplasm are discussed.     

High-resolution melting analysis for SNP genotyping and mapping in tetraploid alfalfa (Medicago sativa L.)

Single nucleotide polymorphisms (SNPs) represent the most abundant type of genetic polymorphism in plant genomes. SNP markers are valuable tools for genetic analysis of complex traits of agronomic importance, linkage and association mapping, genome-wide selection, map-based cloning, and marker-assisted selection. Current challenges for SNP genotyping in polyploid outcrossing species include multiple alleles per loci and lack of high-throughput methods suitable for variant detection. In this study, we report on a high-resolution melting (HRM) analysis system for SNP genotyping and mapping in outcrossing tetraploid genotypes. The sensitivity and utility of this technology is demonstrated by identification of the parental genotypes and segregating progeny in six alfalfa populations based on unique melting curve profiles due to differences in allelic composition at one or multiple loci. HRM using a 384-well format is a fast, consistent, and efficient approach for SNP discovery and genotyping, useful in polyploid species with uncharacterized genomes. Possible applications of this method include variation discovery, analysis of candidate genes, genotyping for comparative and association mapping, and integration of genome-wide selection in breeding programs.     

Development of versatile gene-based SNP assays in maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.)

A large number of maize single nucleotide polymorphism (SNP) candidate sequences have been generated and deposited in public databases. However, very little work has been done to date to comprehensively characterize those SNPs and identify a set of markers, which potentially would have high impact in molecular genetics research and breeding programs. Here we describe a multi-step process to identify highly polymorphic gene-based SNPs among ~130,000 public markers. A set of 695 highly polymorphic SNPs (minor allele frequency value >0.3), identified within exons, 5′ and 3′ untranslated regions of genes, were converted into four of the most popular high-throughput genotyping assays that include Illumina’s GoldenGate and Infinium chemistries, Life Technologies’ TaqMan assay and KBioSciences’ KASPar assay. The term “versatile” was applied to 162 gene-based SNPs that were successfully converted into all four chemistries and had perfect genotypic clustering patterns. This subset of discovered versatile SNP markers represents a universal tool for application in various molecular genetics and breeding projects in maize, where genotyping is based on one of the four above-mentioned chemistries. This study demonstrated that despite the availability of millions of discovered SNPs in maize, only a very small portion of those polymorphisms could be utilized for the development of robust, versatile assays, and has real practical value in marker-assisted selection.     

Identification of genome-wide single nucleotide polymorphisms in allopolyploid crop Brassica napus

Background

Single nucleotide polymorphisms (SNPs) are the most common type of genetic variation. Identification of large numbers of SNPs is helpful for genetic diversity analysis, map-based cloning, genome-wide association analyses and marker-assisted breeding. Recently, identifying genome-wide SNPs in allopolyploid Brassica napus (rapeseed, canola) by resequencing many accessions has become feasible, due to the availability of reference genomes of Brassica rapa (2n = AA) and Brassica oleracea (2n = CC), which are the progenitor species of B. napus (2n = AACC). Although many SNPs in B. napus have been released, the objective in the present study was to produce a larger, more informative set of SNPs for large-scale and efficient genotypic screening. Hence, short-read genome sequencing was conducted on ten elite B. napus accessions for SNP discovery. A subset of these SNPs was randomly selected for sequence validation and for genotyping efficiency testing using the Illumina GoldenGate assay.

Results

A total of 892,536 bi-allelic SNPs were discovered throughout the B. napus genome. A total of 36,458 putative amino acid variants were located in 13,552 protein-coding genes, which were predicted to have enriched binding and catalytic activity as a result. Using the GoldenGate genotyping platform, 94 of 96 SNPs sampled could effectively distinguish genotypes of 130 lines from two mapping populations, with an average call rate of 92%.

Conclusions

Despite the polyploid nature of B. napus, nearly 900,000 simple SNPs were identified by whole genome resequencing. These SNPs were predicted to be effective in high-throughput genotyping assays (51% polymorphic SNPs, 92% average call rate using the GoldenGate assay, leading to an estimated >450 000 useful SNPs). Hence, the development of a much larger genotyping array of informative SNPs is feasible. SNPs identified in this study to cause non-synonymous amino acid substitutions can also be utilized to directly identify causal genes in association studies.     

Single nucleotide polymorphism genotyping in polyploid wheat with the Illumina GoldenGate assay

Single nucleotide polymorphisms (SNPs) are indispensable in such applications as association mapping and construction of high-density genetic maps. These applications usually require genotyping of thousands of SNPs in a large number of individuals. Although a number of SNP genotyping assays are available, most of them are designed for SNP genotyping in diploid individuals. Here, we demonstrate that the Illumina GoldenGate assay could be used for SNP genotyping of homozygous tetraploid and hexaploid wheat lines. Genotyping reactions could be carried out directly on genomic DNA without the necessity of preliminary PCR amplification. A total of 53 tetraploid and 38 hexaploid homozygous wheat lines were genotyped at 96 SNP loci. The genotyping error rate estimated after removal of low-quality data was 0 and 1% for tetraploid and hexaploid wheat, respectively. Developed SNP genotyping assays were shown to be useful for genotyping wheat cultivars. This study demonstrated that the GoldenGate assay is a very efficient tool for high-throughput genotyping of polyploid wheat, opening new possibilities for the analysis of genetic variation in wheat and dissection of genetic basis of complex traits using association mapping approach. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Highly efficient genotyping of rice biparental populations by GoldenGate assays based on parental resequencing

Key message

A new time- and cost-effective strategy was developed for medium-density SNP genotyping of rice biparental populations, using GoldenGate assays based on parental resequencing.

Abstract

Since the advent of molecular markers, crop researchers and breeders have dedicated huge amounts of effort to detecting quantitative trait loci (QTL) in biparental populations for genetic analysis and marker-assisted selection (MAS). In this study, we developed a new time- and cost-effective strategy for genotyping a population of progeny from a rice cross using medium-density single nucleotide polymorphisms (SNPs). Using this strategy, 728,362 “high quality” SNPs were identified by resequencing Teqing and Lemont, the parents of the population. We selected 384 informative SNPs that were evenly distributed across the genome for genotyping the biparental population using the Illumina GoldenGate assay. 335 (87.2 %) validated SNPs were used for further genetic analyses. After removing segregation distortion markers, 321 SNPs were used for linkage map construction and QTL mapping. This strategy generated SNP markers distributed more evenly across the genome than previous SSR assays. Taking the GW5 gene that controls grain shape as an example, our strategy provided higher accuracy (0.8 Mb) and significance (LOD 5.5 and 10.1) in QTL mapping than SSR analysis. Our study thus provides a rapid and efficient strategy for genetic studies and QTL mapping using SNP genotyping assays.     

Sweet Cherry Cultivar Identification by High-Resolution-Melting (HRM) Analysis Using Gene-Based SNP Markers

Single nucleotide polymorphisms (SNPs) provide an important tool for cultivar identification in studies of genetic diversity, but until now, the time-consuming and costly nature of DNA sequencing has limited the identification of new markers. Herein, we describe the application of high-resolution melting (HRM), a recent enhancement to traditional DNA melting analysis, for the characterization of polymerase chain reaction products and the identification of nine gene-based SNPs for distinguishing the main Greek sweet cherry cultivars. The expected heterozygosity value of nine SNPs averaged at 0.518. The combined power of discrimination for the SNP markers was 0.999969. The ability of HRM to accurately discern nucleotide changes in a DNA sequence makes it a cost- and time-effective alternative to traditional sequencing for the detection of gene-based SNPs.     

Inheritance analysis and identification of SNP markers associated with ZYMV resistance in <Emphasis Type="Italic">Cucurbita pepo</Emphasis>

Cucurbit crops are economically important worldwide. One of the most serious threats to cucurbit production is Zucchini yellow mosaic virus (ZYMV). Several resistant accessions were identified in Cucurbita moschata and their resistance was introgressed into Cucurbita pepo. However, the mode of inheritance of ZYMV resistance in C. pepo presents a great challenge to attempts at introgressing resistance into elite germplasm. The main goal of this work was to analyze the inheritance of ZYMV resistance and to identify markers associated with genes conferring resistance. An Illumina GoldenGate assay allowed us to assess polymorphism among nine squash genotypes and to discover six polymorphic single-nucleotide polymorphisms (SNPs) between two near-isogenic lines, “True French” (susceptible to ZYMV) and Accession 381e (resistant to ZYMV). Two F₂ and three BC₁ populations obtained from crossing the ZYMV-resistant Accession 381e with two susceptible ones, the zucchini True French and the cocozelle “San Pasquale,” were assayed for ZYMV resistance. Molecular analysis revealed an approximately 90% association between SNP1 and resistance, which was confirmed using High Resolution Melt (HRM) and a CAPS marker. Co-segregation up to 72% in populations segregating for resistance was observed for two other SNP markers that could be potentially linked to genes involved in resistance expression. A functional prediction of proteins involved in the resistance response was performed on genome scaffolds containing the three SNPs of interest. Indeed, 16 full-length pathogen recognition genes (PRGs) were identified around the three SNP markers. In particular, we discovered that two nucleotide-binding site leucine-rich repeat (NBS-LRR) protein-encoding genes were located near the SNP1 marker. The investigation of ZYMV resistance in squash populations and the genomic analysis performed in this work could be useful for better directing the introgression of disease resistance into elite C. pepo germplasm.     

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

Although a large number of single nucleotide polymorphism (SNP) markers covering the entire genome are needed to enable molecular breeding efforts such as genome wide association studies, fine mapping, genomic selection and marker-assisted selection in peach [Prunus persica (L.) Batsch] and related Prunus species, only a limited number of genetic markers, including simple sequence repeats (SSRs), have been available to date. To address this need, an international consortium (The International Peach SNP Consortium; IPSC) has pursued a coordinated effort to perform genome-scale SNP discovery in peach using next generation sequencing platforms to develop and characterize a high-throughput Illumina Infinium® SNP genotyping array platform. We performed whole genome re-sequencing of 56 peach breeding accessions using the Illumina and Roche/454 sequencing technologies. Polymorphism detection algorithms identified a total of 1,022,354 SNPs. Validation with the Illumina GoldenGate® assay was performed on a subset of the predicted SNPs, verifying ∼75% of genic (exonic and intronic) SNPs, whereas only about a third of intergenic SNPs were verified. Conservative filtering was applied to arrive at a set of 8,144 SNPs that were included on the IPSC peach SNP array v1, distributed over all eight peach chromosomes with an average spacing of 26.7 kb between SNPs. Use of this platform to screen a total of 709 accessions of peach in two separate evaluation panels identified a total of 6,869 (84.3%) polymorphic SNPs.The almost 7,000 SNPs verified as polymorphic through extensive empirical evaluation represent an excellent source of markers for future studies in genetic relatedness, genetic mapping, and dissecting the genetic architecture of complex agricultural traits. The IPSC peach SNP array v1 is commercially available and we expect that it will be used worldwide for genetic studies in peach and related stone fruit and nut species.     

Genome-wide single nucleotide polymorphism discovery and validation in adzuki bean

Adzuki bean, also known as red bean (Vigna angularis), with 2n = 22 chromosomes, is an important legume crop in East Asian countries, including China, Japan, and Korea. For single nucleotide polymorphism (SNP) discovery, we used Vigna accessions, V. angularis IT213134 and its wild relative V. nakashimae IT178530, because of the lack of DNA sequence polymorphism in the cultivated species. Short read sequences of IT213134 and IT178530 of approximately 37 billion and 35 billion bp were produced using the Illumina HiSeq 2000 system to a sequencing depth of 61.5× and 57.7×, respectively. After de novo assembly was carried out with trimmed HiSeq reads from IT213134, 98,441 contigs of various sizes were produced with N50 of 13,755 bp. Using Burrows–Wheeler Aligner software, trimmed short reads of V. nakashimae IT178530 were successfully mapped to IT213134 contigs. All sequence variations at the whole-genome level were examined between the two Vigna species. Of the 1,565,699 SNPs, 59.4 % were transitions and 40.6 % were transversions. A total of 213,758 SNPs, consisting of 122,327 non-synonymous and 91,431 synonymous SNPs, were identified in coding sequences. For SNP validation, 96 SNPs in the genic region were chosen from among IT213134 contigs longer than 10 kb. Of these 96 SNPs, 88 were confirmed by Sanger sequencing of 10 adzuki bean genotypes from various geographic origins as well as IT213134 and its wild relative IT178530. These genome-wide SNP markers will enrich the existing Vigna resources and, specifically, could be of value for constructing a genetic map and evaluating the genetic diversity of adzuki bean.