High-throughput SNP genotyping with the GoldenGate assay in maize

Single nucleotide polymorphisms (SNPs) are abundant and evenly distributed throughout the genomes of most plant species. They have become an ideal marker system for genetic research in many crops. Several high throughput platforms have been developed that allow rapid and simultaneous genotyping of up to a million SNP markers. In this study, a custom GoldenGate assay containing 1,536 SNPs was developed based on public SNP information for maize and used to genotype two recombinant inbred line (RIL) populations (Zong3 x 87-1, and B73 x By804) and a panel of 154 diverse inbred lines. Over 90% of the SNPs were successfully scored in the diversity panel and the two RIL populations, with a genotyping error rate of less than 2%. A total of 975 SNP markers detected polymorphism in at least one of the two mapping populations, with a polymorphic rate of 38.5% in Zong3 x 87-1 and 52.6% in B73 x By804. The polymorphic SNPs in B73 x By804 have been integrated with previously mapped simple sequence repeat markers to construct a high-density linkage map containing 662 markers with a total length of 1,673.7 cM and an average of 2.53 cM between two markers. The minor allelic frequency (MAF) was distributed evenly across 10 continued classes from 0.05 to 0.5, and about 16% of the SNP markers had a MAF below 10% in the diversity panel. Polymorphism rates for individual SNP markers in pair-wise comparisons of genotypes tested ranged from 0.3 to 63.8% with an average of 36.3%. Most SNPs used in this GoldenGate assay appear to be equally useful for diversity analysis, marker-trait association studies, and marker-aided breeding.     

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.     

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.     

A high-throughput SNP marker system for parental polymorphism screening, and diversity analysis in common bean (Phaseolus vulgaris L.)

Single nucleotide polymorphism (SNP) detection has become a marker system of choice, because of the high abundance of source polymorphisms and the ease with which allele calls are automated. Various technologies exist for the evaluation of SNP loci and previously we validated two medium throughput technologies. In this study, our goal was to utilize a 768 feature, Illumina GoldenGate assay for common bean (Phaseolus vulgaris L.) developed from conserved legume gene sequences and to use the new technology for (1) the evaluation of parental polymorphisms in a mini-core set of common bean accessions and (2) the analysis of genetic diversity in the crop. A total of 736 SNPs were scored on 236 diverse common bean genotypes with the GoldenGate array. Missing data and heterozygosity levels were low and 94 % of the SNPs were scorable. With the evaluation of the parental polymorphism genotypes, we estimated the utility of the SNP markers in mapping for inter-genepool and intra-genepool populations, the latter being of lower polymorphism than the former. When we performed the diversity analysis with the diverse genotypes, we found Illumina GoldenGate SNPs to provide equivalent evaluations as previous gene-based SNP markers, but less fine-distinctions than with previous microsatellite marker analysis. We did find, however, that the gene-based SNPs in the GoldenGate array had some utility in race structure analysis despite the low polymorphism. Furthermore the SNPs detected high heterozygosity in wild accessions which was probably a reflection of ascertainment bias. The Illumina SNPs were shown to be effective in distinguishing between the genepools, and therefore were most useful in saturation of inter-genepool genetic maps. The implications of these results for breeding in common bean are discussed as well as the advantages and disadvantages of the GoldenGate system for SNP detection.     

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.     

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.     

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.     

High-throughput genotyping and mapping of single nucleotide polymorphisms in loblolly pine (Pinus taeda L.)

The development and application of genomic tools to loblolly pine (Pinus taeda L.) offer promising insights into the organization and structure of conifer genomes. The application of a high-throughput genotyping assay across diverse forest tree species, however, is currently limited taxonomically. This is despite the ongoing development of genome-scale projects aiming at the construction of expressed sequence tag (EST) libraries and the resequencing of EST-derived unigenes for a diverse array of forest tree species. In this paper, we report on the application of Illumina’s high-throughput GoldenGate™ SNP genotyping assay to a loblolly pine mapping population. Single nucleotide polymorphisms (SNPs) were identified through resequencing of previously identified wood quality, drought tolerance, and disease resistance candidate genes prior to genotyping. From that effort, a 384 multiplexed SNP assay was developed for high-throughput genotyping. Approximately 67% of the 384 SNPs queried converted into high-quality genotypes for the 48 progeny samples. Of those 257 successfully genotyped SNPs, 70 were segregating within the mapping population. A total of 27 candidate genes were subsequently mapped onto the existing loblolly pine consensus map, which consists of 12 linkage groups spanning a total map distance of 1,227.6 cM. The ability of SNPs to be mapped to the same position as fragment-based markers previously developed within the same candidate genes, as well as the pivotal role that SNPs currently play in the dissection of complex phenotypic traits, illustrate the usefulness of high-throughput SNP genotyping technologies to the continued development of pine genomics. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

High-throughput single nucleotide polymorphism genotyping for breeding applications in rice using the BeadXpress platform

Multiplexed single nucleotide polymorphism (SNP) markers have the potential to increase the speed and cost-effectiveness of genotyping, provided that an optimal SNP density is used for each application. To test the efficiency of multiplexed SNP genotyping for diversity, mapping and breeding applications in rice (Oryza sativa L.), we designed seven GoldenGate VeraCode oligo pool assay (OPA) sets for the Illumina BeadXpress Reader. Validated markers from existing 1536 Illumina SNPs and 44?K Affymetrix SNP chips developed at Cornell University were used to select subsets of informative SNPs for different germplasm groups with even distribution across the genome. A 96-plex OPA was developed for quality control purposes and for assigning a sample into one of the five O. sativa population subgroups. Six 384-plex OPAs were designed for genetic diversity analysis, DNA fingerprinting, and to have evenly-spaced polymorphic markers for quantitative trait locus (QTL) mapping and background selection for crosses between different germplasm pools in rice: Indica/Indica, Indica/Japonica, Japonica/Japonica, Indica/O. rufipogon, and Japonica/O. rufipogon. After testing on a diverse set of rice varieties, two of the SNP sets were re-designed by replacing poor-performing SNPs. Pilot studies were successfully performed for diversity analysis, QTL mapping, marker-assisted backcrossing, and developing specialized genetic stocks, demonstrating that 384-plex SNP genotyping on the BeadXpress platform is a robust and efficient method for marker genotyping in rice.     

Analysis of gene-derived SNP marker polymorphism in US wheat (Triticum aestivum L.) cultivars

In this study, we developed 359 detection primers for single nucleotide polymorphisms (SNPs) previously discovered within intron sequences of wheat genes and used them to evaluate SNP polymorphism in common wheat (Triticum aestivum L.). These SNPs showed an average polymorphism information content (PIC) of 0.18 among 20 US elite wheat cultivars, representing seven market classes. This value increased to 0.23 when SNPs were pre-selected for polymorphisms among a diverse set of 13 hexaploid wheat accessions (excluding synthetic wheats) used in the wheat SNP discovery project (). PIC values for SNP markers in the D genome were approximately half of those for the A and B genomes. D genome SNPs also showed a larger PIC reduction relative to the other genomes (P < 0.05) when US cultivars were compared with the more diverse set of 13 wheat accessions. Within those accessions, D genome SNPs show a higher proportion of alleles with low minor allele frequencies (<0.125) than found in the other two genomes. These data suggest that the reduction of PIC values in the D genome was caused by differential loss of low frequency alleles during the population size bottleneck that accompanied the development of modern commercial cultivars. Additional SNP discovery efforts targeted to the D genome in elite wheat germplasm will likely be required to offset the lower diversity of this genome. With increasing SNP discovery projects and the development of high-throughput SNP assay technologies, it is anticipated that SNP markers will play an increasingly important role in wheat genetics and breeding applications. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Single‐nucleotide polymorphism discovery and diversity in the model legume Medicago truncatula

Extensive genomic resources are available in the model legume Medicago truncatula. Here, we present the discovery and design of the first array of single‐nucleotide polymorphism (SNP) markers in M. truncatula through large‐scale Sanger resequencing of genomic fragments spanning the genome, in a diverse panel of 16 M. truncatula accessions. Both anonymous fragments and fragments targeting candidate genes for flowering phenology and symbiosis were surveyed for nucleotide variation in almost 230 kb of unique genomic regions. A set of 384 SNP markers was designed for an Illumina's GoldenGate assay, genotyped on a collection of 192 inbred lines (CC192) representing the geographical range of the species and used to survey the diversity of two natural populations. Finally, 86% of the tested SNPs were of high quality and exhibited polymorphism in the CC192 collection. Even at the population level, we detected polymorphism for more than 50% of the selected SNPs. Analysis of the allele frequency spectrum in the CC192 showed a reduced ascertainment bias, mostly limited to very rare alleles (frequency <0.01). The substantial polymorphism detected at the species and population levels, the high marker quality and the potential to survey large samples of individuals make this set of SNP markers a valuable tool to improve our understanding of the effect of demographic and selective factors that shape the natural genetic diversity within the selfing species Medicago truncatula.     

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.     

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.     

High-Throughput SNP Discovery and Genotyping for Constructing a Saturated Linkage Map of Chickpea (Cicer arietinum L.)

The present study reports the large-scale discovery of genome-wide single-nucleotide polymorphisms (SNPs) in chickpea, identified mainly through the next generation sequencing of two genotypes, i.e. Cicer arietinum ICC4958 and its wild progenitor C. reticulatum PI489777, parents of an inter-specific reference mapping population of chickpea. Development and validation of a high-throughput SNP genotyping assay based on Illumina''s GoldenGate Genotyping Technology and its application in building a high-resolution genetic linkage map of chickpea is described for the first time. In this study, 1022 SNPs were identified, of which 768 high-confidence SNPs were selected for designing the custom Oligo Pool All (CpOPA-I) for genotyping. Of these, 697 SNPs could be successfully used for genotyping, demonstrating a high success rate of 90.75%. Genotyping data of the 697 SNPs were compiled along with those of 368 co-dominant markers mapped in an earlier study, and a saturated genetic linkage map of chickpea was constructed. One thousand and sixty-three markers were mapped onto eight linkage groups spanning 1808.7 cM (centiMorgans) with an average inter-marker distance of 1.70 cM, thereby representing one of the most advanced maps of chickpea. The map was used for the synteny analysis of chickpea, which revealed a higher degree of synteny with the phylogenetically close Medicago than with soybean. The first set of validated SNPs and map resources developed in this study will not only facilitate QTL mapping, genome-wide association analysis and comparative mapping in legumes but also help anchor scaffolds arising out of the whole-genome sequencing of chickpea.     

Single nucleotide polymorphism genotyping using Kompetitive Allele Specific PCR (KASP): overview of the technology and its application in crop improvement

Single nucleotide polymorphism (SNP) data can be obtained using one of the numerous uniplex or multiplex SNP genotyping platforms that combine a variety of chemistries, detection methods, and reaction formats. Kompetitive Allele Specific PCR (KASP) is one of the uniplex SNP genotyping platforms, and has evolved to be a global benchmark technology. However, there are no publications relating either to the technology itself or to its application in crop improvement programs. In this review, we provide an overview of the different aspects of the KASP genotyping platform, discuss its application in crop improvement, and compare it with the chip-based Illumina GoldenGate platform. The International Maize and Wheat Improvement Center routinely uses KASP, generating in excess of a million data points annually for crop improvement purposes. We found that (1) 81 % of the SNPs used in a custom-designed GoldenGate assay were transferable to KASP; (2) using KASP, negative controls (no template) consistently clustered together and rarely produced signals exceeding the threshold values for allele calling, in contrast to the situation observed using GoldenGate assays; (3) KASP’s average genotyping error in positive control DNA samples was 0.7–1.6 %, which is lower than that observed using GoldenGate (2.0–2.4 %); (4) KASP genotyping costs for marker-assisted recurrent selection were 7.9–46.1 % cheaper than those of the BeadXpress and GoldenGate platforms; and (5) KASP offers cost-effective and scalable flexibility in applications that require small to moderate numbers of markers, such as quality control analysis, quantitative trait loci (QTL) mapping in bi-parental populations, marker-assisted recurrent selection, marker-assisted backcrossing, and QTL fine mapping.     

Development,validation and genetic analysis of a large soybean SNP genotyping array

Cultivated soybean (Glycine max) suffers from a narrow germplasm relative to other crop species, probably because of under‐use of wild soybean (Glycine soja) as a breeding resource. Use of a single nucleotide polymorphism (SNP) genotyping array is a promising method for dissecting cultivated and wild germplasms to identify important adaptive genes through high‐density genetic mapping and genome‐wide association studies. Here we describe a large soybean SNP array for use in diversity analyses, linkage mapping and genome‐wide association analyses. More than four million high‐quality SNPs identified from high‐depth genome re‐sequencing of 16 soybean accessions and low‐depth genome re‐sequencing of 31 soybean accessions were used to select 180 961 SNPs for creation of the Axiom^® SoyaSNP array. Validation analysis for a set of 222 diverse soybean lines showed that 170 223 markers were of good quality for genotyping. Phylogenetic and allele frequency analyses of the validation set data indicated that accessions showing an intermediate morphology between cultivated and wild soybeans collected in Korea were natural hybrids. More than 90 unanchored scaffolds in the current soybean reference sequence were assigned to chromosomes using this array. Finally, dense average spacing and preferential distribution of the SNPs in gene‐rich chromosomal regions suggest that this array may be suitable for genome‐wide association studies of soybean germplasm. Taken together, these results suggest that use of this array may be a powerful method for soybean genetic analyses relating to many aspects of soybean breeding.     

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.     

Discovery of SNPs in soybean genotypes frequently used as the parents of mapping populations in the United States and Korea

Single nucleotide polymorphisms (SNPs) including insertion/deletions (indels) serve as useful and informative genetic markers. The availability of high-throughput and inexpensive SNP typing systems has increased interest in the development of SNP markers. After fragments of genes were amplified with primers derived from 110 soybean GenBank ESTs, sequencing data of PCR products from 15 soybean genotypes from Korea and the United States were analyzed by SeqScape software to find SNPs. Among 35 gene fragments with at least one SNP among the 15 genotypes, SNPs occurred at a frequency of 1 per 2,038 bp in 16,302 bp of coding sequence and 1 per 191 bp in 16,960 bp of noncoding regions. This corresponds to a nucleotide diversity (theta) of 0.00017 and 0.00186, respectively. Of the 97 SNPs discovered, 78 or 80.4% were present in the six North American soybean mapping parents. The addition of "Hwaeomputkong," which originated from Japan, increased the number to 92, or 94.8% of the total number of SNPs present among the 15 genotypes. Thus, Hwaeomputkong and the six North American mapping parents provide a diverse set of soybean genotypes that can be successfully used for SNP discovery in coding DNA and closely associated introns and untranslated regions.     

High-throughput genotyping in citrus accessions using an SNP genotyping array

We developed a 384 multiplexed SNP array, named CitSGA-1, for the genotyping of Citrus cultivars, and evaluated the performance and reliability of the genotyping. SNPs were surveyed by direct sequence comparison of the sequence tagged site (STS) fragment amplified from genomic DNA of cultivars representing the genetic diversity of citrus breeding in Japan. Among 1497 SNPs candidates, 384 SNPs for a high-throughput genotyping array were selected based on physical parameters of Illumina’s bead array criteria. The assay using CitSGA-1 was applied to a hybrid population of 88 progeny and 103 citrus accessions for breeding in Japan, which resulted in 73,726 SNP calls. A total of 351 SNPs (91 %) could call different genotypes among the DNA samples, resulting in a success rate for the assay comparable to previously reported rates for other plant species. To confirm the reliability of SNP genotype calls, parentage analysis was applied, and it indicated that the number of reliable SNPs and corresponding STSs were 276 and 213, respectively. The multiplexed SNP genotyping array reported here will be useful for the efficient construction of linkage map, for the detection of markers for marker-assisted breeding, and for the identification of cultivars.