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.     

SNPstream UHT: ultra-high throughput SNP genotyping for pharmacogenomics and drug discovery

Single nucleotide polymorphism (SNP) genotyping is playing an increasing role in genome mapping, pharmacogenetic studies, and drug discovery. To date, genome-wide scans and studies involving thousands of SNPs and samples have been hampered by the lack of a system that can perform genotyping with cost-effective throughput, accuracy, and reliability. To address this need, Orrhid has developed an automated, ultra-high throughput system, SNPstream UHT, which uses multiplexed PCR in conjunction with our next generation SNP-IT tag array single base extension genotyping technology The system employs oligonucleotide microarrays manufactured in a 384-well format on a novel glass-bottomed plate. Multiplexed PCR and genotyping are performed in homogeneous reactions, and assay results are read by direct two-color fluorescence on the SNPstream UHTArray Imager. The systems flexibility enables large projects involving thousands of SNPs and thousands of samples as well as small projects that have hundreds of SNPs and hundreds of samples to be done cost effectively. We have successfully demonstrated this system in greater than 1,000,000 genotyping assays with >96% of samples giving genotypes with >99% accuracy     

High-throughput SNP genotyping on universal bead arrays

We have developed a flexible, accurate and highly multiplexed SNP genotyping assay for high-throughput genetic analysis of large populations on a bead array platform. The novel genotyping system combines high assay conversion rate and data quality with >1500 multiplexing, and Array of Arrays formats. Genotyping assay oligos corresponding to specific SNP sequences are each linked to a unique sequence (address) that can hybridize to its complementary strand on universal arrays. The arrays are made of beads located in microwells of optical fiber bundles (Sentrix Array Matrix) or silicon slides (Sentrix BeadChip). The optical fiber bundles are further organized into a matrix that matches a 96-well microtiter plate. The arrays on the silicon slides are multi-channel pipette compatible for loading multiple samples onto a single silicon slide. These formats allow many samples to be processed in parallel. This genotyping system enables investigators to generate approximately 300,000 genotypes per day with minimal equipment requirements and greater than 1.6 million genotypes per day in a robotics-assisted process. With a streamlined and comprehensive assay, this system brings a new level of flexibility, throughput, and affordability to genetic research.     

Using Next Generation Sequencing for Multiplexed Trait-Linked Markers in Wheat

With the advent of next generation sequencing (NGS) technologies, single nucleotide polymorphisms (SNPs) have become the major type of marker for genotyping in many crops. However, the availability of SNP markers for important traits of bread wheat ( Triticum aestivum L.) that can be effectively used in marker-assisted selection (MAS) is still limited and SNP assays for MAS are usually uniplex. A shift from uniplex to multiplex assays will allow the simultaneous analysis of multiple markers and increase MAS efficiency. We designed 33 locus-specific markers from SNP or indel-based marker sequences that linked to 20 different quantitative trait loci (QTL) or genes of agronomic importance in wheat and analyzed the amplicon sequences using an Ion Torrent Proton Sequencer and a custom allele detection pipeline to determine the genotypes of 24 selected germplasm accessions. Among the 33 markers, 27 were successfully multiplexed and 23 had 100% SNP call rates. Results from analysis of "kompetitive allele-specific PCR" (KASP) and sequence tagged site (STS) markers developed from the same loci fully verified the genotype calls of 23 markers. The NGS-based multiplexed assay developed in this study is suitable for rapid and high-throughput screening of SNPs and some indel-based markers in wheat.     

Development of a SNP genotyping panel for genetic monitoring of the laboratory mouse

We have developed a genotyping system for detecting genetic contamination in the laboratory mouse based on assaying single-nucleotide polymorphism (SNP) markers positioned on all autosomes and the X chromosome. This system provides a fast, reliable, and cost-effective way for genetic monitoring, while maintaining a very high degree of confidence. We describe the allelic distribution of 235 SNPs in 48 mouse strains, thereby creating a database of polymorphisms useful for genotyping purposes. The SNP markers used in this study were chosen from publicly available SNP databases. Four genotyping methods were evaluated, and dynamic two-tube allele-specific PCR assays were developed for each marker and tested on a set of 48 inbred mouse strains. The minimal number of assays sufficient to distinguish groups consisting of different numbers of mouse strains was estimated, and a panel of 28 SNPs sufficient to distinguish virtually all of the inbred strains tested was selected. Amplifluor SNP detection assays were developed for these markers and tested on an extended list of 96 strains. This panel was used as a genetic quality control approach to monitor the genotypes of nearly 300 inbred, wild-derived, congenic, consomic, and recombinant inbred strains maintained at The Jackson Laboratory. We have concluded that this marker panel is sufficient for genetic contamination monitoring in colonies containing a large number of genetically diverse mouse strains and that reduced versions of the panel could be implemented in facilities housing a lower number of strains.     

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.     

Multiplexed SNP genotyping using the Qbead system: a quantum dot-encoded microsphere-based assay

We have developed a new method using the Qbead system for high-throughput genotyping of single nucleotide polymorphisms (SNPs). The Qbead system employs fluorescent Qdot semiconductor nanocrystals, also known as quantum dots, to encode microspheres that subsequently can be used as a platform for multiplexed assays. By combining mixtures of quantum dots with distinct emission wavelengths and intensities, unique spectral 'barcodes' are created that enable the high levels of multiplexing required for complex genetic analyses. Here, we applied the Qbead system to SNP genotyping by encoding microspheres conjugated to allele-specific oligonucleotides. After hybridization of oligonucleotides to amplicons produced by multiplexed PCR of genomic DNA, individual microspheres are analyzed by flow cytometry and each SNP is distinguished by its unique spectral barcode. Using 10 model SNPs, we validated the Qbead system as an accurate and reliable technique for multiplexed SNP genotyping. By modifying the types of probes conjugated to microspheres, the Qbead system can easily be adapted to other assay chemistries for SNP genotyping as well as to other applications such as analysis of gene expression and protein-protein interactions. With its capability for high-throughput automation, the Qbead system has the potential to be a robust and cost-effective platform for a number of applications.     

Single nucleotide polymorphisms for pig identification and parentage exclusion

Single nucleotide polymorphisms (SNPs) have become an important type of marker for commercial diagnostic and parentage genotyping applications as automated genotyping systems have been developed that yield accurate genotypes. Unfortunately, allele frequencies for public SNP markers in commercial pig populations have not been available. To fulfil this need, SNP markers previously mapped in the USMARC swine reference population were tested in a panel of 155 boars that were representative of US purebred Duroc, Hampshire, Landrace and Yorkshire populations. Multiplex assay groups of 5-7 SNP assays/group were designed and genotypes were determined using Sequenom's massarray system. Of 80 SNPs that were evaluated, 60 SNPs with minor allele frequencies >0.15 were selected for the final panel of markers. Overall identity power across breeds was 4.6 x 10(-23), but within-breed values ranged from 4.3 x 10(-14) (Hampshire) to 2.6 x 10(-22) (Yorkshire). Parentage exclusion probability with only one sampled parent was 0.9974 (all data) and ranged from 0.9594 (Hampshire) to 0.9963 (Yorkshire) within breeds. Sire exclusion probability when the dam's genotype was known was 0.99998 (all data) and ranged from 0.99868 (Hampshire) to 0.99997 (Yorkshire) within breeds. Power of exclusion was compared between the 60 SNP and 10 microsatellite markers. The parental exclusion probabilities for SNP and microsatellite marker panels were similar, but the SNP panel was much more sensitive for individual identification. This panel of SNP markers is theoretically sufficient for individual identification of any pig in the world and is publicly available.     

High-throughput SNP genotyping by single-tube PCR with Tm-shift primers

Despite many recent advances in high-throughput single nucleotide polymorphism (SNP) genotyping technologies, there is still a great need for inexpensive and flexible methods with a reasonable throughput. Here we report substantial modifications and improvements to an existing homogenous allele-specific PCR-based SNP genotyping method, making it an attractive new option for researchers engaging in candidate gene studies or following up on genome-wide scans. In this advanced version of the melting temperature (Tm)-shift SNP genotyping method, we attach two GC-rich tails of different lengths to allele-specific PCR primers, such that SNP alleles in genomic DNA samples can be discriminated by the Tms of the PCR products. We have validated 306 SNP assays using this method and achieved a success rate in assay development of greater than 83% under uniform PCR conditions. We have developed a standalone software application to automatically assign genotypes directly from melting curve data. To demonstrate the accuracy of this method, we typed 592 individuals for 6 SNPs and showed a high call rate (>98%) and high accuracy (>99.9%). With this method, 6-10,000 samples can be genotyped per day using a single 384-well real-time thermal cycler with 2-4 standard 384-well PCR instruments.     

Multiplexed SNP genotyping using the Qbead™ system: a quantum dot-encoded microsphere-based assay

We have developed a new method using the Qbead™ system for high-throughput genotyping of single nucleotide polymorphisms (SNPs). The Qbead system employs fluorescent Qdot™ semiconductor nanocrystals, also known as quantum dots, to encode microspheres that subsequently can be used as a platform for multiplexed assays. By combining mixtures of quantum dots with distinct emission wavelengths and intensities, unique spectral ‘barcodes’ are created that enable the high levels of multiplexing required for complex genetic analyses. Here, we applied the Qbead system to SNP genotyping by encoding microspheres conjugated to allele-specific oligonucleotides. After hybridization of oligonucleotides to amplicons produced by multiplexed PCR of genomic DNA, individual microspheres are analyzed by flow cytometry and each SNP is distinguished by its unique spectral barcode. Using 10 model SNPs, we validated the Qbead system as an accurate and reliable technique for multiplexed SNP genotyping. By modifying the types of probes conjugated to microspheres, the Qbead system can easily be adapted to other assay chemistries for SNP genotyping as well as to other applications such as analysis of gene expression and protein–protein interactions. With its capability for high-throughput automation, the Qbead system has the potential to be a robust and cost-effective platform for a number of applications.     

A molecular beacon, bead-based assay for the detection of nucleic acids by flow cytometry

Molecular beacons are dual-labelled probes that are typically used in real-time PCR assays, but have also been conjugated with solid matrices for use in microarrays or biosensors. We have developed a fluid array system using microsphere-conjugated molecular beacons and the flow cytometer for the specific, multiplexed detection of unlabelled nucleic acids in solution. For this array system, molecular beacons were conjugated with microspheres using a biotin-streptavidin linkage. A bridged conjugation method using streptavidin increased the signal-to-noise ratio, allowing for further discrimination of target quantitation. Using beads of different sizes and molecular beacons in two fluorophore colours, synthetic nucleic acid control sequences were specifically detected for three respiratory pathogens, including the SARS coronavirus in proof-of-concept experiments. Considering that routine flow cytometers are able to detect up to four fluorescent channels, this novel assay may allow for the specific multiplex detection of a nucleic acid panel in a single tube.     

Universal SNP genotyping assay with fluorescence polarization detection

The degree of fluorescence polarization (FP) of a fluorescent molecule is a reflection of its molecular weight (Mr). FP is therefore a useful detection methodfor homogeneous assays in which the starting reagents and products differ significantly in Mr. We have previously shown that FP is a good detection method for the single-base extension and the 5'-nuclease assays. In this report, we describe a universal, optimized single-base extension assay for genotyping single nucleotide polymorphisms (SNPs). This assay, which we named the template-directed dye-terminator incorporation assay with fluorescence polarization detection (FP-TDI), uses four spectrally distinct dye terminators to achieve universal assay conditions. Even without optimization, approximately 70% of all SNP markers tested yielded robust assays. The addition of an E. coli ssDNA-binding protein just before the FP reading significantly increased FP values of the products and brought the success rate of FP-TDI assays up to 90%. Increasing the amount of dye terminators and reducing the number of thermal cycles in the single-base extension step of the assay increased the separation of the FP values benveen the products corresponding to different genotypes and improved the success rate of the assay to 100%. In this study the genomic DNA samples of 90 individuals were typed for a total of 38 FP-TDI assays (using both the sense and antisense TDI primers for 19 SNP markers). With the previously described modifications, the FP-TDI assay gave unambiguous genotyping data for all the samples tested in the 38 FP-TDI assays. When the genotypes determined by the FP-TDI and 5'-nuclease assays were compared, they were in 100% concordance for all experiments (a total of 3420 genotypes). The four-dye-terminator master mixture described here can be used for assaying any SNP marker and greatly simplifies the SNP genotyping assay design.     

Genotype imputation in the domestic dog

Application of imputation methods to accurately predict a dense array of SNP genotypes in the dog could provide an important supplement to current analyses of array-based genotyping data. Here, we developed a reference panel of 4,885,283 SNPs in 83 dogs across 15 breeds using whole genome sequencing. We used this panel to predict the genotypes of 268 dogs across three breeds with 84,193 SNP array-derived genotypes as inputs. We then (1) performed breed clustering of the actual and imputed data; (2) evaluated several reference panel breed combinations to determine an optimal reference panel composition; and (3) compared the accuracy of two commonly used software algorithms (Beagle and IMPUTE2). Breed clustering was well preserved in the imputation process across eigenvalues representing 75 % of the variation in the imputed data. Using Beagle with a target panel from a single breed, genotype concordance was highest using a multi-breed reference panel (92.4 %) compared to a breed-specific reference panel (87.0 %) or a reference panel containing no breeds overlapping with the target panel (74.9 %). This finding was confirmed using target panels derived from two other breeds. Additionally, using the multi-breed reference panel, genotype concordance was slightly higher with IMPUTE2 (94.1 %) compared to Beagle; Pearson correlation coefficients were slightly higher for both software packages (0.946 for Beagle, 0.961 for IMPUTE2). Our findings demonstrate that genotype imputation from SNP array-derived data to whole genome-level genotypes is both feasible and accurate in the dog with appropriate breed overlap between the target and reference panels.     

Genome-wide linkage analysis for alcohol dependence: a comparison between single-nucleotide polymorphism and microsatellite marker assays

Both theoretical and applied studies have proven that the utility of single nucleotide polymorphism (SNP) markers in linkage analysis is more powerful and cost-effective than current microsatellite marker assays. Here we performed a whole-genome scan on 115 White, non-Hispanic families segregating for alcohol dependence, using one 10.3-cM microsatellite marker set and two SNP data sets (0.33-cM, 0.78-cM spacing). Two definitions of alcohol dependence (ALDX1 and ALDX2) were used. Our multipoint nonparametric linkage analysis found alcoholism was nominal linked to 12 genomic regions. The linkage peaks obtained by using the microsatellite marker set and the two SNP sets had a high degree of correspondence in general, but the microsatellite marker set was insufficient to detect some nominal linkage peaks. The presence of linkage disequilibrium between markers did not significantly affect the results. Across the entire genome, SNP datasets had a much higher average linkage information content (0.33 cM: 0.93, 0.78 cM: 0.91) than did microsatellite marker set (0.57). The linkage peaks obtained through two SNP datasets were very similar with some minor differences. We conclude that genome-wide linkage analysis by using approximately 5,000 SNP markers evenly distributed across the human genome is sufficient and might be more powerful than current 10-cM microsatellite marker assays.     

Establishment of a high-efficiency SNP-based framework marker set for Arabidopsis

The major goal of this project was the establishment of a tool for rapid mapping of new mutations and genotyping in Arabidopsis consisting of at least 100 evenly spaced framework markers. We assembled a single nucleotide polymorphism (SNP)-based marker set consisting of 112 polymorphic sites with average spacing of 1.15 Mbp derived from an SNP database that we recently developed. This information was used to set up efficient SNP detection reactions based on multiplexed primer extension assays. The 112 Columbia (Col-0)/C24 framework markers were used to assemble 18 multiplexed SNaPshot assays with which up to eight separate loci can be genotyped in a single-tube/single-capillary format. In addition, for 110 framework markers matrix-assisted laser desorption/ionization time of flight (MALDI-ToF) assays have been established for high throughput analyses. We demonstrated the usefulness and the robustness of both procedures of this tool by genotyping 48 BC3F1 individuals created between the accessions Col-0 and C24. Subsets of 10-62 of the established markers discriminate between various combinations of the accessions Col-0, C24, Landsberg erecta (Ler), Cape Verdi Islands (Cvi) and Niederzenz (Nd). Using a subset of 17 evenly distributed and established SNP markers that are also polymorphic between Ler and Col-0, we were able to rapidly map a mutant gene (tbr1) to an interval of 2.3 Mbp in an Ler (tbr1) x Col-0 cross.     

The utility of low-density genotyping for imputation in the Thoroughbred horse

Background

Despite the dramatic reduction in the cost of high-density genotyping that has occurred over the last decade, it remains one of the limiting factors for obtaining the large datasets required for genomic studies of disease in the horse. In this study, we investigated the potential for low-density genotyping and subsequent imputation to address this problem.

Results

Using the haplotype phasing and imputation program, BEAGLE, it is possible to impute genotypes from low- to high-density (50K) in the Thoroughbred horse with reasonable to high accuracy. Analysis of the sources of variation in imputation accuracy revealed dependence both on the minor allele frequency of the single nucleotide polymorphisms (SNPs) being imputed and on the underlying linkage disequilibrium structure. Whereas equidistant spacing of the SNPs on the low-density panel worked well, optimising SNP selection to increase their minor allele frequency was advantageous, even when the panel was subsequently used in a population of different geographical origin. Replacing base pair position with linkage disequilibrium map distance reduced the variation in imputation accuracy across SNPs. Whereas a 1K SNP panel was generally sufficient to ensure that more than 80% of genotypes were correctly imputed, other studies suggest that a 2K to 3K panel is more efficient to minimize the subsequent loss of accuracy in genomic prediction analyses. The relationship between accuracy and genotyping costs for the different low-density panels, suggests that a 2K SNP panel would represent good value for money.

Conclusions

Low-density genotyping with a 2K SNP panel followed by imputation provides a compromise between cost and accuracy that could promote more widespread genotyping, and hence the use of genomic information in horses. In addition to offering a low cost alternative to high-density genotyping, imputation provides a means to combine datasets from different genotyping platforms, which is becoming necessary since researchers are starting to use the recently developed equine 70K SNP chip. However, more work is needed to evaluate the impact of between-breed differences on imputation accuracy.     

BARCSoySNP23: a panel of 23 selected SNPs for soybean cultivar identification

This report describes a set of 23 informative SNPs (BARCSoySNP23) distributed on 19 of the 20 soybean linkage groups that can be used for soybean cultivar identification. Selection of the SNPs to include in this set was made based upon the information provided by each SNP for distinguishing a diverse set of soybean genotypes as well as the linkage map position of each SNP. The genotypes included the ancestors of North American cultivars, modern North American cultivars and a group of Korean cultivars. The procedure used to identify this subset of highly informative SNP markers resulted in a significant increase in the power of identification versus any other randomly selected set of equal number. This conclusion was supported by a simulation which indicated that the 23-SNP panel can uniquely distinguish 2,200 soybean cultivars, whereas sets of randomly selected 23-SNP panels allowed the unique identification of only about 50 cultivars. The 23-SNP panel can efficiently distinguish each of the genotypes within four maturity group sets of additional cultivars/lines that have identical classical pigmentation and morphological traits. Comparatively, the 13 trinucleotide SSR set published earlier (BARCSoySSR13) has more power on a per locus basis because of the multi-allelic nature of SSRs. However, the assay of bi-allelic SNP loci can be multi-plexed using non-gel based techniques allowing for rapid determination of the SNP alleles present in soybean genotypes, thereby compensating for their relatively low information content. Both BARCSoySNP23 and BARCSoySSR13 were highly congruent relative to identifying genotypes and for estimating population genetic differences.     

Suspension arrays for high throughput, multiplexed single nucleotide polymorphism genotyping

BACKGROUND: Genetic diversity can help explain disease susceptibility and differential drug response. The most common type of variant is the single nucleotide polymorphism (SNP). We present a low-cost, high throughput assay for SNP genotyping. METHODS: The assay uses oligonucleotide probes covalently attached to fluorescently encoded microspheres. These probes are hybridized directly to fluorescently labeled polymerase chain reaction (PCR) products and the results are analyzed in a standard flow cytometer. RESULTS: The genotypes determined with our assay are in good agreement with those determined by TaqMan. The range of G/C content for oligonucleotide probes was 23.5-65% in the 17 bases surrounding the SNP. Further optimization of probe length and target concentration is shown to dramatically enhance the assay performance for certain SNPs. Using microspheres which have unique fluorescent signatures, we performed a 32-plex assay where we simultaneously determined the genotypes of eight different polymorphic genes. CONCLUSIONS: We demonstrate, for the first time, the feasibility of multiplexed genotyping with suspension arrays using direct hybridization analyses. Our approach enables probes to be removed from or added to an array, enhancing flexibility over conventional chips. The ability to multiplex both the PCR preparation and the hybridization should enhance the throughput, cost, and speed of the assay.     

GenoSNP: a variational Bayes within-sample SNP genotyping algorithm that does not require a reference population

Current genotyping algorithms typically call genotypes by clustering allele-specific intensity data on a single nucleotide polymorphism (SNP) by SNP basis. This approach assumes the availability of a large number of control samples that have been sampled on the same array and platform. We have developed a SNP genotyping algorithm for the Illumina Infinium SNP genotyping assay that is entirely within-sample and does not require the need for a population of control samples nor parameters derived from such a population. Our algorithm exhibits high concordance with current methods and >99% call accuracy on HapMap samples. The ability to call genotypes using only within-sample information makes the method computationally light and practical for studies involving small sample sizes and provides a valuable independent quality control metric for other population-based approaches. AVAILABILITY: http://www.stats.ox.ac.uk/~giannoul/GenoSNP/.     

Comparison of four flow cytometric SNP detection assays and their use in plant improvement

Single nucleotide polymorphisms (SNPs) are attractive DNA markers due to their abundance and potential for use in automated high-throughput genotyping. Numerous SNP genotyping assays have been developed, but it is unclear which assays are best suited and most efficient for various types of plant improvement research. The objective of this study was to compare the accuracy, efficiency, and cost of four SNP genotyping assays: single-base extension (SBE), allele-specific primer extension (ASPE), oligonucleotide ligation (OL), and direct hybridization (DH). All four assay methods used the same Luminex 100 flow cytometer platform. Fifty-eight F₂-derived soybean [Glycine max (L.) Merr.] lines from a cross between inbred lines G99-G725 and N00-3350 were genotyped at four SNPs. SBE and ASPE clearly differentiated between the two homozygotes and the heterozygote at each SNP. Results were in agreement with those identified using the SNaPshot minisequencing assay as a control. In contrast, the OL and DH assays were unable to differentiate between genotypes at some of the SNPs. However, when the cost per data point for the four different assays was compared, the cost of OL and DH was only about 70% of that for SBE, with DH requiring the least time of the four assays. On the basis of cost and labor, ASPE is more cost-effective and simpler than SBE, and would therefore be a good method for genetic mapping and diversity studies which require a large number of markers and a high level of multiplexing. DH appears to be the most economical assay for marker-assisted selection, though optimization for DH would be required for some SNP markers.