High-throughput SNP genotyping

Whole genome approaches using single nucleotide polymorphism (SNP) markers have the potential to transform complex disease genetics and expedite pharmacogenetics research. This has led to a requirement for high-throughput SNP genotyping platforms. Development of a successful high-throughput genotyping platform depends on coupling reliable assay chemistry with an appropriate detection system to maximise efficiency with respect to accuracy, speed and cost. Current technology platforms are able to deliver throughputs in excess of 100 000 genotypes per day, with an accuracy of >99%, at a cost of 20-30 cents per genotype. In order to meet the demands of the coming years, however, genotyping platforms need to deliver throughputs in the order of one million genotypes per day at a cost of only a few cents per genotype. In addition, DNA template requirements must be minimised such that hundreds of thousands of SNPs can be interrogated using a relatively small amount of genomic DNA. As such, it is predicted that the next generation of high-throughput genotyping platforms will exploit large-scale multiplex reactions and solid phase assay detection systems.     

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.     

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.     

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.     

Large SNP arrays for genotyping in crop plants

Genotyping with large numbers of molecular markers is now an indispensable tool within plant genetics and breeding. Especially through the identification of large numbers of single nucleotide polymorphism (SNP) markers using the novel high-throughput sequencing technologies, it is now possible to reliably identify many thousands of SNPs at many different loci in a given plant genome. For a number of important crop plants, SNP markers are now being used to design genotyping arrays containing thousands of markers spread over the entire genome and to analyse large numbers of samples. In this article, we discuss aspects that should be considered during the design of such large genotyping arrays and the analysis of individuals. The fact that crop plants are also often autopolyploid or allopolyploid is given due consideration. Furthermore, we outline some potential applications of large genotyping arrays including high-density genetic mapping, characterization (fingerprinting) of genetic material and breeding-related aspects such as association studies and genomic selection.     

High-throughput polymorphism screening and genotyping with high-density oligonucleotide arrays

A highly reliable and efficient technology has been developed for high-throughput DNA polymorphism screening and large-scale genotyping. Photolithographic synthesis has been used to generate miniaturized, high-density oligonucleotide arrays. Dedicated instrumentation and software have been developed for array hybridization, fluorescent detection, and data acquisition and analysis. Specific oligonucleotide probe arrays have been designed to rapidly screen human STSs, known genes and full-length cDNAs. This has led to the identification of several thousand biallelic single-nucleotide polymorphisms (SNPs). Meanwhile, a rapid and robust method has been developed for genotyping these SNPs using oligonucleotide arrays. Each allele of an SNP marker is represented on the array by a set of perfect match and mismatch probes. Prototype genotyping chips have been produced to detect 400, 600 and 3000 of these SNPs. Based on the preliminary results, using oligonucleotide arrays to genotype several thousand polymorphic loci simultaneously appears feasible.     

High-throughput SNP genotyping based on solid-phase PCR on magnetic nanoparticles with dual-color hybridization

Single-nucleotide polymorphisms (SNPs) are one-base variations in DNA sequence that can often be helpful when trying to find genes responsible for inherited diseases. In this paper, a microarray-based method for typing single nucleotide polymorphisms (SNPs) using solid-phase polymerase chain reaction (PCR) on magnetic nanoparticles (MNPs) was developed. One primer with biotin-label was captured by streptavidin coated magnetic nanoparticles (SA-MNPs), and PCR products were directly amplified on the surface of SA-MNPs in a 96-well plate. The samples were interrogated by hybridization with a pair of dual-color probes to determine SNP, and then genotype of each sample can be simultaneously identified by scanning the microarray printed with the denatured fluorescent probes. The C677T polymorphisms of methylenetetrahydrofolate reductase (MTHFR) gene from 126 samples were interrogated using this method. The results showed that three different genotypes were discriminated by three fluorescence patterns on the microarray. Without any purification and reduction procedure, and all reactions can be performed in the same vessel, this approach will be a simple and labor-saving method for SNP genotyping and can be applicable towards the automation system to achieve high-throughput SNP detection.     

High-throughput molecular identification of fish eggs using multiplex suspension bead arrays

The location and abundance of fish eggs provide information concerning the timing and location of spawning activities and can provide fishery-independent estimates of spawning biomass. However, the full value of egg and larval surveys is severely restricted because many species' eggs and larvae are morphologically similar, making species-level identification difficult. Recent efforts have shown that nearly all species of fish may be identified by mitochondrial DNA (mtDNA) sequences (e.g. via 'DNA barcoding'). By taking advantage of a DNA barcode database, we have developed oligonucleotide probes for 23 marine fish species that produce pelagic eggs commonly found in California waters. Probes were coupled to fluorescent microspheres to create a suspension bead array. Biotin-labelled primers were used to amplify the mitochondrial cytochrome oxidase subunit I (COI) and 16S ribosomal rRNA genes from individual fish eggs. The amplicons were then hybridized to the bead array, and after the addition of a reporter fluorophore, samples were analysed by flow cytometry with Luminex 100 instrumentation. Probes specifically targeted eggs that are abundant and/or from morphologically indistinguishable species pairs. Results showed that the 33 different probes designed for this study accurately identified all samples when PCR was successful. Suspension bead arrays have a number of benefits over other methods of molecular identification; these arrays permit high multiplexing, simple addition of new probes, high throughput and lower cost than DNA sequencing. The increasing availability of DNA barcode data for numerous fish faunas worldwide suggests that bead arrays could be developed and widely used for fish egg, larval and tissue identifications.     

Technical reproducibility of genotyping SNP arrays used in genome-wide association studies

During the last several years, high-density genotyping SNP arrays have facilitated genome-wide association studies (GWAS) that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified genetic variants only explains a very small fraction of the underlying genetic contribution to the studied phenotypic trait. Moreover, discordance observed in results between independent GWAS indicates the potential for Type I and II errors. High reliability of genotyping technology is needed to have confidence in using SNP data and interpreting GWAS results. Therefore, reproducibility of two widely genotyping technology platforms from Affymetrix and Illumina was assessed by analyzing four technical replicates from each of the six individuals in five laboratories. Genotype concordance of 99.40% to 99.87% within a laboratory for the sample platform, 98.59% to 99.86% across laboratories for the same platform, and 98.80% across genotyping platforms was observed. Moreover, arrays with low quality data were detected when comparing genotyping data from technical replicates, but they could not be detected according to venders' quality control (QC) suggestions. Our results demonstrated the technical reliability of currently available genotyping platforms but also indicated the importance of incorporating some technical replicates for genotyping QC in order to improve the reliability of GWAS results. The impact of discordant genotypes on association analysis results was simulated and could explain, at least in part, the irreproducibility of some GWAS findings when the effect size (i.e. the odds ratio) and the minor allele frequencies are low.     

Automated SNP genotype clustering algorithm to improve data completeness in high-throughput SNP genotyping datasets from custom arrays

High-throughput SNP genotyping platforms use automated genotype calling algorithms to assign genotypes. While these algorithms work efficiently for individual platforms, they are not compatible with other platforms, and have individual biases that result in missed genotype calls. Here we present data on the use of a second complementary SNP genotype clustering algorithm. The algorithm was originally designed for individual fluorescent SNP genotyping assays, and has been optimized to permit the clustering of large datasets generated from custom-designed Affymetrix SNP panels. In an analysis of data from a 3K array genotyped on 1,560 samples, the additional analysis increased the overall number of genotypes by over 45,000, significantly improving the completeness of the experimental data. This analysis suggests that the use of multiple genotype calling algorithms may be advisable in high-throughput SNP genotyping experiments. The software is written in Perl and is available from the corresponding author.     

Pyrosequencing protocol using a universal biotinylated primer for mutation detection and SNP genotyping

DNA sequencing has markedly changed the nature of biomedical research, identifying millions of polymorphisms along the human genome that now require further analysis to study the genetic basis of human diseases. Among the DNA-sequencing platforms available, Pyrosequencing has become a useful tool for medium-throughput single nucleotide polymorphism (SNP) genotyping, mutation detection, copy-number studies and DNA methylation analysis. Its 96-well genotyping format allows reliable results to be obtained at reasonable costs in a few minutes. However, a specific biotinylated primer is usually required for each SNP under study to allow the capture of single-stranded DNA template for the Pyrosequencing assay. Here, we present an alternative to the standard labeling of PCR products for analysis by Pyrosequencing that circumvents the requirement of specific biotinylated primers for each SNP of interest. This protocol uses a single biotinylated primer that is simultaneously incorporated into all M13-tagged PCR products during the amplification reaction. The protocol covers all steps from the PCR amplification and capture of single-stranded template, its preparation, and the Pyrosequencing assay itself. Once the correct primer stoichiometry has been determined, the assay takes around 2 h for PCR amplification, followed by 15-20 min (per plate) to obtain the genotypes.     

Copy number variation detection using SNP genotyping arrays in three Chinese pig breeds

We performed genome‐wide CNV detection based on SNP genotyping data of 96 Chinese‐native Tibetan, Dahe and Wuzhishan pigs. These pigs are particularly interesting because of their excellent adaptation to hypoxia or small body size, which facilitates the use of them as models of different human diseases in addition to valuable agricultural animals. A total of 105 CNV regions (CNVRs) were identified, encompassing 16.71 Mb of the pig genome. Seven of 10 (70%) CNVRs selected randomly were validated by quantitative real‐time PCR. Comparison with previous studies revealed 25 (23.81%) novel CNVRs, indicating that CNV coverage of the pig genome is still incomplete and there exists large diversity between pig breeds. Functional analysis of genes located in these CNVRs confirmed the high representation of genes involved in sensory perception, neurological system processes and other basic metabolic processes. In addition, the majority of these CNVRs were detected to span reported pig QTL that affect various traits, which highlighted three biologically interesting genes with copy number changes (i.e., ANKRD34B, FAM110B and ABCG1). These genes may have economic importance in pig breeding and are worth being further investigated. We also obtained some CNVRs harboring genes that had human orthologs involved in human diseases such as cardiovascular disease and Alzheimer's disease. The findings of this study are a significant extension of the coverage of CNVRs in the pig genome and provide valuable resources for follow‐up‐associated studies of CNVs in pig complex traits as well as important implications of human diseases.     

A genome-wide detection of copy number variation using SNP genotyping arrays in Beijing-You chickens

Copy number variation (CNV) has been recently examined in many species and is recognized as being a source of genetic variability, especially for disease-related phenotypes. In this study, the PennCNV software, a genome-wide CNV detection system based on the 60 K SNP BeadChip was used on a total sample size of 1,310 Beijing-You chickens (a Chinese local breed). After quality control, 137 high confidence CNVRs covering 27.31 Mb of the chicken genome and corresponding to 2.61 % of the whole chicken genome. Within these regions, 131 known genes or coding sequences were involved. Q-PCR was applied to verify some of the genes related to disease development. Results showed that copy number of genes such as, phosphatidylinositol-5-phosphate 4-kinase II alpha, PHD finger protein 14, RHACD8 (a CD8α- like messenger RNA), MHC B-G, zinc finger protein, sarcosine dehydrogenase and ficolin 2 varied between individual chickens, which also supports the reliability of chip-detection of the CNVs. As one source of genomic variation, CNVs may provide new insight into the relationship between the genome and phenotypic characteristics.     

Evaluation of genotyping concordance for commercial bovine SNP arrays using quality‐assurance samples

SNP arrays are widely used in genetic research and agricultural genomics applications, and the quality of SNP genotyping data is of paramount importance. In the present study, SNP genotyping concordance and discordance were evaluated for commercial bovine SNP arrays based on two types of quality assurance (QA) samples provided by Neogen GeneSeek. The genotyping discordance rates (GDRs) between chips were on average between 0.06% and 0.37% based on the QA type I data and between 0.05% and 0.15% based on the QA type II data. The average genotyping error rate (GER) pertaining to single SNP chips, based on the QA type II data, varied between 0.02% and 0.08% per SNP and between 0.01% and 0.06% per sample. These results indicate that genotyping concordance rate was high (i.e. from 99.63% to 99.99%). Nevertheless, mitochondrial and Y chromosome SNPs had considerably elevated GDRs and GERs compared to the SNPs on the 29 autosomes and X chromosome. The majority of genotyping errors resulted from single allotyping errors, which also included the opposite instances for allele ‘dropout’ (i.e. from AB to AA or BB). Simultaneous allotyping errors on both alleles (e.g. mistaking AA for BB or vice versa) were relatively rare. Finally, a list of SNPs with a GER greater than 1% is provided. Interpretation of association effects of these SNPs, for example in genome‐wide association studies, needs to be taken with caution. The genotyping concordance information needs to be considered in the optimal design of future bovine SNP arrays.     

High-throughput genotyping of hop (Humulus lupulus L.) utilising diversity arrays technology (DArT)

Implementation of molecular methods in hop (Humulus lupulus L.) breeding is dependent on the availability of sizeable numbers of polymorphic markers and a comprehensive understanding of genetic variation. However, use of molecular marker technology is limited due to expense, time inefficiency, laborious methodology and dependence on DNA sequence information. Diversity arrays technology (DArT) is a high-throughput cost-effective method for the discovery of large numbers of quality polymorphic markers without reliance on DNA sequence information. This study is the first to utilise DArT for hop genotyping, identifying 730 polymorphic markers from 92 hop accessions. The marker quality was high and similar to the quality of DArT markers previously generated for other species; although percentage polymorphism and polymorphism information content (PIC) were lower than in previous studies deploying other marker systems in hop. Genetic relationships in hop illustrated by DArT in this study coincide with knowledge generated using alternate methods. Several statistical analyses separated the hop accessions into genetically differentiated North American and European groupings, with hybrids between the two groups clearly distinguishable. Levels of genetic diversity were similar in the North American and European groups, but higher in the hybrid group. The markers produced from this time and cost-efficient genotyping tool will be a valuable resource for numerous applications in hop breeding and genetics studies, such as mapping, marker-assisted selection, genetic identity testing, guidance in the maintenance of genetic diversity and the directed breeding of superior cultivars.     

Redundancy in genotyping arrays

Despite their unprecedented density, current SNP genotyping arrays contain large amounts of redundancy, with up to 40 oligonucleotide features used to query each SNP. By using publicly available reference genotype data from the International HapMap, we show that 93.6% sensitivity at <5% false positive rate can be obtained with only four probes per SNP, compared with 98.3% with the full data set. Removal of this redundancy will allow for more comprehensive whole-genome association studies with increased SNP density and larger sample sizes.     

Genomewide linkage searches for Mendelian disease loci can be efficiently conducted using high-density SNP genotyping arrays

Genomewide linkage searches aimed at identifying disease susceptibility loci are generally conducted using 300–400 microsatellite markers. Genotyping bi-allelic single nucleotide polymorphisms (SNPs) provides an alternative strategy. The availability of dense SNP maps coupled with recent technological developments in highly paralleled SNP genotyping makes it practical to now consider the use of these markers for whole-genome genetic linkage analyses. Here, we report the findings from three successful genomewide linkage analyses of families segregating autosomal recessively inherited neonatal diabetes, craniosynostosis and dominantly inherited renal dysplasia using the Affymetrix 10K SNP array. A single locus was identified for each disease state, two of which are novel. The performance of the SNP array, both in terms of efficiency and precision, indicates that such platforms will become the dominant technology for performing genomewide linkage searches.     

MARA: a novel approach for highly multiplexed locus-specific SNP genotyping using high-density DNA oligonucleotide arrays

We have developed a locus-specific DNA target preparation method for highly multiplexed single nucleotide polymorphism (SNP) genotyping called MARA (Multiplexed Anchored Runoff Amplification). The approach uses a single primer per SNP in conjunction with restriction enzyme digested, adapter-ligated human genomic DNA. Each primer is composed of common sequence at the 5′ end followed by locus-specific sequence at the 3′ end. Following a primary reaction in which locus-specific products are generated, a secondary universal amplification is carried out using a generic primer pair corresponding to the oligonucleotide and genomic DNA adapter sequences. Allele discrimination is achieved by hybridization to high-density DNA oligonucleotide arrays. Initial multiplex reactions containing either 250 primers or 750 primers across nine DNA samples demonstrated an average sample call rate of ~95% for 250- and 750-plex MARA. We have also evaluated >1000- and 4000-primer plex MARA to genotype SNPs from human chromosome 21. We have identified a subset of SNPs corresponding to a primer conversion rate of ~75%, which show an average call rate over 95% and concordance >99% across seven DNA samples. Thus, MARA may potentially improve the throughput of SNP genotyping when coupled with allele discrimination on high-density arrays by allowing levels of multiplexing during target generation that far exceed the capacity of traditional multiplex PCR.