Large-scale genotyping by mass spectrometry: experience, advances and obstacles

Single nucleotide polymorphism (SNP) genotyping has become a key technology for genetic studies. In recent years, matrix-assisted laser desorption/ionization (MALDI) time-of-flight mass spectrometry has emerged as a very powerful method for SNP genotyping. Here, we discuss our experience in implementing a high-throughput SNP genotyping facility based on MALDI, and the issues encountered in adapting this to large-scale genetic studies. Most of these issues are not specific to using MALDI approaches, and they will also serve as valuable pointers for establishing high-throughput genotyping with other methods.     

Full flexibility genotyping of single nucleotide polymorphisms by the GOOD assay

Recently a facile method for genotyping single nucleotide polymorphisms (SNPs) using MALDI mass spectrometry, termed the GOOD assay, was developed. It does not require any purification and is performed with simple liquid handling, thermal incubation and cycling steps. Although this method is well suited to automation and high-throughput analysis of SNPs, it did not allow full flexibility due to lack of certain reagents. A complete set of β-cyanoethyl phosphoramidites is presented herein that give this SNP genotyping method full sequence and multiplex capabilities. Applications to SNP genotyping in the prion protein gene, the β-2-adrenergic receptor gene and the angiotensin converting enzyme gene using the GOOD assay are demonstrated. Because SNP genotyping technologies are generally very sensitive to varying DNA quality, the GOOD assay has been stabilised and optimised for low quality DNA. A template extraction method is introduced that allows genotyping from tissue that was taken while placing an ear tag on an animal. This dramatically facilitates the application of genotyping to animal agricultural applications, as it demonstrates that expensive and cumbersome DNA extraction procedures prior to genotyping can be avoided.     

MALDI mass spectrometry analysis of single nucleotide polymorphisms by photocleavage and charge-tagging

High-throughput procedures are an important requirement for future large-scale genetic studies such as genotyping of single nucleotide polymorphisms (SNPs). Matrix-assisted laser desorption/ ionisation mass spectrometry (MALDI-MS) has revolutionised the analysis of biomolecules and, in particular, provides a very attractive solution for the rapid typing of DNA. The analysis of DNA by MALDI can be significantly facilitated by a procedure termed ‘charge-tagging’. We show here a novel approach for the generation of charge-tagged DNA using a photocleavable linker and its implementation in a molecular biological procedure for SNP genotyping consisting of PCR, primer extension, photocleavage and a chemical reaction prior to MALDI target preparation and analysis. The reaction sequence is amenable to liquid handling automation and requires no stringent purification procedures. We demonstrate this new method on SNPs in two genes involved in complex traits.     

Facile method for automated genotyping of single nucleotide polymorphisms by mass spectrometry

In the future, analysis of single nucleotide polymorphisms (SNPs) should become a powerful tool for many genetic applications in areas such as association studies, pharmacogenetics and traceability in the agro-alimentary sector. A number of technologies have been developed for high-throughput genotyping of SNPs. Here we present the simplified GOOD assay for SNP genotyping by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI). The simplified GOOD assay is a single-tube, purification-free, three-step procedure consisting of PCR, primer extension and phosphodiesterase II digestion followed by mass spectrometric analysis. Due to the application of charge-tag technology, no sample purification is required prior to the otherwise very impurity-sensitive MALDI analysis. The use of methylphosphonate containing primers and ddNTPs or α-S-ddNTPs together with a novel DNA polymerase derived from Thermotoga maritima for primer extension allow the fluent preparation of negatively charge-tagged, allele-specific products. A key feature of this polymerase is its preference for ddNTPs and α-S-ddNTPs over dNTPs. The simplified GOOD assay was run with automatic liquid handling at the lowest manageable volumes, automatic data acquisition and interpretation. We applied this novel procedure to genotyping SNPs of candidate genes for hypertension and cardiovascular disease.     

Utilization of the three high-throughput SNP genotyping methods, the GOOD assay, Amplifluor and TaqMan, in diploid and polyploid plants

The application of high-throughput SNP genotyping is a great challenge for many research projects in the plant genetics domain. The GOOD assay for mass spectrometry, Amplifluor and TaqMan are three methods that rely on different principles for allele discrimination and detection, specifically, primer extension, allele-specific PCR and hybridization, respectively. First, with the goal of assessing allele frequencies by means of SNP genotyping, we compared these methods on a set of three SNPs present in the herbicide resistance genes CSR, AXR1 and IXR1 of Arabidopsis thaliana. In this comparison, we obtained the best results with TaqMan based on PCR specificity, flexibility in primer design and success rate. We also used mass spectrometry for genotyping polyploid species. Finally, a combination of the three methods was used for medium- to high-throughput genotyping in a number of different plant species. Here, we show that all three genotyping technologies are successful in discriminating alleles in various plant species and discuss the factors that must be considered in assessing which method to use for a given application.     

High concordance of bovine single nucleotide polymorphism genotypes generated using two independent genotyping strategies

Single nucleotide polymorphisms (SNPs) represent the most common form of DNA sequence variation in mammalian livestock genomes. While the past decade has witnessed major advances in SNP genotyping technologies, genotyping errors caused, in part, by the biochemistry underlying the genotyping platform used, can occur. These errors can distort project results and conclusions and can result in incorrect decisions in animal management and breeding programs; hence, SNP genotype calls must be accurate and reliable. In this study, 263 Bos spp. samples were genotyped commercially for a total of 16 SNPs. Of the total possible 4,208 SNP genotypes, 4,179 SNP genotypes were generated, yielding a genotype call rate of 99.31% (standard deviation?±?0.93%). Between 110 and 263 samples were subsequently re-genotyped by us for all 16 markers using a custom-designed SNP genotyping platform, and of the possible 3,819 genotypes a total of 3,768 genotypes were generated (98.70% genotype call rate, SD?±?1.89%). A total of 3,744 duplicate genotypes were generated for both genotyping platforms, and comparison of the genotype calls for both methods revealed 3,741 concordant SNP genotype call rates (99.92% SNP genotype concordance rate). These data indicate that both genotyping methods used can provide livestock geneticists with reliable, reproducible SNP genotypic data for in-depth statistical analysis.     

High Concordance of Bovine Single Nucleotide Polymorphism Genotypes Generated Using Two Independent Genotyping Strategies

Single nucleotide polymorphisms (SNPs) represent the most common form of DNA sequence variation in mammalian livestock genomes. While the past decade has witnessed major advances in SNP genotyping technologies, genotyping errors caused, in part, by the biochemistry underlying the genotyping platform used, can occur. These errors can distort project results and conclusions and can result in incorrect decisions in animal management and breeding programs; hence, SNP genotype calls must be accurate and reliable. In this study, 263 Bos spp. samples were genotyped commercially for a total of 16 SNPs. Of the total possible 4,208 SNP genotypes, 4,179 SNP genotypes were generated, yielding a genotype call rate of 99.31% (standard deviation ± 0.93%). Between 110 and 263 samples were subsequently re-genotyped by us for all 16 markers using a custom-designed SNP genotyping platform, and of the possible 3,819 genotypes a total of 3,768 genotypes were generated (98.70% genotype call rate, SD ± 1.89%). A total of 3,744 duplicate genotypes were generated for both genotyping platforms, and comparison of the genotype calls for both methods revealed 3,741 concordant SNP genotype call rates (99.92% SNP genotype concordance rate). These data indicate that both genotyping methods used can provide livestock geneticists with reliable, reproducible SNP genotypic data for in-depth statistical analysis.     

Detection of single nucleotide polymorphisms

Single nucleotide polymorphism (SNP) detection technologies are used to scan for new polymorphisms and to determine the allele(s) of a known polymorphism in target sequences. SNP detection technologies have evolved from labor intensive, time consuming, and expensive processes to some of the most highly automated, efficient, and relatively inexpensive methods. Driven by the Human Genome Project, these technologies are now maturing and robust strategies are found in both SNP discovery and genotyping areas. The nearly completed human genome sequence provides the reference against which all other sequencing data can be compared. Global SNP discovery is therefore only limited by the amount of funding available for the activity. Local, target, SNP discovery relies mostly on direct DNA sequencing or on denaturing high performance liquid chromatography (dHPLC). The number of SNP genotyping methods has exploded in recent years and many robust methods are currently available. The demand for SNP genotyping is great, however, and no one method is able to meet the needs of all studies using SNPs. Despite the considerable gains over the last decade, new approaches must be developed to lower the cost and increase the speed of SNP detection.     

SNP genotyping using alkali cleavage of RNA/DNA chimeras and MALDI time-of-flight mass spectrometry

Single nucleotide polymorphisms (SNPs) are now widely used for many DNA analysis applications such as linkage disequilibrium mapping, pharmacogenomics and traceability. Many methods for SNP genotyping exist with diverse strategies for allele-distinction. Mass spectrometers are used most commonly in conjunction with primer extension procedures with allele-specific termination. Here we present a novel concept for allele-preparation for SNP genotyping. Primer extension is carried out with an extension primer positioned immediately upstream of the SNP that is to be genotyped, a complete set of four ribonucleotides and a ribonucleotide incorporating DNA polymerase. The allele-extension products are then treated with alkali, which results in the cleavage immediately after the first added ribonucleotide. In addition, to obtain fragments easily detectable by mass spectrometry, we have included a ribonucleotide in the primer usually at the fourth nucleotide from the 3′ terminus. The method was tested on four SNPs each with a different combination of nucleotides. The advantage over other mass spectrometry-based SNP genotyping assays is that this one only requires a PCR, a primer extension reaction with a universal extension mix and an inexpensive facile cleavage reaction, which makes it overall very cost effective and easy in handling.     

Genomic selection prediction models comparing sequence capture and SNP array genotyping methods

The successful application of genomic selection (GS) approaches is dependent on genetic makers derived from high-throughput and low-cost genotyping methods. Recent GS studies in trees have predominantly relied on SNP arrays as the source of genotyping, though this technology has a high entry cost. The recent development of alternative genotyping platforms, tailored to specific species and with low entry cost, has become possible due to advances in next-generation sequencing and genome complexity reduction methods such as sequence capture. However, the performance of these new platforms in GS models has not yet been evaluated, or compared to models developed from SNP arrays. Here, we evaluate the impact of these genotyping technologies on the development of GS prediction models for a Eucalyptus breeding population composed of 739 trees phenotyped for 13 wood quality and growth traits. Genotyping data obtained with both methods were compared for linkage disequilibrium, minor allele frequency, and missing data. Phenotypic prediction methods RR-BLUP and BayesB were employed, while predictive ability using cross validation was used to evaluate the performance of GS models derived from the different genotyping platforms. Differences in linkage disequilibrium patterns, minor allele frequency, missing data, and marker distribution were detected between sequence capture and SNP arrays. However, RR-BLUP and BayesB GS models resulted in similar predictive abilities. These results demonstrate that both genotyping methods are equivalent for genomic prediction of the traits evaluated. Sequence capture offers an alternative for species where SNP arrays are not available, or for when the initial development cost is too high.     

Development of Genotyping Methods for Single Nucleotide Polymorphism in the Human Pancreatic Ribonuclease Gene (RNASE1) and Their Application to Population Studies

Two potential single nucleotide polymorphisms [SNPs; rs1804215 (G979T) and rs11545379 (G1169T)] have been identified in the human pancreatic ribonuclease, RNase 1, gene (RNASE1) that could give rise to an amino acid substitution in the protein, but relevant population data are not available. We have developed genotyping methods for each SNP using the mismatched PCR-restriction fragment length polymorphism technique. These methods are advantageous in comparison with other SNP genotyping methods because they are technically simpler and do not require specialized instruments. We applied these genotyping methods to examine the genotype distribution of each SNP in four populations, including Japanese populations living in two prefectures, an Ovambo population, and a Turkish population. In all the populations studied, however, only a single genotype for each SNP was found. Therefore, irrespective of differences in ethnic groups, RNASE1 might show markedly low heterogeneity in its genetic structure with regard to these SNPs.     

High throughput SNP genotyping with two mini-sequencing assays

Single nucleotide polymorphisms (SNPs) are veryimportant markers that can be used in many areas such asevolutionary genetics [1], disease-susceptibility genes[2,3], personalized medicine and forensics. Only about20% of human polymorphisms are length polymorphisms,whereas about 80% of human polymorphisms areSNPs. Kruglyak et al. [4] reported that there were about11,000,000 SNPs in the world population. There are many kinds of SNP genotyping technology[5,6]: some are only suitable to low …     

Cross‐platform compatibility of de novo‐aligned SNPs in a nonmodel butterfly genus

High‐throughput sequencing methods for genotyping genome‐wide markers are being rapidly adopted for phylogenetics of nonmodel organisms in conservation and biodiversity studies. However, the reproducibility of SNP genotyping and degree of marker overlap or compatibility between datasets from different methodologies have not been tested in nonmodel systems. Using double‐digest restriction site‐associated DNA sequencing, we sequenced a common set of 22 specimens from the butterfly genus Speyeria on two different Illumina platforms, using two variations of library preparation. We then used a de novo approach to bioinformatic locus assembly and SNP discovery for subsequent phylogenetic analyses. We found a high rate of locus recovery despite differences in library preparation and sequencing platforms, as well as overall high levels of data compatibility after data processing and filtering. These results provide the first application of NGS methods for phylogenetic reconstruction in Speyeria and support the use and long‐term viability of SNP genotyping applications in nonmodel systems.     

Rapid genotyping by MALDI-monitored nuclease selection from probe libraries

Data on five single-nucleotide polymorphisms (SNPs) per gene are estimated to allow association of disease risks or pharmacogenetic parameters with individual genes. Efficient technologies for rapidly detecting SNPs will therefore facilitate the mining of genomic information. Known methods for SNP analysis include restriction-fragment-length polymorphism polymerase chain reaction (PCR), allele-specific oligomer hybridization, oligomer-specific ligation assays, minisequencing, direct sequencing, fluorescence-detected 5'-exonuclease assays, and hybridization with PNA probes. Detection by mass spectrometry (MS) offers speed and high resolution. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF MS) can detect primer extension products, mass-tagged oligonucleotides, DNA created by restriction endonuclease cleavage, and genomic DNA. We have previously reported MALDI-TOF-monitored nuclease selections of modified oligonucleotides with increased affinity for targets. Here we use nuclease selections for genotyping by treating DNA to be analyzed with oligonucleotide probes representing known genotypes and digesting probes that are not complementary to the DNA. With phosphodiesterase I, the target-bound, complementary probe is largely refractory to nuclease attack and its peak persists in mass spectra (Fig. 1A). In optimized assays, both alleles of a heterozygote were genotyped with six nonamer DNA probes (> or = 125 fmol each) and asymmetrically amplified DNA from exon 10 of the cystic fibrosis transmembrane regulatory gene (CFTR).     

Recent patents on high-throughput single nucleotide polymorphism (SNP) genotyping methods

Single nucleotide polymorphisms (SNPs) are single-base inheritable variations in a given and defined genetic location that occur in at least 1% of the population. SNPs are useful markers for genetic association studies in disease susceptibility or adverse drug reactions, in evolutionary studies and forensic science. Given the potential impact of SNPs, the biotechnology industry has focused on the development of high-throughput methods for SNP genotyping. Many highthroughput SNP genotyping technologies are currently available and many others are being patented recently. Each offers a unique combination of scale, accuracy, throughput and cost. In this review, we described some of the most important recent SNP genotyping methods and also recent patents associated with it.     

Genotools SNP manager: a new software for automated high-throughput MALDI-TOF mass spectrometry SNP genotyping

Analysis of single nucleotide polymorphisms (SNPs) is a rapidly growing field of research that provides insights into the most common type of differences between individual genomes. The resulting information has a strong impact in the fields of pharmacogenomics, drug development, forensic medicine, and diagnostics of specific disease markers. The technique of matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) has been shown to be a highly suitable tool for the analysis of DNA. It supplies a very versatile method for addressing a high-throughput SNP genotyping approach. Here, we present the Bruker genotools SNP MANAGER, a new software tool suitable for highly automated MALDI-TOF MS SNP genotyping. The genotools SNP MANAGER administers the sample preparation data, calculates masses of allele-specific primer extension products, performs genotyping analysis, and displays the results. In the current study, we have used the genotools SNP MANAGER to perform an automated duplex SNP analysis of two biallelic markers from the promoter of the gene encoding the inflammatory mediator interleukin-6.     

Effect of genotyping error in model-free linkage analysis using microsatellite or single-nucleotide polymorphism marker maps

Errors while genotyping are inevitable and can reduce the power to detect linkage. However, does genotyping error have the same impact on linkage results for single-nucleotide polymorphism (SNP) and microsatellite (MS) marker maps? To evaluate this question we detected genotyping errors that are consistent with Mendelian inheritance using large changes in multipoint identity-by-descent sharing in neighboring markers. Only a small fraction of Mendelian consistent errors were detectable (e.g., 18% of MS and 2.4% of SNP genotyping errors). More SNP genotyping errors are Mendelian consistent compared to MS genotyping errors, so genotyping error may have a greater impact on linkage results using SNP marker maps. We also evaluated the effect of genotyping error on the power and type I error rate using simulated nuclear families with missing parents under 0, 0.14, and 2.8% genotyping error rates. In the presence of genotyping error, we found that the power to detect a true linkage signal was greater for SNP (75%) than MS (67%) marker maps, although there were also slightly more false-positive signals using SNP marker maps (5 compared with 3 for MS). Finally, we evaluated the usefulness of accounting for genotyping error in the SNP data using a likelihood-based approach, which restores some of the power that is lost when genotyping error is introduced.     

SNPkit: an efficient approach to systematic evaluation of candidate single nucleotide polymorphisms in public databases

There is widespread interest in devising genotyping methods for SNPs that are robust, inexpensive, and simple to perform. Although several high-throughput SNP genotyping technologies have been developed, including the oligonucleotide ligation assay, real-time PCR, and mass spectrometry, the issues of simplicity and cost-effectiveness have not been adequately addressed. Here we describe the application of a novel computer software package, SNPkit, which designs SNP genotyping assays based on a classical approach for discriminating alleles, restriction enzyme digestion. SNPkit can be used in genotyping assays for almost any SNPs including those that do not alter "natural" restriction sites. Using this method, 164 SNPs have been evaluated in DNA samples from 48 immortalized cell lines of randomly selected Chinese subjects. Sixty-two (37.8%) of the SNPs appeared to be common (frequencies of the minor alleles are > or = 5%) and were subsequently applied to a larger population-based sample. Overall, by using SNPkit, we have been able to validate and genotype accurately a large fraction of publicly available SNPs without sophisticated instrumentation.