单核苷酸多态性检测方法的研究进展

单核苷酸多态性（single nucleotide polymorphism, SNP）的研究已成为人类后基因组时代的主要内容之一。因此建立高度自动化和高通量的SNP检测分析技术十分重要。文章系统地介绍了最新发展的几种SNP检测技术的原理和检测平台,详细阐述了等位基因特异性杂交、内切酶酶切技术、引物延伸法、寡核苷酸连接反应等SNP检测原理,以及平板读数仪、基因芯片、微球阵列技术和质谱仪等检测平台,并对SNP高通量检测技术的发展进行了展望。     

Genotyping single nucleotide polymorphisms for selection of barley β-amylase alleles

A high-throughput single nucleotide polymorphism (SNP) genotyping system was developed and used to select barley seedlings carrying superior alleles of β-amylase. In the malting process, β-amylase is a key enzyme involved in the degradation of starch. Four allelic forms of the enzyme are found in barley, each exhibiting a different rate of thermal inactivation, or thermostability. The level of thermostability influences starch degradation, which determines the yield of fermentable sugars for alcohol production during brewing. Control of the fermentability level is important for barley breeding programs to allow targeting quality profiles of new varieties to suit end-user requirements. Alignment of the cDNA sequences encoding the 4 enzyme forms revealed 6 SNPs (cSNPs). The 4 alleles could be identified unambiguously by codominantly genotyping 2 of the cSNPs using a duplex single nucleotide primer extension (SNuPE) assay. Two genotyping primers with their 3^′ ends directly flanking the selected SNPs were annealed to the amplified target sequences and extended by single dideoxynucleotides complementary to the polymorphic nucleotides. Extended primers were analyzed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-ToF MS). Making use of the inherent molecular weight difference between DNA bases, incorporated nucleotides were identified by the increase in mass of the extended primers. A cleaved amplified polymorphic sequence (CAPS) assay enabling broader classification of the alleles was also developed to facilitate the transfer of this marker to other laboratories. Plants carrying alternative β-amylase alleles were selected at the seedling stage for barley breeding.     

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.     

SNPs discovery and CAPS marker conversion in soybean

To discover new SNPs and develop an easy assay method in soybean, we compared the high-throughput pyrosequencing ESTs with whole genome sequences in different soybean varieties and identified 3899 SNPs. Transitions were found to be much more frequent than transversions in these SNPs. We found that SNPs were widely distributed in the soybean genome, targeting numerous genes involved in various physiological and biochemical processes influencing important agronomic traits. A set of 16 SNPs were validated in nine soybean varieties, and seven SNPs were converted into CAPS. From functional gene association analysis, the marker CAPS282 on the 3′-UTR of gene Glyma07g03490 was identified as associated with 100-seed weight in soybean. The SNP discovery and CAPS markers conversion system developed in this study is fast and cost effective, and holds great promise for molecular-assisted breeding of soybean.     

A novel MALDI-TOF based methodology for genotyping single nucleotide polymorphisms

A new MALDI-TOF based detection assay was developed for analysis of single nucleotide polymorphisms (SNPs). It is a significant modification on the classic three-step minisequencing method, which includes a polymerase chain reaction (PCR), removal of excess nucleotides and primers, followed by primer extension in the presence of dideoxynucleotides using modified thermostable DNA polymerase. The key feature of this novel assay is reliance upon deoxynucleotide mixes, lacking one of the nucleotides at the polymorphic position. During primer extension in the presence of depleted nucleotide mixes, standard thermostable DNA polymerases dissociate from the template at positions requiring a depleted nucleotide; this principal was harnessed to create a genotyping assay. The assay design requires a primer- extension primer having its 3'-end one nucleotide upstream from the interrogated site. The assay further utilizes the same DNA polymerase in both PCR and the primer extension step. This not only simplifies the assay but also greatly reduces the cost per genotype compared to minisequencing methodology. We demonstrate accurate genotyping using this methodology for two SNPs run in both singleplex and duplex reactions. We term this assay nucleotide depletion genotyping (NUDGE). Nucleotide depletion genotyping could be extended to other genotyping assays based on primer extension such as detection by gel or capillary electrophoresis.     

SNP2CAPS: a SNP and INDEL analysis tool for CAPS marker development

With the influx of various SNP genotyping assays in recent years, there has been a need for an assay that is robust, yet cost effective, and could be performed using standard gel-based procedures. In this context, CAPS markers have been shown to meet these criteria. However, converting SNPs to CAPS markers can be a difficult process if done manually. In order to address this problem, we describe a computer program, SNP2CAPS, that facilitates the computational conversion of SNP markers into CAPS markers. 413 multiple aligned sequences derived from barley ESTs were analysed for the presence of polymorphisms in 235 distinct restriction sites. 282 (90%) of 314 alignments that contain sequence variation due to SNPs and InDels revealed at least one polymorphic restriction site. After reducing the number of restriction enzymes from 235 to 10, 31% of the polymorphic sites could still be detected. In order to demonstrate the usefulness of this tool for marker development, we experimentally validated some of the results predicted by SNP2CAPS.     

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.     

FRET hybridization probes for the rapid detection of disease resistance alleles in plants: detection of corky root resistance in lettuce

We describe the development of a non-electrophoresis PCR-based assay for allele discrimination at a disease resistance locus. The assay is based on the emission of light by fluorescence resonance energy transfer (FRET) upon annealing of two hybridization probes. The analysis of melting curve profiles of the probes and templates allowed the detection of single nucleotide polymorphisms. The assay was applied to the detection of alleles at the cor locus in lettuce (Lactuca sativa) that confers recessive resistance to corky root disease. Probes and primers for the assay were designed after the characterization of a single nucleotide polymorphism between alleles of PCR products amplified using a linked marker. That polymorphism was validated in a collection of lettuce varieties representing different genetic backgrounds. The FRET hybridization probes approach provided fast and accurate genotyping of breeding material directly in a one-tube reaction. The absence of electrophoresis makes this approach suitable for applications that require automation and high-throughput genotyping analyses such as marker-assisted selection programs.     

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

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

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.     

VCF2CAPS–A high-throughput CAPS marker design from VCF files and its test-use on a genotyping-by-sequencing (GBS) dataset

Next-generation sequencing (NGS) is a powerful tool for massive detection of DNA sequence variants such as single nucleotide polymorphisms (SNPs), multi-nucleotide polymorphisms (MNPs) and insertions/deletions (indels). For routine screening of numerous samples, these variants are often converted into cleaved amplified polymorphic sequence (CAPS) markers which are based on the presence versus absence of restriction sites within PCR products. Current computational tools for SNP to CAPS conversion are limited and usually infeasible to use for large datasets as those generated with NGS. Moreover, there is no available tool for massive conversion of MNPs and indels into CAPS markers. Here, we present VCF2CAPS–a new software for identification of restriction endonucleases that recognize SNP/MNP/indel-containing sequences from NGS experiments. Additionally, the program contains filtration utilities not available in other SNP to CAPS converters–selection of markers with a single polymorphic cut site within a user-specified sequence length, and selection of markers that differentiate up to three user-defined groups of individuals from the analyzed population. Performance of VCF2CAPS was tested on a thoroughly analyzed dataset from a genotyping-by-sequencing (GBS) experiment. A selection of CAPS markers picked by the program was subjected to experimental verification. CAPS markers, also referred to as PCR-RFLPs, belong to basic tools exploited in plant, animal and human genetics. Our new software–VCF2CAPS–fills the gap in the current inventory of genetic software by high-throughput CAPS marker design from next-generation sequencing (NGS) data. The program should be of interest to geneticists involved in molecular diagnostics. In this paper we show a successful exemplary application of VCF2CAPS and we believe that its usefulness is guaranteed by the growing availability of NGS services.

This is a PLOS Computational Biology Software paper.

     

Primer design and marker clustering for multiplex SNP-IT primer extension genotyping assay using statistical modeling

MOTIVATION: The optimization of the primer design is critical for the development of high-throughput SNP genotyping methods. Recently developed statistical models of the SNP-IT primer extension genotyping reaction allow further improvement of primer quality for the assay. RESULTS: Here we describe how the statistical models can be used to improve primer design for the assay. We also show how to optimize clustering of the SNP markers into multiplex panels using statistical model for multiplex SNP-IT. The primer set failure probability calculated by a model is used as a minimization function for both primer selection and primers clustering. Three clustering algorithms for the multiplex genotyping SNP-IT assay are described and their relative performance is evaluated. We also describe the approaches to improve the speed of primer design and clustering calculations when using the statistical models. Our clustering decreases the average failure probability of the marker set by 7-25%. The experimental marker failure rate in the multiplex reaction was reduced dramatically and success rate can be achieved as high as 96%. AVAILABILITY: The primer design using statistical models is freely available from www.autoprimer.com.     

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.     

Analysis of genetic variation in the GenomEUtwin project.

Multiallelic short tandem repeat polymorphisms, or microsatellites, are useful markers in genome wide scans to identify chromosomal regions containing genes underlying disease loci. The biallelic single nucleotide polymorphism (SNP) can be used to fine map previously identified large candidate regions or to test functional candidate genes by association analysis. In the GenomEUtwin project the population based impact of susceptibility genes for six multifactorial traits will be studied. A genome wide panel of informative human microsatellite markers will be analyzed by fluorescent capillary electrophoresis in well characterized twin and population samples. Contrary to microsatellites, selection of the most informative panels of SNPs is hampered by imperfect data on the allele frequencies and population distribution of SNPs markers in the databases. Therefore, selection of SNPs requires a substantial amount of bioinformatics, and, the SNPs need to be validated experimentally in the relevant populations prior to genotyping large sample sets. In the GenomEUtwin project, large scale genotyping of SNPs will be performed using the SNPstreamUHT and MassARRAY genotyping systems that are based on the primer extension reaction principle combined with fluorescent and mass spectrometric detection, respectively. Production of the genotyping data will be a joint effort by GenomEUtwin partners at the University of Helsinki, the National Public Health Institute in Helsinki, Finland and Uppsala University, Sweden. All genotyping data will be stored in a common database established specifically for the GenomEUtwin project, from where it can be accessed by the twin research centres that provided the samples for genotyping.     

Multiplexed genotyping of ABC transporter polymorphisms with the Bioplex suspension array

We have developed and validated a consolidated bead-based genotyping platform, the Bioplex suspension array for simultaneous detection of multiple single nucleotide polymorphisms (SNPs) of the ATP-binding cassette transporters. Genetic polymorphisms have been known to influence therapeutic response and risk of disease pathologies. Genetic screening for therapeutic and diagnostic applications thus holds great promise in clinical management. The allele-specific primer extension (ASPE) reaction was used to assay 22 multiplexed SNPs for eight subjects. Comparison of the microsphere-based ASPE assay results to sequencing results showed complete concordance in genotype assignments. The Bioplex suspension array thus proves to be a reliable, cost-effective and high-throughput technological platform for genotyping. It can be easily adapted to customized SNP panels for specific applications involving large-scale mutation screening of clinically relevant markers.     

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.     

Fluorescence resonance energy transfer (FRET) using ssDNA binding fluorescent dye

There is a need for simple and inexpensive methods for genotyping single nucleotide polymorphisms (SNPs) and short insertion/deletion variations (InDels). In this work, I demonstrate that a single-stranded DNA (ssDNA) binding dye can be used as a donor fluorophore for fluorescence resonance energy transfer (FRET). The method presented is a homogenous assay in which detection is based on the FRET from the fluorescence of the ssDNA dye bound to the unmodified detection primer to the fluorescent nucleotide analog incorporated into this detection primer during cyclic template directed primer extension reaction. Collection of the FRET emission spectrum with a scanning fluorescence spectrophotometer allows powerful data analysis. The fluorescence emission signal is modified by the optical properties of the assay vessel. This seems to be a completely neglected parameter. By proper selection of the optical properties of the assay plate one can improve the detection of the fluorescence emission signal.     

SNP Discovery Using Next Generation Transcriptomic Sequencing in Atlantic Herring (Clupea harengus)

The introduction of Next Generation Sequencing (NGS) has revolutionised population genetics, providing studies of non-model species with unprecedented genomic coverage, allowing evolutionary biologists to address questions previously far beyond the reach of available resources. Furthermore, the simple mutation model of Single Nucleotide Polymorphisms (SNPs) permits cost-effective high-throughput genotyping in thousands of individuals simultaneously. Genomic resources are scarce for the Atlantic herring (Clupea harengus), a small pelagic species that sustains high revenue fisheries. This paper details the development of 578 SNPs using a combined NGS and high-throughput genotyping approach. Eight individuals covering the species distribution in the eastern Atlantic were bar-coded and multiplexed into a single cDNA library and sequenced using the 454 GS FLX platform. SNP discovery was performed by de novo sequence clustering and contig assembly, followed by the mapping of reads against consensus contig sequences. Selection of candidate SNPs for genotyping was conducted using an in silico approach. SNP validation and genotyping were performed simultaneously using an Illumina 1,536 GoldenGate assay. Although the conversion rate of candidate SNPs in the genotyping assay cannot be predicted in advance, this approach has the potential to maximise cost and time efficiencies by avoiding expensive and time-consuming laboratory stages of SNP validation. Additionally, the in silico approach leads to lower ascertainment bias in the resulting SNP panel as marker selection is based only on the ability to design primers and the predicted presence of intron-exon boundaries. Consequently SNPs with a wider spectrum of minor allele frequencies (MAFs) will be genotyped in the final panel. The genomic resources presented here represent a valuable multi-purpose resource for developing informative marker panels for population discrimination, microarray development and for population genomic studies in the wild.