Determining SNP allele frequencies in DNA pools

Single nucleotide polymorphisms (SNPs) are among the most common types of polymorphism used for genetic association studies. A method to allow the accurate quantitation of their allele frequencies from DNA pools would both increase throughput and decrease costs for large-scale genotyping. However, to date, most DNA pooling studies have concentrated on the use of microsatellite polymorphisms. In the case of SNPs that are restriction fragment length polymorphisms (RFLPs), studies have tended to use methods for the quantitation of allele frequency from pools that rely on densitometric evaluation of bands on an autoradiograph. Radiation-based methods have well-known drawbacks, and we present two alternative methods for the determination of SNP allele frequencies. For RFLPs, we used agarose gel electrophoresis of digested PCR products with ethidium bromide staining combined with densitometric analysis of gel images on a PC. For all types of SNP, we used allele-specific fluorescent probes in the Taqman assay to determine the relative frequencies of two different alleles. Both methods gave accurate and reproducible results, suggesting they are suitable for use in DNA pooling experiments.     

High-throughput SNP detection by using DNA pooling and denaturing high performance liquid chromatography (DHPLC)

One of the critical steps in the positional cloning of a complex disease gene involves association analysis between a phenotype and a set of densely spaced diallelic markers, typically single nucleotide repeats (SNPs), covering the region of interest. However, the effort and cost of detecting sufficient numbers of SNPs across relatively large physical distances represents a significant rate-limiting step. We have explored DNA pooling, in conjunction with denaturing high performance liquid chromatography (DHPLC), as a possible strategy for augmenting the efficiency, economy, and throughput of SNP detection. DHPLC is traditionally used to detect variants in polymerase chain reaction products containing both allelic forms of a polymorphism (e.g., heterozygotes or a 1:1 mix of both alleles) via heteroduplex separation and thereby requires separate analyses of multiple individual test samples. We have adapted this technology to identify variants in pooled DNA. To evaluate the utility and sensitivity of this approach, we constructed DNA pools comprised of 20 previously genotyped individuals with a frequency representation of 0%-50% for the variant allele. Mutation detection was performed by using temperature-modulated heteroduplex formation/DHPLC and dye-terminator sequencing. Using DHPLC, we could consistently detect SNPs at lower than 5% frequency, corresponding to the detection of one variant allele in a pool of 20 alleles. In contrast, fluorescent sequencing detected variants in the same pools only if the frequency of the less common allele was at least 10%. We conclude that DNA pooling of samples for DHPLC analysis is an effective way to increase throughput efficiency of SNP detection.     

Single nucleotide polymorphism genotyping by heteroduplex analysis in sunflower (<Emphasis Type="Italic">Helianthus annuus</Emphasis> L.)

Single nucleotide polymorphisms (SNPs) and insertions/deletions (indels) are increasingly used for cultivar identification, construction of genetic maps, genetic diversity assessment, association mapping and marker-assisted breeding. Although there are several highly sensitive methods for the detection of polymorphisms, most of them are often beyond the budget of medium-throughput academic laboratories or seed companies. Heteroduplex analysis by enzymatic cleavage (CEL1CH) or denaturing high-performance liquid chromatography (dHPLC) has been successfully used to examine genetic variation in several plant and animal species. In this work, we assess and compare the performance of both methods in sunflower by genotyping SNPs from a set of 24 selected polymorphic candidate genes. The CEL1CH method allowed us to accurately detect allele differences in 10 out of 24 regions using an in-house prepared CEL1 enzyme (celery single strand endonuclease 1, Apium graveolens L.). Similarly, a total of 11 regions were successfully optimized for dHPLC analysis. As a scaling-up approach, both strategies were tested to genotype either 42 SNPs/indels in 22 sunflower accessions from the local germplasm bank or 33 SNPs/indels in 90 recombinant inbred lines (RILs) for genetic mapping purposes. Summarizing, a total of 601 genotypes were efficiently analyzed either with CEL1CH (110) or dHPCL (491). In conclusion, CEL1CH and dHPLC proved to be robust, complementary methods, allowing medium-scale laboratories to scale up the number of both SNPs and individuals to be included in genetic studies and targeted germplasm diversity characterization (EcoTILLING).     

Estimation of single nucleotide polymorphism allele frequency in DNA pools by using Pyrosequencing

Positional cloning of genes underlying complex diseases, such as type 2 diabetes mellitus (T2DM), typically follows a two-tiered process in which a chromosomal region is first identified by genome-wide linkage scanning, followed by association analyses using densely spaced single nucleotide polymorphic markers to identify the causal variant(s). The success of genome-wide single nucleotide polymorphism (SNP) detection has resulted in a vast number of potential markers available for use in the construction of such dense SNP maps. However, the cost of genotyping large numbers of SNPs in appropriately sized samples is nearly prohibitive. We have explored pooled DNA genotyping as a means of identifying differences in allele frequency between pools of individuals with T2DM and unaffected controls by using Pyrosequencing technology. We found that allele frequencies in pooled DNA were strongly correlated with those in individuals (r=0.99, P<0.0001) across a wide range of allele frequencies (0.02-0.50). We further investigated the sensitivity of this method to detect allele frequency differences between contrived pools, also over a wide range of allele frequencies. We found that Pyrosequencing was able to detect an allele frequency difference of less than 2% between pools, indicating that this method may be sensitive enough for use in association studies involving complex diseases where a small difference in allele frequency between cases and controls is expected.     

Discovery of single nucleotide polymorphisms in Lycopersicon esculentum by computer aided analysis of expressed sequence tags

Single nucleotide polymorphisms (SNPs) are useful for characterizing allelic variation, for genome-wide mapping, and as a tool for marker-assisted selection. Discovery of SNPs through de novo sequencing is inefficient within cultivated tomato (Lycopersicon esculentum Mill.) because the polymorphism rate is more than ten-fold lower than the sequencing error rate. The availability of expressed sequence tag (EST) data has made it feasible to discover putative SNPs in silico prior to experimental verification. By exploiting redundancy among EST data available for different varieties among 148,373 tomato ESTs, we have identified candidate SNPs for use within cultivated germplasm pools. 1,245 contigs having three EST sequences of Rio Grande and three EST sequences of TA496 were used for SNP discovery. We detected 1 SNP for every 8,500 bases analyzed, with 101 candidate SNPs in 44 genes identified. Sixty-six SNPs could be recognized by restriction enzymes, and subsequent experimental verification using restriction digestion or CEL I digestion confirmed 83% of the putative polymorphisms tested. SNPs between TA496 and Rio Grande have a high probability (53%) of detecting polymorphisms between other L. esculentum varieties. Twenty-six SNPs in 18 unigenes were mapped to specific chromosomes. Two SNPs, LEOH23 and LEOH37, were shown to be linked to quantitative trait loci contributing to fruit color within elite breeding populations. These results suggest that the growing databases of DNA sequence will yield information that facilitates improvement within the germplasm pools that have contributed to productive modern varieties.     

Temperature gradient capillary electrophoresis (TGCE)–a tool for the high-throughput discovery and mapping of SNPs and IDPs

Temperature gradient capillary electrophoresis (TGCE) can be used to distinguish heteroduplex from homoduplex DNA molecules and can thus be applied to the detection of various types of DNA polymorphisms. Unlike most single nucleotide polymorphism (SNP) detection technologies, TGCE can be used even in the absence of prior knowledge of the sequences of the underlying polymorphisms. TGCE is both sensitive and reliable in detecting SNPs, small InDel (insertion/deletion) polymorphisms (IDPs) and simple sequence repeats, and using this technique it is possible to detect a single SNP in amplicons of over 800 bp and 1-bp IDPs in amplicons of approximately 500 bp. Genotyping data obtained via TGCE are consistent with data obtained via gel-based detection technologies. For genetic mapping experiments, TGCE has a number of advantages over alternative heteroduplex-detection technologies such as celery endonuclease (CELI) and denaturing high-performance liquid chromatography (dHPLC). Multiplexing can increase TGCEs throughput to 12 markers on 94 recombinant inbreds per day. Given its ability to efficiently and reliably detect a variety of subtle DNA polymorphisms that occur at high frequency in genes, TGCE shows great promise for discovering polymorphisms and conducting genetic mapping and genotyping experiments.Electronic Supplementary Material Supplementary material is available for this article at     

Rapid SNP allele frequency determination in genomic DNA pools by pyrosequencing

Individual genotyping of single nucleotide polymorphisms (SNPs) remains expensive, especially for linkage disequilibrium mapping strategies involving high-throughput SNP genotyping. On one hand, current methods may suit scientific and laboratory needs in regard to accuracy, reproducibility/robustness, and large-scale application. On the other hand, a cheaper and less time-consuming alternative to individual genotyping is the use of SNP allelefrequencies determined in DNA pools. We have developed an accurate and reproducible protocol for allele frequency determination using Pyrosequencing technology in large genomic DNA pools (374 individuals). The measured correlation (R2) in large DNA pools was 0.980. In the context of disease-associated SNPs studies, we compared the allele frequencies between the disease (e.g., type 2 diabetes and obesity) and control groups detected by either individual genotyping or Pyrosequencing of DNA pools. In large pools, the variation between the two methods was 1.5 +/- 0.9%. It may be concluded that the allele frequency determination protocol could reliably detect over 4% differences between populations. The method is economical in regard to amounts of DNA, PCR, and primer extension reagents required. Furthermore, it allows the rapid determination of allelefrequency differences in case/control groups for association studies and susceptibility gene discovery in complex diseases.     

单核苷酸多态性检测分析技术

单核苷酸多态性(SNP)作为第三代遗传标记已经广泛用于基因作图、疾病相关性分析、群体遗传学及药物研究等领域。 文中系统地介绍了目前国内外主要的SNP检测技术,任何一种SNP的检测方法都可将之看成由两部分组成,即区分SNP位点的原理方法和数据的检测分析手段,文章对这两部分做了较详细的介绍,并对SNP检测技术的发展进行了展望。 Abstract :As the third generation of genetic markers SNPs（single nucleotide polymorphisms）has been used extentively in gene mapping,disease-correlativity analysis ,population genetics and drug research.Here methods for detection are reviewed.Most SNP genotyping are a combination of method for interrogating SNPs and analysis tecnique.It described both parts and give a outlook for detection.     

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

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

Assessing allele frequencies of single nucleotide polymorphisms in DNA pools by pyrosequencing technology

Single nucleotide polymorphism (SNP) association studies searching for differences in allele frequencies between cases and controls have been widely used for genetic analysis. Individual genotyping is prohibitively expensive in large sample sizes. Pooling of samples provides the obvious advantage of higher throughput and lower cost. Here we report our results with the analysis of SNP allele frequencies in DNA pools using Pyrosequencing technology. For seven different SNPs, we observed a mean difference of 1.1 +/- 0.6% between allele frequencies determined in two different DNA pools (n = 150 cases and 150 controls) compared to individually genotyped samples.     

An efficient procedure for genotyping single nucleotide polymorphisms

Analysis of single nucleotide polymorphisms (SNPs) has been and will be increasingly utilized in various genetic disciplines, particularly in studying genetic determinants of complex diseases. Such studies will be facilitated by rapid, simple, low cost and high throughput methodologies for SNP genotyping. One such method is reported here, named tetra-primer ARMS-PCR, which employs two primer pairs to amplify, respectively, the two different alleles of a SNP in a single PCR reaction. A computer program for designing primers was developed. Tetra-primer ARMS-PCR was combined with microplate array diagonal gel electrophoresis, gaining the advantage of high throughput for gel-based resolution of tetra-primer ARMS-PCR products. The technique was applied to analyse a number of SNPs and the results were completely consistent with those from an independent method, restriction fragment length polymorphism analysis.     

A simple procedure for the analysis of single nucleotide polymorphisms facilitates map-based cloning in Arabidopsis

We developed a modified allele-specific PCR procedure for assaying single nucleotide polymorphisms (SNPs) and used the procedure (called SNAP for single-nucleotide amplified polymorphisms) to generate 62 Arabidopsis mapping markers. SNAP primers contain a single base pair mismatch within three nucleotides from the 3' end of one allele (the specific allele) and in addition have a 3' mismatch with the nonspecific allele. A computer program called SNAPER was used to facilitate the design of primers that generate at least a 1,000-fold difference in the quantity of the amplification products from the specific and nonspecific SNP alleles. Because SNAP markers can be readily assayed by electrophoresis on standard agarose gels and because a public database of over 25,000 SNPs is available between the Arabidopsis Columbia and Landsberg erecta ecotypes, the SNAP method greatly facilitates the map-based cloning of Arabidopsis genes defined by a mutant phenotype.     

新一代分子标记--SNPs及其应用

单核苷酸多态性(SNPs)是广泛存在于基因组中的一类DNA序列变异,其频率为1%或更高。它是由单个碱基的转换或颠换引起的点突变,稳定而可靠,并通常以二等位基因的形式出现。采用生物芯片和DNA微阵列技术来检测SNP,便于对基因组进行大幅度和高通量分析。因此,作为新一代分子标记,SNP在生物学诸多领域具有广阔应用前景。本文简要叙述SNPs技术的发展历史、研究动态以及相关的理论,介绍了与SNPs相关的基本术语、概念及其特点,列举了发现与检测SNPs主要技术的原理和方法,同时还根据一些具体实例介绍了SNPs在模式动、植物遗传图谱构建、品种鉴定、物种起源与亲缘关系、连锁不平衡与关联分析及其在群体遗传结构及其变化机制研究中的应用。最后展望了SNPs在群体遗传、分子育种和生物进化等研究领域中的应用前景。     

Single-reaction for SNP Genotyping on Agarose Gel by Allele-specific PCR in Black Poplar (Populus nigra L.)

The wide development of single nucleotide polymorphism (SNP) markers also in non-model species increases the need for inexpensive methods that do not require sophisticated equipment and time for optimization. This work presents a new method for polymerase chain reaction (PCR) amplification of multiple specific alleles (PAMSA), which allows efficient discrimination of SNP polymorphisms in one reaction tube with standard PCR conditions. This improved PAMSA requires only three unlabeled primers: a common reverse primer and two allele-specific primers having a tail of different length to differentiate the two SNP alleles by the size of amplification products on agarose gel. A destabilizing mismatch within the five bases of the 3′ end is also added to improve the allele specificity. To validate the accuracy of this method, 94 full-sib individuals were genotyped with three SNPs and compared to the genotypes obtained by cleaved amplified polymorphic sequence (CAPS) or derived CAPS. This method is flexible, inexpensive, and well suited for high throughput and automated genotyping.     

A novel procedure for efficient genotyping of single nucleotide polymorphisms

Due to the surge in interest in using single nucleotide polymorphisms (SNPs) for genotyping a facile and affordable method for this is an absolute necessity. Here we introduce a procedure that combines an easily automatable single tube sample preparation with an efficient high throughput mass spectrometric analysis technique. Known point mutations or single nucleotide polymorphisms are easily analysed by this procedure. It starts with PCR amplification of a short stretch of genomic DNA, for example an exon of a gene containing a SNP. By shrimp alkaline phosphatase digest residual dNTPs are destroyed. Allele-specific products are generated using a special primer, a conditioned set of α-S-dNTPs and α-S-ddNTPs and a fresh DNA polymerase in a primer extension reaction. Unmodified DNA is removed by 5′-phosphodiesterase digestion and the modified products are alkylated to increase the detection sensitivity in the mass spectrometric analysis. All steps of the preparation are simple additions of solutions and incubations. The procedure operates at the lowest practical sample volumes and in contrast to other genotyping protocols with mass spectrometric detection requires no purification. This reduces the cost and makes it easy to implement. Here it is demonstrated in a version using positive ion detection on described mutations in exon 17 of the amyloid precursor protein gene and in a version using negative ion detection on three SNPs of the granulocyte-macrophage colony stimulating factor gene. Preparation and analysis of SNPs is shown separately and simultaneously, thus demonstrating the multiplexibility of this genotyping procedure. The preparation protocol for genotyping is adapted to the conditions used for the SNP discovery method by denaturing HPLC, thus demonstrating a facile link between protocols for SNP discovery and SNP genotyping. Results corresponded unanimously with the control sequencing. The procedure is useful for high throughput genotyping as it is required for gene identification and pharmacogenomics where large numbers of DNA samples have to be analysed. We have named this procedure the ‘GOOD Assay’ for SNP analysis.     

The identification of SNPs with indeterminate positions using the Equine SNP50 BeadChip

We have used linkage disequilibrium (LD) to identify single nucleotide polymorphisms (SNPs) on the Illumina Equine SNP50 BeadChip, which may be incorrectly positioned on the genome map. A total of 1201 Thoroughbred horses were genotyped using the Illumina Equine SNP50 BeadChip. LD was evaluated in a pairwise fashion between all autosomal SNPs, both within and across chromosomes. Filters were then applied to the data, firstly to identify SNPs that may have been mapped to the wrong chromosome and secondly to identify SNPs that may have been incorrectly positioned within chromosomes. We identified a single SNP on ECA28, which showed low LD with neighbouring SNPs but considerable LD with a group of SNPs on ECA10. Furthermore, a cluster of SNPs on ECA5 showed unusually low LD with surrounding SNPs. A total of 39 SNPs met the criteria for unusual within-chromosome LD. The results of this study indicate that some SNPs may be misplaced. This finding is significant, as misplaced SNPs may lead to difficulties in the application of genomic methods, such as homozygosity mapping, for which SNP order is important.     

A cross-sample statistical model for SNP detection in short-read sequencing data

Highly multiplex DNA sequencers have greatly expanded our ability to survey human genomes for previously unknown single nucleotide polymorphisms (SNPs). However, sequencing and mapping errors, though rare, contribute substantially to the number of false discoveries in current SNP callers. We demonstrate that we can significantly reduce the number of false positive SNP calls by pooling information across samples. Although many studies prepare and sequence multiple samples with the same protocol, most existing SNP callers ignore cross-sample information. In contrast, we propose an empirical Bayes method that uses cross-sample information to learn the error properties of the data. This error information lets us call SNPs with a lower false discovery rate than existing methods.     

Characterization of polyploid wheat genomic diversity using a high‐density 90 000 single nucleotide polymorphism array

High‐density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker–trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene‐associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome‐wide distributed SNPs that are represented in populations of diverse geographical origin. We used density‐based spatial clustering algorithms to enable high‐throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model‐free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low‐intensity clusters can provide insight into the distribution of presence–absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.     

Development and assessment of simple PCR markers for SNP genotyping in barley

Simple molecular marker assays underpin routine plant breeding and research activities in many laboratories worldwide. With the rapid growth of single nucleotide polymorphism (SNP) resources for many important crop plants, the availability of routine, low-tech marker assays for genotyping SNPs is of increased importance. In this study, we demonstrate that temperature-switch PCR (TSP) supports the rapid development of robust, allele-specific PCR markers for codominant SNP genotyping on agarose gel. A total of 87 TSP markers for assessing gene diversity in barley were developed and used to investigate the efficacy for marker development, assay reliably and genotyping accuracy. The TSP markers described provide good coverage of the barley genome, are simple to use, easy to interpret and score, and are amenable to assay automation. They provide a resource of informative SNP markers for assessing genetic relationships among individuals, populations and gene pools of cultivated barley (Hordeum vulgare L.) and its wild relative H. spontaneum K. Koch. TSP markers provide opportunities to use available SNP resources for marker-assisted breeding and plant genetic research, and to generate information that can be integrated with SNP data from different sources and studies. TSP markers are expected to provide similar advantages for any animal or plant species. M. J. Hayden and T. Tabone contributed equally to this work.     

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.