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.     

应用FP-TDI技术进行高通量单核苷酸多态分型

FP-TDI (fluorescence polarization template-directed dye-terminator incorporation）是一种操作简单、实验投入少、适于高通量反应的单核苷酸多态等位基因分型技术.使用两种评价分型图像质量的数值指标,可以有效地对分型结果进行评价,使该技术得到了改进.在此基础上优化了实验条件,并应用该技术,对人类基因组3号染色体上随机选取的337个单核苷酸多态性位点进行了高通量分型,反应的一次成功率达到59.94%.     

A rapid, microplate SNP genotype assay for the leptinob allele

A nonsense mutation in the mouse leptin gene causes genetic obesity. As a result of extensive research in the field of obesity, the use of leptinob mice is widespread. This mutation renders mice sterile, creating the need to breed heterozygous mice. For this reason, leptinob genotyping is necessary. To date, gel-based assays have been used for genotyping. Using the Invader Plus assay for single nucleotide polymorphism (SNP) detection, we have developed a gel-free microplate SNP assay for genotyping leptinwt and leptinob alleles.     

Automatic Scoring and Quality Assessment Using Accuracy Bounds for FP-TDI SNP Genotyping Data

BACKGROUND: Human diversity, namely single nucleotide polymorphisms (SNPs), is becoming a focus of biomedical research. Despite the binary nature of SNP determination, the majority of genotyping assay data need a critical evaluation for genotype calling. We applied statistical models to improve the automated analysis of 2-dimensional SNP data. METHODS: We derived several quantities in the framework of Gaussian mixture models that provide figures of merit to objectively measure the data quality. The accuracy of individual observations is scored as the probability of belonging to a certain genotype cluster, while the assay quality is measured by the overlap between the genotype clusters. RESULTS: The approach was extensively tested with a dataset of 438 nonredundant SNP assays comprising >150,000 datapoints. The performance of our automatic scoring method was compared with manual assignments. The agreement for the overall assay quality is remarkably good, and individual observations were scored differently by man and machine in 2.6% of cases, when applying stringent probability threshold values. CONCLUSION: Our definition of bounds for the accuracy for complete assays in terms of misclassification probabilities goes beyond other proposed analysis methods. We expect the scoring method to minimise human intervention and provide a more objective error estimate in genotype calling.     

SNP allele frequency estimation in DNA pools and variance components analysis

The estimation of single nucleotide polymorphism (SNP) allele frequency in pooled DNA samples has been proposed as a cost-effective approach to whole genome association studies. However, the key issue is the allele frequency window in which a genotyping method operates and provides a statistically reliable answer. We assessed the homogeneous mass extend assay and estimated the variance associated with each experimental stage. We report that a relationship between estimated allele frequency and variance might exist, suggesting that high statistical power can be retained at low, as well as high, allele frequencies. Assuming this relationship, the formation of subpools consisting of 100 samples retains an effective sample size greater than 70% of the true sample size, with a savings of 11-fold the cost of an individual genotyping study, regardless of allele frequency.     

SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries

High-density single-nucleotide polymorphism (SNP) arrays have revolutionized the ability of genome-wide association studies to detect genomic regions harboring sequence variants that affect complex traits. Extensive numbers of validated SNPs with known allele frequencies are essential to construct genotyping assays with broad utility. We describe an economical, efficient, single-step method for SNP discovery, validation and characterization that uses deep sequencing of reduced representation libraries (RRLs) from specified target populations. Using nearly 50 million sequences generated on an Illumina Genome Analyzer from DNA of 66 cattle representing three populations, we identified 62,042 putative SNPs and predicted their allele frequencies. Genotype data for these 66 individuals validated 92% of 23,357 selected genome-wide SNPs, with a genotypic and sequence allele frequency correlation of r = 0.67. This approach for simultaneous de novo discovery of high-quality SNPs and population characterization of allele frequencies may be applied to any species with at least a partially sequenced genome.     

Universal,robust, highly quantitative SNP allele frequency measurement in DNA pools

Detecting alleles that confer small increments in susceptibility to disease will require large-scale allelic association studies of single-nucleotide polymorphisms (SNPs) in candidate, or positional candidate, genes. However, current genotyping technologies are one to two orders of magnitude too expensive to permit the analysis of thousands of SNPs in large samples. We have developed and thoroughly validated a highly accurate protocol for SNP allele frequency estimation in DNA pools based upon the SNaPshot (Applied Biosystems) chemistry adaptation of primer extension. Using this assay, we were able to estimate the difference in allele frequencies between pooled cases and controls (Delta) with a mean error of 0.01. Moreover, when we genotyped seven different SNPs in a single multiplex reaction, the results were similar, with a mean error for Delta of 0.008. The assay performed well for alleles of low frequency alleles (f approximately 0.05) and was accurate even with relatively poor quality DNA template extracted from mouthwashes. Our assay conditions are generalisable, universal, robust and, therefore, for the first time, permit high-throughput association analysis at a realistic cost.     

Single nucleotide polymorphism (SNP) allele frequency estimation in DNA pools using Pyrosequencing

Identifying the genetic variation underlying complex disease requires analysis of many single nucleotide polymorphisms (SNPs) in a large number of samples. Several high-throughput SNP genotyping techniques are available; however, their cost promotes the use of association screening with pooled DNA. This protocol describes the estimation of SNP allele frequencies in pools of DNA using the quantitative sequencing method Pyrosequencing (PSQ). PSQ is a relatively recently described high-throughput method for genotyping, allele frequency estimation and DNA methylation analysis based on the detection of real-time pyrophosphate release during synthesis of the complementary strand to a PCR product. The protocol involves the following steps: (i) quantity and quality assessment of individual DNA samples; (ii) DNA pooling, which may be undertaken at the pre- or post-PCR stage; (iii) PCR amplification of PSQ template containing the variable sequence region of interest; and (iv) PSQ to determine the frequency of alleles at a particular SNP site. Once the quantity and quality of individual DNA samples has been assessed, the protocol usually requires a few days for setting up pre-PCR pools, depending on sample number. After PCR amplification, preparation and analysis of PCR amplicon by PSQ takes 1 h per plate.     

SNP calling, genotype calling, and sample allele frequency estimation from new-generation sequencing data

We present a statistical framework for estimation and application of sample allele frequency spectra from New-Generation Sequencing (NGS) data. In this method, we first estimate the allele frequency spectrum using maximum likelihood. In contrast to previous methods, the likelihood function is calculated using a dynamic programming algorithm and numerically optimized using analytical derivatives. We then use a Bayesian method for estimating the sample allele frequency in a single site, and show how the method can be used for genotype calling and SNP calling. We also show how the method can be extended to various other cases including cases with deviations from Hardy-Weinberg equilibrium. We evaluate the statistical properties of the methods using simulations and by application to a real data set.     

Determination of detection and quantification limits for SNP allele frequency estimation in DNA pools using real time PCR

The quantification of single nucleotide polymorphism (SNP) allele frequencies in pooled DNA samples using real time PCR is a promising approach for large-scale diagnostics and genotyping. The limits of detection (LOD) and limits of quantification (LOQ) for mutant SNP alleles are of particular importance for determination of the working range, which, in the case of allele-specific real time PCR, can be limited by the variance of calibration data from serially diluted mutant allele samples as well as by the variance of the 100% wild-type allele samples (blank values). In this study, 3σ and 10σ criteria were applied for the calculation of LOD and LOQ values. Alternatively, LOQ was derived from a 20% threshold for the relative standard deviation (%RSD) of measurements by fitting a curve for the relationship between %RSD and copy numbers of the mutant alleles. We found that detection and quantification of mutant alleles were exclusively limited by the variance of calibration data since the estimated LOD_calibration (696 in 30000000 copies, 0.0023%), LOQ_20%RSD (1470, 0.0049%) and LOQ_calibration (2319, 0.0077) values were significantly higher than the LOD_blank (130, 0.0004%) and LOQ_blank (265, 0.0009%) values derived from measurements of wild-type allele samples. No significant matrix effects of the genomic background DNA on the estimation of LOD and LOQ were found. Furthermore, the impact of large genome sizes and the general application of the procedure for the estimation of LOD and LOQ in quantitative real time PCR diagnostics are discussed.     

FP-TDI SNP scoring by manual and statistical procedures: a study of error rates and types

For technologies that are commonly used in ordinary laboratories such as fluorescence-polarization detection with template-directed, dye-terminator incorporation (FP-TDI), SNP genotype scoring is usually done manually. Here we study rates of errors and missing genotypes obtained with this procedure. We also introduce three statistical genotype scoring methods to examine whether they form a viable alternative. Data consisted of eight SNPs typed in about 1400 individuals from 268 pedigrees. The statistical procedures performed better on several internal criteria, such as the number of Mendelian errors, and showed much higher agreement with discrepant genotypes re-scored by two raters. The best results were obtained with the statistical procedure that incorporated information about regularities in the error structure of the FP-TDI data. We estimated that there were about 1.6% more errors if genotypes were scored manually. About 0.6% of these errors could be explained by data manipulation errors, leaving 1% as the result of possible incorrect scoring. There were 3.3% more missing genotypes in the manual scoring due to errors in data manipulation (1.7%) and conservative scoring (1.6%).     

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.     

Quantitative determination of allele frequency in pooled DNA by using sequencing method

Quantitative determination of the allele frequency of single-nucleotide polymorphism (SNP) in pooled DNA samples is a promising approach to clarify the relationships between SNPs and diseases. Here, we present such a simple, accurate, and inexpensive method for quantitative determining the allele frequency in pooled DNA samples. Three steps of DNA pooling, PCR amplification and sequencing are involved in this assay. Although direct determination of the allele frequency from the two allele-specific fluorescence intensities is possible, correction for differential response of alleles is important. We explored the effect of differential response of alleles on test statistics and provide a solution to this problem based on heterozygous fluorescence intensities. We demonstrate the accuracy and reliability of this assay on pooled DNA samples with pre-determined allele frequencies from 7.1% to 53.9%. The accuracy of allele frequency measurements is high, with a correlation coefficient of r2 = 0.997 between measured and known frequencies. We believe that by providing a means for SNP genotyping up to hundreds of samples simultaneously, inexpensively, and reproducibly, this method is a powerful strategy for detecting meaningful polymorphic differences in candidate gene association studies.     

A highly sensitive quantitative real-time PCR assay for determination of mutant JAK2 exon 12 allele burden

Mutations in the Janus kinase 2 (JAK2) gene have become an important identifier for the Philadelphia-chromosome negative chronic myeloproliferative neoplasms. In contrast to the JAK2V617F mutation, the large number of JAK2 exon 12 mutations has challenged the development of quantitative assays. We present a highly sensitive real-time quantitative PCR assay for determination of the mutant allele burden of JAK2 exon 12 mutations. In combination with high resolution melting analysis and sequencing the assay identified six patients carrying previously described JAK2 exon 12 mutations and one novel mutation. Two patients were homozygous with a high mutant allele burden, whereas one of the heterozygous patients had a very low mutant allele burden. The allele burden in the peripheral blood resembled that of the bone marrow, except for the patient with low allele burden. Myeloid and lymphoid cell populations were isolated by cell sorting and quantitative PCR revealed similar mutant allele burdens in CD16+ granulocytes and peripheral blood. The mutations were also detected in B-lymphocytes in half of the patients at a low allele burden. In conclusion, our highly sensitive assay provides an important tool for quantitative monitoring of the mutant allele burden and accordingly also for determining the impact of treatment with interferon-α-2, shown to induce molecular remission in JAK2V617F-positive patients, which may be a future treatment option for JAK2 exon 12-positive patients as well.     

ALFRED: An allele frequency database for anthropology

The deluge of data from the human genome project (HGP) presents new opportunities for molecular anthropologists to study human variation through the promise of vast numbers of new polymorphisms (e.g., single nucleotide polymorphisms or SNPs). Collecting the resulting data into a single, easily accessible resource will be important to facilitate this research. We created a prototype Web-accessible database named ALFRED (ALelle FREquency Database, http://alfred.med.yale.edu/alfred/) to store and make publicly available allele frequency data on diverse polymorphic sites for many populations. In constructing this database, we considered many different concerns relating to the types of information needed for anthropology, population genetics, molecular genetics, and statistics, as well as issues of data integrity and ease of access to data. We also developed links to other Web-based databases as well as procedures for others to make links to the data in ALFRED. Here we present an overview of the issues considered and provisional solutions, as well as an example of data already available. It is our hope that this database will be useful for research and teaching in a wide range of fields, and that colleagues from various fields will contribute to making ALFRED an important resource for many studies as yet unforeseen.     

Combining allele-specific fluorescent probes and restriction assay in real-time PCR to achieve SNP scoring beyond allele ratios of 1:1000

TaqMan-nuclease assays are widely used for the qualitative detection of single nucleotide polymorphisms (SNPs) and the determination of biallelic states in pooled or heterozygous DNA samples. These assays are highly specific, reproducible, and suitable for high-throughput approaches. A crucial limitation of this method, and others, is the detection qf minor allele frequencies with detection limits of generally 3% to 9% for minor allele contributions. Here we describe the combination of customized TaqMan-nuclease assay and allele-specific restriction to increase the sensitivity of this method, allowing the qualitative detection of allele contributions as low as 0.05%.     

Site frequency spectra from genomic SNP surveys

Genomic survey data now permit an unprecedented level of sensitivity in the detection of departures from canonical evolutionary models, including expansions in population size and selective sweeps. Here, we examine the effects of seemingly subtle differences among sampling distributions on goodness of fit analyses of site frequency spectra constructed from single nucleotide polymorphisms. Conditioning on the observation of exactly two alleles in a random sample results in a site frequency spectrum that is independent of the scaled rate of neutral substitution (θ). Other sampling distributions, including conditioning on a single mutational event in the sample genealogy or randomly selecting a single mutation from a genealogy with multiple mutations, have distinct site frequency spectra that show highly significant departures from the predictions of the biallelic model. Some aspects of data filtering may contribute to significant departures of site frequency spectra from expectation, apart from any violation of the standard neutral model.     

Development of a 25-plex SNP assay for traceability in cattle

Single nucleotide polymorphisms (SNPs) are amenable to automation and therefore have become the marker of choice for DNA profiling. SNaPshot , a primer extension-based method, was used to multiplex 25 SNPs that have been previously validated as useful for identity control. Detection of extended products was based on four different fluorochromes and extension primers with oligonucleotide tails of differing lengths, thus controlling the concise length of the entire chromatogram to 81 bases. Allele frequencies for Holstein, Simmental, Limousin, Angus, Charolais and Tux Cattle were estimated and significant positive Pearson-correlation coefficients were obtained among the analysed breeds. The probability that two randomly unrelated individuals would share identical genotypes for all 25 loci varied from 10⁻⁸ to 10⁻¹⁰ for these breeds. For parentage control, the exclusion power was found to be 99.9% when the genotypes of both putative parents are known. A traceability test of duplicated samples indicated a high genotyping precision of >0.998. This was further corroborated by analysis of 60 cases of parent–sib pairs and trio families. The 25-plex SNaPshot assay is adapted for low- and high-throughput capacity and thus presents an alternative for DNA-based traceability in the major commercial cattle breeds.     

A correction for allele frequency estimates derived from isofemale lines

Isofemale lines are commonly used inDrosophila and other genera for the purpose of assaying genetic variation. Isofemale lines can be kept in the laboratory for many generations before genetic work is carried out, and permit the confirmation of newly discovered alleles. A problem not realized by many workers is that the commonly used estimate of allele frequency from these lines is biased. This estimation bias occurs at all times after the first laboratory generation, regardless of whether single individuals or pooled samples are used in each well of an electrophoretic gel. This bias can potentially affect the estimation of population genetic parameters, and in the case of rare allele analysis it can cause gross overestimates of gene flow. This paper provides a correction for allele frequency estimates derived from isofemale lines for any time after the lines are established in the laboratory. When pooled samples are used, this estimator performs better than the standard estimator at all times after the first generation. The estimator is also insensitive to multiple inseminations. After the lines have drifted oneN _e generations, multiple inseminations actually make the new estimator perform better than it does in singly inseminated females. Simulations show that estimates made using either estimator after the lines have drifted to fixation have a much greater error associated with their use than do those estimates made earlier in time using the correction. In general it is better to use corrected estimates of gene frequency soon after lines are established than to use uncorrected estimates made after the first laboratory generation. This work was supported by an NSERC fellowship to A.D.L.