Estimation of relative allele frequencies of single-nucleotide polymorphisms in different populations by microarray hybridization of pooled DNA

Single-nucleotide polymorphisms (SNPs) are considered useful polymorphic markers for genetic studies of polygenic traits. A new practical approach to high-throughput genotyping of SNPs in a large number of individuals is needed in association study and other studies on relationships between genes and diseases. We have developed an accurate and high-throughput method for determining the allele frequencies by pooling the DNA samples and applying a DNA microarray hybridization analysis. In this method, the combination of the microarray, DNA pooling, probe pair hybridization, and fluorescent ratio analysis solves the dual problems of parallel multiple sample analysis, and parallel multiplex SNP genotyping for association study. Multiple DNA samples are immobilized on a slide and a single hybridization is performed with a pool of allele-specific oligonucleotide probes. The results of this study show that hybridization of microarray from pooled DNA samples can accurately obtain estimates of absolute allele frequencies in a sample pool. This method can also be used to identify differences in allele frequencies in distinct populations. It is amenable to automation and is suitable for immediate utilization for high-throughput genotyping of SNP.     

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.     

Estimation of allele frequency in pooled DNA by using PCR–RFLP combined with microchip electrophoresis

Biallelic marker, most commonly single nucleotide polymorphism (SNP), is widely utilized in genetic association analysis, which can be speeded up by estimating allele frequency in pooled DNA instead of individual genotyping. Several methods have shown high accuracy and precision for allele frequency estimation in pools. Here, we explored PCR restriction fragment length polymorphism (PCR–RFLP) combined with microchip electrophoresis as a possible strategy for allele frequency estimation in DNA pools. We have used the commercial available Agilent 2100 microchip electrophoresis analysis system for quantifying the enzymatically digested DNA fragments and the fluorescence intensities to estimate the allele frequencies in the DNA pools. In this study, we have estimated the allele frequencies of five SNPs in a DNA pool composed of 141 previously genotyped health controls and a DNA pool composed of 96 previously genotyped gastric cancer patients with a frequency representation of 10–90% for the variant allele. Our studies show that accurate, quantitative data on allele frequencies, suitable for investigating the association of SNPs with complex disorders, can be estimated from pooled DNA samples by using this assay. This approach, being independent of the number of samples, promises to drastically reduce the labor and cost of genotyping in the initial association analysis.     

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.     

Precise estimation of allele frequencies of single-nucleotide polymorphisms by a quantitative SSCP analysis of pooled DNA

We show that single-nucleotide polymorphisms (SNPs) of moderate to high heterozygosity (minor allele frequencies >10%) can be efficiently detected, and their allele frequencies accurately estimated, by pooling the DNA samples and applying a capillary-based SSCP analysis. In this method, alleles are separated into peaks, and their frequencies can be reliably and accurately quantified from their peak heights (SD <1.8%). We found that as many as 40% of publicly available SNPs that were analyzed by this method have widely differing allele frequency distributions among groups of different ethnicity (parents of Centre d'Etude Polymorphisme Humaine families vs. Japanese individuals). These results demonstrate the effectiveness of the present pooling method in the reevaluation of candidate SNPs that have been collected by examination of limited numbers of individuals. The method should also serve as a robust quantitative technique for studies in which a precise estimate of SNP allele frequencies is essential-for example, in linkage disequilibrium analysis.     

Estimation of population allele frequencies from next‐generation sequencing data: pool‐versus individual‐based genotyping

Molecular markers produced by next‐generation sequencing (NGS) technologies are revolutionizing genetic research. However, the costs of analysing large numbers of individual genomes remain prohibitive for most population genetics studies. Here, we present results based on mathematical derivations showing that, under many realistic experimental designs, NGS of DNA pools from diploid individuals allows to estimate the allele frequencies at single nucleotide polymorphisms (SNPs) with at least the same accuracy as individual‐based analyses, for considerably lower library construction and sequencing efforts. These findings remain true when taking into account the possibility of substantially unequal contributions of each individual to the final pool of sequence reads. We propose the intuitive notion of effective pool size to account for unequal pooling and derive a Bayesian hierarchical model to estimate this parameter directly from the data. We provide a user‐friendly application assessing the accuracy of allele frequency estimation from both pool‐ and individual‐based NGS population data under various sampling, sequencing depth and experimental error designs. We illustrate our findings with theoretical examples and real data sets corresponding to SNP loci obtained using restriction site–associated DNA (RAD) sequencing in pool‐ and individual‐based experiments carried out on the same population of the pine processionary moth (Thaumetopoea pityocampa). NGS of DNA pools might not be optimal for all types of studies but provides a cost‐effective approach for estimating allele frequencies for very large numbers of SNPs. It thus allows comparison of genome‐wide patterns of genetic variation for large numbers of individuals in multiple populations.     

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.     

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.     

Evaluation of DNA pooling for the estimation of microsatellite allele frequencies: a case study using striped bass (Morone saxatilis)

Using striped bass (Morone saxatilis) and six multiplexed microsatellite markers, we evaluated procedures for estimating allele frequencies by pooling DNA from multiple individuals, a method suggested as cost-effective relative to individual genotyping. Using moment-based estimators, we estimated allele frequencies in experimental DNA pools and found that the three primary laboratory steps, DNA quantitation and pooling, PCR amplification, and electrophoresis, accounted for 23, 48, and 29%, respectively, of the technical variance of estimates in pools containing DNA from 2-24 individuals. Exact allele-frequency estimates could be made for pools of sizes 2-8, depending on the locus, by using an integer-valued estimator. Larger pools of size 12 and 24 tended to yield biased estimates; however, replicates of these estimates detected allele frequency differences among pools with different allelic compositions. We also derive an unbiased estimator of Hardy-Weinberg disequilibrium coefficients that uses multiple DNA pools and analyze the cost-efficiency of DNA pooling. DNA pooling yields the most potential cost savings when a large number of loci are employed using a large number of individuals, a situation becoming increasingly common as microsatellite loci are developed in increasing numbers of taxa.     

DNA 池结合DHPLC 和直接测序技术在江豚SNPs 检测中的应用

选取江豚基因组中的2 个已知单核苷酸多态性(single nucleotide polymorphisms,SNPs)位点,通过PCR 扩增,将PCR 产物按基因频率不同制备成0 ～ 50% 的11 个DNA 池(DNA pool),用于变性高效液相色谱(denaturing high performance liquid chromatography,DHPLC)和直接测序分析,以探讨DNA 池中基因频率的最低要求。结果显示,当稀有等位基因的基因频率不少于5% 时可在DHPLC 检测过程中明显分辨;而利用DNA 池进行直接测序时的基因频率则需达到10% 。这提示,为保证DHPLC 分析的准确性和可靠性,制备DNA 池时等摩尔DNA 混合的个体数最好不超过10 个。DNA 池结合DHPLC 技术的高效性与准确性可在大规模的SNPs 位点筛选中发挥作用。     

Kinetic FP-TDI assay for SNP allele frequency determination

Strategies for identifying genetic risk factors in complex diseases by association studies require the comparison of allele frequencies of numerous SNPs between affected and control populations. Theoretically, hundreds of thousands of SNP markers across the genome will have to be genotyped in these studies. Genotyping SNPs one sample at a time is extremely costly and time consuming. To streamline whole genome association studies, some have proposed to screen SNPs by pooling the DNA samples initially for allele frequency determination and perform individual genotyping only when there is a significant discrepancy in allele frequencies between the affected and control populations. Here we describe a new method for determining the allele frequency of SNPs in pooled DNA samples using a two-color primer extension assay with real-time monitoring of fluorescence polarization (named kinetic FP-TDI assay). By comparing the ratio of the rate of incorporation of the two allele-specific dye-terminators, one can calculate the relative amounts of each allele in the pooled sample. The accuracy of allele frequency determination with pooled samples is within 3.3 +/- 0.8% of that determined by genotyping individual samples that make up the pool.     

Rapid Assessment of Genetic Ancestry in Populations of Unknown Origin by Genome-Wide Genotyping of Pooled Samples

As we move forward from the current generation of genome-wide association (GWA) studies, additional cohorts of different ancestries will be studied to increase power, fine map association signals, and generalize association results to additional populations. Knowledge of genetic ancestry as well as population substructure will become increasingly important for GWA studies in populations of unknown ancestry. Here we propose genotyping pooled DNA samples using genome-wide SNP arrays as a viable option to efficiently and inexpensively estimate admixture proportion and identify ancestry informative markers (AIMs) in populations of unknown origin. We constructed DNA pools from African American, Native Hawaiian, Latina, and Jamaican samples and genotyped them using the Affymetrix 6.0 array. Aided by individual genotype data from the African American cohort, we established quality control filters to remove poorly performing SNPs and estimated allele frequencies for the remaining SNPs in each panel. We then applied a regression-based method to estimate the proportion of admixture in each cohort using the allele frequencies estimated from pooling and populations from the International HapMap Consortium as reference panels, and identified AIMs unique to each population. In this study, we demonstrated that genotyping pooled DNA samples yields estimates of admixture proportion that are both consistent with our knowledge of population history and similar to those obtained by genotyping known AIMs. Furthermore, through validation by individual genotyping, we demonstrated that pooling is quite effective for identifying SNPs with large allele frequency differences (i.e., AIMs) and that these AIMs are able to differentiate two closely related populations (HapMap JPT and CHB).     

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.     

Finding Markers That Make a Difference: DNA Pooling and SNP-Arrays Identify Population Informative Markers for Genetic Stock Identification

Genetic stock identification (GSI) using molecular markers is an important tool for management of migratory species. Here, we tested a cost-effective alternative to individual genotyping, known as allelotyping, for identification of highly informative SNPs for accurate genetic stock identification. We estimated allele frequencies of 2880 SNPs from DNA pools of 23 Atlantic salmon populations using Illumina SNP-chip. We evaluated the performance of four common strategies (global F _ST, pairwise F _ST, Delta and outlier approach) for selection of the most informative set of SNPs and tested their effectiveness for GSI compared to random sets of SNP and microsatellite markers. For the majority of cases, SNPs selected using the outlier approach performed best followed by pairwise F _ST and Delta methods. Overall, the selection procedure reduced the number of SNPs required for accurate GSI by up to 53% compared with randomly chosen SNPs. However, GSI accuracy was more affected by populations in the ascertainment group rather than the ranking method itself. We demonstrated for the first time the compatibility of different large-scale SNP datasets by compiling the largest population genetic dataset for Atlantic salmon to date. Finally, we showed an excellent performance of our top SNPs on an independent set of populations covering the main European distribution range of Atlantic salmon. Taken together, we demonstrate how combination of DNA pooling and SNP arrays can be applied for conservation and management of salmonids as well as other species.     

DNA pooling: a comprehensive, multi-stage association analysis of ACSL6 and SIRT5 polymorphisms in schizophrenia

Many candidate gene association studies have evaluated incomplete, unrepresentative sets of single nucleotide polymorphisms (SNPs), producing non-significant results that are difficult to interpret. Using a rapid, efficient strategy designed to investigate all common SNPs, we tested associations between schizophrenia and two positional candidate genes: ACSL6 (Acyl-Coenzyme A synthetase long-chain family member 6) and SIRT5 (silent mating type information regulation 2 homologue 5). We initially evaluated the utility of DNA sequencing traces to estimate SNP allele frequencies in pooled DNA samples. The mean variances for the DNA sequencing estimates were acceptable and were comparable to other published methods (mean variance: 0.0008, range 0-0.0119). Using pooled DNA samples from cases with schizophrenia/schizoaffective disorder (Diagnostic and Statistical Manual of Mental Disorders edition IV criteria) and controls (n=200, each group), we next sequenced all exons, introns and flanking upstream/downstream sequences for ACSL6 and SIRT5. Among 69 identified SNPs, case-control allele frequency comparisons revealed nine suggestive associations (P<0.2). Each of these SNPs was next genotyped in the individual samples composing the pools. A suggestive association with rs 11743803 at ACSL6 remained (allele-wise P=0.02), with diminished evidence in an extended sample (448 cases, 554 controls, P=0.062). In conclusion, we propose a multi-stage method for comprehensive, rapid, efficient and economical genetic association analysis that enables simultaneous SNP detection and allele frequency estimation in large samples. This strategy may be particularly useful for research groups lacking access to high throughput genotyping facilities. Our analyses did not yield convincing evidence for associations of schizophrenia with ACSL6 or SIRT5.     

Genotyping pooled DNA using 100K SNP microarrays: a step towards genomewide association scans

The identification of quantitative trait loci (QTLs) of small effect size that underlie complex traits poses a particular challenge for geneticists due to the large sample sizes and large numbers of genetic markers required for genomewide association scans. An efficient solution for screening purposes is to combine single nucleotide polymorphism (SNP) microarrays and DNA pooling (SNP-MaP), an approach that has been shown to be valid, reliable and accurate in deriving relative allele frequency estimates from pooled DNA for groups such as cases and controls for 10K SNP microarrays. However, in order to conduct a genomewide association study many more SNP markers are needed. To this end, we assessed the validity and reliability of the SNP-MaP method using Affymetrix GeneChip^® Mapping 100K Array set. Interpretable results emerged for 95% of the SNPs (nearly 110000 SNPs). We found that SNP-MaP allele frequency estimates correlated 0.939 with allele frequencies for 97605 SNPs that were genotyped individually in an independent population; the correlation was 0.971 for 26 SNPs that were genotyped individually for the 1028 individuals used to construct the DNA pools. We conclude that extending the SNP-MaP method to the Affymetrix GeneChip^® Mapping 100K Array set provides a useful screen of >100000 SNP markers for QTL association scans.     

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.     

Quantitative approach to single-nucleotide polymorphism analysis using MALDI-TOF mass spectrometry

Pooling of DNA samples before genotyping is a valuable means of streamlining large-scale genotyping efforts in disease association studies, single-nucleotide polymorphism (SNP) validation or mutant allele screening programs. In this report, we explore the application of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to quantitative analysis of SNPs. The measurements are based on MALDI-TOF MS analysis of primer extension assays performed on standard mixtures of pooled PCR products at several test loci. The inherent high molecular weight resolution of MALDI-TOF MS conveys high specificity and good signal-to-noise ratio for performing accurate quantitation. The methods described maximize the sensitivity and quantitative capacity of MALDI-TOF MS while preserving the throughput and economic advantages of the MALDI-TOF platform. Using the format described, we demonstrate that allele frequencies as low as 5% can be detected quantitatively and unambiguously.     

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.     

Different real time PCR approaches for the fine quantification of SNP's alleles in DNA pools: assays development, characterization and pre-validation

Single nucleotide polymorphisms (SNPs) are becoming the most common type of markers used in genetic analysis. In the present report a SNP has been chosen to test the applicability of Real Time PCR to discriminate and quantify SNPs alleles on DNA pools. Amplification Refractory Mutation System (ARMS) and Mismatch Amplification Mutation Assay (MAMA) has been applied. Each assay has been pre-validated testing specificity and performances (linearity, PCR efficiency, interference limit, limit of detection, limit of quantification, precision and accuracy). Both the approaches achieve a precise and accurate estimation of the allele frequencies on pooled DNA samples in the range from 5 % to 95 % and don't require standard curves or calibrators. The lowest measurement that could be significantly distinguished from the background noise has been determined around the 1 % for both the approaches, allowing to extend the range of quantifications from 1 % to 99 %. Furthermore applicability of Real Time PCR assays for general diagnostic purposes is discussed.