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.     

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.     

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.     

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.     

Cheap, accurate and rapid allele frequency estimation of single nucleotide polymorphisms by primer extension and DHPLC in DNA pools

At present, the cost of genotyping single nucleotide polymorphisms (SNPs) in large numbers of subjects poses a formidable problem for molecular genetic approaches to complex diseases. We have tested the possibility of using primer extension and denaturing high performance liquid chromatography to estimate allele frequencies of SNPs in pooled DNA samples. Our data show that this method should allow the accurate estimation of absolute allele frequencies in pooled samples of DNA and also of the difference in allele frequency between different pooled DNA samples. This technique therefore offers an efficient and cheap method for genotyping SNPs in large case-control and family-based association samples.     

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.     

Validation of SNP Allele Frequencies Determined by Pooled Next-Generation Sequencing in Natural Populations of a Non-Model Plant Species

Sequencing of pooled samples (Pool-Seq) using next-generation sequencing technologies has become increasingly popular, because it represents a rapid and cost-effective method to determine allele frequencies for single nucleotide polymorphisms (SNPs) in population pools. Validation of allele frequencies determined by Pool-Seq has been attempted using an individual genotyping approach, but these studies tend to use samples from existing model organism databases or DNA stores, and do not validate a realistic setup for sampling natural populations. Here we used pyrosequencing to validate allele frequencies determined by Pool-Seq in three natural populations of Arabidopsis halleri (Brassicaceae). The allele frequency estimates of the pooled population samples (consisting of 20 individual plant DNA samples) were determined after mapping Illumina reads to (i) the publicly available, high-quality reference genome of a closely related species (Arabidopsis thaliana) and (ii) our own de novo draft genome assembly of A. halleri. We then pyrosequenced nine selected SNPs using the same individuals from each population, resulting in a total of 540 samples. Our results show a highly significant and accurate relationship between pooled and individually determined allele frequencies, irrespective of the reference genome used. Allele frequencies differed on average by less than 4%. There was no tendency that either the Pool-Seq or the individual-based approach resulted in higher or lower estimates of allele frequencies. Moreover, the rather high coverage in the mapping to the two reference genomes, ranging from 55 to 284x, had no significant effect on the accuracy of the Pool-Seq. A resampling analysis showed that only very low coverage values (below 10-20x) would substantially reduce the precision of the method. We therefore conclude that a pooled re-sequencing approach is well suited for analyses of genetic variation in natural populations.     

PPC: an algorithm for accurate estimation of SNP allele frequencies in small equimolar pools of DNA using data from high density microarrays

Robust estimation of allele frequencies in pools of DNA has the potential to reduce genotyping costs and/or increase the number of individuals contributing to a study where hundreds of thousands of genetic markers need to be genotyped in very large populations sample sets, such as genome wide association studies. In order to make accurate allele frequency estimations from pooled samples a correction for unequal allele representation must be applied. We have developed the polynomial based probe specific correction (PPC) which is a novel correction algorithm for accurate estimation of allele frequencies in data from high-density microarrays. This algorithm was validated through comparison of allele frequencies from a set of 10 individually genotyped DNA's and frequencies estimated from pools of these 10 DNAs using GeneChip 10K Mapping Xba 131 arrays. Our results demonstrate that when using the PPC to correct for allelic biases the accuracy of the allele frequency estimates increases dramatically.     

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.     

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.     

Multiplex SNP genotyping in pooled DNA samples by a four-colour microarray system

We selected 125 candidate single nucleotide polymorphisms (SNPs) in genes belonging to the human type 1 interferon (IFN) gene family and the genes coding for proteins in the main type 1 IFN signalling pathway by screening databases and by in silico comparison of DNA sequences. Using quantitative analysis of pooled DNA samples by solid-phase mini-sequencing, we found that only 20% of the candidate SNPs were polymorphic in the Finnish and Swedish populations. To allow more effective validation of candidate SNPs, we developed a four-colour microarray-based mini-sequencing assay for multiplex, quantitative allele frequency determination in pooled DNA samples. We used cyclic mini-sequencing reactions with primers carrying 5′-tag sequences, followed by capture of the products on microarrays by hybridisation to complementary tag oligonucleotides. Standard curves prepared from mixtures of known amounts of SNP alleles demonstrate the applicability of the system to quantitative analysis, and showed that for about half of the tested SNPs the limit of detection for the minority allele was below 5%. The microarray-based genotyping system established here is universally applicable for genotyping and quantification of any SNP, and the validated system for SNPs in type 1 IFN-related genes should find many applications in genetic studies of this important immunoregulatory pathway.     

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.     

Large-scale genotyping of complex DNA

Genetic studies aimed at understanding the molecular basis of complex human phenotypes require the genotyping of many thousands of single-nucleotide polymorphisms (SNPs) across large numbers of individuals. Public efforts have so far identified over two million common human SNPs; however, the scoring of these SNPs is labor-intensive and requires a substantial amount of automation. Here we describe a simple but effective approach, termed whole-genome sampling analysis (WGSA), for genotyping thousands of SNPs simultaneously in a complex DNA sample without locus-specific primers or automation. Our method amplifies highly reproducible fractions of the genome across multiple DNA samples and calls genotypes at >99% accuracy. We rapidly genotyped 14,548 SNPs in three different human populations and identified a subset of them with significant allele frequency differences between groups. We also determined the ancestral allele for 8,386 SNPs by genotyping chimpanzee and gorilla DNA. WGSA is highly scaleable and enables the creation of ultrahigh density SNP maps for use in genetic studies.     

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.     

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.     

High-resolution SNP scan of chromosome 6p21 in pooled samples from patients with complex diseases

We apply a high-throughput protocol of chip-based mass spectrometry (matrix-assisted laser desorption/ionization time-of-flight; MALDI-TOF) as a method of screening for differences in single-nucleotide polymorphism (SNP) allele frequencies. Using pooled DNA from individuals with asthma, Crohn's disease (CD), schizophrenia, type 1 diabetes (T1D), and controls, we selected 534 SNPs from an initial set of 1435 SNPs spanning a 25-Mb region on chromosome 6p21. The standard deviations of measurements of time of flight at different dots, from different PCRs, and from different pools indicate reliable results on each analysis step. In 90% of the disease-control comparisons we found allelic differences of <10%. Of the T1D samples, which served as a positive control, 10 SNPs with significant differences were observed after taking into account multiple testing. Of these 10 SNPs, 5 are located between DQB1 and DRB1, confirming the known association with the DR3 and DR4 haplotypes whereas two additional SNPs also reproduced known associations of T1D with DOB and LTA. In the CD pool also, two earlier described associations were found with SNPs close to DRB1 and MICA. Additional associations were found in the schizophrenia and asthma pools. They should be confirmed in individual samples or can be used to develop further quality criteria for accepting true differences between pools. The determination of SNP allele frequencies in pooled DNA appears to be of value in assigning further genotyping priorities also in large linkage regions.     

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.     

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.