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.     

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.     

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.     

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.     

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.     

Single nucleotide polymorphism (SNP) discovery in porcine expressed genes

High-throughput genotyping of swine populations is a potentially efficient method for establishing animal lineage and identification of loci important to animal health and efficient pork production. Markers were developed based upon single nucleotide polymorphisms (SNPs), which are abundant and amenable to automated genotyping platforms. The focus of this research was SNP discovery in expressed porcine genes providing markers to develop the porcine/human comparative map. Locus specific amplification (LSA) and comparative sequencing were used to generate PCR products and allelic information from parents of a swine reference family. Discovery of 1650 SNPs in 403 amplicons and strategies for optimizing LSA-based SNP discovery using alternative methods of PCR primer design, data analysis, and germplasm selection that are applicable to other populations and species are described. These data were the first large-scale assessment of frequency and distribution of porcine SNPs.     

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.     

Predicting allele frequencies in DNA pools using high density SNP genotyping data

To evaluate the ability to use DNA pools with the Illumina Infinium genotyping platform, two sets of gradient pools were created using two pairs of highly inbred chicken lines. Replicate pools containing 0%, 10%, 20%, 40%, 60%, 80%, 90% and 100% of DNA from line A vs. B or line C vs. D were created, for a total of 28 pools. All pools were genotyped for 12 046 SNPs. Three frequency estimation methods proposed in the literature (standard, heterozygote‐corrected and normalized) were compared with three alternate methods proposed herein based on mean square error (MSE), bias and variance of estimated vs. true allele frequencies and the fit of regression of estimated on true frequencies. The three new methods had average square root MSE of 4.6%, 4.6% and 4.7% compared to 5.2%, 5.5% and 11.2% for the three literature methods. Average absolute biases of the literature methods were 2.4%, 2.7% and 8.2% compared to 2.4% for all new methods. Standard deviations of estimates were also smaller for the new methods, at 3.1%, 3.2% and 3.2% compared to 3.5%, 4.0% and 5.0% for previously reported methods. In conclusion, intensity data from the Illumina Infinium Assay can be efficiently used to estimate allele frequencies in pools, in particular using any of the new methods proposed herein.     

Single nucleotide polymorphism (SNP) discovery in mammals: a targeted-gene approach

Single nucleotide polymorphisms (SNPs) have rarely been exploited in nonhuman and nonmodel organism genetic studies. This is due partly to difficulties in finding SNPs in species where little DNA sequence data exist, as well as to a lack of robust and inexpensive genotyping methods. We have explored one SNP discovery method for molecular ecology, evolution, and conservation studies to evaluate the method and its limitations for population genetics in mammals. We made use of 'CATS' (or 'EPIC') primers to screen for novel SNPs in mammals. Most of these primer sets were designed from primates and/or rodents, for amplifying intron regions from conserved genes. We have screened 202 loci in 16 representatives of the major mammalian clades. Polymerase chain reaction (PCR) success correlated with phylogenetic distance from the human and mouse sequences used to design most primers; for example, specific PCR products from primates and the mouse amplified the most consistently and the marsupial and armadillo amplifications were least successful. Approximately 24% (opossum) to 65% (chimpanzee) of primers produced usable PCR product(s) in the mammals tested. Products produced generally high but variable levels of readable sequence and similarity to the expected genes. In a preliminary screen of chimpanzee DNA, 12 SNPs were identified from six (of 11) sequenced regions, yielding a SNP on average every 400 base pairs (bp). Given the progress in genome sequencing, and the large numbers of CATS-like primers published to date, this approach may yield sufficient SNPs per species for population and conservation genetic studies in nonmodel mammals and other organisms.     

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.     

Single nucleotide polymorphism (SNP) discovery and linkage mapping of bovine cytokine genes

Polymorphic markers at bovine gene loci facilitate the integration of cattle genetic maps with those of humans and mice. To this end, 31 single nucleotide polymorphism (SNP) markers were developed for seven bovine chemokine genes. Loci were amplified from bovine genomic DNA by the polymerase chain reaction, and candidate amplicons were sequenced to determine their identity. Amplified loci from 24 founding parents and select progeny from a beef cattle reference population were sequenced and analyzed for SNPs. SNP haplotype alleles were determined by examining segregation patterns and used to establish the locus position on the bovine linkage map. Loci for growth-related proteins (GRO3, GRO1, and GROX) were clustered with the related CXC chemokine genes, interleukin (IL) 8, and epithelial cell inflammatory protein 1, at 84 cM from the centromeric end of the bovine chromosome (BTA) 6 linkage group. Bovine loci for a cluster of IL8 receptors, a stromal cell-derived factor 1, interferon-γ, and tumor necrosis factor-α were mapped at 90, 55, 59, and 34 cM, respectively, from the centromeric ends of the BTA 2, 28, 5, and 23 linkage groups. The positions of these bovine loci were compared with those of orthologous loci on the human map to refine the boundaries of conserved synteny. These seven loci provide examples of SNP development in which the efficiency was largely dependent on the availability of bovine genomic or cDNA sequence. The polymorphic nature of these SNP haplotype markers suggests that they will be useful for mapping complex traits in cattle, such as resistance to infectious disease. Received: 30 April 1999 / Accepted: 12 July 1999     

Single nucleotide polymorphism (SNP) in alpha-lactalbumin gene of Indian Jamunapari breed of Capra hircus

Alpha-lactalbumin is a major whey protein found in milk. It influences lactose synthesis by modifying the substrate specificity of galactosyl-transferase, is important to milk synthesis since lactose, an impermeable disaccharide, is the major osmole of milk. The present study was undertaken to detect polymorphism in the full coding region of alpha-lactalbumin at the genetic level and to explore allelic variability of this gene. Samples of Jamunapari breed of goat (n = 50) were included under the present study. Jamunapari is the highest milk producer among local Indian goat breeds. PCR-SSCP of all four exons of alpha-lactalbumin (ALA) revealed a total of 9 gel phenotypes of Jamunapari breed of goat. These were sequenced, analyzed and deposited in GenBank, NCBI (accession nos. EU573193–EU573195). Nucleotide and amino acid variations were searched within breeds of Indian goats and homology between caprine, ovine, bovine, bubaline and human. In the present study we describe for the first time two novel gene variants on the goat alpha-lactalbumin gene exon 4.     

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.     

Multiplex single nucleotide polymorphism (SNP)-based genotyping in allohexaploid wheat using padlock probes

Single nucleotide polymorphisms are the most common polymorphism in plant and animal genomes and, as such, are the logical choice for marker-assisted selection. However, many plants are also polyploid, and marker-assisted selection can be complicated by the presence of highly similar, but non-allelic, homoeologous sequences. Despite this, there is practical and academic demand for high-throughput genotyping in several polyploid crop species, such as allohexaploid wheat. In this paper, we present such a system, which utilizes public single nucleotide polymorphisms previously identified in both agronomically important genes and in randomly selected, mapped, expressed sequence tags developed by the wheat community. To achieve relatively high levels of multiplexing, we used non-amplified genomic DNA and padlock probe pairs, together with high annealing temperatures, to differentiate between similar sequences in the wheat genome. Our results suggest that padlock probes are capable of discriminating between homoeologous sequences and hence can be used to efficiently genotype wheat varieties.     

Nanoparticle-based detection and quantification of DNA with single nucleotide polymorphism (SNP) discrimination selectivity

Sequence-specific DNA detection is important in various biomedical applications such as gene expression profiling, disease diagnosis and treatment, drug discovery and forensic analysis. Here we report a gold nanoparticle-based method that allows DNA detection and quantification and is capable of single nucleotide polymorphism (SNP) discrimination. The precise quantification of single-stranded DNA is due to the formation of defined nanoparticle-DNA conjugate groupings in the presence of target/linker DNA. Conjugate groupings were characterized and quantified by gel electrophoresis. A linear correlation between the amount of target DNA and conjugate groupings was found. For SNP detection, single base mismatch discrimination was achieved for both the end- and center-base mismatch. The method described here may be useful for the development of a simple and quantitative DNA detection assay.     

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.     

Single nucleotide polymorphism discovery in barley using autoSNPdb

Molecular markers are used to provide the link between genotype and phenotype, for the production of molecular genetic maps and to assess genetic diversity within and between related species. Single nucleotide polymorphisms (SNPs) are the most abundant molecular genetic marker. SNPs can be identified in silico , but care must be taken to ensure that the identified SNPs reflect true genetic variation and are not a result of errors associated with DNA sequencing. The SNP detection method autoSNP has been developed to identify SNPs from sequence data for any species. Confidence in the predicted SNPs is based on sequence redundancy, and haplotype co-segregation scores are calculated for a further independent measure of confidence. We have extended the autoSNP method to produce autoSNPdb, which integrates SNP and gene annotation information with a graphical viewer. We have applied this software to public barley expressed sequences, and the resulting database is available over the Internet. SNPs can be viewed and searched by sequence, functional annotation or predicted synteny with a reference genome, in this case rice. The correlation between SNPs and barley cultivar, expressed tissue type and development stage has been collated for ease of exploration. An average of one SNP per 240 bp was identified, with SNPs more prevalent in the 5' regions and simple sequence repeat (SSR) flanking sequences. Overall, autoSNPdb can provide a wealth of genetic polymorphism information for any species for which sequence data are available.     

A graphene-based platform for single nucleotide polymorphism (SNP) genotyping

A facile, rapid, stable and sensitive approach for fluorescent detection of single nucleotide polymorphism (SNP) is designed based on DNA ligase reaction and π-stacking between the graphene and the nucleotide bases. In the presence of perfectly matched DNA, DNA ligase can catalyze the linkage of fluorescein amidite-labeled single-stranded DNA (ssDNA) and a phosphorylated ssDNA, and thus the formation of a stable duplex in high yield. However, the catalytic reaction cannot effectively carry out with one-base mismatched DNA target. In this case, we add graphene to the system in order to produce different quenching signals due to its different adsorption affinity for ssDNA and double-stranded DNA. Taking advantage of the unique surface property of graphene and the high discriminability of DNA ligase, the proposed protocol exhibits good performance in SNP genotyping. The results indicate that it is possible to accurately determine SNP with frequency as low as 2.6% within 40 min. Furthermore, the presented flexible strategy facilitates the development of other biosensing applications in the future.     

Targeted single nucleotide polymorphism (SNP) discovery in a highly polyploid plant species using 454 sequencing

Discovering single nucleotide polymorphisms (SNPs) in specific genes in a heterozygous polyploid plant species, such as sugarcane, is challenging because of the presence of a large number of homologues. To discover SNPs for mapping genes of interest, 454 sequencing of 307 polymerase chain reaction (PCR) amplicons (> 59 kb of sequence) was undertaken. One region of a four-gasket sequencing run, on a 454 Genome Sequencer FLX, was used for pooled PCR products amplified from each parent of a quantitative trait locus (QTL) mapping population (IJ76-514 × Q165). The sequencing yielded 96 755 (IJ76-514) and 86 241 (Q165) sequences with perfect matches to a PCR primer used in amplification, with an average sequence depth of approximately 300 and an average read length of 220 bases. Further analysis was carried out on amplicons whose sequences clustered into a single contig using an identity of 80% with the program cap 3. In the more polymorphic sugarcane parent (Q165), 94% of amplicons (227/242) had evidence of a reliable SNP – an average of one every 35 bases. Significantly fewer SNPs were found in the pure Saccharum officinarum parent – with one SNP every 58 bases and SNPs in 86% (213/247) of amplicons. Using automatic SNP detection, 1632 SNPs were detected in Q165 sequences and 1013 in IJ76-514. From 225 candidate SNP sites tested, 209 (93%) were validated as polymorphic using the Sequenom MassARRAY system. Amplicon re-sequencing using the 454 system enables cost-effective SNP discovery that can be targeted to genes of interest and is able to perform in the highly challenging area of polyploid genomes.