Determining SNP allele frequencies in DNA pools.
TL;DR: Both radiation-based methods for the determination of SNP allele frequencies gave accurate and reproducible results, suggesting they are suitable for use in DNA pooling experiments.
Abstract: 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.
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TL;DR: Recent developments in quantitative genotyping assays and in the design and analysis of pooling studies are discussed.
Abstract: DNA pooling is a practical way to reduce the cost of large-scale association studies to identify susceptibility loci for common diseases. Pooling allows allele frequencies in groups of individuals to be measured using far fewer PCR reactions and genotyping assays than are used when genotyping individuals. Here, we discuss recent developments in quantitative genotyping assays and in the design and analysis of pooling studies. Sophisticated pooling designs are being developed that can take account of hidden population stratification, confounders and inter-loci interactions, and that allow the analysis of haplotypes.
582 citations
TL;DR: The current efforts to identify and characterize the large numbers of SNPs required and the practicalities of association studies for the identification of genes involved in complex traits are described.
Abstract: The development of detailed single nucleotide polymorphism (SNP) maps of the human genome coupled with high-throughput genotyping technologies may allow us to unravel complex genetic traits, such as multifactorial disease or drug response, over the next few years. Here we describe the current efforts to identify and characterize the large numbers of SNPs required and discuss the practicalities of association studies for the identification of genes involved in complex traits.
251 citations
Cites background from "Determining SNP allele frequencies ..."
...One potential way of reducing the number of assays required (and hence cost), together with preserving valuable DNA resources, is to genotype equimolar pools of DNA from affected individuals and corresponding pools from controls and quantify the results (40)....
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TL;DR: It is shown that multiple SNP sites from different genes over distant parts of the genome are better at identifying breast cancer patients than any one SNP alone.
Abstract: Hereditary predisposition and causative environmental exposures have long been recognized in human malignancies. In most instances, cancer cases occur sporadically, suggesting that environmental influences are critical in determining cancer risk. To test the influence of genetic polymorphisms on breast cancer risk, we have measured 98 single nucleotide polymorphisms (SNPs) distributed over 45 genes of potential relevance to breast cancer etiology in 174 patients and have compared these with matched normal controls. Using machine learning techniques such as support vector machines (SVMs), decision trees, and naive Bayes, we identified a subset of three SNPs as key discriminators between breast cancer and controls. The SVMs performed maximally among predictive models, achieving 69% predictive power in distinguishing between the two groups, compared with a 50% baseline predictive power obtained from the data after repeated random permutation of class labels (individuals with cancer or controls). However, the simpler naive Bayes model as well as the decision tree model performed quite similarly to the SVM. The three SNP sites most useful in this model were (a) the +4536T/C site of the aldosterone synthase gene CYP11B2 at amino acid residue 386 Val/Ala (T/C) (rs4541); (b) the +4328C/G site of the aryl hydrocarbon hydroxylase CYP1B1 at amino acid residue 293 Leu/Val (C/G) (rs5292); and (c) the +4449C/T site of the transcription factor BCL6 at amino acid 387 Asp/Asp (rs1056932). No single SNP site on its own could achieve more than 60% in predictive accuracy. We have shown that multiple SNP sites from different genes over distant parts of the genome are better at identifying breast cancer patients than any one SNP alone. As high-throughput technology for SNPs improves and as more SNPs are identified, it is likely that much higher predictive accuracy will be achieved and a useful clinical tool developed.
189 citations
Cites methods from "Determining SNP allele frequencies ..."
...DNA was quantitated using the Pico green fluorescence assay (31)....
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TL;DR: This work has 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 and, for the first time, permit high-throughput association analysis at a realistic cost.
Abstract: 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 001 Moreover, when we genotyped seven different SNPs in a single multiplex reaction, the results were similar, with a mean error for Delta of 0008 The assay performed well for alleles of low frequency alleles (f approximately 005) 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
176 citations
TL;DR: A new method for SNP analysis based on the detection of pyrophosphate (PPi) is demonstrated, which is capable of detecting small allele frequency differences between two DNA pools for genetic association studies other than SNP typing.
Abstract: A new method for SNP analysis based on the detection of pyrophosphate (PPi) is demonstrated, which is capable of detecting small allele frequency differences between two DNA pools for genetic association studies other than SNP typing. The method is based on specific primer extension reactions coupled with PPi detection. As the specificity of the primer-directed extension is not enough for quantitative SNP analysis, artificial mismatched bases are introduced into the 3′-terminal regions of the specific primers as a way of improving the switching characteristics of the primer extension reactions. The best position in the primer for such artificial mismatched bases is the third position from the primer 3′-terminus. Contamination with endogenous PPi, which produces a large background signal level in SNP analysis, was removed using PPase to degrade the PPi during the sample preparation process. It is possible to accurately and quantitatively analyze SNPs using a set of primers that correspond to the wild-type and mutant DNA segments. The termini of these primers are at the mutation positions. Various types of SNPs were successfully analyzed. It was possible to very accurately determine SNPs with frequencies as low 0.02. It is very reproducible and the allele frequency difference can be determined. It is accurate enough to detect meaningful genetic differences among pooled DNA samples. The method is sensitive enough to detect 14 amol ssM13 DNA. The proposed method seems very promising in terms of realizing a cost-effective, large-scale human genetic testing system.
159 citations
References
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TL;DR: Nick-translation PCR was performed with fluorogenic probes that generated fluorescence from its indicator dye only when the sequence between the indicator and quencher dyes was perfectly complementary to target.
Abstract: Nick-translation PCR was performed with fluorogenic probes. Two probes were used: one complementary to a sequence containing the F508 codon of the normal human cystic fibrosis (CF) gene (wt DNA) and one complementary to a sequence containing the delta F508 three base pair deletion (mut DNA). Each probe contained a unique and spectrally resolvable fluorescent indicator dye at the 5' end and a common quencher dye attached to the seventh nucleotide from the 5' end. The F508/delta F508 site was located between the indicator and quencher. The probes were added at the start of a PCR containing mut DNA, wt DNA or heterozygous DNA and were degraded during thermal cycling. Although both probes were degraded, each probe generated fluorescence from its indicator dye only when the sequence between the indicator and quencher dyes was perfectly complementary to target. The identify of the target DNA could be determined from the post-PCR fluorescence emission spectrum.
957 citations
TL;DR: A novel G→T polymorphism in a regulatory region of COLIA1 at a recognition site for the transcription factor Sp17 that is significantly related to bone mass and osteoporotic fracture is described.
Abstract: Osteoporosis is a common disease with a strong genetic component1–3, characterized by reduced bone mass and increased fracture risk4 Current evidence suggests that the inheritance of bone mass is under polygenic control5 but the genes responsible are poorly defined Type I collagen is the major protein of bone encoded by the COLIA1 and COLIA2 genes While these are strong candidates for the genetic regulation of bone mass, no abnormality of either gene has so far been defined in osteoporosis6 In this study, we describe a novel G→T polymorphism in a regulatory region of COLIA1 at a recognition site for the transcription factor Sp17 that is significantly related to bone mass and osteoporotic fracture G/T heterozygotes at the polymorphic Sp1 site (Ss) had significantly lower bone mineral density (BMD) than G/G homozygotes (SS) in two populations of British women and BMD was lower still in T/T homozygotes (ss) The unfavourable Ss and ss genotypes were over-represented in patients with severe osteoporosis and vertebral fractures (54%), as compared with controls (27%), equivalent to a relative risk of 297 (95% confidence interval 163–956) for vertebral fracture in individuals who carry the ‘s’ allele While the mechanisms that underlie this association remain to be defined, the COLIA1 Sp1 polymorphism appears to be an important marker for low bone mass and vertebral fracture, raising the possibility that genotyping at this site may be of value in identifying women who are at risk of osteoporosis
645 citations
TL;DR: Use of pooled DNA amplifications is reported for the accurate determination of marker-disease associations for both case-control and nuclear family-based data, including application of correction methods for stutter artifact and preferential amplification.
Abstract: Genomic screening to map disease loci by association requires automation, pooling of DNA samples, and 3,000-6,000 highly polymorphic, evenly spaced microsatellite markers. Case-control samples can be used in an initial screen, followed by family-based data to confirm marker associations. Association mapping is relevant to genetic studies of complex diseases in which linkage analysis may be less effective and to cases in which multigenerational data are difficult to obtain, including rare or late-onset conditions and infectious diseases. The method can also be used effectively to follow up and confirm regions identified in linkage studies or to investigate candidate disease loci. Study designs can incorporate disease heterogeneity and interaction effects by appropriate subdivision of samples before screening. Here we report use of pooled DNA amplifications-the accurate determination of marker-disease associations for both case-control and nuclear family-based data-including application of correction methods for stutter artifact and preferential amplification. These issues, combined with a discussion of both statistical power and experimental design to define the necessary requirements for detecting of disease loci while virtually eliminating false positives, suggest the feasibility and efficiency of association mapping using pooled DNA screening.
220 citations