Abstract
The International HapMap Project and the arrival of technologies that type more than 100,000 SNPs in a single experiment have made genome-wide single nucleotide polymorphism (GW-SNP) assay a realistic endeavor. This has sparked considerable debate regarding the promise of GW-SNP typing to identify genetic association in disease. As has already been shown, this approach has the potential to localize common genetic variation underlying disease risk. The data provided from this technology also lends itself to several other lines of investigation; autozygosity mapping in consanguineous families and outbred populations, direct detection of structural variation, admixture analysis, and other population genetic approaches. In this review we will discuss the potential uses and practical application of GW-SNP typing including those above and beyond simple association testing.
Highlights
The first steps toward effective whole genome association experiments were taken with the inception and completion of stages I and II of the International HapMap Project
This project aimed to produce a minimal set of informative single nucleotide polymorphisms (SNPs) to tag variation throughout the genome [3]
There are two prominent companies offering high-throughput genome-wide (GW) genotyping that can be applied within an end user’s laboratory: Affymetrix and Illumina. The combination of these technological and informatic advances make genome-wide single nucleotide polymorphism (GW-SNP) genotyping a realistic possibility for well-funded laboratories; the likely decrease in cost that will occur over the five years suggests that this technology will become a standard technique in molecular genetic and clinical diagnostic laboratories
Summary
The first steps toward effective whole genome association experiments were taken with the inception and completion of stages I and II of the International HapMap Project (http:// www.hapmap.org; [1,2]). Much of the discussion surrounding the application of GW-SNP assays has centered on the utility of this method in identifying common genetic variability that underlies disease [5,6] This discussion has focused on the relative power of these types of study and the potential problems and pitfalls associated with this approach, resulting in numerous review and opinion pieces. The considerable cost of these experiments coupled with the potential promise of this approach has led funding agencies to encourage sharing of resources to perform these assays, including both sharing of DNA samples and public release of genotype data This policy highlights a strength of GW-SNP experiments, i.e., genotype data are essentially digital and additive; experiments on the same platform can be compared or combined to increase power and sensitivity.
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