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Linkage Disequilibrium SNP Mapping Studies
Targeted Association Studies
The Problem: Narrowing Down a Group of Candidate Genes to the Gene of InterestMany genotyping studies are carried out when a strong prior hypothesis already exists as a list of candidate genes, either from family linkage studies or from gene expression experiments. Family studies using linkage analysis can highlight areas of the genome, or linkage peaks, where causative genes are likely to reside. Gene expression studies and biochemical insight can yield candidate pathways containing large sets of functional candidate genes. Genotyping as an approach to narrow down the set of candidate genes is arguably the most powerful approach to pinpointing the causative allele. However, to be effective as an approach, genotyping studies must be designed with sufficient statistical power. Many failed studies in the literature used too few markers (because of technological and practical limitations) and thus sacrificed the statistical power necessary to uncover significant but subtle genetic associations.
The Solution: Dense SNP Genotyping Focused on the Candidate GenesTo definitively test lists of candidate genes, dense single nucleotide polymorphism (SNP) genotyping can be used to narrow down the candidate gene set to reveal the precise genes involved by using association analysis such as transmission disequilibrium test (TDT) or case control. It is important to analyze a sufficient density of SNPs, to cover the entire linkage peak (or multiple linkage peaks), and to construe the gene lists as broadly as possible in order to ensure that all potential alleles are included in the set tested. If insufficient SNPs are analyzed, then the probability of finding the genes of interest is significantly reduced. For instance, the statistical power is reduced by nearly a factor of two in going from 20kb to 40kb SNP spacing.
The Density of SNP Markers greatly affects the statistical power of genetic studies.
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| Figure 1: The sample size required to reach a given power is approximately 1/r^2 the sample size needed when directly interrogating the predisposing allele. Here, r^2 is the standard measure of linkage disequilibrium between two genetic markers. This graph shows the decay of linkage disequilibrium as a function of distance (data from the HapMap). On average, at 20kb spacing, the sample size is threefold larger than that needed for direct detection. With half as many markers (in other words, 40kb spacing), the increase in sample size is approximately fivefold. As such, the density of the marker map greatly affects the power of a genetic study. As an example, for linkage peaks or candidate regions covering 60Mb, one would nearly double the power by going from 1,500 to 3,000 SNPs. |
Comprehensive coverage of typical linkage peaks (approximately 30Mb to 60Mb) at a sufficient SNP density should include rare SNPs and regions of limited linkage disequilibrium so as not to sacrifice power. This requires analysis of at least one SNP per 10kb, or 3,000 to 5,000 SNPs for average linkage regions. Similarly, comprehensive coverage of 300 to 500 candidate genes typically requires 3,000 to 5,000 SNPs. Clearly, flexibility is needed in study design, according to the size of linkage peak or list of candidate genes; therefore, ParAllele offers custom, focused genotyping products to analyze thousands of SNPs in a single reaction.
Accurate Measurements Allow Predictive ResultsAccurate identification of a gene of interest requires well-characterized diseased and control patient populations as well as a highly accurate SNP genotyping platform. Compromising on either significantly reduces the predictive power of the results. Another key factor that affects the power of genetic fine-mapping studies is SNP choice. Targeted SNP studies clearly benefit when all possible SNPs can be interrogated. Thus, it is essential that a high conversion rate from in-silico selected SNPs to high accuracy assays is possible. ParAllele has the highest first-pass conversion rate from database SNPs to validated assays, significantly increasing the chances of success in a targeted association study.
ProductsParAllele provides customizable SNP assay panels to genotype thousands of SNPs in a single reaction. These panels are available either as a MegAllele Genotyping Service from ParAllele or as MegAllele Genotyping Products.
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