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Complex human diseases are known to have a significant genetic component. Despite some important successes (Altshuler et al. 2000; Hugot et al. 2001), the elucidation of the underlying genetic determinants have proven resistant to standard methods. Linkage analysis using affected sib pairs has limited power to uncover such signals, as each individual functional variant contributes only modestly to disease risk (Risch 2000). Large-scale association studies that would allow genome-wide mapping in large collections of cases with matched controls have therefore been proposed (e.g., Kruglyak 1999; Risch 2000). Some of the barriers to adopting such strategies, including the need to establish large-case control populations (Geschwind et al. 2001; Shmulewitz et al. 2001; Cupples et al. 2003) and develop comprehensive SNP resources (dbSNP), have been overcome. In addition, the International HapMap project (The International HapMap Consortium 2003) is completing a first draft of a whole genome haplotype map in the Centre d'Etude du Polymorphisme Humain (CEU) population by the end of 2004. The Hap-Map effort will yield a broad view of the genetic architecture of human populations and allow for the efficient selection of the most informative tagging SNPs for subsequent association studies. The remaining requirement to fully enable large-scale genetic association studies is the development of truly cost-effective and scalable SNP genotyping technologies. These methods must allow hundreds of thousands of markers to be efficiently and accurately scored in thousands of patients. The first generation of SNP genotyping technologies were based on single amplification reactions for each locus and were not appropriate for these largescale, whole-genome studies. Recent advances have assayed thousands of random SNPs using ultra high-density wafer hybridizations (Matsuzaki et al. 2004) but will not allow the advantages of the tagging SNP approach to be fully realized because these technologies will not be able to convert all the informative tagging SNPs and/or putative functional SNPs into working genotyping assays. Multiplexed genotyping technologies that allow the multiplexing of hundreds of targeted SNPs have recently been developed based on various versions of the Oligo Ligation Assay (OLA) (Grossman et al. 1994; Samiotaki et al. 1994; Oliphant et al. 2002). These technologies would still demand a fairly large infrastructure in order to process the thousands of reactions necessary per patient. Here, we describe an advanced Molecular Inversion Probe (MIP) genotyping technology (Hardenbol et al. 2003) that combines the strengths of all of the above methods. MIP exploits the advantages of the OLA methodologies but can be more highly multiplexed due to a unique unimolecular method of action and an enzymology that combines the specificity of both ligase and polymerase enzymes. This assay enables the use of >12,000 oligo probes to simultaneously interrogate human genomic DNA and, following a single PCR, detect the results via a single universal tag DNA chip array. The application of MIP to generate a haplotype map of Chromosome 12 in CEU families (The International HapMap Consortium 2003) as part of the Human HapMap project has yielded 3,509,052 genotypes from 38,429 assays. In this study we analyze the important features of the assay performance that will enable MIP to be effectively used for many future largescale studies.

A targeted discovery effort is required to identify low frequency single nucleotide polymorphisms (SNPs) in human coding and regulatory regions. We here describe combining mismatch repair detection (MRD) with dideoxy terminator sequencing to detect SNPs in pooled DNA samples. MRD enriches for variant alleles in the pooled sample, and sequencing determines the nature of the variants. By using a genomic DNA pool as a template, ∼100 fragments were amplified and subsequently combined and subjected en masse to the MRD procedure. The variant-enriched pool from this one MRD reaction is enriched for the population variants of all the tested fragments. Each fragment was amplified from the variant-enriched pool and sequenced, allowing the discovery of alleles with frequencies as low as 1% in the initial population. Our results support that MRD-based SNP discovery can be used for large-scale discovery of SNPs at low frequencies in a population.