Highly parallel SNP genotyping.

genetic factors underlying common disease are largely unknown. Discovery of disease-causing genes will transform our knowledge of the genetic contribution to human disease, lead to new genetic screens, and underpin research into new cures and improved lifestyles. The se-quencing of the human genome has catalyzed efforts to search for disease genes by the strategy of associating sequence variants with measurable phenotypes. In particular , the Human Genome Project and follow-on efforts to characterize genetic variation have resulted in the discovery of millions of single-nucleotide polymorphisms (SNPs) (Patil et al. 2001; Sachidanandam et al. 2001; Reich et al. 2003). This represents a significant fraction of common genetic variation in the human genome and creates an unprecedented opportunity to associate genes with phenotypes via large-scale SNP genotyping studies. To make use of this information, efficient and accurate SNP genotyping technologies are needed. However, most methods were designed to analyze only one or a few SNPs per assay, and are costly to scale up (Kwok 2001; Syvanen 2001). To help enable genome-wide association studies and other large-scale genetic analysis projects, we have developed an integrated SNP genotyping system that combines a highly multiplexed assay with an accurate readout technology based on random arrays of DNA-coated beads (Michael et al. 1998; Oliphant et al. 2002; Gunderson et al. 2004). Our aim was to reduce costs and increase productivity by ~2 orders of magnitude. We chose a multiplexed approach because it is more easily scalable and is intrinsically cost-efficient (Wang et al. 1998). Although existing multiplexed approaches lacked the combination of accuracy, robustness, scalability, and cost-effectiveness needed for truly large-scale endeavors, we hypothesized that some of these limitations could be overcome by designing an assay specifically for multiplexing. To increase throughput and decrease costs by ~2 orders of magnitude, it was necessary to eliminate bottlenecks throughout the genotyping process. It was also desirable to minimize sources of variability and human error in order to ensure data quality and reproducibility. We therefore took a systems-level view to technology design, development , and integration. Although the focus of this paper is on a novel, highly multiplexed genotyping assay, the GoldenGate ™ assay, four other key technologies that were developed in parallel, as part of the complete BeadLab system (Oliphant et al. 2002), are briefly described below. BEADARRAY™ PLATFORM We developed an array technology based on random assembly of beads in micro-wells located at the end of an …