Publications by authors named "Mark Pohl"

Motivation: The optimization of the primer design is critical for the development of high-throughput SNP genotyping methods. Recently developed statistical models of the SNP-IT primer extension genotyping reaction allow further improvement of primer quality for the assay.

Results: Here we describe how the statistical models can be used to improve primer design for the assay.

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Background: SNP genotyping typically incorporates a review step to ensure that the genotype calls for a particular SNP are correct. For high-throughput genotyping, such as that provided by the GenomeLab SNPstream instrument from Beckman Coulter, Inc., the manual review used for low-volume genotyping becomes a major bottleneck.

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Using an empirical panel of more than 20 000 single base primer extension (SNP-IT) assays we have developed a set of statistical scores for evaluating and rank ordering various parameters of the SNP-IT reaction to facilitate high-throughput assay primer design with improved likelihood of success. Each score predicts either signal magnitude from primer extension or signal noise caused by mispriming of primers and structure of the PCR product. All scores have been shown to correlate with the success/failure rate of the SNP-IT reaction, based on analysis of assay results.

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Single nucleotide polymorphism (SNP) genotyping is playing an increasing role in genome mapping, pharmacogenetic studies, and drug discovery. To date, genome-wide scans and studies involving thousands of SNPs and samples have been hampered by the lack of a system that can perform genotyping with cost-effective throughput, accuracy, and reliability. To address this need, Orrhid has developed an automated, ultra-high throughput system, SNPstream UHT, which uses multiplexed PCR in conjunction with our next generation SNP-IT tag array single base extension genotyping technology The system employs oligonucleotide microarrays manufactured in a 384-well format on a novel glass-bottomed plate.

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