Research Project
6595838
DESCRIPTION: (provided by applicant) The majority of genes involved in common disease remain unknown. Discovery of these genes will transform our knowledge of the genetic contribution to human disease, and lead to the provision of new genetic screens, and underpin research into new cures or improved lifestyles. A leading strategy for their discovery is to test specific sequence variants for association with a measurable phenotype, and from this to identify the causative variant and hence the gene involved. An important first step is to create a haplotype map of the genome and identify a minimal set of SNPs that can be used to detect common haplotype patterns in multiple populations. This will enable comprehensive genome-wide genetic association studies, potentially revolutionizing the search for the genetic basis of common diseases. The overall aim of this project is to select common variants in the form of single nucleotide polymorphisms (SNP) from the human genome sequence, and to carry out large-scale genotyping with the goal of creating such a haplotype map for a significant fraction of the human genome. Genotyping will be carried out using a novel, parallel large-scale genotyping system that combines a highly multiplexed assay format, a miniaturized bead-based array platform, and positively-tracked, LIMS-based, modular automation. The system has a base capacity of ~1,000,000 genotypes per day, and is easily scaled up to much higher capacities. It will be used to develop and screen assays for 400,000 SNPs. The SNPs will be genotyped in a set of samples representing African, Asian, and Caucasian populations, and will provide a data set of-~ 74 million genotypes for analysis. The data will be used to define haplotype patterns that are common in each population, and to identify a specific set of SNPs ("tag SNPs") which will be maximally informative for future genome wide association studies to investigate the role of common variants in common disease. This study will form part of an international collaborative programme (the "HapMap" project) which will make all the information relating to this work freely available in the public domain.
