( The International HapMap Consortium bo...)International HapMap consortium expands mapping effort

The International HapMap Consortium, boosted by an additional $3.3 million in public-private support, today announced plans to create an even more powerful map of human genetic variation than originally envisioned. The map will accelerate the discovery of genes related to common diseases, such as asthma, cancer, diabetes and heart disease.

When the project was launched in October 2002, the consortium set September 2005 as the target for completing its map of common patterns of human genetic variation, also known as haplotypes. By the end of February 2005, however, the group already will have reached completion of its first draft of the human haplotype map, or HapMap, which will consist of 1 million markers of genetic variation, called single nucleotide polymorphisms (SNPs).

The consortium's new goal is to build an improved version of the HapMap that is about five times denser than the original plan. This "Phase II" HapMap will take advantage of the rapid, high-throughput genotyping capacity of Perlegen Sciences, Inc., of Mountain View, Calif., to test another 4.6 million SNPs from publicly available databases, and add that information to the map. As a result of a grant competition last summer, Perlegen received a $6.1 million award from the National Human Genome Research Institute (NHGRI), part of the National Institutes of Health (NIH), to add data on 2.25 million additional SNPs to HapMap. The new development, enabled by a partnership among multiple funding sources, will expand that effort and test virtually the entire known catalog of human variation on the HapMap samples. This will increase the density of SNP "signposts" across the genome from the current average of one every 3,000 bases to about one every 600 bases.

"This will help us create a far more powerful HapMap than we ever imagined. We sincerely thank all those who are giving their time, technology and money to help turn this dream into reality. The payoff will be a better underst
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Source:NIH/National Human Genome Research Institute

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