In addition, the larger scale of the new dataset reinforces the result found by previous smaller studies that non-African diversity is largely a subset of African diversity. The researchers also found that the third-generation HapMap increases the power to identify signals of natural selectionvariants that increased rapidly in frequency very recently in some populations because they were somehow beneficial to human health.
The researchers assessed the latest generation HapMap for its ability to predict SNPs in other populations. They found that using one population to predict another population's variants works for common variants and for some less-common variants in related populations. However, it does not work well for rare variants in related populations, meaning that rare variants are likely to make much more population-specific contributions to disease. This finding underscores the value of efforts already underway that use efficient 'next-generation' DNA sequencing technologies to sequence large numbers of whole genomes within various populations to find rare variants that contribute to disease.
Many of the HapMap researchers are part of the 1000 Genomes Project, an international public-private consortium launched in 2008 that is building an even more detailed map of human genetic variation. Project researchers are currently using next-generation DNA sequencing technologies to build a public database containing information from the complete genomes of 2,500 people from 27 populations around the world, many of which were studied in the HapMap project. Disease researchers will be able to use the catalogue, which is being developed over the next two years, in their studies of the contribution of common and rarer genetic variation to illness.
The Consortium that produced this latest HapMap included researchers Baylor College of Medicine in Houston;
|Contact: Geoff Spencer|
NIH/National Human Genome Research Institute