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Study Results Point to Faster Mapping of Disease-Related SNPs

NEW YORK, May 9 – The size of blocks of SNPs in the human genome are significantly larger than previously believed, a finding that could lead researchers to more quickly develop gene maps for common diseases, according to a study to be published in the May 10 issue of Nature .

The authors, who include Eric Lander, director of the Whitehead Institute Center for Genome Research, and researchers from the Institute of Biological Anthropology at the University of Oxford, describe the results from a large-scale experiment analyzing the size of linkage disequilibrium (LD) blocks used to map genes that cause disease.

The authors looked at 19 randomly selected regions of SNPs along the human genome. The results show that LD in a group of Americans of north-European descent typically extends 60 kilobases from common alleles. This implies “that LD mapping is likely to be practical in this population,” write the authors.

By contrast, blocks of LD in a Nigerian population were found to extend less than five kilobases.

The size of LD blocks had previously been subject to debate, with suggestions varying from a few kilobases to greater than 100.

"Depending on how large the blocks are determines the way you map the genes," David Reich, lead author and Whitehead Institute scientist, told GenomeWeb. "This is a validation. It's a reasonable thing to map out all of the haplotypes in a human to optimize genetic population studies."

Reich noted that in northern European populations, the blocks might be eight times larger than researchers originally thought and, therefore, eight times easier to map.

Similarly, the small blocks found in other populations, such as the Nigerian population, which was studied by the authors, could allow scientists to find the single letter cause of a particular disease.

"Our results have implications for disease gene mapping, suggesting a possible two-tiered strategy for using LD," the authors state.

Reich speculated that results of the study may impact the way gene mapping tools are designed.

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