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FEATURE: Linkage Disequilibrium Findings Support Commercial Efforts

NEW YORK, May 24 – Eric Lander and others showed in a May 10 Nature paper that the size of blocks of SNPs in the human genome are significantly larger than previously believed.  

“If you read the literature before, you may have thought [using linkage disequilibrium to map disease-causing genes] wasn’t worth doing, it was too hard,” Lander, director of the Whitehead Institute Center for Genome Research, told GenomeWeb. “These results have a huge impact on the field of using genetic markers such as SNPs to find disease genes. The tasks of finding disease genes should be feasible.”

The results of the large-scale experiment have bolstered the linkage disequilibrium (LD) research and the approach several companies have already adopted.

“The bigger the LD, the easier it is to find the neighborhood but the harder it is to find the gene,” explained Charles Cantor, chief scientific officer at Sequenom. “This [paper] indicates more forcefully than before that there is no perfect population to study. We will pay attention to these results to see which population to choose first. By and large we are searching a Northern European population, so we have made the right choice.”

In the Lander paper, the authors looked at 19 randomly selected regions of SNPs along the human genome and found that LD in a group of Americans of north-European descent typically extends 60 kilobases from common alleles versus less than five kilobases for a Nigerian population. 

That there is a difference in LD between populations did not come as a surprise, according to scientists, but this paper quantified some of those differences, dispelling a “theoretical wet blanket” according to Clay Stephens, executive director of population genomics at Genaissance.

The study “adds a bit of data,” said Stephens. “Data is where the answers are going to come from.”

Yet beyond population, there is also the question of where to focus within the LD blocks.

“This paper will give courage to people that you don’t have to look at every SNP on earth, you can be selective,” said Hugh Rienhoff, CEO of DNA Sciences. 

But, of course, there is still the question of which ones to select.

“There’s no doubt LD mapping will be done,” said Rienhoff. “The fundamental issue is will it be done with common or uncommon haplotypes. Everyone now has access to the genome and can start building maps. There may be two maps being built out there, rare and uncommon. Within 12 months we’ll start seeing results.”

Rienhoff has placed his company’s bets on uncommon haplotypes in the quest to find disease genes. “We are at that stage where 100 kilobase pairs in an individual is not too much to sequence. So the question is can you find the region of a disease allele using common haplotypes? I believe it is rare haplotypes.”

Whatever approach yields the best results, if in fact any one approach is better than any other, one thing does seem clear: translating LD research into finding disease genes won’t be easy.

“LD is highly variable region to region,” points out DNAPrint Genomics Tony Frudakis. “I’m not sure there is a simple solution.”

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