Over the past few years, several gene variants have been found to influence disease risk, but there are other signals that have also been found to be associated with disease that fall nowhere near any genes, says Genomes Unzipped's Joe Pickrell. "How," he asks, "can we hope to explore how polymorphisms affect disease risk if they don't seem to fall in any sort of genome annotation that we understand?" A paper recently published in Nature attempts to answer this question, presenting evidence that variants that influence genes are not random, but tend to fall in particular regions like enhancer elements, Pickrell says. Because DNA in the cell is wrapped around histones and histones can be chemically modified, he adds, "it is now clear that particular patterns of modifications are predictive of the function of the DNA in the region — some modifications indicate transcribed genes, others regions of enhancer activity, others repressed regions, etc." The authors of the paper generated genome-wide maps of several histone modifications in nine different cell types and used the data to predict the function of each 200 base pair segment of the genome in each cell, Pickrell says. When they took sets of SNPs associated with disease and explored whether the SNPs were enriched in regions with any particular functional prediction, what they found was that the SNPs that influenced certain phenotypes were enriched in enhancers in cells associated with a relevant disease. For example, SNPs that influence lipid levels were enriched in enhancers in a liver cancer cell line. "As these types of functional maps are generated in more cell types, I imagine there will be more stories like this," Pickrell says. "The problem with interpreting disease association studies, it seems likely, is largely due to our lack of understanding of genome function."
Apr 14, 2011