Researchers from the University of North Carolina have developed a sequencing technique to create maps of regulatory regions in the genome, and used it to identify a gene variant involved in diabetes. The authors of the study, which was published last week in Nature Genetics, say the technique can be applied to other types of disease-relevant tissue samples and will even work on solid tumors.
By crosslinking open chromatin regions with formaldehyde, and then performing a phenol-chloroform extraction, the researchers were able to identify and separate out those regions of the chromatin where regulatory proteins can bind. They then used the Illumina Genome Analyzer to sequence those regions, using 36-base pair single-end reads, generating 60 million mapped reads of the sample they analyzed.
While the method is relatively new, other labs have begun to use it as well. Karine Le Roch, assistant professor of cell biology and neuroscience at the University of California, Riverside, uses it to study malaria and agreed that the method yields clean, reliable data. "We've used microarrays before, and this sequencing technology is much cleaner," she said. "You get resolution at the single-nucleotide level, and it eliminates any type of contamination.
Aside from the breast cancer study, Lieb's group has received funding to continue to identify functional regulatory SNPs involved in diabetes and obesity. In the future, his team is interested in mapping open chromatin in cell lines from the HapMap project. Since these cell lines are derived from white blood cells, they may be useful in identifying which variants associated with autoimmune diseases like lupus or rheumatoid arthritis fall within regulatory regions. He also wants to study chromatin variation among healthy individuals.
By crosslinking open chromatin regions with formaldehyde, and then performing a phenol-chloroform extraction, the researchers were able to identify and separate out those regions of the chromatin where regulatory proteins can bind. They then used the Illumina Genome Analyzer to sequence those regions, using 36-base pair single-end reads, generating 60 million mapped reads of the sample they analyzed.
While the method is relatively new, other labs have begun to use it as well. Karine Le Roch, assistant professor of cell biology and neuroscience at the University of California, Riverside, uses it to study malaria and agreed that the method yields clean, reliable data. "We've used microarrays before, and this sequencing technology is much cleaner," she said. "You get resolution at the single-nucleotide level, and it eliminates any type of contamination.
Aside from the breast cancer study, Lieb's group has received funding to continue to identify functional regulatory SNPs involved in diabetes and obesity. In the future, his team is interested in mapping open chromatin in cell lines from the HapMap project. Since these cell lines are derived from white blood cells, they may be useful in identifying which variants associated with autoimmune diseases like lupus or rheumatoid arthritis fall within regulatory regions. He also wants to study chromatin variation among healthy individuals.
