Merging data sets to fight human disease
The sequencing of the human genome has spawned a wealth of knowledge, much of it now available online. According to Vamsi K. Mootha, M.D., a postdoctoral fellow at the Broad Institute in Cambridge, Mass., this is making possible new approaches to medical research. “The real challenge,” Mootha said in a talk sponsored by the Department of Genetics in March, “will be to integrate these data sets with each other as well as with what we know from the previous literature.”
As an example, Mootha described his participation on an international team that sought the gene mutation responsible for Leigh syndrome, a fatal metabolic disorder that is prevalent in a region of French Quebec. The team had first determined that the culprit gene was one of 30 on chromosome 2. “The critical feature of the disease suggested that there might be a mitochondrial pathology,” Mootha said. Using this clue, the team analyzed RNA data sets and a map of mitochondrial peptides to home in on their target. “Using relatively freely available data we were able to identify the candidate gene,” Mootha said.