“I think this is the wave of the future,” says Thomas Bird, director of the Neurogenetics Clinic at the University of Washington, in Seattle, who was not involved in the research. “Genetic testing is going to become more and more important in medicine as the technology becomes more extensive and less expensive.”
Understanding the genetic mutation that causes Lupski’s disorder can help scientists search for treatments. For example, animals genetically engineered to mimic the gene duplication responsible for about 70 percent of the human cases of Charcot-Marie-Tooth can be helped by an estrogen-blocking drug, which is now in clinical trials. (Other genetic variations, including some yet to be discovered, are responsible for the remaining 30 percent.) The same week that Lupski identified his disease mutation, he received a research paper to review that described the creation of a mouse lacking the same gene, SH3TG2. “Suddenly we’re starting to get insight into the disease process for the first time in 25 years,” says Lupski, who hopes to repeat his success by sequencing patients with other unexplained nerve disorders.
In the Science study, Leroy Hood and collaborators at the Institute for Systems Biology, in Seattle, sequenced the complete genomes of a nuclear family of four, the first published example of familial whole-genome sequencing. Both children in the family have Miller syndrome, a rare craniofacial disorder. By comparing the sequence of parents and offspring, researchers could calculate the rate of spontaneous mutations arising in the human genome from one generation to the next. The rate equates to about 30 mutations per child, lower than previous estimates.
One of the major problems with analyzing whole-genome data is isolating important genetic signals from noise–both sequencing errors and thousands of harmless genetic variations that have little or no impact on a person’s health. Comparing intergenerational genomes allowed scientists to filter out some of this noise. They honed in on the genetic changes that appeared from one generation to the next and then resequenced those regions to identify true changes. Hood estimates that errors are about 1,000 times more prevalent than true mutations. “In the future, when all of us have our genomes done, we’ll almost certainly have them done in families, because it increases the accuracy of the data,” says Hood.
By comparing the genomes of the unaffected parents to their affected children, researchers identified four candidate genes for Miller syndrome. One candidate overlapped a gene linked to the disease in a study published in January. That study sequenced just the gene-coding regions of these children and two others with Miller syndrome. (Lupski’s study, in contrast, focused on genes known to be related to Charcot-Marie-Tooth or other nerve disorders. But that approach would be ineffective in identifying unexpected genes or genes for diseases that are not well-studied.)