Techniques in this rapidly expanding field make use of existing Web databanks such as GenBank, which contains more than 100 billion DNA and protein sequence elements collected from all walks of life. "These databases already contain the outcomes of nature's experiment, which we can harness by using bioinformatics," says Kumar.
DNA medicine typically uses a suite of computer tools to assess whether a newly discovered protein change is potentially disease-causing or benign. Kumar's study tested the reliability of two of the most widely-used tests, known as SIFT and PolyPhen, by examining over 20,000 mutations from both diagnosed patients and healthy individuals. The results demonstrate that these tests make false predictions of risk up to 40 percent of the time, a rate of reliability that renders them impractical for clinical use.
The objective of the study was to identify where SIFT and PolyPhen tend to fail and where their predictions appear to be more reliable. To accomplish this, Kumar's group examined the proteins in 44 species, from frogs to fish, chimps and gorillas. His group discovered that benign mutations tend to occur in regions of the genome that allow variation over evolutionary time across species. In these regions, it is easier to make accurate predictions of benign mutations.
In contrast, DNA information essential for life is persistent from species to species. Many DNA positions
permit no change over evolutionary time in order to preserve proper functionmutations here would likely be
|Contact: Joe Caspermeyer|
Arizona State University