How to Predict If a Genetic Mutation Could Lead to Disease

Spliceman, a new online tool developed by a team of researchers at Brown University, can help spot problem areas when splicing DNA.

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There are many ways to skin a cat. There are also many ways to cause terrible mutations. These range from point mutations and InDels (insertions and deletions) in DNA to splicing changes in mRNA, which account for about 10 percent of the mutations in the Human Gene Mutation Database. Now, a team from Brown University has released a free, online program that will allow researchers to predict whether genetic mutations are likely to disrupt mRNA splicing and lead to disease.

Called Spliceman, the program has successfully predicted the known effects of many mutations and shown that "perhaps as many as a third of the disease-causing mutations in the Human Genome Mutation Database do so by causing errant gene splicing." The press release describes the theory of splicing mutations and foundation for how Spliceman works:

Splicing of RNA, based on instructions in DNA, is like a film editing process. A gene includes raw footage and instructions on how it should be edited to produce a protein. If the editing instructions are faulty, the scenes extracted from the raw footage may be spliced together in the wrong order or the wrong scenes might be used.

Each of a person's 20,000 genes has about 20 splice sites. Sequences that regulate splicing often occur close to splice sites, and every possible "word" of DNA letters (e.g. AAA) has a signature distribution around the splice sites. But a mutation creates a new word. For example, an A-to-T mutation could change "AAA" to "ATA." In a normal genome, if AAA encodes proper splicing, its average distance to the nearest splice site will be short and if ATA doesn't encode proper splicing its distance would be longer. A mutation that changes a word close to splicing sites into one that is typically found far from splicing sites would be of particular concern because it could have a likely adverse effect on splicing.

There is a silver lining, however. Because mRNA splicing mutations are a processing defect, as opposed to hard-coded point mutations in DNA, they can "potentially be detected and fixed more easily and safely." Researchers have already developed proteins that can correct problematic splicing operations. Spliceman may help them identify even more targets.

Additionally, the program features data from 11 species, including humans, chimpanzees, rhesus monkeys, mice, rats, dogs, cats, chickens, guinea pigs, frogs, and zebra fish. So what are you waiting for? Check out Spliceman to start predicting splicing mutations today.


This post also appears on medGadget, an Atlantic partner site.

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