Genome Scan Predicts Splicing Mutations

June 12, 2011

By Bio-IT World Staff

June 13, 2011 | According to a paper published in the Proceedings of the National Academy of Sciences this week, nearly one third of the mutations listed in the Human Gene Mutation Database (HGMD) may be caused by splicing errors in mRNA (see, The State of Mutation Curation). “Splicing mutations are already known to be a large fraction, but we’re saying they are even more,” said William Fairbrother, assistant professor of biology at Brown University and senior author of the study.  

The increased splicing rate was predicted by computer modeling done by Kian Huat Lim, a computer science graduate student on Fairbrother’s team in Brown’s Department of Molecular Biology, Cell Biology, and Biochemistry. 

Lim wrote a program to analyze HGMD data looking at short sequences that occur many times in the genome. The locations of these multiple occurrences told the scientists something about the function of the sequence. Sequences that help splicing often occur close to splice sites. 

The team eventually started to notice that mutations that affected splicing created new sequence motifs that changed their distribution around splice sites in distinctive ways compared to mutations that did not affect splicing. They quantified and calculated this mathematical distance from the norm.    

“The bigger the distance, the more likely that it affects splicing,” Lim said. In the past, Fairbrother told Bio-IT World, “The importance of location in splicing element function was not fully appreciated.”     

The program gave the team cues about which mutations from the HGMD to test in the lab. In most cases, the computer program was correct about the effect the mutation would have on splicing. The team tested mutations associated with diseases including albinism and colorectal cancer and found that they do indeed cause splicing errors.

Lim said the program gives genetics researchers a way to triage the many mutations that pique their curiosity, to see which ones are most likely to have a clinical effect. 

“Many times it is just too costly and too expensive to go into the lab and test every sequence you have,” Lim said. “It is much more helpful to have a computational tool that can filter out most of your sequences to leave you with some that the tool predicts will be the interesting ones.”    

Splicing mutations are often very disruptive to gene function, causing entire exons to be lost, but a patient carrying a mutation that results in a faulty splicing, Fairbrother said, may eventually have a brighter outlook than a patient who has mutations in the exons themselves. 

“A processing defect may be able to be detected and fixed much more easily and safely than a protein coding defect,” Fairbrother said. Researchers have already used engineered proteins called antisense oligoes to interfere with errant splicing operations, and an antisense oligo therapy that successfully fixed a splicing problem implicated in one disease could likely be easily adapted for fixing a splicing problem implicated in another disease, he continued.  

Fairbrother’s group is working with a five-year, $1.5-million National Institutes of Health grant to further investigate splicing therapies. The team is considering making the program available via the Web later this year.