Science & Research

‘Spliceman’ app catches disruptive mutations

By
Contributing Writer

Spliceman is not a superhero, but it does have the power to accomplish superhuman feats. Developed by a team of University researchers, the web-based application to identify mutations in gene processing was described in the journal Bioinformatics last week.

In order for a gene to be expressed correctly, segments of RNA that do not code for protein must be removed from the RNA transcript, which provides the set of directions from DNA used to build proteins. This process of cutting out superfluous sequences, called splicing, must be carried out at precise locations as dictated by DNA. 

“Many mutations and variations disrupt this process and, by disrupting the process, they disrupt the gene,” wrote William Fairbrother, assistant professor of biology and lead author of the study, in an email to The Herald. 

Fairbrother and his team developed Spliceman as part of a study published in the Proceedings of the National Academy of Sciences last year. The research showed that about one-third of the disease-causing mutations in the Human Genome Mutation Database are caused by errors in RNA splicing.

“Spliceman calculates how likely these mutations are to disrupt splicing through a statistical model,” said graduate student Kian Huat Lim GS, who played a large role in designing the Spliceman software. 

In the study, mutations that disrupted splicing were identified based on their locations in relation to important known splice sites in the genome sequence. Splicing signals are position-dependent, so mutations that occur close to splice sites are more likely to affect the gene’s function. 

The one-third of mutations identified in the study may underestimate the actual number of mutations caused by splicing errors, Lim said. These mutations are easier to remedy than other errors, he said. 

“A processing defect, RNA processing in this case, is easier to be detected and fixed with safer and cheaper options than, for instance, a protein coding defect,” Lim said. 

Spliceman – which was nearly named Splicegirl, “after the popular and completely dreadful all-girls 90’s pop band, Spice Girls,” Fairbrother wrote ­- has superhuman computing abilities. It can analyze the vast number of possible variances, a task that would be impossible to accomplish manually through genetic assays.  

“There are many tools to evaluate the effect of mutations on protein,” Fairbrother wrote. “This new tool to look at processing effects (complements) the existing software nicely.” The software is already being used to understand the unexplained genetic conditions of clinical patients in this year’s CLARITY challenge, hosted by Children’s Hospital Boston. 

In this challenge, teams attempt to find the genetic basis of conditions in three pediatric patients by studying their entire genome sequences. Spliceman will be used to identify potentially interesting genomic variance that may have an effect on splicing. Then, in addition to the location of the mutation, researchers will consider factors such as mode of inheritance and gene function to determine the most likely cause of the disorder. 

Developing computational tools, such as Spliceman, for genetic analyses will be increasingly important for the field in upcoming years, said Shamil Sunyaev, head of the Harvard-based multidisciplinary genetics group participating in the challenge. “Because sequencing itself is becoming less and less expensive, the interpretation is where the focus of the field is going to be for years to come,” Sunyaev said. 

Advances in gene sequencing technology will eventually make it possible for each person to access their entire genome sequence, Sunyaev said. Computational software programs like Spliceman will be key in assessing human variance and determining which differences lead to significant changes in the physical manifestation of the genes. 

Fairbrother and his team are continuing to elucidate the mechanisms of splicing and are developing new splicing therapies with a $1.5 million grant from the National Institutes of Health.

For Fairbrother, the greatest payoff of this project is seeing how Spliceman can be used to help children with genetic disorders understand more about their disease. 

“The most sobering part of the project was queries from parents with sick children who are trying to find out more about their disease,” Fairbrother wrote. “It really underscores how lucky we are and how important it is to put your best work out there.”