Computer Model Identifies RNA Splicing Enhancers

Researchers have found a way to predict which mutations in a gene's exons, those sections of the RNA which code for proteins, are likely to cause the exons to be skipped by the splicing machinery, which typically results in inactivation of the gene's product and can lead to disease. This discovery was reported July 11, 2002, in the online journal Science Express.

Messenger RNA (mRNA) molecules contain strings of genetic material called exons, which code for proteins, and introns, which do not. Introns are removed from mRNA by a splicing mechanism that joins exons together. RNA splicing determines which segments of the gene end up being expressed and which do not.

The purpose of the study carried out at the Massachusetts Institute of Technology (MIT, Cambridge, USA; www.mit.edu) was to identify exonic splicing enhancers (ESEs). These are short RNA sequences that, when present in the exons of a human gene, enhance the splicing of the exons and thereby increase the proportion of mRNAs that contain them.

A computational method was developed, called RESCUE-ESE, that predicts which sequences have ESE activity by statistical analysis of exon-intron and splice site composition. When large datasets of human gene sequences were used, this method identified ten predicted ESE motifs. Representatives of all ten motifs were found to possess enhancer activity in vivo, whereas point mutants of these sequences exhibited sharply reduced activity.

"We developed a computational method to predict which sequences would function as ESEs, and then did experiments to test these predictions and found that all of the sequences predicted to function as splicing enhancers did indeed have this activity,” said senior author Dr. Christopher Burge, assistant professor in the biology department at MIT. "Eventually, we hope to be able to fully understand and model the process by which exons and introns are identified by the human RNA splicing machinery.”




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