Predictive Identification of Exonic Splicing Enhancers in Human Genes

Abstract

Specific short oligonucleotide sequences that enhance pre-mRNA splicing when present in exons, termed exonic splicing enhancers (ESEs), play important roles in constitutive and alternative splicing. We have developed a computational method, RESCUE-ESE, that predicts which sequences have ESE activity by statistical analysis of exon-intron and splice site composition. Using large datasets of human gene sequences resulting from the near completed human genome project, this method identified ten predicted ESE motifs. Representatives of all ten motifs were shown to possess significant enhancer activity in vivo, while point mutants of these sequences exhibited sharply reduced activity. The motifs identified enable prediction of the splicing phenotypes of exonic mutations in human genes.