Rescue-ESE

RESCUE-ESE: Computational Prediction of Exonic Splicing Enhancers

RESCUE-ESE predicts exonic splicing enhancer (ESE) motifs by statistically analyzing exon–intron structures and splice site compositions in gene sequences.

Key Features:

• Predictive Computational Methodology: Implements the RESCUE-ESE algorithm to identify ESE motifs from large-scale sequence datasets using statistical enrichment analyses of exon–intron architecture and splice site composition.
• Validated ESE Motifs: Identified 10 predicted ESE motifs in human genes; experimental validation demonstrated in vivo enhancer activity, with point mutations causing reduced activity.
• ESE Hexamer Database: Provides a curated set of 238 candidate ESE hexamers derived from human gene sequences.
• Cross-Species Analysis: Extended to mouse, zebrafish, and pufferfish to enable comparative genomic analysis of ESE motifs.

Scientific Applications:

• Splicing Phenotype Prediction: Predicts effects of exonic mutations on ESE disruption, exon skipping, mRNA processing, and protein synthesis; supports studies of genetic diseases involving splicing defects and comparative analyses of splicing regulation across species.

Methodology:

Applies statistical enrichment analysis to compare hexamer frequencies between exonic and intronic regions while controlling for splice site strength, identifying candidate ESE motifs based on overrepresentation in exons with weak splice sites. Predicted motifs are validated through functional assays assessing enhancer activity and sensitivity to point mutations.