ExonSkipDB

ExonSkipDB provides comprehensive functional annotations of exon skipping (ES) events to characterize effects on open reading frames (ORFs) and protein functional domains across 14,272 genes, 90,616 ES events in 33 TCGA cancer types and 89,845 ES events in 31 GTEx normal tissues.

Key Features:

• Extensive Data Collection: Compiles 14,272 genes with 90,616 exon skipping events across 33 cancer types from The Cancer Genome Atlas (TCGA) and 89,845 exon skipping events in 31 normal tissues from Genotype-Tissue Expression (GTEx).
• ORF and Protein Feature Annotation: Assigns ORF status for transcripts affected by exon skipping and annotates loss of protein functional features resulting from ES events.
• Multi-omics Correlation Analysis: Correlates exon skipping events with genetic mutations and DNA methylation patterns using integrated multi-omics evidence.
• Therapeutic Target Identification: Focuses on individual exon units to identify genes and exon-level events as potential therapeutic targets in cancer research and drug development.

Scientific Applications:

• Identification of disease-associated ES events: Enables detection of exon skipping events associated with cancer types and normal tissue phenotypes.
• Mechanistic exploration: Facilitates investigation of molecular mechanisms by linking ES-induced ORF changes and loss of protein domains to functional consequences.
• Therapeutic discovery: Supports discovery of novel therapeutic targets by mapping exon-level alterations to cancer-specific and tissue-specific contexts.

Methodology:

Annotations are generated by identifying skipped exons in TCGA and GTEx datasets and integrating multi-omics data (genetic mutations and DNA methylation) to assess ORF changes and loss of protein functional features.