Computational Identification of Tissue-Specific Splicing Regulatory Elements in Human Genes from RNA-Seq Data

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Alternative splicing is crucial for gene expression regulation and proteomic diversity.
• Splicing factors bind to splicing regulatory elements (SREs) to control tissue-specific gene expression.

Purpose of the Study:

• To perform a genome-wide analysis of alternative splicing across multiple human tissues (brain, heart, liver, muscle).
• To develop a computational pipeline for identifying differential exons and tissue-specific SREs.

Main Methods:

• Utilized the DEXSeq package and previously developed algorithms.
• Analyzed publicly available RNA-Seq data from the Human BodyMap project.
• Identified differential exons and tissue-specific exonic splicing enhancers (ESEs).

Main Results:

• Identified 28,100 differentially used exons across the four studied tissues.
• Discovered tissue-specific ESEs, many overlapping with existing databases.
• Revealed a complex regulatory network of exonic enhancers and silencers, including combinatorial elements.

Conclusions:

• The study identified a significant number of differentially spliced exons and tissue-specific regulatory elements.
• A complex regulatory network involving exonic enhancers and silencers was elucidated.
• Putative combinatorial enhancers and silencers suggest intricate control over alternative splicing in a tissue-specific manner.