The differential disease regulome.

Area of Science:

• Genomics
• Systems Biology
• Bioinformatics

Background:

• Transcription factors (TFs) regulate gene expression and are implicated in disease pathways, representing potential drug targets.
• Current resources lack a global overview of TF-disease relationships, with analyses often disease-specific.
• Existing large-scale analysis pipelines are data-source specific, necessitating generic methods for integrating genomic information.

Purpose of the Study:

• To create a comprehensive resource mapping the relationships between multiple transcription factors and diseases.
• To provide a global statistical overview of TF-disease interrelationships.
• To develop a generic methodology for integrating diverse genomic data for TF-disease analysis.

Main Methods:

• A novel methodology was developed for pairwise, genome-wide comparison of annotation tracks.
• Analysis involved comparing 446 transcription factors against 1010 diseases.
• The differential disease regulome was visualized using the Google map engine for dynamic presentation.

Main Results:

• A global map, the differential disease regulome, was generated, detailing the over- and under-representation of 446 TFs across 1010 diseases.
• The map provides a statistical overview of complex interrelationships between diseases, genes, and regulatory elements.
• The methodology was extended to incorporate Gene Ontology and histone modification data, with a web interface for custom map generation.

Conclusions:

• A first-of-its-kind resource, the differential disease regulome, offers a global overview of TF-disease associations.
• Future improvements in ChIP-seq data will enhance the accuracy of the disease regulome maps.
• The developed approach enables reproducible and upgradable integrative genome analysis, moving beyond one-time efforts.