Regulatory annotation of genomic intervals based on tissue-specific expression QTLs

Area of Science:

• Genomics
• Computational Biology
• Systems Biology

Background:

• Annotating genomic loci, especially non-coding regions, is challenging.
• Gene set enrichment analysis is effective for gene annotation.
• Extending this to genomic intervals can reveal functional connections.

Purpose of the Study:

• To develop a novel computational strategy, loci2path, for annotating genomic intervals.
• To leverage genome-wide and tissue-specific expression quantitative trait loci (eQTL) data for regulatory annotation.
• To connect genomic intervals to functional pathways and gene sets.

Main Methods:

• Developed loci2path, a computational strategy using eQTL information.
• Input genomic intervals are analyzed for the presence of millions of eQTLs.
• eQTLs are grouped by target gene pathways/gene sets (MSigDB) for annotation.
• Utilized Genotype-Tissue Expression (GTEx) project data (1.7M eQTLs, 44 tissues).

Main Results:

• loci2path successfully links genomic intervals to functional pathways and gene sets.
• The method identified relevant biological pathways and disease mechanisms for psoriasis and immune-related diseases.
• Tissue-specific eQTL analysis provided insights into distinct tissue roles in disease.

Conclusions:

• loci2path offers a novel approach to genomic interval annotation using eQTLs.
• The method overcomes limitations of proximity-based gene-locus association.
• It provides tissue-specific regulatory context, enhancing understanding of disease mechanisms.