Cross-population joint analysis of eQTLs: fine mapping and functional annotation

Area of Science:

• Genomics
• Statistical Genetics
• Molecular Biology

Background:

• Expression quantitative trait loci (eQTL) mapping is crucial for understanding the genetic basis of complex traits at the molecular level.
• Existing methods often face limitations in power and resolution when analyzing diverse populations.

Purpose of the Study:

• To develop and apply an integrative statistical approach for eQTL analysis across multiple population groups.
• To enhance the power of eQTL discovery and improve the fine-mapping resolution of causal variants.
• To enable high-resolution functional analysis of identified eQTLs by integrating genomic annotations.

Main Methods:

• Leveraging eQTL data from multiple population groups for integrative analysis.
• Accounting for population-specific allele frequencies and linkage disequilibrium patterns.
• Integrating genomic annotations to facilitate functional interpretation of eQTLs.

Main Results:

• Joint analysis across populations significantly improved eQTL discovery power and fine-mapping resolution.
• Identified multiple independent cis-eQTL signals consistent across populations.
• Discovered significant enrichment of eQTLs in genetic variants that disrupt transcription factor binding sites (p-value = 4.93 × 10(-22)).

Conclusions:

• Cross-population eQTL analysis offers substantial benefits for genetic discovery and functional annotation.
• Genes frequently exhibit multiple independent eQTLs within their cis-regulatory regions.
• Transcription factor binding site disruption is a key mechanism underlying observed eQTL associations.