Master regulator activity QTL protocol to implicate regulatory pathways potentially mediating GWAS signals using eQTL...

Area of Science:

• Genetics
• Systems Biology
• Bioinformatics

Background:

• Germline variants in DNA are associated with complex traits.
• Identifying the biological mechanisms underlying these associations is challenging.
• Expression quantitative trait loci (eQTLs) help link genetic variants to gene expression but do not capture all regulatory effects.

Purpose of the Study:

• To present a novel protocol for identifying transcriptional regulators that mediate the effects of germline variants on complex traits.
• To enable functional hypothesis generation independent of eQTLs.
• To provide a framework for understanding the regulatory landscape of complex traits.

Main Methods:

• Tissue-/cell-type-specific co-expression network modeling.
• Inference of expression regulator activity.
• Identification of phenotypic master regulators.
• Activity quantitative trait loci (aQTL) and eQTL analyses.

Main Results:

• The protocol successfully identifies potential transcriptional regulators.
• It allows for functional hypothesis generation without relying solely on eQTL colocalization.
• It integrates genotype, expression, and phenotype data for comprehensive analysis.

Conclusions:

• This protocol offers a robust method for dissecting the regulatory mechanisms of complex traits.
• It expands the toolkit for functional genomics by providing an eQTL-independent approach.
• It facilitates a deeper understanding of how genetic variation impacts biological function and disease risk.