Trans -eQTLs reveal the architecture of human gene regulatory networks

Abstract Many non-coding variants influence complex traits and diseases through gene regulation, yet the mechanisms linking these variants to downstream biology remain poorly understood. Here, we present eQTLGen Phase 2 , a comprehensive genome-wide analysis of gene expression quantitative trait loci (eQTLs) in 43,301 blood samples from 52 datasets. Beyond local cis -effects, this sample size enabled the first systematic mapping of trans -eQTLs at scale. We identify cis -eQTLs for nearly all expressed genes (94.7%) and trans -eQTLs for over half (56.2%). Second, by colocalizing cis -eQTLs with trans -eQTLs, we infer a directed gene regulatory network comprising 47,554 directed gene regulatory relationships. These networks reveal how genetic perturbations in upstream regulators produce dose-dependent downstream effects, supported by Perturb-seq and ChIP-seq data. Third, integrating this network with 87 genome-wide association studies allows us to systematically prioritize trait-relevant pathways and candidate genes. Variants exerting both cis – and trans -effects are markedly more likely to colocalize with trait associations than cis -only variants, delineating a subset of functionally active cis -eQTLs from a large group with limited downstream impact. This distinction provides a conceptual framework for identifying regulatory variants that truly mediate complex trait biology. Together, these results provide a publicly available resource of cis – and trans -eQTLs and an in vivo scaffold for human gene-regulatory networks, elucidating how propagation of cis -effects modulates complex disease.