1 Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
2 Oncode Institute, Utrecht, the Netherlands.
3 Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
4 Swiss Institute of Bioinformatics, Lausanne, Switzerland.
5 Institute of Computer Science, University of Tartu, Tartu, Estonia.
6 Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA.
7 Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
8 Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA.
9 Center for Integrative Genomics, Georgia Institute of Technology, Atlanta, GA, USA.
10 Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.
11 LIFE - Leipzig Research Center for Civilization Diseases, Leipzig University, Leipzig, Germany.
12 Institute for Medical Informatics, Statistics and Epidemiology, Leipzig University, Leipzig, Germany.
13 Sidra Medicine, Doha, Qatar.
14 Institute of Neurogenomics, Computational Health Center, Helmholtz Munich, Neuherberg, Germany.
15 Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
16 Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
17 Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
18 DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany.
19 Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland.
20 Concordia University, Centre for Functional and Structural Genomics, Biology department, Montreal, Canada.
21 Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
22 British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
23 Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
24 Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
25 Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
26 Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
27 Amsterdam Public Health research institute, Amsterdam, the Netherlands.
28 Neurological Disorder Research Center, Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University (HBKU), Qatar Foundation, Doha P.O. Box 5825, Qatar.
29 Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research, Granada, Spain.
30 Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
31 Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
32 Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland.
33 Biological Sciences Division, Public Health Sciences, University of Chicago, Chicago, IL, USA.
34 Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan.
35 Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
36 Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
37 M&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan.
38 Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.

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 ciseffects, 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.