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Systematic differences in discovery of genetic effects on gene expression and complex traits
Open accessAbstract
Most signals in genome-wide association studies (GWAS) of complex traits implicate noncoding genetic variants with putative gene regulatory effects. However, currently identified regulatory variants, notably expression quantitative trait loci (eQTLs), explain only a small fraction of GWAS signals. Here, we show that GWAS and cis-eQTL hits are systematically different: eQTLs cluster strongly near transcription start sites, whereas GWAS hits do not. Genes near GWAS hits are enriched in key functional annotations, are under strong selective constraint and have complex regulatory landscapes across different tissue/cell types, whereas genes near eQTLs are depleted of most functional annotations, show relaxed constraint, and have simpler regulatory landscapes. We describe a model to understand these observations, including how natural selection on complex traits hinders discovery of functionally relevant eQTLs. Our results imply that GWAS and eQTL studies are systematically biased toward different types of variant, and support the use of complementary functional approaches alongside the next generation of eQTL studies.
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“A previous study found that disease-associated genes from GWAS were enriched in selectively constrained genes, while eQTL genes were depleted in selectively constrained genes52.”
From Inferring gene regulatory networks from single-cell multiome data using atlas-scale external data (2025) · cites this paper as [52]
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“However, these studies are not able to resolve most genome-wide association study (GWAS) loci (6).”
From Low overlap of plasma and CSF protein quantitative trait loci affects protein discovery for neurological disease (2026) · cites this paper as [6]
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“it has been recently shown that genes near GWAS signals are enriched for key functional annotations and are under strong selective constraint, while genes near eQTLs lack most functional annotations and show relaxed constraint68”
From Variant-to-function mapping of late-onset Alzheimer’s disease GWAS signals in human microglial cell models implicates RTFDC1 at the CASS4 locus (2024) · cites this paper as [68]
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Metadata
- Authors
- Mostafavi, H., Spence, J. P., Naqvi, S., & Pritchard, J. K.
- Affiliations
- Stanford University (US)
- Corresponding author
- Mostafavi, Hakhamanesh
- Pritchard, Jonathan K.
- Venue
- Nature Genetics
- Published
- 2023-10-19
- Volume
- 55
- Issue
- 11
- Pages
- 1866-1875
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC12270542
- OpenAlex
- W4387782515
- Cited by
- 336
- References
- 80
- Citations by year
- 2026: 109 · 2025: 128 · 2024: 90 · 2023: 8
- FWCI
- 55.62
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (R01HG008140, R01HG011432, U01HG012069)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Keywords
- expression quantitative trait loci, cis-eQTL, complex traits, non-coding variants, transcription start sites, natural selection, selective constraint, regulatory landscape, tissue-specific gene expression
- MeSH terms
- Gene Expression Regulation, Gene Expression, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study
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