Multiple causal variants underlie genetic associations in humans

Associations between genetic variation and traits are often in noncoding regions with strong linkage disequilibrium (LD), where a single causal variant is assumed to underlie the association. We applied a massively parallel reporter assay (MPRA) to functionally evaluate genetic variants in high, loc...

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Veröffentlicht in:Science (American Association for the Advancement of Science) Jg. 375; H. 6586; S. 1247
Hauptverfasser: Abell, Nathan S, DeGorter, Marianne K, Gloudemans, Michael J, Greenwald, Emily, Smith, Kevin S, He, Zihuai, Montgomery, Stephen B
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 18.03.2022
Schlagworte:
Alleles
Asthma - genetics
Chromatin - metabolism
Genetic Predisposition to Disease
Genetic Variation
Genome, Human
Genome-Wide Association Study
Haplotypes
Histone Code
Humans
Inflammatory Bowel Diseases - genetics
Linkage Disequilibrium
Multifactorial Inheritance
Multiple Sclerosis - genetics
Phenotype
Platelet Count
Quantitative Trait Loci
Transcription Factors - genetics
Transcription Factors - metabolism
Untranslated Regions
ISSN:1095-9203, 1095-9203
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Zusammenfassung:Associations between genetic variation and traits are often in noncoding regions with strong linkage disequilibrium (LD), where a single causal variant is assumed to underlie the association. We applied a massively parallel reporter assay (MPRA) to functionally evaluate genetic variants in high, local LD for independent cis-expression quantitative trait loci (eQTL). We found that 17.7% of eQTLs exhibit more than one major allelic effect in tight LD. The detected regulatory variants were highly and specifically enriched for activating chromatin structures and allelic transcription factor binding. Integration of MPRA profiles with eQTL/complex trait colocalizations across 114 human traits and diseases identified causal variant sets demonstrating how genetic association signals can manifest through multiple, tightly linked causal variants.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1095-9203
1095-9203
DOI:10.1126/science.abj5117