Genetic variant effects on gene expression in human pancreatic islets and their implications for T2D
Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship be...
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Veröffentlicht in: | Nature communications 2020-09, Vol.11 (1), p.4912-14, Article 4912 |
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Sprache: | eng |
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Zusammenfassung: | Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using data from 420 donors. We find: (a) 7741
cis
-eQTLs in islets with a replication rate across 44 GTEx tissues between 40% and 73%; (b) marked overlap between islet
cis-
eQTL signals and active regulatory sequences in islets, with reduced eQTL effect size observed in the stretch enhancers most strongly implicated in GWAS signal location; (c) enrichment of islet
cis-
eQTL signals with T2D risk variants identified in genome-wide association studies; and (d) colocalization between 47 islet
cis-
eQTLs and variants influencing T2D or glycemic traits, including
DGKB
and
TCF7L2
. Our findings illustrate the advantages of performing functional and regulatory studies in disease relevant tissues.
Mechanistic inference following GWAS is hampered by the lack of tissue-specific transcriptomic resources. Here the authors combine genetic variants predisposing to type 2 diabetes with human pancreatic islet RNA-seq data. They identify 7741 islet expression quantitative trait loci (eQTLs), providing a resource for functional interpretation of association signals mapping to non-coding sequence. |
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ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-020-18581-8 |