Dataset Information

Cis-eQTL mapping of human pancreatic islets

ABSTRACT: The intersection of genome-wide association analyses with physiological and functional data indicates that variants regulating islet gene transcription influence type 2 diabetes predisposition and glucose homeostasis. However, the specific genes through which these regulatory variants act remain poorly characterized. In this study, we generated eQTL data from human islet samples to establish the extent to which this allowed us to identify candidate effector transcripts at GWAS loci for T2D and glycemic traits.

PROVIDER: EGAS00001001265 | EGA |

REPOSITORIES: EGA

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Publications

Transcript Expression Data from Human Islets Links Regulatory Signals from Genome-Wide Association Studies for Type 2 Diabetes and Glycemic Traits to Their Downstream Effectors.

van de Bunt Martijn M Manning Fox Jocelyn E JE Dai Xiaoqing X Barrett Amy A Grey Caleb C Li Lei L Bennett Amanda J AJ Johnson Paul R PR Rajotte Raymond V RV Gaulton Kyle J KJ Dermitzakis Emmanouil T ET MacDonald Patrick E PE McCarthy Mark I MI Gloyn Anna L AL

PLoS genetics 20151201 12

The intersection of genome-wide association analyses with physiological and functional data indicates that variants regulating islet gene transcription influence type 2 diabetes (T2D) predisposition and glucose homeostasis. However, the specific genes through which these regulatory variants act remain poorly characterized. We generated expression quantitative trait locus (eQTL) data in 118 human islet samples using RNA-sequencing and high-density genotyping. We identified fourteen loci at which ...[more]

PMID: 26624892

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Project description:Recent advances in the understanding of the genetics of type 2 diabetes (T2D) susceptibility have focused attention on the regulation of transcriptional activity within the pancreatic beta-cell. MicroRNAs (miRNAs) represent an important component of regulatory control, and have proven roles in the development of human disease and control of glucose homeostasis. We set out to establish the miRNA profile of human pancreatic islets and of enriched beta-cell populations, and to explore their potential involvement in T2D susceptibility. We used Illumina small RNA sequencing to profile the miRNA fraction in three preparations each of primary human islets and of enriched beta-cells generated by fluorescence-activated cell sorting. In total, 366 miRNAs were found to be expressed (i.e. >100 cumulative reads) in islets and 346 in beta-cells; of the total of 384 unique miRNAs, 328 were shared. A comparison of the islet-cell miRNA profile with those of 15 other human tissues identified 40 miRNAs predominantly expressed (i.e. >50% of all reads seen across the tissues) in islets. Several highly-expressed islet miRNAs, such as miR-375, have established roles in the regulation of islet function, but others (e.g. miR-27b-3p, miR-192-5p) have not previously been described in the context of islet biology. As a first step towards exploring the role of islet-expressed miRNAs and their predicted mRNA targets in T2D pathogenesis, we looked at published T2D association signals across these sites. We found evidence that predicted mRNA targets of islet-expressed miRNAs were globally enriched for signals of T2D association (p-values <0.01, q-values <0.1). At six loci with genome-wide evidence for T2D association (AP3S2, KCNK16, NOTCH2, SCL30A8, VPS26A, and WFS1) predicted mRNA target sites for islet-expressed miRNAs overlapped potentially causal variants. In conclusion, we have described the miRNA profile of human islets and beta-cells and provide evidence linking islet miRNAs to T2D pathogenesis. Examination of the miRNA profiles in 3 preparations of isolated pancreatic islets and 3 preparations of FACS-enriched pancreatic beta-cells

Dataset Information

Cis-eQTL mapping of human pancreatic islets

Publications

Transcript Expression Data from Human Islets Links Regulatory Signals from Genome-Wide Association Studies for Type 2 Diabetes and Glycemic Traits to Their Downstream Effectors.

Similar Datasets

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