Dataset Information

TIGER: The gene expression regulatory variation landscape of human pancreatic islets.

ABSTRACT: Genome-wide association studies (GWASs) identified hundreds of signals associated with type 2 diabetes (T2D). To gain insight into their underlying molecular mechanisms, we have created the translational human pancreatic islet genotype tissue-expression resource (TIGER), aggregating >500 human islet genomic datasets from five cohorts in the Horizon 2020 consortium T2DSystems. We impute genotypes using four reference panels and meta-analyze cohorts to improve the coverage of expression quantitative trait loci (eQTL) and develop a method to combine allele-specific expression across samples (cASE). We identify >1 million islet eQTLs, 53 of which colocalize with T2D signals. Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identify eight cASE colocalizations, among which we found a T2D-associated SLC30A8 variant. We make all data available through the TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translates into therapeutic insight and precision medicine for T2D.

SUBMITTER: Alonso L

PROVIDER: S-EPMC8864863 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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TIGER: The gene expression regulatory variation landscape of human pancreatic islets.

Alonso Lorena L Piron Anthony A Morán Ignasi I Guindo-Martínez Marta M Bonàs-Guarch Sílvia S Atla Goutham G Miguel-Escalada Irene I Royo Romina R Puiggròs Montserrat M Garcia-Hurtado Xavier X Suleiman Mara M Marselli Lorella L Esguerra Jonathan L S JLS Turatsinze Jean-Valéry JV Torres Jason M JM Nylander Vibe V Chen Ji J Eliasson Lena L Defrance Matthieu M Amela Ramon R Mulder Hindrik H Gloyn Anna L AL Groop Leif L Marchetti Piero P Eizirik Decio L DL Ferrer Jorge J Mercader Josep M JM Cnop Miriam M Torrents David D

Cell reports 20211001 2

Genome-wide association studies (GWASs) identified hundreds of signals associated with type 2 diabetes (T2D). To gain insight into their underlying molecular mechanisms, we have created the translational human pancreatic islet genotype tissue-expression resource (TIGER), aggregating >500 human islet genomic datasets from five cohorts in the Horizon 2020 consortium T2DSystems. We impute genotypes using four reference panels and meta-analyze cohorts to improve the coverage of expression quantitati ...[more]

PMID: 34644572

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Project description:Genetic and epigenetic mechanisms may interact and together affect biological processes and disease development. However, most previous studies have investigated genetic and epigenetic mechanisms independently, and studies examining their interactions throughout the human genome are lacking. To identify genetic loci that interact with the epigenome, we performed the first genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human pancreatic islets. We related 574,553 single nucleotide polymorphisms (SNPs) with genome-wide DNA methylation data of 468,787 CpG sites targeting 99% of RefSeq genes in islets from 89 donors. We identified 67,438 SNP-CpG pairs in cis, corresponding to 36,783 SNPs (6.4% of tested SNPs) and 11,735 CpG sites (2.5% of tested CpGs), and 2,562 significant SNP-CpG pairs in trans, corresponding to 1,465 SNPs (0.3% of tested SNPs) and 383 CpG sites (0.08% of tested CpGs), showing significant associations after correction for multiple testing. These include reported diabetes loci, e.g. ADCY5, KCNJ11, HLA-DQA1, INS, PDX1 and GRB10. CpGs of significant cis-mQTLs were overrepresented in the gene body and outside of CpG islands. Follow-up analyses further identified mQTLs associated with gene expression and insulin secretion in human islets. Causal inference test (CIT) identified SNP-CpG pairs where DNA methylation in human islets is the potential mediator of the genetic association with gene expression or insulin secretion. Functional analyses further demonstrated that identified candidate genes (GPX7, GSTT1 and SNX19) directly affect key biological processes such as proliferation and apoptosis in pancreatic β-cells. Finally, we found direct correlations between DNA methylation of 22,773 (4.9%) CpGs with mRNA expression of 4,876 genes, where 90% of the correlations were negative when CpGs were located in the region surrounding transcription start site. Our study demonstrates for the first time how genome-wide genetic and epigenetic variation interacts to influence gene expression, islet function and potential diabetes risk in humans.

Project description:microRNAs (miRNAs) play an important role in pancreatic development and adult ?-cell physiology. Our hypothesis is based on the assumption that each islet cell type has a specific pattern of miRNA expression. We sought to determine the profile of miRNA expression in ?-and ?-cells, the main components of pancreatic islets, because this analysis may lead to a better understanding of islet gene regulatory pathways. Highly enriched (>98%) subsets of human ?-and ?-cells were obtained by flow cytometric sorting after intracellular staining with c-peptide and glucagon antibody. The method of sorting based on intracellular staining is possible because miRNAs are stable after fixation. MiRNA expression levels were determined by quantitative high throughput PCR-based miRNA array platform screening. Most of the miRNAs were preferentially expressed in ?-cells. From the total of 667 miRNAs screened, the Significant Analysis of Microarray identified 141 miRNAs, of which only 7 were expressed more in ?-cells (?-miRNAs) and 134 were expressed more in ?-cells (?-miRNAs). Bioinformatic analysis identified potential targets of ?-miRNAs analyzing the Beta Cell Gene Atlas, described in the T1Dbase, the web platform, supporting the type 1 diabetes (T1D) community. cMaf, a transcription factor regulating glucagon expression expressed selectively in ?-cells (TF?) is targeted by ?-miRNAs; miR-200c, miR-125b and miR-182. Min6 cells treated with inhibitors of these miRNAs show an increased expression of cMaf RNA. Conversely, over expression of miR-200c, miR-125b or miR-182 in the mouse alpha cell line ?TC6 decreases the level of cMAF mRNA and protein. MiR-200c also inhibits the expression of Zfpm2, a TF? that inhibits the PI3K signaling pathway, at both RNA and protein levels.In conclusion, we identified miRNAs differentially expressed in pancreatic ?- and ?-cells and their potential transcription factor targets that could add new insights into different aspects of islet biology and pathophysiology.

Dataset Information

TIGER: The gene expression regulatory variation landscape of human pancreatic islets.

Publications

TIGER: The gene expression regulatory variation landscape of human pancreatic islets.

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