Co-regulation of intragenic microRNA miR-153 and its host gene Ia-2 beta: identification of miR-153 target genes with functions related to IA-2 beta in pancreas and brain

AIMS/HYPOTHESIS: We analysed the genomic organisation of miR-153, a microRNA embedded in genes that encode two of the major type 1 diabetes autoantigens, islet-associated protein (IA)-2 and IA-2β. We also identified miR-153 target genes that correlated with IA-2β localisation and function. METHODS: A bioinformatics approach was used to identify miR-153's genomic organisation. To analyse the co-regulation of miR-153 and IA-2β, quantitative PCR analysis of miR-153 and Ia-2β (also known as Ptprn2) was performed after a glucose stimulation assay in MIN6B cells and isolated murine pancreatic islets, and also in wild-type Ia-2 (also known as Ptprn), Ia-2β single knockout and Ia-2/Ia-2β double knockout mouse brain and pancreatic islets. Bioinformatics identification of miR-153 target genes and validation via luciferase reporter assays, western blotting and quantitative PCR were also carried out. RESULTS: Two copies of miR-153, miR-153-1 and miR-153-2, are localised in intron 19 of Ia-2 and Ia-2β, respectively. In rodents, only miR-153-2 is conserved. We demonstrated that expression of miR-153-2 and Ia-2β in rodents is partially co-regulated as demonstrated by a strong reduction of miR-153 expression levels in Ia-2β knockout and Ia-2/Ia-2β double knockout mice. miR-153 levels were unaffected in Ia-2 knockout mice. In addition, glucose stimulation, which increases Ia-2 and Ia-2β expression, also significantly increased expression of miR-153. Several predicted targets of miR-153 were reduced after glucose stimulation in vitro, correlating with the increase in miR-153 levels. CONCLUSIONS/INTERPRETATION: This study suggests the involvement of miR-153, IA-2β and miR-153 target genes in a regulatory network, which is potentially relevant to insulin and neurotransmitter release.status: publishe

Genome-Wide Associations between Genetic and Epigenetic Variation Influence mRNA Expression and Insulin Secretion in Human Pancreatic Islets.

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