REST is a major negative regulator of endocrine differentiation during pancreas organogenesis.

Multiple transcription factors have been shown to promote pancreatic ß-cell differentiation, yet much less is known about negative regulators. Earlier epigenomic studies suggested that the transcriptional repressor REST could be a suppressor of endocrinogenesis in the embryonic pancreas. However, pancreatic Rest knockout mice failed to show abnormal numbers of endocrine cells, suggesting that REST is not a major regulator of endocrine differentiation. Using a different conditional allele that enables profound REST inactivation, we observed a marked increase in pancreatic endocrine cell formation. REST inhibition also promoted endocrinogenesis in zebrafish and mouse early postnatal ducts and induced ß-cell-specific genes in human adult duct-derived organoids. We also defined genomic sites that are bound and repressed by REST in the embryonic pancreas. Our findings show that REST-dependent inhibition ensures a balanced production of endocrine cells from embryonic pancreatic progenitors.

Pancreatic microexons regulate islet function and glucose homeostasis.

Pancreatic islets control glucose homeostasis by the balanced secretion of insulin and other hormones, and their abnormal function causes diabetes or hypoglycaemia. Here we uncover a conserved programme of alternative microexons included in mRNAs of islet cells, particularly in genes involved in vesicle transport and exocytosis. Islet microexons (IsletMICs) are regulated by the RNA binding protein SRRM3 and represent a subset of the larger neural programme that are particularly sensitive to SRRM3 levels. Both SRRM3 and IsletMICs are induced by elevated glucose levels, and depletion of SRRM3 in human and rat beta cell lines and mouse islets, or repression of particular IsletMICs using antisense oligonucleotides, leads to inappropriate insulin secretion. Consistently, mice harbouring mutations in Srrm3 display defects in islet cell identity and function, leading to hyperinsulinaemic hypoglycaemia. Importantly, human genetic variants that influence SRRM3 expression and IsletMIC inclusion in islets are associated with fasting glucose variation and type 2 diabetes risk. Taken together, our data identify a conserved microexon programme that regulates glucose homeostasis.

Regulatory de novo mutations underlying intellectual disability.

The genetic aetiology of a major fraction of patients with intellectual disability (ID) remains unknown. De novo mutations (DNMs) in protein-coding genes explain up to 40% of cases, but the potential role of regulatory DNMs is still poorly understood. We sequenced 63 whole genomes from 21 ID probands and their unaffected parents. In addition, we analysed 30 previously sequenced genomes from exome-negative ID probands. We found that regulatory DNMs were selectively enriched in fetal brain-specific enhancers as compared with adult brain enhancers. DNM-containing enhancers were associated with genes that show preferential expression in the prefrontal cortex. Furthermore, we identified recurrently mutated enhancer clusters that regulate genes involved in nervous system development (CSMD1, OLFM1, and POU3F3). Most of the DNMs from ID probands showed allele-specific enhancer activity when tested using luciferase assay. Using CRISPR-mediated mutation and editing of epigenomic marks, we show that DNMs at regulatory elements affect the expression of putative target genes. Our results, therefore, provide new evidence to indicate that DNMs in fetal brain-specific enhancers play an essential role in the aetiology of ID.

Genetic regulation of RNA splicing in human pancreatic islets.

BACKGROUND: Non-coding genetic variants that influence gene transcription in pancreatic islets play a major role in the susceptibility to type 2 diabetes (T2D), and likely also contribute to type 1 diabetes (T1D) risk. For many loci, however, the mechanisms through which non-coding variants influence diabetes susceptibility are unknown. RESULTS: We examine splicing QTLs (sQTLs) in pancreatic islets from 399 human donors and observe that common genetic variation has a widespread influence on the splicing of genes with established roles in islet biology and diabetes. In parallel, we profile expression QTLs (eQTLs) and use transcriptome-wide association as well as genetic co-localization studies to assign islet sQTLs or eQTLs to T2D and T1D susceptibility signals, many of which lack candidate effector genes. This analysis reveals biologically plausible mechanisms, including the association of T2D with an sQTL that creates a nonsense isoform in ERO1B, a regulator of ER-stress and proinsulin biosynthesis. The expanded list of T2D risk effector genes reveals overrepresented pathways, including regulators of G-protein-mediated cAMP production. The analysis of sQTLs also reveals candidate effector genes for T1D susceptibility such as DCLRE1B, a senescence regulator, and lncRNA MEG3. CONCLUSIONS: These data expose widespread effects of common genetic variants on RNA splicing in pancreatic islets. The results support a role for splicing variation in diabetes susceptibility, and offer a new set of genetic targets with potential therapeutic benefit.

CRISPR-based genome editing in primary human pancreatic islet cells.

Gene targeting studies in primary human islets could advance our understanding of mechanisms driving diabetes pathogenesis. Here, we demonstrate successful genome editing in primary human islets using clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 9 (Cas9). CRISPR-based targeting efficiently mutated protein-coding exons, resulting in acute loss of islet ß-cell regulators, like the transcription factor PDX1 and the KATP channel subunit KIR6.2, accompanied by impaired ß-cell regulation and function. CRISPR targeting of non-coding DNA harboring type 2 diabetes (T2D) risk variants revealed changes in ABCC8, SIX2 and SIX3 expression, and impaired ß-cell function, thereby linking regulatory elements in these target genes to T2D genetic susceptibility. Advances here establish a paradigm for genetic studies in human islet cells, and reveal regulatory and genetic mechanisms linking non-coding variants to human diabetes risk.

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

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.

Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of type 2 diabetes.

Genetic studies promise to provide insight into the molecular mechanisms underlying type 2 diabetes (T2D). Variants associated with T2D are often located in tissue-specific enhancer clusters or super-enhancers. So far, such domains have been defined through clustering of enhancers in linear genome maps rather than in three-dimensional (3D) space. Furthermore, their target genes are often unknown. We have created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated enhancers to their target genes, often located hundreds of kilobases away. It also revealed >1,300 groups of islet enhancers, super-enhancers and active promoters that form 3D hubs, some of which show coordinated glucose-dependent activity. We demonstrate that genetic variation in hubs impacts insulin secretion heritability, and show that hub annotations can be used for polygenic scores that predict T2D risk driven by islet regulatory variants. Human islet 3D chromatin architecture, therefore, provides a framework for interpretation of T2D genome-wide association study (GWAS) signals.

Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes.

The reanalysis of existing GWAS data represents a powerful and cost-effective opportunity to gain insights into the genetics of complex diseases. By reanalyzing publicly available type 2 diabetes (T2D) genome-wide association studies (GWAS) data for 70,127 subjects, we identify seven novel associated regions, five driven by common variants (LYPLAL1, NEUROG3, CAMKK2, ABO, and GIP genes), one by a low-frequency (EHMT2), and one driven by a rare variant in chromosome Xq23, rs146662057, associated with a twofold increased risk for T2D in males. rs146662057 is located within an active enhancer associated with the expression of Angiotensin II Receptor type 2 gene (AGTR2), a modulator of insulin sensitivity, and exhibits allelic specific activity in muscle cells. Beyond providing insights into the genetics and pathophysiology of T2D, these results also underscore the value of reanalyzing publicly available data using novel genetic resources and analytical approaches.

Publisher Correction: Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes.

In the originally published version of this Article, the affiliation details for Santi González, Jian'an Luan and Claudia Langenberg were inadvertently omitted. Santi González should have been affiliated with 'Barcelona Supercomputing Center (BSC), Joint BSC-CRG-IRB Research Program in Computational Biology, 08034 Barcelona, Spain', and Jian'an Luan and Claudia Langenberg should have been affiliated with 'MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK'. Furthermore, the abstract contained an error in the SNP ID for the rare variant in chromosome Xq23, which was incorrectly given as rs146662057 and should have been rs146662075. These errors have now been corrected in both the PDF and HTML versions of the Article.

Conservation priorities for endangered Indian tigers through a genomic lens.

Tigers have lost 93% of their historical range worldwide. India plays a vital role in the conservation of tigers since nearly 60% of all wild tigers are currently found here. However, as protected areas are small (<300 km2 on average), with only a few individuals in each, many of them may not be independently viable. It is thus important to identify and conserve genetically connected populations, as well as to maintain connectivity within them. We collected samples from wild tigers (Panthera tigris tigris) across India and used genome-wide SNPs to infer genetic connectivity. We genotyped 10,184 SNPs from 38 individuals across 17 protected areas and identified three genetically distinct clusters (corresponding to northwest, southern and central India). The northwest cluster was isolated with low variation and high relatedness. The geographically large central cluster included tigers from central, northeastern and northern India, and had the highest variation. Most genetic diversity (62%) was shared among clusters, while unique variation was highest in the central cluster (8.5%) and lowest in the northwestern one (2%). We did not detect signatures of differential selection or local adaptation. We highlight that the northwest population requires conservation attention to ensure persistence of these tigers.