Pancreatic Islet Transcriptional Enhancers and Diabetes

Heterozygous missense variant in GLI2 impairs human endocrine pancreas development

Missense variants are the most common type of coding genetic variants. Their functional assessment is fundamental for defining any implication in human diseases and may also uncover genes that are essential for human organ development. Here, we apply CRISPR-Cas9 gene editing on human iPSCs to study a heterozygous missense variant in GLI2 identified in two siblings with early-onset and insulin-dependent diabetes of unknown cause. GLI2 is a primary mediator of the Hedgehog pathway, which regulates pancreatic β-cell development in mice. However, neither mutations in GLI2 nor Hedgehog dysregulation have been reported as cause or predisposition to diabetes. We establish and study a set of isogenic iPSC lines harbouring the missense variant for their ability to differentiate into pancreatic β-like cells. Interestingly, iPSCs carrying the missense variant show altered GLI2 transcriptional activity and impaired differentiation of pancreatic progenitors into endocrine cells. RNASeq and network analyses unveil a crosstalk between Hedgehog and WNT pathways, with the dysregulation of non-canonical WNT signaling in pancreatic progenitors carrying the GLI2 missense variant. Collectively, our findings underscore an essential role for GLI2 in human endocrine development and identify a gene variant that may lead to diabetes.

Multiplexed CRISPR gene editing in primary human islet cells with Cas9 ribonucleoprotein

Successful genome editing in primary human islets could reveal features of the genetic regulatory landscape underlying β cell function and diabetes risk. Here, we describe a CRISPR-based strategy to interrogate functions of predicted regulatory DNA elements using electroporation of a complex of Cas9 ribonucleoprotein (Cas9 RNP) and guide RNAs into primary human islet cells. We successfully targeted coding regions including the PDX1 exon 1, and non-coding DNA linked to diabetes susceptibility. CRISPR-Cas9 RNP approaches revealed genetic targets of regulation by DNA elements containing candidate diabetes risk SNPs, including an in vivo enhancer of the MPHOSPH9 gene. CRISPR-Cas9 RNP multiplexed targeting of two cis-regulatory elements linked to diabetes risk in PCSK1, which encodes an endoprotease crucial for Insulin processing, also demonstrated efficient simultaneous editing of PCSK1 regulatory elements, resulting in impaired β cell PCSK1 regulation and Insulin secretion. Multiplex CRISPR-Cas9 RNP provides powerful approaches to investigate and elucidate human islet cell gene regulation in health and diabetes.

Multiplexed CRISPR gene editing in primary human islet cells with Cas9 ribonucleoprotein

Successful genome editing in primary human islets could reveal features of the genetic regulatory landscape underlying β cell function and diabetes risk. Here, we describe a CRISPR-based strategy to interrogate functions of predicted regulatory DNA elements using electroporation of a complex of Cas9 ribonucleoprotein (Cas9 RNP) and guide RNAs into primary human islet cells. We successfully targeted coding regions including the PDX1 exon 1, and non-coding DNA linked to diabetes susceptibility. CRISPR/Cas9 RNP approaches revealed genetic targets of regulation by DNA elements containing candidate diabetes risk SNPs, including an in vivo enhancer of the MPHOSPH9 gene. CRISPR/Cas9 RNP multiplexed targeting of two cis-regulatory elements linked to diabetes risk in PCSK1, which encodes an endoprotease crucial for insulin processing, also demonstrated efficient simultaneous editing of PCSK1 regulatory elements, resulting in impaired β cell PCSK1 regulation and insulin secretion. Multiplex CRISPR/Cas9 RNP provides powerful approaches to investigate and elucidate human islet cell gene regulation in health and diabetes.

Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits

Genetic association studies have identified hundreds of independent signals associated with type 2 diabetes (T2D) and related traits. Despite these successes, the identification of specific causal variants underlying a genetic association signal remains challenging. In this study, we describe a deep learning (DL) method to analyze the impact of sequence variants on enhancers. Focusing on pancreatic islets, a T2D relevant tissue, we show that our model learns islet-specific transcription factor (TF) regulatory patterns and can be used to prioritize candidate causal variants. At 101 genetic signals associated with T2D and related glycemic traits where multiple variants occur in linkage disequilibrium, our method nominates a single causal variant for each association signal, including three variants previously shown to alter reporter activity in islet-relevant cell types. For another signal associated with blood glucose levels, we biochemically test all candidate causal variants from statistical fine-mapping using a pancreatic islet beta cell line and show biochemical evidence of allelic effects on TF binding for the model-prioritized variant. To aid in future research, we publicly distribute our model and islet enhancer perturbation scores across ~67 million genetic variants. We anticipate that DL methods like the one presented in this study will enhance the prioritization of candidate causal variants for functional studies.

Chromatin accessibility differences between alpha, beta, and delta cells identifies common and cell type-specific enhancers

BACKGROUND

High throughput sequencing has enabled the interrogation of the transcriptomic landscape of glucagon-secreting alpha cells, insulin-secreting beta cells, and somatostatin-secreting delta cells. These approaches have furthered our understanding of expression patterns that define healthy or diseased islet cell types and helped explicate some of the intricacies between major islet cell crosstalk and glucose regulation. All three endocrine cell types derive from a common pancreatic progenitor, yet alpha and beta cells have partially opposing functions, and delta cells modulate and control insulin and glucagon release. While gene expression signatures that define and maintain cellular identity have been widely explored, the underlying epigenetic components are incompletely characterized and understood. However, chromatin accessibility and remodeling is a dynamic attribute that plays a critical role to determine and maintain cellular identity.

RESULTS

Here, we compare and contrast the chromatin landscape between mouse alpha, beta, and delta cells using ATAC-Seq to evaluate the significant differences in chromatin accessibility. The similarities and differences in chromatin accessibility between these related islet endocrine cells help define their fate in support of their distinct functional roles. We identify patterns that suggest that both alpha and delta cells are poised, but repressed, from becoming beta-like. We also identify patterns in differentially enriched chromatin that have transcription factor motifs preferentially associated with different regions of the genome. Finally, we not only confirm and visualize previously discovered common endocrine- and cell specific- enhancer regions across differentially enriched chromatin, but identify novel regions as well. We compiled our chromatin accessibility data in a freely accessible database of common endocrine- and cell specific-enhancer regions that can be navigated with minimal bioinformatics expertise.

CONCLUSIONS

Both alpha and delta cells appear poised, but repressed, from becoming beta cells in murine pancreatic islets. These data broadly support earlier findings on the plasticity in identity of non-beta cells under certain circumstances. Furthermore, differential chromatin accessibility shows preferentially enriched distal-intergenic regions in beta cells, when compared to either alpha or delta cells.

Transcriptional enhancers at 40: evolution of a viral DNA element to nuclear architectural structures

Gene regulation by transcriptional enhancers is the dominant mechanism driving cell type- and signal-specific transcriptional diversity in metazoans. However, over four decades since the original discovery, how enhancers operate in the nuclear space remains largely enigmatic. Recent multidisciplinary efforts combining real-time imaging, genome sequencing, and biophysical strategies provide insightful but conflicting models of enhancer-mediated gene control. Here, we review the discovery and progress in enhancer biology, emphasizing the recent findings that acutely activated enhancers assemble regulatory machinery as mesoscale architectural structures with distinct physical properties. These findings help formulate novel models that explain several mysterious features of the assembly of transcriptional enhancers and the mechanisms of spatial control of gene expression.