Loss of RREB1 in pancreatic beta cells reduces cellular insulin content and affects endocrine cell gene expression.

AIMS/HYPOTHESIS: Genome-wide studies have uncovered multiple independent signals at the RREB1 locus associated with altered type 2 diabetes risk and related glycaemic traits. However, little is known about the function of the zinc finger transcription factor Ras-responsive element binding protein 1 (RREB1) in glucose homeostasis or how changes in its expression and/or function influence diabetes risk. METHODS: A zebrafish model lacking rreb1a and rreb1b was used to study the effect of RREB1 loss in vivo. Using transcriptomic and cellular phenotyping of a human beta cell model (EndoC-ßH1) and human induced pluripotent stem cell (hiPSC)-derived beta-like cells, we investigated how loss of RREB1 expression and activity affects pancreatic endocrine cell development and function. Ex vivo measurements of human islet function were performed in donor islets from carriers of RREB1 type 2 diabetes risk alleles. RESULTS: CRISPR/Cas9-mediated loss of rreb1a and rreb1b function in zebrafish supports an in vivo role for the transcription factor in beta cell mass, beta cell insulin expression and glucose levels. Loss of RREB1 also reduced insulin gene expression and cellular insulin content in EndoC-ßH1 cells and impaired insulin secretion under prolonged stimulation. Transcriptomic analysis of RREB1 knockdown and knockout EndoC-ßH1 cells supports RREB1 as a novel regulator of genes involved in insulin secretion. In vitro differentiation of RREB1KO/KO hiPSCs revealed dysregulation of pro-endocrine cell genes, including RFX family members, suggesting that RREB1 also regulates genes involved in endocrine cell development. Human donor islets from carriers of type 2 diabetes risk alleles in RREB1 have altered glucose-stimulated insulin secretion ex vivo, consistent with a role for RREB1 in regulating islet cell function. CONCLUSIONS/INTERPRETATION: Together, our results indicate that RREB1 regulates beta cell function by transcriptionally regulating the expression of genes involved in beta cell development and function.

A genome-wide CRISPR screen identifies CALCOCO2 as a regulator of beta cell function influencing type 2 diabetes risk.

Identification of the genes and processes mediating genetic association signals for complex diseases represents a major challenge. As many of the genetic signals for type 2 diabetes (T2D) exert their effects through pancreatic islet-cell dysfunction, we performed a genome-wide pooled CRISPR loss-of-function screen in a human pancreatic beta cell line. We assessed the regulation of insulin content as a disease-relevant readout of beta cell function and identified 580 genes influencing this phenotype. Integration with genetic and genomic data provided experimental support for 20 candidate T2D effector transcripts including the autophagy receptor CALCOCO2. Loss of CALCOCO2 was associated with distorted mitochondria, less proinsulin-containing immature granules and accumulation of autophagosomes upon inhibition of late-stage autophagy. Carriers of T2D-associated variants at the CALCOCO2 locus further displayed altered insulin secretion. Our study highlights how cellular screens can augment existing multi-omic efforts to support mechanistic understanding and provide evidence for causal effects at genome-wide association studies loci.

HOTAIR interacts with PRC2 complex regulating the regional preadipocyte transcriptome and human fat distribution.

Mechanisms governing regional human adipose tissue (AT) development remain undefined. Here, we show that the long non-coding RNA HOTAIR (HOX transcript antisense RNA) is exclusively expressed in gluteofemoral AT, where it is essential for adipocyte development. We find that HOTAIR interacts with polycomb repressive complex 2 (PRC2) and we identify core HOTAIR-PRC2 target genes involved in adipocyte lineage determination. Repression of target genes coincides with PRC2 promoter occupancy and H3K27 trimethylation. HOTAIR is also involved in modifying the gluteal adipocyte transcriptome through alternative splicing. Gluteal-specific expression of HOTAIR is maintained by defined regions of open chromatin across the HOTAIR promoter. HOTAIR expression levels can be modified by hormonal (estrogen, glucocorticoids) and genetic variation (rs1443512 is a HOTAIR eQTL associated with reduced gynoid fat mass). These data identify HOTAIR as a dynamic regulator of the gluteal adipocyte transcriptome and epigenome with functional importance for human regional AT development.

Heterogeneity in phenotype, disease progression and drug response in type 2 diabetes.

Type 2 diabetes (T2D) is a complex chronic disease characterized by considerable phenotypic heterogeneity. In this study, we applied a reverse graph embedding method to routinely collected data from 23,137 Scottish patients with newly diagnosed diabetes to visualize this heterogeneity and used partitioned diabetes polygenic risk scores to gain insight into the underlying biological processes. Overlaying risk of progression to outcomes of insulin requirement, chronic kidney disease, referable diabetic retinopathy and major adverse cardiovascular events, we show how these risks differ by patient phenotype. For example, patients at risk of retinopathy are phenotypically different from those at risk of cardiovascular events. We replicated our findings in the UK Biobank and the ADOPT clinical trial, also showing that the pattern of diabetes drug monotherapy response differs for different drugs. Overall, our analysis highlights how, in a European population, underlying phenotypic variation drives T2D onset and affects subsequent diabetes outcomes and drug response, demonstrating the need to incorporate these factors into personalized treatment approaches for the management of T2D.

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study.

The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired ß cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments.

Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study.

BACKGROUND: The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D. METHODS: Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts. RESULTS: We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling. CONCLUSIONS: Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.

Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals.

Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict epigenome features from DNA sequence - to support inference concerning the regulatory effects of disease-associated variants. Here, we evaluate the advantages of training convolutional neural network (CNN) models on a broad set of epigenomic features collected in a single disease-relevant tissue - pancreatic islets in the case of type 2 diabetes (T2D) - as opposed to models trained on multiple human tissues. We report convergence of CNN-based metrics of regulatory function with conventional approaches to variant prioritization - genetic fine-mapping and regulatory annotation enrichment. We demonstrate that CNN-based analyses can refine association signals at T2D-associated loci and provide experimental validation for one such signal. We anticipate that these approaches will become routine in downstream analyses of GWAS.

Analysis of Differentiation Protocols Defines a Common Pancreatic Progenitor Molecular Signature and Guides Refinement of Endocrine Differentiation.

Several distinct differentiation protocols for deriving pancreatic progenitors (PPs) from human pluripotent stem cells have been described, but it remains to be shown how similar the PPs are across protocols and how well they resemble their in vivo counterparts. Here, we evaluated three differentiation protocols, performed RNA and assay for transposase-accessible chromatin using sequencing on isolated PPs derived with these, and compared them with fetal human pancreas populations. This enabled us to define a shared transcriptional and epigenomic signature of the PPs, including several genes not previously implicated in pancreas development. Furthermore, we identified a significant and previously unappreciated cross-protocol variation of the PPs through multi-omics analysis and demonstrate how such information can be applied to refine differentiation protocols for derivation of insulin-producing beta-like cells. Together, our study highlights the importance of a detailed characterization of defined cell populations derived from distinct differentiation protocols and provides a valuable resource for exploring human pancreatic development.

NKX6.1 induced pluripotent stem cell reporter lines for isolation and analysis of functionally relevant neuronal and pancreas populations.

Recent studies have reported significant advances in the differentiation of human pluripotent stem cells to clinically relevant cell types such as the insulin producing beta-like cells and motor neurons. However, many of the current differentiation protocols lead to heterogeneous cell cultures containing cell types other than the targeted cell fate. Genetically modified human pluripotent stem cells reporting the expression of specific genes are of great value for differentiation protocol optimization and for the purification of relevant cell populations from heterogeneous cell cultures. Here we present the generation of human induced pluripotent stem cell (iPSC) lines with a GFP reporter inserted in the endogenous NKX6.1 locus. Characterization of the reporter lines demonstrated faithful GFP labelling of NKX6.1 expression during pancreas and motor neuron differentiation. Cell sorting and gene expression profiling by RNA sequencing revealed that NKX6.1-positive cells from pancreatic differentiations closely resemble human beta cells. Furthermore, functional characterization of the isolated cells demonstrated that glucose-stimulated insulin secretion is mainly confined to the NKX6.1-positive cells. We expect that the NKX6.1-GFP iPSC lines and the results presented here will contribute to the further refinement of differentiation protocols and characterization of hPSC-derived beta cells and motor neurons for disease modelling and cell replacement therapies.

Patterns of differential gene expression in a cellular model of human islet development, and relationship to type 2 diabetes predisposition.

AIMS/HYPOTHESIS: Most type 2 diabetes-associated genetic variants identified via genome-wide association studies (GWASs) appear to act via the pancreatic islet. Observed defects in insulin secretion could result from an impact of these variants on islet development and/or the function of mature islets. Most functional studies have focused on the latter, given limitations regarding access to human fetal islet tissue. Capitalising upon advances in in vitro differentiation, we characterised the transcriptomes of human induced pluripotent stem cell (iPSC) lines differentiated along the pancreatic endocrine lineage, and explored the contribution of altered islet development to the pathogenesis of type 2 diabetes. METHODS: We performed whole-transcriptome RNA sequencing of human iPSC lines from three independent donors, at baseline and at seven subsequent stages during in vitro islet differentiation. Differentially expressed genes (q < 0.01, log2 fold change [FC] > 1) were assigned to the stages at which they were most markedly upregulated. We used these data to characterise upstream transcription factors directing different stages of development, and to explore the relationship between RNA expression profiles and genes mapping to type 2 diabetes GWAS signals. RESULTS: We identified 9409 differentially expressed genes across all stages, including many known markers of islet development. Integration of differential expression data with information on transcription factor motifs highlighted the potential contribution of REST to islet development. Over 70% of genes mapping within type 2 diabetes-associated credible intervals showed peak differential expression during islet development, and type 2 diabetes GWAS loci of largest effect (including TCF7L2; log2FC = 1.2; q = 8.5 × 10-10) were notably enriched in genes differentially expressed at the posterior foregut stage (q = 0.002), as calculated by gene set enrichment analyses. In a complementary analysis of enrichment, genes differentially expressed in the final, beta-like cell stage of in vitro differentiation were significantly enriched (hypergeometric test, permuted p value <0.05) for genes within the credible intervals of type 2 diabetes GWAS loci. CONCLUSIONS/INTERPRETATION: The present study characterises RNA expression profiles during human islet differentiation, identifies potential transcriptional regulators of the differentiation process, and suggests that the inherited predisposition to type 2 diabetes is partly mediated through modulation of islet development. DATA AVAILABILITY: Sequence data for this study has been deposited at the European Genome-phenome Archive (EGA), under accession number EGAS00001002721.

Correction to: Dual RNA-seq reveals viral infections in asthmatic children without respiratory illness which are associated with changes in the airway transcriptome.

In our recent article [1], it has come to our attention that the sample labels are not consistent between Table 1, the data labels deposited in the Sequence Read Archive, and Additional file 1: Table S2. We are therefore providing an updated Additional file 1: Table S2 so identical samples now have the same label.

ROP: dumpster diving in RNA-sequencing to find the source of 1 trillion reads across diverse adult human tissues.

High-throughput RNA-sequencing (RNA-seq) technologies provide an unprecedented opportunity to explore the individual transcriptome. Unmapped reads are a large and often overlooked output of standard RNA-seq analyses. Here, we present Read Origin Protocol (ROP), a tool for discovering the source of all reads originating from complex RNA molecules. We apply ROP to samples across 2630 individuals from 54 diverse human tissues. Our approach can account for 99.9% of 1 trillion reads of various read length. Additionally, we use ROP to investigate the functional mechanisms underlying connections between the immune system, microbiome, and disease. ROP is freely available at https://github.com/smangul1/rop/wiki .

Cadherin-26 (CDH26) regulates airway epithelial cell cytoskeletal structure and polarity.

Polarization of the airway epithelial cells (AECs) in the airway lumen is critical to the proper function of the mucociliary escalator and maintenance of lung health, but the cellular requirements for polarization of AECs are poorly understood. Using human AECs and cell lines, we demonstrate that cadherin-26 (CDH26) is abundantly expressed in differentiated AECs, localizes to the cell apices near ciliary membranes, and has functional cadherin domains with homotypic binding. We find a unique and non-redundant role for CDH26, previously uncharacterized in AECs, in regulation of cell-cell contact and cell integrity through maintaining cytoskeletal structures. Overexpression of CDH26 in cells with a fibroblastoid phenotype increases contact inhibition and promotes monolayer formation and cortical actin structures. CDH26 expression is also important for localization of planar cell polarity proteins. Knockdown of CDH26 in AECs results in loss of cortical actin and disruption of CRB3 and other proteins associated with apical polarity. Together, our findings uncover previously unrecognized functions for CDH26 in the maintenance of actin cytoskeleton and apicobasal polarity of AECs.

Genes Associated with Pancreas Development and Function Maintain Open Chromatin in iPSCs Generated from Human Pancreatic Beta Cells.

Current in vitro islet differentiation protocols suffer from heterogeneity and low efficiency. Induced pluripotent stem cells (iPSCs) derived from pancreatic beta cells (BiPSCs) preferentially differentiate toward endocrine pancreas-like cells versus those from fibroblasts (FiPSCs). We interrogated genome-wide open chromatin in BiPSCs and FiPSCs via ATAC-seq and identified ∼8.3k significant, differential open chromatin sites (DOCS) between the two iPSC subtypes (false discovery rate [FDR] < 0.05). DOCS where chromatin was more accessible in BiPSCs (Bi-DOCS) were significantly enriched for known regulators of endodermal development, including bivalent and weak enhancers, and FOXA2 binding sites (FDR < 0.05). Bi-DOCS were associated with genes related to pancreas development and beta-cell function, including transcription factors mutated in monogenic diabetes (PDX1, NKX2-2, HNF1A; FDR < 0.05). Moreover, Bi-DOCS correlated with enhanced gene expression in BiPSC-derived definitive endoderm and pancreatic progenitor cells. Bi-DOCS therefore highlight genes and pathways governing islet-lineage commitment, which can be exploited for differentiation protocol optimization, diabetes disease modeling, and therapeutic purposes.

Dual RNA-seq reveals viral infections in asthmatic children without respiratory illness which are associated with changes in the airway transcriptome.

BACKGROUND: Respiratory illness caused by viral infection is associated with the development and exacerbation of childhood asthma. Little is known about the effects of respiratory viral infections in the absence of illness. Using quantitative PCR (qPCR) for common respiratory viruses and for two genes known to be highly upregulated in viral infections (CCL8/CXCL11), we screened 92 asthmatic and 69 healthy children without illness for respiratory virus infections. RESULTS: We found 21 viral qPCR-positive and 2 suspected virus-infected subjects with high expression of CCL8/CXCL11. We applied a dual RNA-seq workflow to these subjects, together with 25 viral qPCR-negative subjects, to compare qPCR with sequencing-based virus detection and to generate the airway transcriptome for analysis. RNA-seq virus detection achieved 86% sensitivity when compared to qPCR-based screening. We detected additional respiratory viruses in the two CCL8/CXCL11-high subjects and in two of the qPCR-negative subjects. Viral read counts varied widely and were used to stratify subjects into Virus-High and Virus-Low groups. Examination of the host airway transcriptome found that the Virus-High group was characterized by immune cell airway infiltration, downregulation of cilia genes, and dampening of type 2 inflammation. Even the Virus-Low group was differentiated from the No-Virus group by 100 genes, some involved in eIF2 signaling. CONCLUSIONS: Respiratory virus infection without illness is not innocuous but may determine the airway function of these subjects by driving immune cell airway infiltration, cellular remodeling, and alteration of asthmogenic gene expression.

IL1RL1 asthma risk variants regulate airway type 2 inflammation.

Genome-wide association studies of asthma have identified genetic variants in the IL1RL1 gene, but the molecular mechanisms conferring risk are unknown. IL1RL1 encodes the ST2 receptor (ST2L) for IL-33 and an inhibitory decoy receptor (sST2). IL-33 promotes type 2 inflammation, which is present in some but not all asthmatics. We find that two single nucleotide polymorphisms (SNPs) in IL1RL1 - rs1420101 and rs11685480 - are strongly associated with plasma sST2 levels, though neither is an expression quantitative trait locus (eQTL) in whole blood. Rather, rs1420101 and rs11685480 mark eQTLs in airway epithelial cells and distal lung parenchyma, respectively. We find that the genetically determined plasma sST2 reservoir, derived from the lung, neutralizes IL-33 activity, and these eQTL SNPs additively increase the risk of airway type 2 inflammation among asthmatics. These risk variants define a population of asthmatics at risk of IL-33-driven type 2 inflammation.

Alternative splicing of interleukin-33 and type 2 inflammation in asthma.

Type 2 inflammation occurs in a large subgroup of asthmatics, and novel cytokine-directed therapies are being developed to treat this population. In mouse models, interleukin-33 (IL-33) activates lung resident innate lymphoid type 2 cells (ILC2s) to initiate airway type 2 inflammation. In human asthma, which is chronic and difficult to model, the role of IL-33 and the target cells responsible for persistent type 2 inflammation remain undefined. Full-length IL-33 is a nuclear protein and may function as an "alarmin" during cell death, a process that is uncommon in chronic stable asthma. We demonstrate a previously unidentified mechanism of IL-33 activity that involves alternative transcript splicing, which may operate in stable asthma. In human airway epithelial cells, alternative splicing of the IL-33 transcript is consistently present, and the deletion of exons 3 and 4 (Δ exon 3,4) confers cytoplasmic localization and facilitates extracellular secretion, while retaining signaling capacity. In nonexacerbating asthmatics, the expression of Δ exon 3,4 is strongly associated with airway type 2 inflammation, whereas full-length IL-33 is not. To further define the extracellular role of IL-33 in stable asthma, we sought to determine the cellular targets of its activity. Comprehensive flow cytometry and RNA sequencing of sputum cells suggest basophils and mast cells, not ILC2s, are the cellular sources of type 2 cytokines in chronic asthma. We conclude that IL-33 isoforms activate basophils and mast cells to drive type 2 inflammation in chronic stable asthma, and novel IL-33 inhibitors will need to block all biologically active isoforms.

Airway Progenitor Clone Formation Is Enhanced by Y-27632-Dependent Changes in the Transcriptome.

The application of conditional reprogramming culture (CRC) methods to nasal airway epithelial cells would allow more wide-spread incorporation of primary airway epithelial culture models into complex lung disease research. In this study, we adapted the CRC method to nasal airway epithelial cells, investigated the growth advantages afforded by this technique over standard culture methods, and determined the cellular and molecular basis of CRC cell culture effects. We found that the CRC method allowed the production of 7.1 × 10(10) cells after 4 passages, approximately 379 times more cells than were generated by the standard bronchial epithelial growth media (BEGM) method. These nasal airway epithelial cells expressed normal basal cell markers and could be induced to form a mucociliary epithelium. Progenitor cell frequency was significantly higher using the CRC method in comparison to the standard culture method, and progenitor cell maintenance was dependent on addition of the Rho-kinase inhibitor Y-27632. Whole-transcriptome sequencing analysis demonstrated widespread gene expression changes in Y-27632-treated basal cells. We found that Y-27632 treatment altered expression of genes fundamental to the formation of the basal cell cytoskeleton, cell-cell junctions, and cell-extracellular matrix (ECM) interactions. Importantly, we found that Y-27632 treatment up-regulated expression of unique basal cell intermediate filament and desmosomal genes. Conversely, Y-27632 down-regulated multiple families of protease/antiprotease genes involved in ECM remodeling. We conclude that Y-27632 fundamentally alters cell-cell and cell-ECM interactions, which preserves basal progenitor cells and allows greater cell amplification.

Kinome-wide decoding of network-attacking mutations rewiring cancer signaling.

Cancer cells acquire pathological phenotypes through accumulation of mutations that perturb signaling networks. However, global analysis of these events is currently limited. Here, we identify six types of network-attacking mutations (NAMs), including changes in kinase and SH2 modulation, network rewiring, and the genesis and extinction of phosphorylation sites. We developed a computational platform (ReKINect) to identify NAMs and systematically interpreted the exomes and quantitative (phospho-)proteomes of five ovarian cancer cell lines and the global cancer genome repository. We identified and experimentally validated several NAMs, including PKCγ M501I and PKD1 D665N, which encode specificity switches analogous to the appearance of kinases de novo within the kinome. We discover mutant molecular logic gates, a drift toward phospho-threonine signaling, weakening of phosphorylation motifs, and kinase-inactivating hotspots in cancer. Our method pinpoints functional NAMs, scales with the complexity of cancer genomes and cell signaling, and may enhance our capability to therapeutically target tumor-specific networks.