RESUMO
Proteotoxicity is a contributor to the development of type 2 diabetes (T2D), but it is unknown whether protein misfolding in T2D is generalized or has special features. Here, we report a robust accumulation of misfolded proteins within the mitochondria of human pancreatic islets in T2D and elucidate its impact on ß cell viability. Surprisingly, quantitative proteomics studies of protein aggregates reveal that human islets from donors with T2D have a signature more closely resembling mitochondrial rather than ER protein misfolding. The matrix protease LonP1 and its chaperone partner mtHSP70 were among the proteins enriched in protein aggregates. Deletion of LONP1 in mice yields mitochondrial protein misfolding and reduced respiratory function, ultimately leading to ß cell apoptosis and hyperglycemia. Intriguingly, LONP1 gain of function ameliorates mitochondrial protein misfolding and restores human ß cell survival following glucolipotoxicity via a protease-independent effect requiring LONP1-mtHSP70 chaperone activity. Thus, LONP1 promotes ß cell survival and prevents hyperglycemia by facilitating mitochondrial protein folding. These observations may open novel insights into the nature of impaired proteostasis on ß cell loss in the pathogenesis of T2D that could be considered as future therapeutic targets.
RESUMO
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.
Assuntos
Aprendizado Profundo , Diabetes Mellitus Tipo 2 , Elementos Facilitadores Genéticos , Ilhotas Pancreáticas , Diabetes Mellitus Tipo 2/genética , Diabetes Mellitus Tipo 2/metabolismo , Diabetes Mellitus Tipo 2/patologia , Ilhotas Pancreáticas/metabolismo , Ilhotas Pancreáticas/patologia , Variação Genética , Humanos , Simulação por ComputadorRESUMO
The Diversity Outbred (DO) mice and their inbred founders are widely used models of human disease. However, although the genetic diversity of these mice has been well documented, their epigenetic diversity has not. Epigenetic modifications, such as histone modifications and DNA methylation, are important regulators of gene expression and, as such, are a critical mechanistic link between genotype and phenotype. Therefore, creating a map of epigenetic modifications in the DO mice and their founders is an important step toward understanding mechanisms of gene regulation and the link to disease in this widely used resource. To this end, we performed a strain survey of epigenetic modifications in hepatocytes of the DO founders. We surveyed four histone modifications (H3K4me1, H3K4me3, H3K27me3, and H3K27ac), as well as DNA methylation. We used ChromHMM to identify 14 chromatin states, each of which represents a distinct combination of the four histone modifications. We found that the epigenetic landscape is highly variable across the DO founders and is associated with variation in gene expression across strains. We found that epigenetic state imputed into a population of DO mice recapitulated the association with gene expression seen in the founders, suggesting that both histone modifications and DNA methylation are highly heritable mechanisms of gene expression regulation. We illustrate how DO gene expression can be aligned with inbred epigenetic states to identify putative cis-regulatory regions. Finally, we provide a data resource that documents strain-specific variation in the chromatin state and DNA methylation in hepatocytes across nine widely used strains of laboratory mice.
Assuntos
Metilação de DNA , Histonas , Humanos , Camundongos , Animais , Histonas/genética , Histonas/metabolismo , Regiões Promotoras Genéticas , Cromatina/genética , Epigênese Genética , Código das Histonas , Camundongos Endogâmicos , Expressão GênicaRESUMO
Cis-Regulatory elements (cis-REs) include promoters, enhancers, and insulators that regulate gene expression programs via binding of transcription factors. ATAC-seq technology effectively identifies active cis-REs in a given cell type (including from single cells) by mapping accessible chromatin at base-pair resolution. However, these maps are not immediately useful for inferring specific functions of cis-REs. For this purpose, we developed a deep learning framework (CoRE-ATAC) with novel data encoders that integrate DNA sequence (reference or personal genotypes) with ATAC-seq cut sites and read pileups. CoRE-ATAC was trained on 4 cell types (n = 6 samples/replicates) and accurately predicted known cis-RE functions from 7 cell types (n = 40 samples) that were not used in model training (mean average precision = 0.80, mean F1 score = 0.70). CoRE-ATAC enhancer predictions from 19 human islet samples coincided with genetically modulated gain/loss of enhancer activity, which was confirmed by massively parallel reporter assays (MPRAs). Finally, CoRE-ATAC effectively inferred cis-RE function from aggregate single nucleus ATAC-seq (snATAC) data from human blood-derived immune cells that overlapped with known functional annotations in sorted immune cells, which established the efficacy of these models to study cis-RE functions of rare cells without the need for cell sorting. ATAC-seq maps from primary human cells reveal individual- and cell-specific variation in cis-RE activity. CoRE-ATAC increases the functional resolution of these maps, a critical step for studying regulatory disruptions behind diseases.
Assuntos
Sequenciamento de Cromatina por Imunoprecipitação/métodos , Aprendizado Profundo , Sequências Reguladoras de Ácido Nucleico/genética , Análise de Célula Única/métodos , Células Cultivadas , Biologia Computacional , DNA/análise , DNA/genética , Humanos , Ilhotas Pancreáticas/citologia , Monócitos/citologiaRESUMO
Genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs) at >250 loci in the human genome to type 2 diabetes (T2D) risk. For each locus, identifying the functional variant(s) among multiple SNPs in high linkage disequilibrium is critical to understand molecular mechanisms underlying T2D genetic risk. Using massively parallel reporter assays (MPRA), we test the cis-regulatory effects of SNPs associated with T2D and altered in vivo islet chromatin accessibility in MIN6 ß cells under steady state and pathophysiologic endoplasmic reticulum (ER) stress conditions. We identify 1,982/6,621 (29.9%) SNP-containing elements that activate transcription in MIN6 and 879 SNP alleles that modulate MPRA activity. Multiple T2D-associated SNPs alter the activity of short interspersed nuclear element (SINE)-containing elements that are strongly induced by ER stress. We identify 220 functional variants at 104 T2D association signals, narrowing 54 signals to a single candidate SNP. Together, this study identifies elements driving ß cell steady state and ER stress-responsive transcriptional activation, nominates causal T2D SNPs, and uncovers potential roles for repetitive elements in ß cell transcriptional stress response and T2D genetics.
Assuntos
Diabetes Mellitus Tipo 2/genética , Estresse do Retículo Endoplasmático/genética , Células Secretoras de Insulina/patologia , Polimorfismo de Nucleotídeo Único , Ativação Transcricional/genética , Alelos , Animais , Linhagem Celular , Cromatina/metabolismo , Diabetes Mellitus Tipo 2/patologia , Estudo de Associação Genômica Ampla , Humanos , Camundongos , Locos de Características Quantitativas , Elementos Nucleotídeos Curtos e Dispersos/genéticaRESUMO
Detecting multiplets in single nucleus (sn)ATAC-seq data is challenging due to data sparsity and limited dynamic range. AMULET (ATAC-seq MULtiplet Estimation Tool) enumerates regions with greater than two uniquely aligned reads across the genome to effectively detect multiplets. We evaluate the method by generating snATAC-seq data in the human blood and pancreatic islet samples. AMULET has high precision, estimated via donor-based multiplexing, and high recall, estimated via simulated multiplets, compared to alternatives and identifies multiplets most effectively when a certain read depth of 25K median valid reads per nucleus is achieved.
Assuntos
Sequenciamento de Cromatina por Imunoprecipitação , Software , Idoso , DNA/genética , Humanos , Leucócitos Mononucleares/metabolismo , Funções Verossimilhança , Transposases/metabolismoRESUMO
ß cells may participate and contribute to their own demise during Type 1 diabetes (T1D). Here we report a role of their expression of Tet2 in regulating immune killing. Tet2 is induced in murine and human ß cells with inflammation but its expression is reduced in surviving ß cells. Tet2-KO mice that receive WT bone marrow transplants develop insulitis but not diabetes and islet infiltrates do not eliminate ß cells even though immune cells from the mice can transfer diabetes to NOD/scid recipients. Tet2-KO recipients are protected from transfer of disease by diabetogenic immune cells.Tet2-KO ß cells show reduced expression of IFNγ-induced inflammatory genes that are needed to activate diabetogenic T cells. Here we show that Tet2 regulates pathologic interactions between ß cells and immune cells and controls damaging inflammatory pathways. Our data suggests that eliminating TET2 in ß cells may reduce activating pathologic immune cells and killing of ß cells.
Assuntos
Proteínas de Ligação a DNA/metabolismo , Diabetes Mellitus Tipo 1/patologia , Inflamação/patologia , Células Secretoras de Insulina/metabolismo , Células Secretoras de Insulina/patologia , Proteínas Proto-Oncogênicas/metabolismo , Animais , Sequência de Bases , Citotoxicidade Imunológica , Diabetes Mellitus Tipo 1/genética , Diabetes Mellitus Tipo 1/imunologia , Dioxigenases , Progressão da Doença , Feminino , Humanos , Imunidade , Inflamação/genética , Camundongos Endogâmicos C57BL , Camundongos Endogâmicos NOD , Linfócitos T/imunologia , Transcrição GênicaRESUMO
Effective interpretation of genome function and genetic variation requires a shift from epigenetic mapping of cis-regulatory elements (CREs) to characterization of endogenous function. We developed hybridization chain reaction fluorescence in situ hybridization coupled with flow cytometry (HCR-FlowFISH), a broadly applicable approach to characterize CRISPR-perturbed CREs via accurate quantification of native transcripts, alongside CRISPR activity screen analysis (CASA), a hierarchical Bayesian model to quantify CRE activity. Across >325,000 perturbations, we provide evidence that CREs can regulate multiple genes, skip over the nearest gene and display activating and/or silencing effects. At the cholesterol-level-associated FADS locus, we combine endogenous screens with reporter assays to exhaustively characterize multiple genome-wide association signals, functionally nominate causal variants and, importantly, identify their target genes.
Assuntos
Hibridização in Situ Fluorescente/métodos , Sequências Reguladoras de Ácido Nucleico , Proteínas Adaptadoras de Transdução de Sinal/genética , Teorema de Bayes , Repetições Palindrômicas Curtas Agrupadas e Regularmente Espaçadas , Dessaturase de Ácido Graxo Delta-5 , Desoxirribonuclease I/genética , Desoxirribonuclease I/metabolismo , Ácidos Graxos Dessaturases/genética , Citometria de Fluxo , Fator de Transcrição GATA1/genética , Humanos , Células K562 , Proteínas com Domínio LIM/genética , Modelos Genéticos , Polimorfismo de Nucleotídeo Único , Proteínas Proto-Oncogênicas/genética , Locos de Características Quantitativas , RNA Guia de CinetoplastídeosRESUMO
Identifying the tissue-specific molecular signatures of active regulatory elements is critical to understand gene regulatory mechanisms. Here, we identify transcription start sites (TSS) using cap analysis of gene expression (CAGE) across 57 human pancreatic islet samples. We identify 9,954 reproducible CAGE tag clusters (TCs), â¼20% of which are islet specific and occur mostly distal to known gene TSS. We integrated islet CAGE data with histone modification and chromatin accessibility profiles to identify epigenomic signatures of transcription initiation. Using a massively parallel reporter assay, we validated the transcriptional enhancer activity for 2,279 of 3,378 (â¼68%) tested islet CAGE elements (5% false discovery rate). TCs within accessible enhancers show higher enrichment to overlap type 2 diabetes genome-wide association study (GWAS) signals than existing islet annotations, which emphasizes the utility of mapping CAGE profiles in disease-relevant tissue. This work provides a high-resolution map of transcriptional initiation in human pancreatic islets with utility for dissecting active enhancers at GWAS loci.
Assuntos
Ilhotas Pancreáticas/fisiologia , Sítio de Iniciação de Transcrição , Elementos Facilitadores Genéticos , Estudo de Associação Genômica Ampla , Humanos , Polimorfismo de Nucleotídeo Único , Locos de Características QuantitativasRESUMO
Immune cell activation assays have been widely used for immune monitoring and for understanding disease mechanisms. However, these assays are typically limited in scope. A holistic study of circulating immune cell responses to different activators is lacking. Here we developed a cost-effective high-throughput multiplexed single-cell RNA-seq combined with epitope tagging (CITE-seq) to determine how classic activators of T cells (anti-CD3 coupled with anti-CD28) or monocytes (LPS) alter the cell composition and transcriptional profiles of peripheral blood mononuclear cells (PBMCs) from healthy human donors. Anti-CD3/CD28 treatment activated all classes of lymphocytes either directly (T cells) or indirectly (B and NK cells) but reduced monocyte numbers. Activated T and NK cells expressed senescence and effector molecules, whereas activated B cells transcriptionally resembled autoimmune disease- or age-associated B cells (e.g., CD11c, T-bet). In contrast, LPS specifically targeted monocytes and induced two main states: early activation characterized by the expression of chemoattractants and a later pro-inflammatory state characterized by expression of effector molecules. These data provide a foundation for future immune activation studies with single cell technologies (https://czi-pbmc-cite-seq.jax.org/).
Assuntos
Leucócitos Mononucleares/imunologia , Ativação Linfocitária/genética , Adulto , Anticorpos Monoclonais/imunologia , Antígenos CD28/imunologia , Complexo CD3/imunologia , Células Cultivadas , Senescência Celular/genética , Quimiotaxia/genética , Feminino , Perfilação da Expressão Gênica , Ensaios de Triagem em Larga Escala , Humanos , Imunização , Lipopolissacarídeos/imunologia , Masculino , Análise de Célula Única , Adulto JovemRESUMO
Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using data from 420 donors. We find: (a) 7741 cis-eQTLs in islets with a replication rate across 44 GTEx tissues between 40% and 73%; (b) marked overlap between islet cis-eQTL signals and active regulatory sequences in islets, with reduced eQTL effect size observed in the stretch enhancers most strongly implicated in GWAS signal location; (c) enrichment of islet cis-eQTL signals with T2D risk variants identified in genome-wide association studies; and (d) colocalization between 47 islet cis-eQTLs and variants influencing T2D or glycemic traits, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in disease relevant tissues.
Assuntos
Glicemia/genética , Diabetes Mellitus Tipo 2/genética , Predisposição Genética para Doença , Ilhotas Pancreáticas/metabolismo , Locos de Características Quantitativas , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Animais , Glicemia/metabolismo , Linhagem Celular Tumoral , Estudos de Coortes , Diabetes Mellitus Tipo 2/sangue , Diacilglicerol Quinase/genética , Diacilglicerol Quinase/metabolismo , Elementos Facilitadores Genéticos , Feminino , Regulação da Expressão Gênica , Estudo de Associação Genômica Ampla , Humanos , Masculino , Camundongos , Pessoa de Meia-Idade , Polimorfismo de Nucleotídeo Único , RNA-Seq , Análise de Sequência de DNA , Proteína 2 Semelhante ao Fator 7 de Transcrição/genética , Proteína 2 Semelhante ao Fator 7 de Transcrição/metabolismo , Adulto JovemRESUMO
BACKGROUND: Pancreatic Islets of Langerhans are heterogeneous tissues consisting of multiple endocrine cell types that carry out distinct yet coordinated roles to regulate blood glucose homeostasis. Islet dysfunction and specifically failure of the beta cells to secrete adequate insulin are known precursors to type 2 diabetes (T2D) onset. However, the exact genetic, (epi)genomic, and environmental mechanisms that contribute to islet failure, and ultimately to T2D pathogenesis, require further elucidation. SCOPE OF REVIEW: This review summarizes efforts and advances in dissection of the complex genetic underpinnings of islet function and resilience in T2D pathogenesis. In this review, we will highlight results of the latest T2D genome-wide association study (GWAS) and discuss how these data are being combined with clinical measures in patients to uncover putative T2D subtypes and with functional (epi)genomic studies in islets to understand the genetic programming of islet cell identity, function, and adaptation. Finally, we discuss new and important opportunities to address major knowledge gaps in our understanding of islet (dys)function in T2D risk and progression. MAJOR CONCLUSIONS: Genetic variation exerts clear effects on the islet epigenome, regulatory element usage, and gene expression. Future (epi)genomic comparative analyses between T2D and normal islets should incorporate genetics to distinguish patient-specific from disease-specific differences. Incorporating genotype information into future analyses and studies will also enable more precise insights into the molecular genetics of islet deficiency and failure in T2D risk, and should ultimately contribute to a stratified view of T2D and more precise treatment strategies. Islet cellular heterogeneity continues to remain a challenge for understanding the associations between islet failure and T2D development. Further efforts to obtain purified islet cell type populations and determine the specific genetic and environmental effects on each will help address this. Beyond observation of islets at steady state conditions, more research of islet stress and stimulation responses are needed to understand the transition of these tissues from a healthy to diseased state. Together, focusing on these objectives will provide more opportunities to prevent, treat, and manage T2D.
Assuntos
Diabetes Mellitus Tipo 2/genética , Diabetes Mellitus Tipo 2/metabolismo , Epigênese Genética/genética , Células Secretoras de Insulina/metabolismo , Animais , HumanosRESUMO
EndoC-ßH1 is emerging as a critical human ß cell model to study the genetic and environmental etiologies of ß cell (dys)function and diabetes. Comprehensive knowledge of its molecular landscape is lacking, yet required, for effective use of this model. Here, we report chromosomal (spectral karyotyping), genetic (genotyping), epigenomic (ChIP-seq and ATAC-seq), chromatin interaction (Hi-C and Pol2 ChIA-PET), and transcriptomic (RNA-seq and miRNA-seq) maps of EndoC-ßH1. Analyses of these maps define known (e.g., PDX1 and ISL1) and putative (e.g., PCSK1 and mir-375) ß cell-specific transcriptional cis-regulatory networks and identify allelic effects on cis-regulatory element use. Importantly, comparison with maps generated in primary human islets and/or ß cells indicates preservation of chromatin looping but also highlights chromosomal aberrations and fetal genomic signatures in EndoC-ßH1. Together, these maps, and a web application we created for their exploration, provide important tools for the design of experiments to probe and manipulate the genetic programs governing ß cell identity and (dys)function in diabetes.
Assuntos
Redes Reguladoras de Genes/genética , Células Secretoras de Insulina/metabolismo , Linhagem Celular , HumanosRESUMO
Epigenomic signatures from histone marks and transcription factor (TF)-binding sites have been used to annotate putative gene regulatory regions. However, a direct comparison of these diverse annotations is missing, and it is unclear how genetic variation within these annotations affects gene expression. Here, we compare five widely used annotations of active regulatory elements that represent high densities of one or more relevant epigenomic marks-"super" and "typical" (nonsuper) enhancers, stretch enhancers, high-occupancy target (HOT) regions, and broad domains-across the four matched human cell types for which they are available. We observe that stretch and super enhancers cover cell type-specific enhancer "chromatin states," whereas HOT regions and broad domains comprise more ubiquitous promoter states. Expression quantitative trait loci (eQTL) in stretch enhancers have significantly smaller effect sizes compared to those in HOT regions. Strikingly, chromatin accessibility QTL in stretch enhancers have significantly larger effect sizes compared to those in HOT regions. These observations suggest that stretch enhancers could harbor genetically primed chromatin to enable changes in TF binding, possibly to drive cell type-specific responses to environmental stimuli. Our results suggest that current eQTL studies are relatively underpowered or could lack the appropriate environmental context to detect genetic effects in the most cell type-specific "regulatory annotations," which likely contributes to infrequent colocalization of eQTL with genome-wide association study signals.
Assuntos
Elementos Facilitadores Genéticos , Locos de Características Quantitativas , Ativação Transcricional , Cromatina/genética , Cromatina/metabolismo , Células-Tronco Embrionárias/metabolismo , Células Hep G2 , Humanos , Especificidade de Órgãos , Fatores de Transcrição/metabolismoRESUMO
Transcription factor (TF) footprinting uncovers putative protein-DNA binding via combined analyses of chromatin accessibility patterns and their underlying TF sequence motifs. TF footprints are frequently used to identify TFs that regulate activities of cell/condition-specific genomic regions (target loci) in comparison to control regions (background loci) using standard enrichment tests. However, there is a strong association between the chromatin accessibility level and the GC content of a locus and the number and types of TF footprints that can be detected at this site. Traditional enrichment tests (e.g. hypergeometric) do not account for this bias and inflate false positive associations. Therefore, we developed a novel post-processing method, Bias-free Footprint Enrichment Test (BiFET), that corrects for the biases arising from the differences in chromatin accessibility levels and GC contents between target and background loci in footprint enrichment analyses. We applied BiFET on TF footprint calls obtained from EndoC-ßH1 ATAC-seq samples using three different algorithms (CENTIPEDE, HINT-BC and PIQ) and showed BiFET's ability to increase power and reduce false positive rate when compared to hypergeometric test. Furthermore, we used BiFET to study TF footprints from human PBMC and pancreatic islet ATAC-seq samples to show its utility to identify putative TFs associated with cell-type-specific loci.
Assuntos
Análise de Sequência de DNA/métodos , Fatores de Transcrição/metabolismo , Algoritmos , Composição de Bases , Viés , Linhagem Celular , DNA/química , Humanos , Motivos de Nucleotídeos , SoftwareRESUMO
Enhancers are cis-acting sequences that regulate transcription rates of their target genes in a cell-specific manner and harbor disease-associated sequence variants in cognate cell types. Many complex diseases are associated with enhancer malfunction, necessitating the discovery and study of enhancers from clinical samples. Assay for Transposase Accessible Chromatin (ATAC-seq) technology can interrogate chromatin accessibility from small cell numbers and facilitate studying enhancers in pathologies. However, on average, ~35% of open chromatin regions (OCRs) from ATAC-seq samples map to enhancers. We developed a neural network-based model, Predicting Enhancers from ATAC-Seq data (PEAS), to effectively infer enhancers from clinical ATAC-seq samples by extracting ATAC-seq data features and integrating these with sequence-related features (e.g., GC ratio). PEAS recapitulated ChromHMM-defined enhancers in CD14+ monocytes, CD4+ T cells, GM12878, peripheral blood mononuclear cells, and pancreatic islets. PEAS models trained on these 5 cell types effectively predicted enhancers in four cell types that are not used in model training (EndoC-ßH1, naïve CD8+ T, MCF7, and K562 cells). Finally, PEAS inferred individual-specific enhancers from 19 islet ATAC-seq samples and revealed variability in enhancer activity across individuals, including those driven by genetic differences. PEAS is an easy-to-use tool developed to study enhancers in pathologies by taking advantage of the increasing number of clinical epigenomes.
Assuntos
Sítios de Ligação , Elementos Facilitadores Genéticos , Redes Neurais de Computação , Transposases/metabolismo , Linhagem Celular , Biologia Computacional/métodos , Perfilação da Expressão Gênica , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Curva ROC , Sensibilidade e Especificidade , Análise de Sequência de DNA , Transcriptoma , Transposases/químicaRESUMO
Type 2 diabetes (T2D) is a complex disorder in which both genetic and environmental risk factors contribute to islet dysfunction and failure. Genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs), most of which are noncoding, in >200 loci to islet dysfunction and T2D. Identification of the putative causal variants and their target genes and whether they lead to gain or loss of function remains challenging. Here, we profiled chromatin accessibility in pancreatic islet samples from 19 genotyped individuals and identified 2,949 SNPs associated with in vivo cis-regulatory element use (i.e., chromatin accessibility quantitative trait loci [caQTL]). Among the caQTLs tested (n = 13) using luciferase reporter assays in MIN6 ß-cells, more than half exhibited effects on enhancer activity that were consistent with in vivo chromatin accessibility changes. Importantly, islet caQTL analysis nominated putative causal SNPs in 13 T2D-associated GWAS loci, linking 7 and 6 T2D risk alleles, respectively, to gain or loss of in vivo chromatin accessibility. By investigating the effect of genetic variants on chromatin accessibility in islets, this study is an important step forward in translating T2D-associated GWAS SNP into functional molecular consequences.