Biology subjects

Stitzel, M. L.

Publications and source records attributed to Stitzel, M. L..

At least 19 recordsLinked to original sources

bioRxiv2026

PanKbase Integrated Single-Cell Map: A Comprehensive Atlas of Human Pancreatic Islets

Single-cell RNA sequencing (scRNA-seq) of human pancreatic islet tissue is a powerful tool for investigating type 1 diabetes (T1D). However, individual datasets are limited in size and fragmented across donors, laboratories, and experimental conditions. To address this, we constructed a comprehensive, integrated scRNA-seq atlas of isolated human pancreatic islets by collating publicly available data generated from tissue provided by resources including the Human Pancreas Analysis Program, the Integrated Islet Distribution Program, and Prodo Labs. Systematic quality controls were implemented to select high-quality samples, reads, and cells. During integration, we accounted for important variables such as age, sex, body mass index, origin study, treatments, islet distribution resources, and sequencing chemistry. Our single-cell atlas comprises 191 high-quality samples from 140 donors (59 female, 81 male) across five phenotypic groups: no diabetes (controls, n=69), autoantibody positivity without diabetes (n=12), pre-diabetes (n=11), T1D (n=12), and type 2 diabetes (T2D) (n=36). In total, the atlas contains 448,935 cells, capturing 13 distinct populations, including alpha cells (43.3%) and beta cells (26.8%), as well as groups such as immune cells (0.6%). Publicly available at www.pankbase.org, this atlas provides a platform for hypothesis-driven investigation of diabetes pathophysiology and, given rigorous quality control, is well-suited for downstream machine-learning applications. Article HighlightsO_LICurrent scRNA-seq datasets of pancreatic islet tissue are limited in size and scattered across donors, laboratories, and experimental conditions, underscoring the need for a consolidated resource. C_LIO_LIWe harmonized datasets from multiple sources to build a comprehensive single-cell map of isolated human pancreatic islets. C_LIO_LIOur atlas captures 448,935 cells from 191 high-quality samples across 140 donors and multiple phenotypic groups, identifying 13 distinct cell populations. C_LIO_LIAvailable at www.pankbase.org, the atlas provides a scalable, rigorously curated platform to support hypothesis-driven diabetes research and can enable a broad range of downstream computational applications. C_LI

genomics↗

bioRxiv2026

Lifestyle intervention is associated with attenuation of ER stress/inflammation and enhancement of naive immune cell identity in older adults with metabolic disease

Chronic inflammation and cellular stress are hallmarks of aging, obesity, and type 2 diabetes (T2D), but whether these programs can be modulated by lifestyle intervention in late life, particularly in the presence of established metabolic disease, remain unknown. We profiled circulating immune cells from older adults with obesity and T2D (ages 66-83 years; n = 9) before and after a 6-month lifestyle intervention combining caloric restriction with exercise training. Participants showed substantial weight loss ([~]7%) alongside improvements in glycemic control, insulin sensitivity, and physical performance. Longitudinal single-cell transcriptomic and epigenomic profiling identified two major changes. First, intervention was associated with downregulation of inflammatory and endoplasmic reticulum (ER) stress transcriptional programs, with the most pronounced effects observed in CD14+ monocytes. DDIT3 (CHOP) was transcriptionally and epigenetically downregulated and its inferred regulatory network encompassed multiple inflammatory mediators. Second, naive CD4+ T, naive Treg, and naive B cells exhibited an upregulation of naive cell identity genes, with naiveness scores increasing after intervention, which declines with age in an independent healthy adult cohort. Together, these findings suggest that lifestyle intervention is associated with coordinated remodeling of both innate and adaptive immune compartments in older adults, revealing substantial plasticity of the aging immune system especially targeting ER stress, inflammation, and naive lymphocyte identity programs.

immunology↗

bioRxiv2025

Modeling metabolic disease susceptibility and resilience in genetically diverse mice

Model organisms have provided critical insights into the basic biology of metabolic disorders, however, one of the greatest limitations to translation has been the absence of the genetic heterogeneity that is characteristic of human populations. We examined metabolic health across three genetically diverse mouse strains fed control (low fat, no sucrose) or unhealthy (high fat, high sucrose) diets and observed a wide range of metabolic responses from overt type 2 diabetes in NZO/HlLtJ mice, to obesity and glucose intolerance in C57BL/6J mice, to complete resilience in CAST/EiJ mice. Analysis of multi-tissue gene expression revealed strain- and tissue-specific responses to diet, with strongest responses in white adipose tissue and pancreatic islets. In pancreatic islets, diet response was limited to just NZO mice, which showed high levels of inflammation and associated {beta} cell dysfunction. Adipose tissue was responsive to diet across all three strains and revealed both common and strain-specific changes in inflammatory and metabolic pathways. Using a complementary outbred mouse resource, we mapped genetic loci associated with strain-specific diet responses, including a monocyte regulatory locus on mChr19. This multi-strain approach to modeling metabolic disease revealed a prominent role of white adipose tissue and lipid-associated inflammation in the determination of individual disease risk in response to unhealthy diets.

physiology↗

bioRxiv2025

Single-cell decoding of human islet cell type-specific alterations in type 2 diabetes reveals converging genetic- and state-driven β-cell gene expression defects

Pancreatic islets maintain glucose homeostasis through coordinated action of their constituent endocrine and affiliate cell types and are central to type 2 diabetes (T2D) genetics and pathophysiology. Our understanding of robust human islet cell type-specific alterations in T2D remains limited. Here, we report comprehensive single cell transcriptome profiling of 245,878 human islet cells from a 48-donor cohort spanning non-diabetic (ND), pre-diabetic (PD), and T2D states, identifying 14 distinct cell types detected in every donor from each glycemic state. Cohort analysis reveals [~]25-30% loss of functional beta cell mass in T2D vs. ND or PD donors resulting from (1) reduced total beta cell numbers/proportions and (2) reciprocal loss of high function and gain of senescent {beta}-cell subpopulations. We identify in T2D {beta}-cells 511 differentially expressed genes (DEGs), including new (66.5%) and validated genes (e.g., FXYD2, SLC2A2, SYT1), and significant neuronal transmission and vitamin A metabolism pathway alterations. Importantly, we demonstrate newly identified DEG roles in human {beta}-cell viability and/or insulin secretion and link 47 DEGs to diabetes-relevant phenotypes in knockout mice, implicating them as potential causal islet dysfunction genes. Additionally, we nominate as candidate T2D causal genes and therapeutic targets 27 DEGs for which T2D genetic risk variants (GWAS SNPs) and pathophysiology (T2D vs. ND) exert concordant expression effects. We provide this freely accessible atlas for data exploration, analysis, and hypothesis testing. Together, this study provides new genomic resources for and insights into T2D pathophysiology and human islet dysfunction.

genomics↗

bioRxiv2024

LONP1 regulation of mitochondrial protein folding provides insight into beta cell failure in type 2 diabetes

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 {beta} 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 {beta} cell apoptosis and hyperglycemia. Intriguingly, LONP1 gain of function ameliorates mitochondrial protein misfolding and restores human {beta} cell survival following glucolipotoxicity via a protease-independent effect requiring LONP1-mtHSP70 chaperone activity. Thus, LONP1 promotes {beta} cell survival and prevents hyperglycemia by facilitating mitochondrial protein folding. These observations may open novel insights into the nature of impaired proteostasis on {beta} cell loss in the pathogenesis of T2D that could be considered as future therapeutic targets.

cell biology↗

bioRxiv2024

Comparative Multi-omic Mapping of Human Pancreatic Islet Endoplasmic Reticulum and Cytokine Stress Responses Provides Insights into Type 2 Diabetes Genetics

Endoplasmic reticulum (ER) and inflammatory stress responses are two pathophysiologic factors contributing to islet dysfunction and failure in Type 2 Diabetes (T2D). However, how human islet cells respond to these stressors and whether T2D-associated genetic variants modulate these responses is unknown. To fill this knowledge gap, we profiled transcriptional (RNA-seq) and epigenetic (ATAC-seq) remodeling in human islets exposed to ex vivo ER (thapsigargin) or inflammatory (IL-1{beta}+IFN-{gamma}) stress. 5,427 genes ([~]32%) were associated with stress responses; most were stressor-specific, including upregulation of genes mediating unfolded protein response (e.g. DDIT3, ATF4) and NFKB signaling (e.g. NFKB1, NFKBIA) in ER stress and cytokine-induced inflammation respectively. Islet single-cell RNA-seq profiling revealed strong but heterogeneous beta cell ER stress responses, including a distinct beta cell subset that highly expressed apoptotic genes. Epigenetic profiling uncovered 14,968 stress-responsive cis-regulatory elements (CREs; [~]14%), the majority of which were stressor-specific, and revealed increased accessibility at binding sites of transcription factors that were induced upon stress (e.g. ATF4 for ER stress, IRF8 for cytokine-induced inflammation). Eighty-six stress-responsive CREs overlapped known T2D-associated variants, including 20 residing within CREs that were more accessible upon ER stress. Among these, we linked the rs6917676 T2D risk allele (T) to increased in vivo accessibility of an islet ER stress-responsive CRE and allele-specific beta cell nuclear factor binding in vitro. We showed that MAP3K5, the only ER stress-responsive gene in this locus, promotes beta cell apoptosis. Consistent with its pro-apoptotic and putative diabetogenic roles, MAP3K5 expression inversely correlated with beta cell abundance in human islets and was induced in beta cells from T2D donors. Together, this study provides new genome-wide insights into human islet stress responses and putative mechanisms of T2D genetic variants.

genomics↗

bioRxiv2022

Variation in histone configurations correlates with gene expression across nine inbred strains of mice

It is well established that epigenetic features, such as histone modifications and DNA methylation, are associated with variation in gene expression across cell types. Less well known is the extent to which epigenetic states vary across genetically diverse individuals, and whether such variation corresponds to inter-individual variation in gene expression. To investigate genetically driven variation in epigenetics, we conducted a survey of epigenetic modifications and gene expression in hepatocytes of nine inbred mouse strains. We surveyed four histone modifications (H3K4me1, H3K4me3, H3K27me3, and H3K27ac), and DNA methylation. We used ChromHMM to identify 14 chromatin states, each of which represented a distinct combination of the four histone modifications. We found that chromatin states varied widely across the nine strains and that epigenetic state was strongly correlated with local gene expression. We replicated this correspondence between chromatin state and gene expression in an independent population of Diversity Outbred mice in which we imputed local chromatin state. In contrast, we found that DNA methylation did not vary across the inbred strains and was not correlated with variation in gene expression in DO mice. This work suggests that chromatin state is highly influenced by local genotype and may be a primary mode through which expression quantitative trait loci (eQTLs) are mediated. Through examples, we demonstrate that naturally occurring chromatin state variation, in conjunction with gene expression, can aid in functional annotation of the mouse genome. Finally, we provide a data resource that documents variation in chromatin state in hepatocytes across genetically distinct mice.

genomics↗

bioRxiv2022

Retrograde mitochondrial signaling governs the identity and maturity of metabolic tissues

Mitochondrial damage is a hallmark of metabolic diseases, including diabetes and metabolic dysfunction-associated steatotic liver disease, yet the consequences of impaired mitochondria in metabolic tissues are often unclear. Here, we report that dysfunctional mitochondrial quality control engages a retrograde (mitonuclear) signaling program that impairs cellular identity and maturity across multiple metabolic tissues. Surprisingly, we demonstrate that defects in the mitochondrial quality control machinery, which we observe in pancreatic {beta} cells of humans with type 2 diabetes, cause reductions of {beta} cell mass due to dedifferentiation, rather than apoptosis. Utilizing transcriptomic profiling, lineage tracing, and assessments of chromatin accessibility, we find that targeted deficiency anywhere in the mitochondrial quality control pathway (e.g., genome integrity, dynamics, or turnover) activate the mitochondrial integrated stress response and promote cellular immaturity in {beta} cells, hepatocytes, and brown adipocytes. Intriguingly, pharmacologic blockade of mitochondrial retrograde signaling in vivo restores {beta} cell mass and identity to ameliorate hyperglycemia following mitochondrial damage. Thus, we observe that a shared mitochondrial retrograde response controls cellular identity across metabolic tissues and may be a promising target to treat or prevent metabolic disorders.

cell biology↗

bioRxiv2021

A read count-based method to detect multiplets and their cellular origins from snATAC-seq data

Similar to other droplet-based single cell assays, single nucleus ATAC-seq (snATAC-seq) data harbor multiplets that confound downstream analyses. Detecting multiplets in snATAC-seq data is particularly challenging due to its sparsity and trinary nature (0 reads: closed chromatin, 1: open in one allele, 2: open in both alleles), yet offers a unique opportunity to infer multiplets when >2 uniquely aligned reads are observed at multiple loci. Here, we implemented the first read count-based multiplet detection method, ATAC-DoubletDetector, that detects multiplets independently of cell-type. Using PBMC and pancreatic islet datasets, ATAC-DoubletDetector captured simulated heterotypic multiplets (different cell-types) with [~]0.60 recall, showing [~]24% improvement over state of the art. ATAC-DoubletDetector detected homotypic multiplets with [~]0.61 recall, representing the first method to detect multiplets originating from the same cell type. Using our novel clustering-based algorithm, multiplets were annotated to their cellular origins with [~]85% accuracy. Application of ATAC-DoubletDetector will improve downstream analysis of snATAC-seq.

bioinformatics↗

bioRxiv2020

Single cell analysis of blood mononuclear cells stimulated through CD3 and CD28 shows collateral activation of B and NK cells and demise of monocytes

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/). Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

immunology↗

bioRxiv2020

Tet2 Controls Beta cells Responses to Inflammation in Type 1 Diabetes

{beta} cells may participate and contribute to their own demise during Type 1 diabetes (T1D). We identified a novel role of Tet2 in regulating immune killing of {beta} cells. Tet2 is induced in murine and human {beta} cells with inflammation but its expression is reduced in surviving {beta} cells. Tet2-KO mice that receive WT bone marrow transplants develop insulitis but not diabetes and islet infiltrates do not eliminate {beta} cells even though immune cells from the mice can transfer diabetes to NOD/scid recipients. Tet2-KO {beta} cells show reduced expression of inflammatory genes, associated with closed transcription factor binding sites. Tet2-KO recipients are protected from transfer of disease by diabetogenic immune cells. We conclude that Tet2 regulates pathologic interactions between {beta} cells and immune cells and controls intrinsic protective pathways. Modulating TET2 may enable survival of {beta} cells or their replacements in the setting of pathologic immune cells.

immunology↗

bioRxiv2020

CoRE-ATAC: A Deep Learning model for the functional Classification of Regulatory Elements from single cell and bulk ATAC-seq data

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). 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.Author Summary Non-coding DNA sequences serve different functional roles to regulate gene expression. For these sequences to be active, they must be accessible for proteins and other factors to bind in order to carry out a specific regulatory function. Even so, mutations within these sequences or other regulatory events may modulate their activity or regulatory function. It is therefore critical that we identify these non-coding sequences and their specific regulatory function to fully understand how specific genes are regulated. Current sequencing technologies allow us to identify accessible sequences via chromatin accessibility maps from low cell numbers, enabling the study of clinical samples. However, determining the functional role associated with these sequences remains a challenge. Towards this goal, we harnessed the power of deep learning to unravel the intricacies of chromatin accessibility maps to infer their associated gene regulatory functions. We demonstrate that our method, CoRE-ATAC, can infer regulatory functions in diverse cell types, captures activity differences modulated by genetic mutations, and can be applied to accessibility maps of single cell clusters to infer regulatory functions of rare cell populations. These inferences will further our understanding of how genes are regulated and enable the study of these mechanisms as they relate to disease.Competing Interest StatementThe authors have declared no competing interest.View Full Text

bioinformatics↗

bioRxiv2020

Functional characterization of thousands of type 2 diabetes-associated and chromatin-modulating variants under steady state and endoplasmic reticulum stress

A major goal in functional genomics and complex disease genetics is to identify functional cis-regulatory elements (CREs) and single nucleotide polymorphisms (SNPs) altering CRE activity in disease-relevant cell types and environmental conditions. We tested >13,000 sequences containing each allele of 6,628 SNPs associated with altered in vivo chromatin accessibility in human islets and/or type 2 diabetes risk (T2D GWAS SNPs) for transcriptional activity in {beta} cell under steady state and endoplasmic reticulum (ER) stress conditions using the massively parallel reporter assay (MPRA). Approximately 30% (n=1,983) of putative CREs were active in at least one condition. SNP allelic effects on in vitro MPRA activity strongly correlated with their effects on in vivo islet chromatin accessibility (Pearson r=0.52), i.e., alleles associated with increased chromatin accessibility exhibited higher MPRA activity. Importantly, MPRA identified 220/2500 T2D GWAS SNPs, representing 104 distinct association signals, that significantly altered transcriptional activity in {beta} cells. This study has thus identified functional {beta} cell transcription-activating sequences with in vivo relevance, uncovered regulatory features that modulate transcriptional activity in {beta} cells under steady state and ER stress conditions, and substantially expanded the set of putative functional variants that modulate transcriptional activity in {beta} cells from thousands of genetically-linked T2D GWAS SNPs.

genomics↗

bioRxiv2019

Integrating enhancer RNA signatures with diverse omics data identifies characteristics of transcription initiation in pancreatic islets

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), ~20% of which are islet-specific and occur mostly distal to known gene TSSs. 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 validate transcriptional enhancer activity (5% FDR) for 2,279 of 3,378 (~68%) tested islet CAGE elements. 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 functional enhancers at GWAS loci.

genomics↗

bioRxiv2019

Influence of genetic variants on gene expression in human pancreatic islets - implications for type 2 diabetes

Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.

genomics↗

bioRxiv2018

EndoC-βH1 multi-genomic profiling defines gene regulatory programs governing human pancreatic β cell identity and function

EndoC-{beta}H1 is emerging as a critical human beta cell model to study the genetic and environmental etiologies of beta cell function, especially in the context of diabetes. Comprehensive knowledge of its molecular landscape is lacking yet required to fully take advantage of this model. Here, we report extensive chromosomal (spectral karyotyping), genetic (genotyping), epigenetic (ChIP-seq, ATAC-seq), chromatin interaction (Hi-C, Pol2 ChIA-PET), and transcriptomic (RNA-seq, miRNA-seq) maps of this cell model. Integrated analyses of these maps define known (e.g., PDX1, ISL1) and putative (e.g., PCSK1, mir-375) beta cell-specific chromatin interactions and transcriptional cis-regulatory networks, and identify allelic effects on cis-regulatory element use and expression.\n\nImportantly, comparative analyses with maps generated in primary human islets/beta cells indicate substantial preservation of chromatin looping, but also highlight chromosomal heterogeneity and fetal genomic signatures in EndoC-{beta}H1. Together, these maps, and an interactive web application we have created for their exploration, provide important tools for the broad community in the design and success of experiments to probe and manipulate the genetic programs governing beta cell identity and (dys)function in diabetes.

genomics↗

bioRxiv2018

BiFET: A Bias-free Transcription Factor Footprint Enrichment Test

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 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 human EndoC-{beta}H1 ATAC-seq samples using three different algorithms (CENTIPEDE, HINT-BC, and PIQ) and showed BiFETs 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.

genomics↗

bioRxiv2017

Chromatin accessibility profiling uncovers genetic- and T2D disease state-associated changes in cis-regulatory element use in human islets

Genetic and environmental factors both contribute to islet dysfunction and failure, resulting in type 2 diabetes (T2D). The islet epigenome integrates these cues and can be remodeled by genetic and environmental variation. However, our knowledge of how genetic variants and T2D disease state alter human islet chromatin landscape and cis-regulatory element (RE) use is lacking. To fill this gap, we profiled and analyzed human islet chromatin accessibility maps from 19 genotyped individuals (5 with T2D) using ATAC-seq technology. Chromatin accessibility quantitative trait locus (caQTL) analyses identified 3001 sequence variants (FDR<10%) altering putative cis-RE use/activity. Islet caQTL were significantly and specifically enriched in islet stretch enhancers and islet-specific transcription factor binding motifs, such as FOXA2, NKX6.1, RFX5/6 and PDX1. Importantly, these analyses identified putative functional single nucleotide variants (SNVs) in 13 T2D-associated GWAS loci, including those previously associated with altered ZMIZ1, MTNR1B, RNF6, and ADCY5 islet expression, and linked the risk alleles to increased (n=8) or decreased (n=5) islet chromatin accessibility. Luciferase reporter assays confirmed allelic differences in cis-RE activity for 5/9 caQTL sequences tested, including a T2D-associated SNV in the IL20RA locus. Comparison of T2D and non-diabetic islets revealed 1882 open chromatin sites exhibiting T2D-associated chromatin accessibility changes (FDR<10%). Together, this study provides new insights into genetic variant and T2D disease state effects on islet cis-RE use and serves as an important resource to identify putative functional variants in T2D-and islet dysfunction-associated GWAS loci and link their risk allele to in vivo loss or gain of chromatin accessibility.

genomics↗