ATAC-seq Peaks Research Articles

Inherited and De Novo Genetic Risk for Autism Impacts Shared Networks.

We performed a comprehensive assessment of rareinherited variation in autism spectrum disorder (ASD) by analyzing whole-genome sequences of 2,308 individuals from families with multiple affected children. We implicate 69 genes in ASD risk, including 24 passing genome-wide Bonferroni correction and 16 new ASD risk genes, most supported by rare inherited variants, a substantial extensionof previousfindings. Biological pathways enriched for genes harboring inherited variants represent cytoskeletal organization and ion transport, which are distinct from pathways implicated in previous studies. Nevertheless, the de novo and inherited genes contribute to a common protein-protein interaction network. We also identified structural variants (SVs) affecting non-coding regions, implicating recurrent deletions in the promoters of DLG2 and NR3C2. Loss of nr3c2 function in zebrafish disrupts sleep and social function, overlapping with human ASD-related phenotypes. These data support the utility of studying multiplex families in ASD and are available through the Hartwell Autism Research and Technology portal.

ATAC-seq reveals alterations in open chromatin in pancreatic islets from subjects with type 2 diabetes

Impaired insulin secretion from pancreatic islets is a hallmark of type 2 diabetes (T2D). Altered chromatin structure may contribute to the disease. We therefore studied the impact of T2D on open chromatin in human pancreatic islets. We used assay for transposase-accessible chromatin using sequencing (ATAC-seq) to profile open chromatin in islets from T2D and non-diabetic donors. We identified 57,105 and 53,284 ATAC-seq peaks representing open chromatin regions in islets of non-diabetic and diabetic donors, respectively. The majority of ATAC-seq peaks mapped near transcription start sites. Additionally, peaks were enriched in enhancer regions and in regions where islet-specific transcription factors (TFs), e.g. FOXA2, MAFB, NKX2.2, NKX6.1 and PDX1, bind. Islet ATAC-seq peaks overlap with 13 SNPs associated with T2D (e.g. rs7903146, rs2237897, rs757209, rs11708067 and rs878521 near TCF7L2, KCNQ1, HNF1B, ADCY5 and GCK, respectively) and with additional 67 SNPs in LD with known T2D SNPs (e.g. SNPs annotated to GIPR, KCNJ11, GLIS3, IGF2BP2, FTO and PPARG). There was enrichment of open chromatin regions near highly expressed genes in human islets. Moreover, 1,078 open chromatin peaks, annotated to 898 genes, differed in prevalence between diabetic and non-diabetic islet donors. Some of these peaks are annotated to candidate genes for T2D and islet dysfunction (e.g. HHEX, HMGA2, GLIS3, MTNR1B and PARK2) and some overlap with SNPs associated with T2D (e.g. rs3821943 near WFS1 and rs508419 near ANK1). Enhancer regions and motifs specific to key TFs including BACH2, FOXO1, FOXA2, NEUROD1, MAFA and PDX1 were enriched in differential islet ATAC-seq peaks of T2D versus non-diabetic donors. Our study provides new understanding into how T2D alters the chromatin landscape, and thereby accessibility for TFs and gene expression, in human pancreatic islets.

Human iPSC-Derived Retinal Pigment Epithelium: A Model System for Prioritizing and Functionally Characterizing Causal Variants at AMD Risk Loci.

SummaryWe evaluate whether human induced pluripotent stem cell-derived retinal pigment epithelium (iPSC-RPE) cells can be used to prioritize and functionally characterize causal variants at age-related macular degeneration (AMD) risk loci. We generated iPSC-RPE from six subjects and show that they have morphological and molecular characteristics similar to those of native RPE. We generated RNA-seq, ATAC-seq, and H3K27ac ChIP-seq data and observed high similarity in gene expression and enriched transcription factor motif profiles between iPSC-RPE and human fetal RPE. We performed fine mapping of AMD risk loci by integrating molecular data from the iPSC-RPE, adult retina, and adult RPE, which identified rs943080 as the probable causal variant at VEGFA. We show that rs943080 is associated with altered chromatin accessibility of a distal ATAC-seq peak, decreased overall gene expression of VEGFA, and allele-specific expression of a non-coding transcript. Our study thus provides a potential mechanism underlying the association of the VEGFA locus with AMD.

HSCs Transition from Fetal to Adult Transcriptional States through Gradual Epigenomic Reprogramming That Begins Shortly after Birth

Fetal and adult hematopoietic stem cells (HSCs) have distinct gene expression profiles and distinct functional properties. Differences between fetal and adult HSCs have been extensively characterized, but the mechanisms that regulate the transition from fetal to adult identity remain unclear. These mechanisms are important because they underlie temporal changes in self-renewal, lineage commitment and leukemogenesis. In mice, HSCs are generally thought to transition from fetal- to adult-like states between 3 and 4 weeks after birth. The transition is thought to be regulated by a cell-intrinsic program, and it is thought to be rapid. This model raises an important mechanistic question. How do HSCs record developmental time so that they can transition from fetal to adult states on cue?To address this question, we performed single cell RNA-seq on HSCs and committed hematopoietic progenitors (HPCs) at various pre- and post-natal time points. We used quadratic programming to calculate adult and fetal identity scores for each HSC at each age. Our analyses revealed several surprising findings. HSCs began transitioning from fetal to adult transcriptional states shortly after birth rather than at 3 weeks after birth. This was well before they became quiescent, and it was independent of location (i.e. P0 liver and bone progenitors had similar transcriptional states). The fetal to adult transition appeared graded rather than bi-modal (Figure 1). In other words, HSCs became incrementally more “adult-like” with each passing week, and all HSCs had relatively synchronous changes in their fetal and adult identity scores. Similar patterns were observed in HPCs.The graded transition of HSCs from fetal to adult identity raises the question of how such a transition could be encoded within the cis-regulatory architecture of the genome. To answer this question, we performed ATAC-seq and ChIP-seq (H3K4me1 and H3K27ac) to identify fetal- and adult-specific enhancers. We performed the assays in highly purified HSCs and HPCs, and we obtained similar results for each cell population. Adult-specific enhancers (adult-specific ATAC-seq peaks with overlapping H3K4me1 peaks) were enriched near genes that are more highly expressed in adult HSCs than in fetal HSCs, as one might expect. The putative enhancer regions were highly enriched for ETS, RUNX1 and AP-1 binding sites. When we evaluated these enhancers at E16.5, P7, P14 and P21, we found that ATAC-seq peak heights gradually increased as development progressed. To achieve this pattern at a population level, individual HSCs must commission enhancers in a non-uniform manner. Otherwise, fetal to adult peak-height changes would be binary.Our data suggest a simple mechanism for coordinating slow, graded, changes in HSC identity. As time passes, or as HSCs divide, individual enhancers may flip, stochastically but irreversibly, from fetal- to adult-like states. In this model, the transition from fetal to adult identity is not guided by hard-wired developmental cues. Rather, the rate of change depends on the stochastic probability of activating adult enhancers and inactivating fetal enhancers. This system differs from other developmental circuits wherein well-defined inductive signals activate super-enhancers and feed-forward loops to induce robust, uniform changes in cell identity. A stochastic circuit is simple, but it leads to epigenomic and transcriptional heterogeneity that has implications for lineage priming and leukemia initiation, particularly in children. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Dissecting the Epigenetic Landscape of Smoldering, Newly Diagnosed and Relapsed Multiple Myeloma Revealed IRAK3 As a Marker of Disease Progression

Introduction. Multiple myeloma (MM) is a complex and heterogeneous malignancy of plasma cells that has two precursor states: monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). MGUS and SMM are asymptomatic states that eventually give rise to overt MM, with some patients progressing, while others do not. Recent studies in MM pathobiology have highlighted epigenetic alterations that contribute to the onset, progression and heterogeneity of MM. Global hypomethylation of DNA, including tumor suppressor genes, and hypermethylation of B-cell specific enhancers, abnormal histone methylation patterns due to the overexpression of histone methyltransferases such as MMSET, and deregulation of non-coding RNAs along with mutations in different classes of chromatin modulators underline a potential for epigenetic biomarkers in disease prognosis and treatment. This study aimed to define epigenetic pathways that lead to the dynamic regulation of gene expression in MM pathogenesis.Methods. We performed ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) and RNA-seq on 10 MM cell lines and CD138+ plasma cells isolated from bone marrow aspirates of 3 healthy donors, 9 SMM, 8 newly diagnosed MM (NDMM) and 9 relapsed (RRMM) patients. ATAC-seq reads were trimmed of adapters, aligned to hg19 using bowtie2, and filtered for mapping quality >=Q30 using the ENCODE ATAC-seq pipeline. Reads mapping to promoter regions, defined as -400 to +250 bases from a refseq transcription start site, were counted using bedtools for each sample. Promoter read counts were then normalized by the total number of reads in promoters in the sample, scaled to 1 million total reads, and converted to log10(x+1) space.Results. To characterize the epigenetic contribution to disease progression in MM, we first identified accessible promoter regions in normal plasma cells (NPC), SMM, NDMM and RRMM patients and found regions displaying differential accessibility in MM progression. Next, we intersected the list of differential accessible regions (DARs) with matched transcriptome data and observed two main clusters: genes with unaltered transcription profiles and genes in which the dynamics of open chromatin regions (OCRs) correlated with gene expression. Transcriptomic analysis revealed that a large portion of the differentially expressed (DE) genes in SMM remain DE in NDMM as compared to NPCs (882 genes out of 1642 and 1150 DE genes in SMM and NDMM, respectively). Those genes were significantly enriched for pathways like epithelial mesenchymal transition, cell cycle checkpoints and mitosis, KRAS signaling and interleukin-JAK-STAT pathways. To investigate the genes that behaved differently among the stages of disease, we looked at differential accessibility and expression in NDMM and SMM samples, and integrated them with Whole-Genome Bisulfite-Sequencing and 450K DNA-methylation data from MM patients and healthy donors (BLUEPRINT). This analysis led to the identification of novel genes in MM progression, such as the transcriptional repressor ZNF254 and IRAK3, a negative regulator of the TLR/IL1R signaling pathway. Although gene expression data for these genes showed comparable mRNA levels in SMM and NPCs, followed by a significant decrease in NDMM/ RRMM, ATAC-seq revealed a striking drop in promoter accessibility in SMM, NDMM and RRMM cases. Comparison of ATAC-seq peaks to DNA methylation and ChIP-seq data revealed that the altered OCR of IRAK3 is actually hypermethylated in MM patients and marked by H3K4me3, a marker of active promoters, in MM cell lines. Hypermethylation of IRAK3 has been described in hepatocellular carcinoma, where it is associated with poor prognosis. Together, our data suggest that the identified IRAK3 OCR may act as a bivalent domain that loses accessibility in the precursor states and gains DNA methylation in MM progression. Hence, IRAK3 methylation could be a novel prognostic marker in MM.Conclusion. We have generated a global epigenetic map of primary tumors from patients at the smoldering, newly diagnosed and relapsed/refractory stage of multiple myeloma. Integrative analysis of ATAC-seq data with DNA methylome, transcriptome and whole-genome map of active and repressive histone marks in our study led to the identification of IRAK3 as a novel epigenetic biomarker of disease progression. DisclosuresLicht:Celgene: Research Funding. Ghobrial:Takeda: Consultancy; BMS: Consultancy; Celgene: Consultancy; Janssen: Consultancy.

Young genes have distinct gene structure, epigenetic profiles, and transcriptional regulation.

Species-specific, new, or “orphan” genes account for 10%–30% of eukaryotic genomes. Although initially considered to have limited function, an increasing number of orphan genes have been shown to provide important phenotypic innovation. How new genes acquire regulatory sequences for proper temporal and spatial expression is unknown. Orphan gene regulation may rely in part on origination in open chromatin adjacent to preexisting promoters, although this has not yet been assessed by genome-wide analysis of chromatin states. Here, we combine taxon-rich nematode phylogenies with Iso-Seq, RNA-seq, ChIP-seq, and ATAC-seq to identify the gene structure and epigenetic signature of orphan genes in the satellite model nematode Pristionchus pacificus. Consistent with previous findings, we find young genes are shorter, contain fewer exons, and are on average less strongly expressed than older genes. However, the subset of orphan genes that are expressed exhibit distinct chromatin states from similarly expressed conserved genes. Orphan gene transcription is determined by a lack of repressive histone modifications, confirming long-held hypotheses that open chromatin is important for new gene formation. Yet orphan gene start sites more closely resemble enhancers defined by H3K4me1, H3K27ac, and ATAC-seq peaks, in contrast to conserved genes that exhibit traditional promoters defined by H3K4me3 and H3K27ac. Although the majority of orphan genes are located on chromosome arms that contain high recombination rates and repressive histone marks, strongly expressed orphan genes are more randomly distributed. Our results support a model of new gene origination by rare integration into open chromatin near enhancers.

Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia

Schizophrenia genome-wide association studies have identified >150 regions of the genome associated with disease risk, yet there is little evidence that coding mutations contribute to this disorder. To explore the mechanism of non-coding regulatory elements in schizophrenia, we performed ATAC-seq on adult prefrontal cortex brain samples from 135 individuals with schizophrenia and 137 controls, and identified 118,152 ATAC-seq peaks. These accessible chromatin regions in the brain are highly enriched for schizophrenia SNP heritability. Accessible chromatin regions that overlap evolutionarily conserved regions exhibit an even higher heritability enrichment, indicating that sequence conservation can further refine functional risk variants. We identify few differences in chromatin accessibility between cases and controls, in contrast to thousands of age-related differential accessible chromatin regions. Altogether, we characterize chromatin accessibility in the human prefrontal cortex, the effect of schizophrenia and age on chromatin accessibility, and provide evidence that our dataset will allow for fine mapping of risk variants.

GUAVA: A Graphical User Interface for the Analysis and Visualization of ATAC-seq Data.

Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq) is a powerful genomic technology that is used for the global mapping and analysis of open chromatin regions. However, for users to process and analyze such data they either have to use a number of complicated bioinformatic tools or attempt to use the currently available ATAC-seq analysis software, which are not very user friendly and lack visualization of the ATAC-seq results. Because of these issues, biologists with minimal bioinformatics background who wish to process and analyze their own ATAC-seq data by themselves will find these tasks difficult and ultimately will need to seek help from bioinformatics experts. Moreover, none of the available tools provide complete solution for ATAC-seq data analysis. Therefore, to enable non-programming researchers to analyze ATAC-seq data on their own, we developed a tool called Graphical User interface for the Analysis and Visualization of ATAC-seq data (GUAVA). GUAVA is a standalone software that provides users with a seamless solution from beginning to end including adapter trimming, read mapping, the identification and differential analysis of ATAC-seq peaks, functional annotation, and the visualization of ATAC-seq results. We believe GUAVA will be a highly useful and time-saving tool for analyzing ATAC-seq data for biologists with minimal or no bioinformatics background. Since GUAVA can also operate through command-line, it can easily be integrated into existing pipelines, thus providing flexibility to users with computational experience.

Abstract 4318: Identifying drivers of SMARCA4/BRG1-deficient SCCOHT tumorigenesis by integrative multi-omic analysis

Abstract Over 94% of small cell carcinomas of the ovary, hypercalcemic type (SCCOHT), a rare and aggressive form of ovarian cancer, have mutations and concomitant protein loss in SMARCA4 (BRG1), one of the two mutually exclusive ATPases of the SWI/SNF chromatin remodeling complex. SCCOHT tumors rarely have secondary mutations, making them an excellent model for understanding the role BRG1 and SWI/SNF complexes play in tumor suppression. We hypothesize that BRG1 loss drives SCCOHT tumorigenesis by altering chromatin accessibility and gene expression. We have previously shown that BRG1 re-expression in SCCOHT cell lines suppresses cell growth and induces an elongated, neuronal-like morphology. To identify the top genes and transcription factors driving SCCOHT tumorigenesis, we performed ATAC-seq and RNA-seq in a SCCOHT cell line +/- BRG1 re-expression. BRG1 re-expression increased overall chromatin accessibly, shown by an increase in the number of ATAC-seq peaks. ATAC peaks gained following BRG1 re-expression were enriched in transcription factor binding motifs from FOS/JUN/AP-1, TEAD, and SOX family members. RNA-seq analysis demonstrated that BRG1 re-expression upregulated more genes than those downregulated, consistent with the increase in ATAC-seq peaks. Preliminary pathway analysis identified gene enrichments in epithelial-mesenchymal transition pathway and extracellular matrix remodeling following BRG1 re-expression, consistent with the observed morphology change. Cell types enrichment analysis (xCell) identified a shift from a mesenchymal stem cell-like gene signature in the control SCCOHT cells to an epithelial cell-like gene signature following BRG1 re-expression, further suggesting a possible mesenchymal-epithelial transition in SCCOHT cells after BRG1 re-expression. Future studies include integration of the ATAC/RNA-seq data to further identify correlations between gene expression changes and enriched transcription factor binding motifs, integrative ChIP-seq analysis for BRG1 following re-expression, and proteomic analyses. These studies will uncover the key genes, proteins, and transcription factors affected by BRG1 loss in other adult cancers, provide insight into BRG1's role in SCCOHT tumorigenesis, and potentially yield novel therapeutic targets. Citation Format: Krystal A. Orlando, Jesse R. Raab, Jessica D. Lang, William P. Hendricks, Yemin Wang, David G. Huntsman, Jeffrey M. Trent, Joel S. Parker, Bernard E. Weissman. Identifying drivers of SMARCA4/BRG1-deficient SCCOHT tumorigenesis by integrative multi-omic analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4318.

829 The EDC enhancer 923 is required for Ivl, Smcp, and Lce6a gene expression and chromatin accessibility

The mechanisms by which gene expression is activated at the chromatin level are poorly understood. The Epidermal Differentiation Complex (EDC), locus whose genes are expressed upon keratinocyte differentiation, provides a unique opportunity to address this question. Previously we identified a role for the epidermal-specific 923 enhancer in dynamic chromatin remodeling. Here we sought to investigate whether 923 is necessary for EDC activation using CRISPR/Cas9-mediated deletion. 923-/- KO mice (both 923delA and 923delB) appeared phenotypically normal under homeostatic conditions. However, transcriptional profiling of 923delA-/- embryonic skin captured during epidermal development (E14.5–NB) revealed decreased proximal gene expression of involucrin (Ivl), late cornified envelope 6a (Lce6a), and sperm mitochondrial-associated cysteine rich protein (Smcp). The requirement for the 923 enhancer was further validated in 923delB-/- newborn keratinocytes. ATAC-seq in 923delA-/- and wild-type littermate newborn keratinocytes further identified more closed chromatin (fewer ATAC-seq peaks) observed at the 5’ and 3’ ends of the EDC in 923delA-/-, indicating a requirement for the 923 enhancer for chromatin organization at the EDC boundaries. Male fertility defects associated with decreased 923 enhancer target gene Smcp expression in 923delA-/- male testes were observed with reduced progeny and slower sperm motility. Our genomic study reporting in vivo functional effect for the deletion of an epidermal-specific enhancer, identifies a requirement for 923 in proximal Ivl, Lce6a, and Smcp target gene expression, higher level chromatin accessibility in the EDC, and downstream male fertility function for its Smcp target gene, thus addressing a knowledge gap for enhancer function in chromatin level gene expression.

Integration of ATAC-seq and RNA-seq identifies human alpha cell and beta cell signature genes.

ObjectiveAlthough glucagon-secreting α-cells and insulin-secreting β-cells have opposing functions in regulating plasma glucose levels, the two cell types share a common developmental origin and exhibit overlapping transcriptomes and epigenomes. Notably, destruction of β-cells can stimulate repopulation via transdifferentiation of α-cells, at least in mice, suggesting plasticity between these cell fates. Furthermore, dysfunction of both α- and β-cells contributes to the pathophysiology of type 1 and type 2 diabetes, and β-cell de-differentiation has been proposed to contribute to type 2 diabetes. Our objective was to delineate the molecular properties that maintain islet cell type specification yet allow for cellular plasticity. We hypothesized that correlating cell type-specific transcriptomes with an atlas of open chromatin will identify novel genes and transcriptional regulatory elements such as enhancers involved in α- and β-cell specification and plasticity.MethodsWe sorted human α- and β-cells and performed the “Assay for Transposase-Accessible Chromatin with high throughput sequencing” (ATAC-seq) and mRNA-seq, followed by integrative analysis to identify cell type-selective gene regulatory regions.ResultsWe identified numerous transcripts with either α-cell- or β-cell-selective expression and discovered the cell type-selective open chromatin regions that correlate with these gene activation patterns. We confirmed cell type-selective expression on the protein level for two of the top hits from our screen. The “group specific protein” (GC; or vitamin D binding protein) was restricted to α-cells, while CHODL (chondrolectin) immunoreactivity was only present in β-cells. Furthermore, α-cell- and β-cell-selective ATAC-seq peaks were identified to overlap with known binding sites for islet transcription factors, as well as with single nucleotide polymorphisms (SNPs) previously identified as risk loci for type 2 diabetes.ConclusionsWe have determined the genetic landscape of human α- and β-cells based on chromatin accessibility and transcript levels, which allowed for detection of novel α- and β-cell signature genes not previously known to be expressed in islets. Using fine-mapping of open chromatin, we have identified thousands of potential cis-regulatory elements that operate in an endocrine cell type-specific fashion.

Enhancer Accessibility during Erythropoiesis and Megakaryopoiesis Correlates with Lineage-Specific Gene Expression

Enhancers are epigenetic regulatory modules critical to lineage-specific transcript expression. Understanding the development and maintenance of enhancers will help clarify lineage commitment decisions. The ENCODE Project Consortium used a variety of cell lines to define enhancer regulatory maps. Our goal is to build ENCODE-like enhancer maps for primary mouse hematopoietic cells. To accomplish this we have performed genome-wide open chromatin surveys (Assay for Transposable-Accessible Chromatin [ATACSeq]) and transcriptome analysis (RNASeq) in enriched populations of hematopoietic stem and progenitor cells (LSK), common myeloid progenitors (CMP), megakaryocyte-erythroid progenitors (MEP), and erythroid and megakaryocytic progenitors (CFUE and CFUMeg, respectively). In addition to ATACSeq and RNASeq we performed ChIPSeq in erythroblasts (EB) and megakaryocytes (MEG). Together these data provide a high-quality map of essential enhancers and correlated transcription profiles at specific stages of hematopoiesis.Enhancers are associated with DNase I hypersensitivity and monomethylation at lysine 4 of histone H3 (H3K4me1), while active enhancer regions (AERs) are also acetylated at lysine 27 of histone H3 (H3K27ac). We identified several thousand candidate enhancer regions (cERs) in EB and MEG (Table). More than 70% of cERs also contained the H3K27ac mark and thus were candidate AERs (cAERs). In 90% of cases cAERs were closer to an active transcriptional start site (TSS) than to any other TSS. 23 of these erythroid cAERs were shown to be active in a luciferase assay.We next evaluated the major trends in acquisition and maintenance of cERs during hematopoietic differentiation and their correlation with altered gene expression. We focused on cAERs and examined their appearance and retention in progenitor cells (Table). Almost all cell-specific (97% of EB and 93% of MEG) cAERs are in accessible chromatin as monitored by ATACSeq (HC cAERs). This high degree of correlation allows us to use overlaps with progenitor ATACSeq data to estimate the presence of the cAERs identified in the mature cells. Our initial results show that the mature cell HC cAERs overlap with progenitor cell ATACSeq data (MEP and CMP) is greater for EB cAERs than MEG, suggesting that chromatin in these cells is more similar to that of EB. However, in LSK, 50% of both EB and MEG cAERs overlap with ATACSeq peaks, suggesting that half of cell-specific cAERs are present in LSK while the rest are established during differentiation. In contrast, 82% of shared EB and MEG cAERs overlapped with LSK ATACSeq peaks and were maintained throughout differentiation.Candidate super enhancers (cSEs) are the cAERs with the highest levels of H3K27ac as measured by ChIPSeq. Within the top 2% of AERs we identified 101 EB and 98 MEG HC cSEs (i.e., overlap ATACSeq peaks). There was no overlap between the EB and MEG cSEs, indicating that cSEs are more cell-specific than all cAERs (Χ2 ≤ 0.04). RNASeq data confirmed that 92% of cSEs were closest to an active TSS. These data indicate that cSEs are more cell-specific than cAERs and are associated with increased gene expression.Approximately 96% of EB-specific cSEs correlated with ATACSeq peaks in CFUE chromatin, 94% in MEP, 82% in CMP, and 65% in LSK. In contrast, 95% of MEG-specific cSEs correlated with ATACSeq peaks in CFUMeg chromatin, 81% in MEP and CMP, and 75% in LSKs. The higher percentage of MEG cSEs in LSK is significantly different from all MEG cAERs (Χ2 ≤ 0.003), indicating that, unlike cAERs, MEG-specific cSEs are established early and maintained throughout differentiation.We have shown that cAERs, especially cSEs, are highly cell-specific in primary murine erythroid and megakaryocytic cells and correlate with gene expression. Examining changes in cAERs, cSEs, and gene expression allows us to map the specific epigenetic changes in chromatin that define erythroid and megakaryocytic differentiation. These results will enable us to test hypotheses about the mechanism of erythroid and megakaryocytic lineage commitment.TableEB-specificMEG-specificCommonNo.PercentNo.PercentNo.PercentcER7153n/a4196n/a619n/acAER6097100%3064100%468100%HC cAER593497%284893%43493%HC cAER + CFUE ATACSeq581898%n/an/an/an/aHC cAER + CFUMeg ATACSeqn/an/a260692%n/an/aHC cAER + MEP ATACSeq559194%150953%39491%HC cAER + CMP ATACSeq475480%147352%38589%HC cAER + LSK ATACSeq371963%136848%35181% DisclosuresNo relevant conflicts of interest to declare.

Whole-Genome Bisulfite Sequencing of Primary AML Cells with the DNMT3A R882H Mutation Identifies Regions of Focal Hypomethylation That Are Associated with Open Chromatin

Mutations in the de novo DNA methyltransferase DNMT3A are found in ~25% of patients with acute myeloid leukemia (AML) and most commonly affect codon 882 within the catalytic domain of the protein. We have previously shown that this mutation has dominant negative activity in vitro and is associated with hypomethylation at specific CpG dinucleotides in primary AML samples using array-based methylation data. However, the genome-wide extent and patterns of DNA methylation associated with this hypomethylation are currently unknown. In addition, it is unclear if the methylation differences caused by this mutation result in RNA expression changes at specific targets across the genome, or whether they are associated with altered chromatin structure.To explore the genome-wide consequences of the DNMT3A R882H mutation on DNA methylation and chromatin structure, we carried out whole-genome bisulfite sequencing (WGBS) and transposase-mediated chromatin accessibility profiling (ATAC-seq) on 3 primary normal karyotype AML samples with the DNMT3A R882H mutation and 4 matched AML samples without a DNMT3A mutation. All 7 had the NPMc mutation but lacked mutations in other genes involved in DNA methylation, including IDH1, IDH2, and TET2. WGBS produced methylation data on >93% of the CpGs in the human reference sequence with a median coverage of 7-13x. The overall mean methylation was not statistically different in the samples with R882H mutations, although there was a small but statistically significant difference in the methylation at CpGs in CpG islands (DNMT3A R882H mean: 18.1%, DNMT3A wild-type mean: 21.4%; P=0.02). Differential methylation analysis was performed on ~5 million CpG clusters (median of 5 CpGs per cluster; median cluster size of 202 bp) and identified 95,845 differentially methylated clusters with a mean difference >25% and a q-value < 0.01, the majority of which (88,512; 93%) were hypomethylated in the DNMT3A R882H samples. Using more strict criteria (>50% mean difference) and merging differentially methylated clusters within 50 bp, we identified 2,782 differentially methylated regions (DMRs) with a mean size of 255 bp (median of 11 CpGs), of which 97% were hypomethylated. These DMRs were distributed across the genome and were statistically associated with CpG dense regions, including annotated CpG islands and shores (islands: 1,104 of 2,782; 29.9%; shores: 1,118 of 2,782; 30.3%; P<10-10), and gene promoters (816 of 2,782; 23.7%; P< 10-12).Analysis of chromatin accessibility data from 6 samples (3 DNMT3A R882H and 3 DNMT3A wild-type) showed that a subset of the DNMT3A R882H-associated hypomethylated DMRs (366 of 2,704; 13.5%) were located within 100 bp of an ATAC-seq peak unique to DNMT3A R882H AML samples. Further analysis of all DMRs showed ATAC-seq signal enrichment in the R882H samples specifically at hypomethylated loci (Figure 1). Similar enrichment was not observed in the DNMT3A wild-type AMLs at hypomethylated DMRs (N=78), suggesting that hypomethylation caused by the DNMT3A R882H mutation is specifically associated with changes in chromatin structure. Initial analysis of existing PolyA+ RNA-seq data for these AMLs did not reveal canonical expression changes in annotated genes located near the DMRs, implying that methylation and other epigenetic changes might affect distant genes or previously unannotated RNA species that were not present in our dataset. Efforts to sequence all RNA species present in these samples are therefore underway.In summary, we have conducted an initial analysis of genome-wide, CpG-resolution DNA methylation data from primary AML samples with the DNMT3A R882H mutation. This mutation is associated with a genome-wide, focal hypomethylation phenotype that occurs at small, CpG-dense loci across the genome. We also found that many hypomethylated loci are associated with changes in chromatin structure. These findings represent the first evidence that the methylation changes caused by this mutation can have functional consequences on the epigenetic state of specific loci in AML cells, and set the stage for defining the specific events that are responsible for AML pathogenesis in patients who have this mutation. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.