ALBERT

Beschreibung: Abstract 211 The hematopoietic system is ideal for the study of epigenetic changes in primary cells because hematopoietic cells representing distinct stages of hematopoiesis can be enriched and isolated by differences in surface marker expression. DNA methylation is an essential epigenetic mark that is required for normal development. Conditional knockout of the DNA methyltransferase enzymes in the mouse hematopoietic compartment have revealed that methylation is critical for long-term renewal and lineage differentiation of hematopoietic stem cells (Broske et al 2009, Trowbridge el al 2009). To better understand the role of DNA methylation in self-renewal and differentiation of hematopoietic cells, we characterized genome-wide DNA methylation in primary cells representing three distinct stages of hematopoiesis. We isolated mouse hematopoietic stem cells (HSC; Lin- Sca-1+ c-kit+), common myeloid progenitor cells (CMP; Lin- Sca-1- c-kit+), and erythroblasts (ERY; CD71+ Ter119+). Methyl Binding Domain Protein 2 (MBD2) is an endogenous reader of DNA methylation that recognizes DNA with a high concentration of methylated CpG residues. Recombinant MBD2 enrichment of DNA followed by massively-parallel sequencing was used to map and compare genome-wide DNA methylation patterns in HSC, CMP and ERY. Two biological replicates were sequenced for each cell type with total read counts ranging from 32,309,435–46,763,977. Model-based analysis of ChIP Seq (MACS) with a significance cutoff of p

Beschreibung: The ENCODE project has demonstrated that epigenetic signatures, including DNA methylation and transcription factor (TF) occupancy, define gene expression. However, ENCODE was constructed using static cells that were not capable of further differentiation. We hypothesize that specific epigenetic profiles are associated with erythroid and megakaryocytic differentiation. To test this hypothesis, we isolated primary erythroblasts (EBs) and megakaryocytes (Megs) from mouse bone marrow by flow cytometry and prepared: 1) DNA for genome-wide methylation analysis using MBD2 Methyl-Seq; 2) RNA for both RNA-Seq analysis and microarray analysis of novel and annotated lncRNA expression levels; and 3) chromatin for genome-wide chromatin immunoprecipitation (ChIP-Seq) analysis of occupancy by the TFs GATA1 and NFE2. We developed the web-based high-throughput sequencing tool suite SigSeeker (http://sigseeker.org) to predict regions of methylation and TF occupancy across the genome. High-confidence methylation, GATA1, and NFE2 profiles, represented by the intersection of two independent EB and Meg biological replicates, are shown in Table 1. Of the approximate 100,000 methylated regions in EBs and Megs, 45% were shared between the two cell types. Unlike methylation, GATA1 and NFE2 occupancy showed strong cell type-specific profiles, with most GATA1 occupied sites (79%) being EB-specific, and most NFE2 occupied sites (72%) being Meg-specific. While 26% of EB-specific GATA1 peaks were co-occupied by NFE2, co-occupancy by GATA1 and NFE2 in Megs was rare (0.6%). We developed a second web-based tool called SBR (http://sbrblood.msseeker.org) to correlate ChIP-Seq and Methyl-Seq profiles with RNA-Seq and lncRNA transcriptional data sets. Almost 95% of RefSeq (coding) genes with methylation in the promoter regions were not expressed. Fewer than 5% of methylated RefSeq promoters also had TF occupancy. Unlike promoters, the bodies of RefSeq genes had a high degree of overlap between methylation and TF binding. In EBs, 38% of RefSeq genes with GATA1 occupancy in the body were methylated. Of genes with this profile, 81% were transcriptionally silent. In Megs, 42% of RefSeq genes with NFE2 occupancy in the body were methylated. However, 80% of these Meg-specific genes were transcriptionally active. In contrast to RefSeq genes, lncRNA genes have a different signature. More than 85% of EB-expressed lncRNA promoters are methylated and ∼25% of these promoters are occupied by GATA1 and/or NFE2. Over 90% of EB-expressed lncRNA gene bodies occupied by GATA1 and/or NFE2 are methylated. In contrast less than 10% of Meg-expressed lncRNA promoters are methylated and ∼only 2% of these promoters are occupied by NFE2. However, 90% of Meg-expressed lncRNA gene bodies occupied by GATA1 and/or NFE2 are methylated. Ingenuity IPA analysis of the transcriptional profiles associated with different epigenetic signatures revealed differentially regulated cellular pathways. In EBs, GATA1 occupancy in the promoters of silent genes was associated with cardiovascular (p≤ 10-7) and nervous system development (p≤ 10-7). In Megs, NFE2 promoter occupancy was associated with active genes involved in nucleic acid metabolism (p≤ 10-3) and nervous system development (p≤ 10-5). Genes expressed in both EBs and Megs were involved in transcription (p≤ 10-6), cell cycle progression (p≤ 10-5), and decreased hypoplasia (p≤ 10-20). GATA1 and NFE2 co-occupied genes expressed in both EBs and Megs were associated with suppression of bone-related (p≤ 10-6) and neuron-related transcripts (p≤ 10-8). In summary, we show that TF occupancy and methylation significantly overlap in RefSeq gene bodies, but not in promoters. These profiles have revealed that GATA1 occupancy, independent of NFE2 co-occupancy, correlates with EB-specific transcriptional silencing, whereas Meg-specific transcriptional activation is associated with NFE2 occupancy. In contrast, over 90% active and TF-occupied lncRNA (both novel and previously annotated) gene bodies are methylated. These epigenetic correlations will be important for future studies assessing the regulation of mRNAs and lncRNAs. Disclosures: No relevant conflicts of interest to declare.

Beschreibung: To date numerous datasets of gene expression and epigenetic profiles for mouse and human hematopoietic cells have been generated. While individual data sets for a particular cell type have been correlated, no approach exists to harness all expression and epigenetic profiles for the different types of hematopoietic cells. Our goal is to develop a systems biology platform to compare epigenetic profiles of hematopoietic cells towards a better understanding of epigenetic mechanisms governing hematopoiesis. To provide the necessary foundation to support systematic studies of hematopoiesis, we have developed the Systems Biology Repository (SBR, http://sbrblood.nhgri.nih.gov), a data "ranch" for organizing and analyzing transcriptome and epigenome data cells throughout differentiation. To populate SBR, we extracted, curated, annotated, and integrated all human and mouse hematopoietic datasets available through the Encyclopedia of DNA Elements (ENCODE), the Gene Expression Omnibus (GEO) and the Short Read Repository (SRR). These include genome-wide profiles of DNA methylation, histone methylation and acetylation, transcription factor occupancy (ChIPSeq), chromatin accessibility (DNaseISeq, ATACSeq, FAIRESeq), and coding as well as non-coding transcriptional profiles (RNASeq). To demonstrate the utility of SBR, we conducted three different analyses. The first was a vertical study of HistoneSeq (H3K4me1, H3K4me2, H3K4me3, and H3K27ac), DNA methylation and RNASeq profiles during mouse erythroid differentiation. We found a global decrease in DNA methylation from hematopoietic stem and progenitor cells (HSC) through common myeloid progenitors (CMP), erythroid progenitor cells (MEP) and erythroblasts (ERY; 92936 peaks in HSC to 14422 in ERY). The number of expressed genes (using a tags per million cutoff of 10) increased in erythroid progenitors (8901 in HSC to 10778 in CMP and 10670 in MEP) before decreasing in ERY (8654). 62% of histone marks delineating active enhancers (H3K27ac, H3K4me1) are present in both HSC and ERY, while 48% arise de novo during differentiation. In contrast, only 16% of active promoter specific histone marks (H3K4me2, H3K4me3) are present in both HSC and ERY. For a horizontal analysis we compared the DNA methylation, RNASeq, histone modification (H3K4me1, H3K4me2, H3K4me3, and H3K27ac) and transcription factor binding (GATA1 and NFE2) profiles of erythroblasts (ERY) and megakaryocytes (MEG). We found a similar relationship between gene expression and the histone and DNA methylation profiles in each cell type but differences between expression and in transcription factor occupancy. DNA methylation and H3K4me3 was enriched in the gene body of expressed genes (〉36%) for both ERY (p ≤ 0.001) and MEG (p ≤ 0.01). In contrast DNA methylation was enriched in the upstream and downstream regions of non-coding RNA genes (p ≤ 0.001). Transcription factor occupancy was cell type specific: 79% of GATA1 sites are in ERY and 72% of NFE2 sites are in MEG. In erythroblasts, DNA methylation and GATA1 binding in the gene body are associated with gene silencing (4 fold difference, p ≤ 0.001), while in megakaryocytes, DNA methylation and NFE2 binding in the gene body are associated with gene activation (8 fold difference, p ≤ 0.001). We used the Mouse Genome Informatics homology map data to perform a cross-species comparison of the expression profiles of mouse and human multipotent progenitors (MPP), proerythroblasts and orthochromatic erythroblasts. We found a total of 5247 genes expressed at significantly different levels (p ≤ 0.001) between human and mouse MPP, while only 2010 genes were expressed at significantly similar levels (p ≤ 0.001). At the proerythroblast and orthochromatic erythroblast stages 7696 genes and 6571 genes were expressed at significantly different levels (p ≤ 0.001) between human and mouse respectively, while 2024 and 2560 genes were expressed at significantly similar levels (p ≤ 0.001). These data are consistent with previous studies showing differences in the transcriptional profiles of mouse and human hematopoietic cells. In summary, SBR provides a foundation to model the genetic and epigenetic landscape in both the mouse and human hematopoietic system, and enables functional correlations to be made between the species. As SBR is expanded to include data from patient cells, it will be possible to model epigenetic changes associated with disease. Disclosures No relevant conflicts of interest to declare.

Beschreibung: Background: Diamond Blackfan anemia (DBA) is a congenital anemia characterized by failure of adequate erythrocyte expansion from hematopoietic precursors. The genetic basis of DBA is largely established, with mutation or deletion of at least 19 structural ribosomal protein (RP) genes, a RP chaperone (TSR2), or a pivotal erythroid transcription factor (GATA1) identifiable in most DBA cases. However, the marked clinical variability in DBA-including varying ages of presentation, severity of anemia, responsiveness to corticosteroids, and sporadic hematologic remissions-remains unexplained by genotype and may be modulated by epigenetic factors. Further understanding of this variability is of potential therapeutic relevance for biomarkers of steroid response and remission as well as in application to novel treatment approaches. Aim: We characterized genome-wide methylation and chromatin accessibility of erythroid progenitors from normal controls and DBA patients during erythroid commitment in order to identify the epigenetic features associated with erythroid failure in DBA, steroid response, and remission. Methods: We expanded and sorted CD71+/CD235- (transferrin receptor/glycophorin A) and CD71+/CD235+ erythroid cell fractions from DBA patients and controls after isolation of primary circulating CD34+ cells from peripheral blood (O'Brien et al, Blood 129(23):3111, 2017). We performed DNA methylation analysis using Illumina Epic arrays in 9 control and 22 DBA subjects (11 transfusion-dependent, 6 steroid responsive, 5 remission), characterizing differentially methylated probes and regions among groups. To define broad chromatin domains, we identified A/B chromatin compartments (representing open/closed chromatin) using long-range correlations in methylation data as previously described (Fortin et al. Genome Biol 16:180, 2015). To identify discrete local changes in chromatin accessibility, we performed ATAC-sequencing in 9 controls and 17 DBA patients (10 transfusion, 6 steroid, 1 remission). Results: Global DNA methylation falls during erythroid commitment, with 258,618 differentially hypermethylated CpG sites in normal control GlyA- cells compared to their more differentiated GlyA+ counterparts. This pattern is exaggerated in DBA samples, with 297,926 sites hypermethylated in GlyA- cells. We identified 17,392 CpC sites that distinguish GlyA- DBA progenitors from normal progenitors (16,953 hyper- and 439 hypomethylated). We identified 1,749 differentially methylated sites in comparison of transfusion dependent and remission DBA, as well as 79 sites different between transfusion dependent and steroid responsive DBA. Using genome-wide methylation data, we evaluated A/B compartment organization among these groups to identify large regions of open and closed chromatin during normal and DBA early erythroid differentiation. We observe significant shifts in A/B compartments in normal cells concurrent with the acquisition of GlyA surface expression. At genome scale, transfusion dependent and steroid resistant DBA samples are generally similar to each other, with thousands of regions where A/B identity are closely matched in DBA, but diametrically opposed to the configuration in stage-matched normal controls. Intriguingly, remission samples generally matched A/B compartments of other DBA samples in GlyA- fractions but GlyA+ compartments more closely resemble those of the controls, indicating that normalization of chromatin structural maturation accompanies hematologic remission. We generated a uniform set of 8,877 enriched ATAC-seq peaks on autosomes for differential chromatin accessibility analysis. As with methylation data, a large proportion (25%; 1085 up and 1114 down, B-H adj. P 〈 0.1) showed differential accessibility in normal control GlyA- vs GlyA+ cells. Steroid-responsive cases showed additional regions of differential accessibility during early maturation, with 31% of regions (1515 up and 1248 down) differentially accessible. Among transfusion dependent DBA patients, this count was much higher, with over half of peak regions (52%, 2400 up and 2216 down, B-H adj. P 〈 0.1) showing differential accessibility. Conclusion: Epigenetic maturation is broadly altered in DBA erythroid progenitors compared to stage matched normal controls, with specific changes identifiable in patients responding to steroids and in remission. Disclosures No relevant conflicts of interest to declare.

Beschreibung: Enhancers are cis acting regulatory modules associated with lineage-specific gene expression. The Encyclopedia of DNA Elements project (ENCODE) showed that enhancers are in open chromatin regions identified by the Assay for Transposable-Accessible Chromatin (ATAC) and bound with histone H3 is mono-methylated at lysine 4 (H3K4me1). Chromatin regions marked by H3K4me1 alone identifies "poised" enhancers (not active), while the additional presence and histone H3 acetylated at lysine 27 (H3K27ac) identifies "active" enhancers. To establish a genome-wide enhancer map in the erythro-megakaryocytic lineage, we performed ChIPSeq of H3K4me1 and H3K27ac in primary erythroblasts (EB) and megakaryocytes (MEG) isolated from mouse bone marrow. We also assayed primary mouse EB, MEG, hematopoietic stem and progenitor cells (LSK), and common myeloid progenitor cells (CMP) for open chromatin regions with ATAC and transcriptome profiling by RNASeq. Finally, we compared histone-defined enhancers in mature cells with the corresponding ATAC regions in progenitor cells to identify the preservation of poised and active enhancers through hematopoiesis. We identified 6565 and 3543 active enhancers in EB and MEG respectively; approximately 10% (434) were shared. We further refined our enhancer set to the ~90% of EB and MEG active enhancers that overlap with ATAC regions (AER, histone-marked active enhancer within an ATAC region). To identify enhancers in the open chromatin of progenitor cells, we overlaid EB and MEG AER with CMP ATAC sites. This revealed that 82% (5226/6399) of EB AER and 87% (1437/3302) of MEG AER were present in CMP. Overlaying the EB and MEG AER onto LSK ATAC showed that 67% (4278/6399) of EB-specific AER and 79% (2594/3302) of MEG-specific AER overlapped with LSK ATAC sites. To identify the EB and MEG AER in LSK-accessible chromatin that are active (not poised), we compared our LSK enhancer set with the indexing-first ChIP (iChIP) histone marks identified by Lara-Astiaso et al., (Science, 2014). 1840 of the 4278 (43%) LSK-accessible EB AER overlapped with LSK iChIP H3K4me1 marks; 632 of these (15% overall) also had the active H3K27ac mark. 1083 of the 2594 (42%) MEG AER that were present in LSK overlapped with LSK iChIP H3K4me1 marks; 241 of these (9% overall) had the H3K27ac mark. For both EB and MEG, AER not marked by iChIP K4me1 were within gene bodies. To further characterize enhancer roles in lineage commitment, we profiled super enhancers (SE), which have highly lineage-specific activity. We defined SE as the 2% of AER with the highest H3K27ac levels (Hnisz et al., Cell, 2013) and identified 101 EB and 98 MEG SE; all of these were cell-specific. We found that 65% (66/101) of EB SE and 87% (85/98) of MEG SE overlapped with LSK ATAC sites. 30 of the 66 (45%) LSK-accessible EB SE overlapped with LSK iChIP H3K4me1 marks; 9 of these (14% overall) also had the active H3K27ac mark. In comparison, 15 of the 85 (18%) LSK-accessible MEG SE overlapped with LSK iChIP H3K4me1 marks; 4 of these (5% overall) also had the active H3K27ac mark. We correlated our LSK-accessible, iChIP-marked active AER with gene expression by assigning each AER to the nearest gene. We then used RNASeq data to perform gene set enrichment analysis via Ingenuity Pathway Analysis. We found that the LSK-accessible EB-specific AER gene set included erythropoietin-regulated genes (p £ 9x10-5) and genes associated with Fanconi anemia (6x10-4). Conversely, LSK-accessible and iChIP-active MEG AER were associated an increase of progenitor cell populations and proliferation activities for several hematopoietic lineages (p £ 2x10-5). However, the genes in the non-megakaryocyte pathways were significantly down-regulated as LSK committed to the megakaryocyte lineage. In summary, our results demonstrate the establishment of poised and active enhancers in hematopoietic progenitors and their preservation through erythro-megakaryopoiesis. We show that 〉40% of EB and MEG enhancers were also enhancers in LSK and CMP; the EB and MEG enhancers that were not LSK enhancers were primarily within gene bodies. We also found that MEG, but not EB, super enhancers were less likely than conventional enhancers to be established in LSK. Finally, our data show that, while LSK-established EB enhancers target EB-specific functions, LSK-established MEG enhancers have more universal hematopoietic functions that are down-regulated during megakaryocytic lineage commitment. Disclosures No relevant conflicts of interest to declare.