Potential impact of celiac disease genetic risk factors on T cell receptor signaling in gluten-specific CD4+ T cells.

Celiac disease is an auto-immune disease in which an immune response to dietary gluten leads to inflammation and subsequent atrophy of small intestinal villi, causing severe bowel discomfort and malabsorption of nutrients. The major instigating factor for the immune response in celiac disease is the activation of gluten-specific CD4+ T cells expressing T cell receptors that recognize gluten peptides presented in the context of HLA-DQ2 and DQ8. Here we provide an in-depth characterization of 28 gluten-specific T cell clones. We assess their transcriptional and epigenetic response to T cell receptor stimulation and link this to genetic factors associated with celiac disease. Gluten-specific T cells have a distinct transcriptional profile that mostly resembles that of Th1 cells but also express cytokines characteristic of other types of T-helper cells. This transcriptional response appears not to be regulated by changes in chromatin state, but rather by early upregulation of transcription factors and non-coding RNAs that likely orchestrate the subsequent activation of genes that play a role in immune pathways. Finally, integration of chromatin and transcription factor binding profiles suggest that genes activated by T cell receptor stimulation of gluten­specific T cells may be impacted by genetic variation at several genetic loci associated with celiac disease.

Chromatin-Based Classification of Genetically Heterogeneous AMLs into Two Distinct Subtypes with Diverse Stemness Phenotypes.

Global investigation of histone marks in acute myeloid leukemia (AML) remains limited. Analyses of 38 AML samples through integrated transcriptional and chromatin mark analysis exposes 2 major subtypes. One subtype is dominated by patients with NPM1 mutations or MLL-fusion genes, shows activation of the regulatory pathways involving HOX-family genes as targets, and displays high self-renewal capacity and stemness. The second subtype is enriched for RUNX1 or spliceosome mutations, suggesting potential interplay between the 2 aberrations, and mainly depends on IRF family regulators. Cellular consequences in prognosis predict a relatively worse outcome for the first subtype. Our integrated profiling establishes a rich resource to probe AML subtypes on the basis of expression and chromatin data.

Predicting stimulation-dependent enhancer-promoter interactions from ChIP-Seq time course data.

We have developed a machine learning approach to predict stimulation-dependent enhancer-promoter interactions using evidence from changes in genomic protein occupancy over time. The occupancy of estrogen receptor alpha (ERα), RNA polymerase (Pol II) and histone marks H2AZ and H3K4me3 were measured over time using ChIP-Seq experiments in MCF7 cells stimulated with estrogen. A Bayesian classifier was developed which uses the correlation of temporal binding patterns at enhancers and promoters and genomic proximity as features to predict interactions. This method was trained using experimentally determined interactions from the same system and was shown to achieve much higher precision than predictions based on the genomic proximity of nearest ERα binding. We use the method to identify a genome-wide confident set of ERα target genes and their regulatory enhancers genome-wide. Validation with publicly available GRO-Seq data demonstrates that our predicted targets are much more likely to show early nascent transcription than predictions based on genomic ERα binding proximity alone.

Time-resolved analysis of DNA-protein interactions in living cells by UV laser pulses.

Interactions between DNA and proteins are mainly studied through chemical procedures involving bi-functional reagents, mostly formaldehyde. Chromatin immunoprecipitation is used to identify the binding between transcription factors (TFs) and chromatin, and to evaluate the occurrence and impact of histone/DNA modifications. The current bottleneck in probing DNA-protein interactions using these approaches is caused by the fact that chemical crosslinkers do not discriminate direct and indirect bindings or short-lived chromatin occupancy. Here, we describe a novel application of UV laser-induced (L-) crosslinking and demonstrate that a combination of chemical and L-crosslinking is able to distinguish between direct and indirect DNA-protein interactions in a small number of living cells. The spatial and temporal dynamics of TF bindings to chromatin and their role in gene expression regulation may thus be assessed. The combination of chemical and L-crosslinking offers an exciting and unprecedented tool for biomedical applications.

The Hematopoietic Transcription Factors RUNX1 and ERG Prevent AML1-ETO Oncogene Overexpression and Onset of the Apoptosis Program in t(8;21) AMLs.

The t(8;21) acute myeloid leukemia (AML)-associated oncoprotein AML1-ETO disrupts normal hematopoietic differentiation. Here, we have investigated its effects on the transcriptome and epigenome in t(8,21) patient cells. AML1-ETO binding was found at promoter regions of active genes with high levels of histone acetylation but also at distal elements characterized by low acetylation levels and binding of the hematopoietic transcription factors LYL1 and LMO2. In contrast, ERG, FLI1, TAL1, and RUNX1 bind at all AML1-ETO-occupied regulatory regions, including those of the AML1-ETO gene itself, suggesting their involvement in regulating AML1-ETO expression levels. While expression of AML1-ETO in myeloid differentiated induced pluripotent stem cells (iPSCs) induces leukemic characteristics, overexpression increases cell death. We find that expression of wild-type transcription factors RUNX1 and ERG in AML is required to prevent this oncogene overexpression. Together our results show that the interplay of the epigenome and transcription factors prevents apoptosis in t(8;21) AML cells.

eFORGE: A Tool for Identifying Cell Type-Specific Signal in Epigenomic Data.

Epigenome-wide association studies (EWAS) provide an alternative approach for studying human disease through consideration of non-genetic variants such as altered DNA methylation. To advance the complex interpretation of EWAS, we developed eFORGE (http://eforge.cs.ucl.ac.uk/), a new standalone and web-based tool for the analysis and interpretation of EWAS data. eFORGE determines the cell type-specific regulatory component of a set of EWAS-identified differentially methylated positions. This is achieved by detecting enrichment of overlap with DNase I hypersensitive sites across 454 samples (tissues, primary cell types, and cell lines) from the ENCODE, Roadmap Epigenomics, and BLUEPRINT projects. Application of eFORGE to 20 publicly available EWAS datasets identified disease-relevant cell types for several common diseases, a stem cell-like signature in cancer, and demonstrated the ability to detect cell-composition effects for EWAS performed on heterogeneous tissues. Our approach bridges the gap between large-scale epigenomics data and EWAS-derived target selection to yield insight into disease etiology.

ß-Glucan Reverses the Epigenetic State of LPS-Induced Immunological Tolerance.

Innate immune memory is the phenomenon whereby innate immune cells such as monocytes or macrophages undergo functional reprogramming after exposure to microbial components such as lipopolysaccharide (LPS). We apply an integrated epigenomic approach to characterize the molecular events involved in LPS-induced tolerance in a time-dependent manner. Mechanistically, LPS-treated monocytes fail to accumulate active histone marks at promoter and enhancers of genes in the lipid metabolism and phagocytic pathways. Transcriptional inactivity in response to a second LPS exposure in tolerized macrophages is accompanied by failure to deposit active histone marks at promoters of tolerized genes. In contrast, ß-glucan partially reverses the LPS-induced tolerance in vitro. Importantly, ex vivo ß-glucan treatment of monocytes from volunteers with experimental endotoxemia re-instates their capacity for cytokine production. Tolerance is reversed at the level of distal element histone modification and transcriptional reactivation of otherwise unresponsive genes. VIDEO ABSTRACT.

Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells.

Characterizing the multifaceted contribution of genetic and epigenetic factors to disease phenotypes is a major challenge in human genetics and medicine. We carried out high-resolution genetic, epigenetic, and transcriptomic profiling in three major human immune cell types (CD14+ monocytes, CD16+ neutrophils, and naive CD4+ T cells) from up to 197 individuals. We assess, quantitatively, the relative contribution of cis-genetic and epigenetic factors to transcription and evaluate their impact as potential sources of confounding in epigenome-wide association studies. Further, we characterize highly coordinated genetic effects on gene expression, methylation, and histone variation through quantitative trait locus (QTL) mapping and allele-specific (AS) analyses. Finally, we demonstrate colocalization of molecular trait QTLs at 345 unique immune disease loci. This expansive, high-resolution atlas of multi-omics changes yields insights into cell-type-specific correlation between diverse genomic inputs, more generalizable correlations between these inputs, and defines molecular events that may underpin complex disease risk.

ZMYND8 Co-localizes with NuRD on Target Genes and Regulates Poly(ADP-Ribose)-Dependent Recruitment of GATAD2A/NuRD to Sites of DNA Damage.

NuRD (nucleosome remodeling and histone deacetylase) is a versatile multi-protein complex with roles in transcription regulation and the DNA damage response. Here, we show that ZMYND8 bridges NuRD to a number of putative DNA-binding zinc finger proteins. The MYND domain of ZMYND8 directly interacts with PPPLΦ motifs in the NuRD subunit GATAD2A. Both GATAD2A and GATAD2B exclusively form homodimers and define mutually exclusive NuRD subcomplexes. ZMYND8 and NuRD share a large number of genome-wide binding sites, mostly active promoters and enhancers. Depletion of ZMYND8 does not affect NuRD occupancy genome-wide and only slightly affects expression of NuRD/ZMYND8 target genes. In contrast, the MYND domain in ZMYND8 facilitates the rapid, poly(ADP-ribose)-dependent recruitment of GATAD2A/NuRD to sites of DNA damage to promote repair by homologous recombination. Thus, these results show that a specific substoichiometric interaction with a NuRD subunit paralogue provides unique functionality to distinct NuRD subcomplexes.

Recruitment of the Mammalian Histone-modifying EMSY Complex to Target Genes Is Regulated by ZNF131.

Recent work from others and us revealed interactions between the Sin3/HDAC complex, the H3K4me3 demethylase KDM5A, GATAD1, and EMSY. Here, we characterize the EMSY/KDM5A/SIN3B complex in detail by quantitative interaction proteomics and ChIP-sequencing. We identify a novel substoichiometric interactor of the complex, transcription factor ZNF131, which recruits EMSY to a large number of active, H3K4me3 marked promoters. Interestingly, using an EMSY knock-out line and subsequent rescue experiments, we show that EMSY is in most cases positively correlated with transcriptional activity of its target genes and stimulates cell proliferation. Finally, by immunohistochemical staining of primary breast tissue microarrays we find that EMSY/KDM5A/SIN3B complex subunits are frequently overexpressed in primary breast cancer cases in a correlative manner. Taken together, these data open venues for exploring the possibility that sporadic breast cancer patients with EMSY amplification might benefit from epigenetic combination therapy targeting both the KDM5A demethylase and histone deacetylases.

Genome-wide modeling of transcription kinetics reveals patterns of RNA production delays.

Genes with similar transcriptional activation kinetics can display very different temporal mRNA profiles because of differences in transcription time, degradation rate, and RNA-processing kinetics. Recent studies have shown that a splicing-associated RNA production delay can be significant. To investigate this issue more generally, it is useful to develop methods applicable to genome-wide datasets. We introduce a joint model of transcriptional activation and mRNA accumulation that can be used for inference of transcription rate, RNA production delay, and degradation rate given data from high-throughput sequencing time course experiments. We combine a mechanistic differential equation model with a nonparametric statistical modeling approach allowing us to capture a broad range of activation kinetics, and we use Bayesian parameter estimation to quantify the uncertainty in estimates of the kinetic parameters. We apply the model to data from estrogen receptor α activation in the MCF-7 breast cancer cell line. We use RNA polymerase II ChIP-Seq time course data to characterize transcriptional activation and mRNA-Seq time course data to quantify mature transcripts. We find that 11% of genes with a good signal in the data display a delay of more than 20 min between completing transcription and mature mRNA production. The genes displaying these long delays are significantly more likely to be short. We also find a statistical association between high delay and late intron retention in pre-mRNA data, indicating significant splicing-associated production delays in many genes.

Epigenetic programming of monocyte-to-macrophage differentiation and trained innate immunity.

Monocyte differentiation into macrophages represents a cornerstone process for host defense. Concomitantly, immunological imprinting of either tolerance or trained immunity determines the functional fate of macrophages and susceptibility to secondary infections. We characterized the transcriptomes and epigenomes in four primary cell types: monocytes and in vitro-differentiated naïve, tolerized, and trained macrophages. Inflammatory and metabolic pathways were modulated in macrophages, including decreased inflammasome activation, and we identified pathways functionally implicated in trained immunity. ß-glucan training elicits an exclusive epigenetic signature, revealing a complex network of enhancers and promoters. Analysis of transcription factor motifs in deoxyribonuclease I hypersensitive sites at cell-type-specific epigenetic loci unveiled differentiation and treatment-specific repertoires. Altogether, we provide a resource to understand the epigenetic changes that underlie innate immunity in humans.

Genome-wide binding of MBD2 reveals strong preference for highly methylated loci.

MBD2 is a subunit of the NuRD complex that is postulated to mediate gene repression via recruitment of the complex to methylated DNA. In this study we adopted an MBD2 tagging-approach to study its genome wide binding characteristics. We show that in vivo MBD2 is mainly recruited to CpG island promoters that are highly methylated. Interestingly, MBD2 binds around 1 kb downstream of the transcription start site of a subset of ∼ 400 CpG island promoters that are characterized by the presence of active histone marks, RNA polymerase II (Pol2) and low to medium gene expression levels and H3K36me3 deposition. These tagged-MBD2 binding sites in MCF-7 show increased methylation in a cohort of primary breast cancers but not in normal breast samples, suggesting a putative role for MBD2 in breast cancer.

Inference of RNA polymerase II transcription dynamics from chromatin immunoprecipitation time course data.

Gene transcription mediated by RNA polymerase II (pol-II) is a key step in gene expression. The dynamics of pol-II moving along the transcribed region influence the rate and timing of gene expression. In this work, we present a probabilistic model of transcription dynamics which is fitted to pol-II occupancy time course data measured using ChIP-Seq. The model can be used to estimate transcription speed and to infer the temporal pol-II activity profile at the gene promoter. Model parameters are estimated using either maximum likelihood estimation or via Bayesian inference using Markov chain Monte Carlo sampling. The Bayesian approach provides confidence intervals for parameter estimates and allows the use of priors that capture domain knowledge, e.g. the expected range of transcription speeds, based on previous experiments. The model describes the movement of pol-II down the gene body and can be used to identify the time of induction for transcriptionally engaged genes. By clustering the inferred promoter activity time profiles, we are able to determine which genes respond quickly to stimuli and group genes that share activity profiles and may therefore be co-regulated. We apply our methodology to biological data obtained using ChIP-seq to measure pol-II occupancy genome-wide when MCF-7 human breast cancer cells are treated with estradiol (E2). The transcription speeds we obtain agree with those obtained previously for smaller numbers of genes with the advantage that our approach can be applied genome-wide. We validate the biological significance of the pol-II promoter activity clusters by investigating cluster-specific transcription factor binding patterns and determining canonical pathway enrichment. We find that rapidly induced genes are enriched for both estrogen receptor alpha (ERα) and FOXA1 binding in their proximal promoter regions.

Context-selective death of acute myeloid leukemia cells triggered by the novel hybrid retinoid-HDAC inhibitor MC2392.

HDAC inhibitors (HDACi) are widely used in the clinic to sensitize tumorigenic cells for treatment with other anticancer compounds. The major drawback of HDACi is the broad inhibition of the plethora of HDAC-containing complexes. In acute promyelocytic leukemia (APL), repression by the PML-RARα oncofusion protein is mediated by an HDAC-containing complex that can be dissociated by pharmacologic doses of all trans retinoic acid (ATRA) inducing differentiation and cell death at the expense of side effects and recurrence. We hypothesized that the context-specific close physical proximity of a retinoid and HDACi-binding protein in the repressive PML-RARα-HDAC complex may permit selective targeting by a hybrid molecule of ATRA with a 2-aminoanilide tail of the HDAC inhibitor MS-275, yielding MC2392. We show that MC2392 elicits weak ATRA and essentially no HDACi activity in vitro or in vivo. Genome-wide epigenetic analyses revealed that in NB4 cells expressing PML-RARα, MC2392 induces changes in H3 acetylation at a small subset of PML-RARα-binding sites. RNA-seq reveals that MC2392 alters expression of a number of stress-responsive and apoptotic genes. Concordantly, MC2392 induced rapid and massive, caspase-8-dependent cell death accompanied by RIP1 induction and ROS production. Solid and leukemic tumors are not affected by MC2392, but expression of PML-RARα conveys efficient MC2392-induced cell death. Our data suggest a model in which MC2392 binds to the RARα moiety and selectively inhibits the HDACs resident in the repressive complex responsible for the transcriptional impairment in APLs. Our findings provide proof-of-principle of the concept of a context-dependent targeted therapy.

Dnmt3L antagonizes DNA methylation at bivalent promoters and favors DNA methylation at gene bodies in ESCs.

The de novo DNA methyltransferase 3-like (Dnmt3L) is a catalytically inactive DNA methyltransferase that cooperates with Dnmt3a and Dnmt3b to methylate DNA. Dnmt3L is highly expressed in mouse embryonic stem cells (ESCs), but its function in these cells is unknown. Through genome-wide analysis of Dnmt3L knockdown in ESCs, we found that Dnmt3L is a positive regulator of methylation at the gene bodies of housekeeping genes and, more surprisingly, is also a negative regulator of methylation at promoters of bivalent genes. Dnmt3L is required for the differentiation of ESCs into primordial germ cells (PGCs) through the activation of the homeotic gene Rhox5. We demonstrate that Dnmt3L interacts with the Polycomb PRC2 complex in competition with the DNA methyltransferases Dnmt3a and Dnmt3b to maintain low methylation levels at the H3K27me3 regions. Thus, in ESCs, Dnmt3L counteracts the activity of de novo DNA methylases to maintain hypomethylation at promoters of bivalent developmental genes.

Integrative analysis of deep sequencing data identifies estrogen receptor early response genes and links ATAD3B to poor survival in breast cancer.

Identification of responsive genes to an extra-cellular cue enables characterization of pathophysiologically crucial biological processes. Deep sequencing technologies provide a powerful means to identify responsive genes, which creates a need for computational methods able to analyze dynamic and multi-level deep sequencing data. To answer this need we introduce here a data-driven algorithm, SPINLONG, which is designed to search for genes that match the user-defined hypotheses or models. SPINLONG is applicable to various experimental setups measuring several molecular markers in parallel. To demonstrate the SPINLONG approach, we analyzed ChIP-seq data reporting PolII, estrogen receptor α (ERα), H3K4me3 and H2A.Z occupancy at five time points in the MCF-7 breast cancer cell line after estradiol stimulus. We obtained 777 ERa early responsive genes and compared the biological functions of the genes having ERα binding within 20 kb of the transcription start site (TSS) to genes without such binding site. Our results show that the non-genomic action of ERα via the MAPK pathway, instead of direct ERa binding, may be responsible for early cell responses to ERα activation. Our results also indicate that the ERα responsive genes triggered by the genomic pathway are transcribed faster than those without ERα binding sites. The survival analysis of the 777 ERα responsive genes with 150 primary breast cancer tumors and in two independent validation cohorts indicated the ATAD3B gene, which does not have ERα binding site within 20 kb of its TSS, to be significantly associated with poor patient survival.

Whole-genome bisulfite sequencing of two distinct interconvertible DNA methylomes of mouse embryonic stem cells.

The use of two kinase inhibitors (2i) enables derivation of mouse embryonic stem cells (ESCs) in the pluripotent ground state. Using whole-genome bisulfite sequencing (WGBS), we show that male 2i ESCs are globally hypomethylated compared to conventional ESCs maintained in serum. In serum, female ESCs are hypomethyated similarly to male ESCs in 2i, and DNA methylation is further reduced in 2i. Regions with elevated DNA methylation in 2i strongly correlate with the presence of H3K9me3 on endogenous retroviruses (ERVs) and imprinted loci. The methylome of male ESCs in serum parallels postimplantation blastocyst cells, while 2i stalls ESCs in a hypomethylated, ICM-like state. WGBS analysis during adaptation of 2i ESCs to serum suggests that deposition of DNA methylation is largely random, while loss of DNA methylation during reversion to 2i occurs passively, initiating at TET1 binding sites. Together, our analysis provides insight into DNA methylation dynamics in cultured ESCs paralleling early developmental processes.

Comparative genome-wide DNA methylation analysis of colorectal tumor and matched normal tissues.

Aberrant DNA methylation often occurs in colorectal cancer (CRC). In our study we applied a genome-wide DNA methylation analysis approach, MethylCap-seq, to map the differentially methylated regions (DMRs) in 24 tumors and matched normal colon samples. In total, 2687 frequently hypermethylated and 468 frequently hypomethylated regions were identified, which include potential biomarkers for CRC diagnosis. Hypermethylation in the tumor samples was enriched at CpG islands and gene promoters, while hypomethylation was distributed throughout the genome. Using epigenetic data from human embryonic stem cells, we show that frequently hypermethylated regions coincide with bivalent loci in human embryonic stem cells. DNA methylation is commonly thought to lead to gene silencing; however, integration of publically available gene expression data indicates that 75% of the frequently hypermethylated genes were most likely already lowly or not expressed in normal tissue. Collectively, our study provides genome-wide DNA methylation maps of CRC, comprehensive lists of DMRs, and gives insights into the role of aberrant DNA methylation in CRC formation.

Sequential ChIP-bisulfite sequencing enables direct genome-scale investigation of chromatin and DNA methylation cross-talk.

Cross-talk between DNA methylation and histone modifications drives the establishment of composite epigenetic signatures and is traditionally studied using correlative rather than direct approaches. Here, we present sequential ChIP-bisulfite-sequencing (ChIP-BS-seq) as an approach to quantitatively assess DNA methylation patterns associated with chromatin modifications or chromatin-associated factors directly. A chromatin-immunoprecipitation (ChIP)-capturing step is used to obtain a restricted representation of the genome occupied by the epigenetic feature of interest, for which a single-base resolution DNA methylation map is then generated. When applied to H3 lysine 27 trimethylation (H3K27me3), we found that H3K27me3 and DNA methylation are compatible throughout most of the genome, except for CpG islands, where these two marks are mutually exclusive. Further ChIP-BS-seq-based analysis in Dnmt triple-knockout (TKO) embryonic stem cells revealed that total loss of CpG methylation is associated with alteration of H3K27me3 levels throughout the genome: H3K27me3 in localized peaks is decreased while broad local enrichments (BLOCs) of H3K27me3 are formed. At an even broader scale, these BLOCs correspond to regions of high DNA methylation in wild-type ES cells, suggesting that DNA methylation prevents H3K27me3 deposition locally and at a megabase scale. Our strategy provides a unique way of investigating global interdependencies between DNA methylation and other chromatin features.