Search

Histone modifications are associated with distinct transcriptional states, but it is unclear whether they instruct gene expression. To investigate this, we mutated histone H3.3 K9 and K27 residues in mouse embryonic stem cells (mESCs). Here, we find that H3.3K9 is essential for controlling specific distal intergenic regions and for proper H3K27me3 deposition at promoters. The H3.3K9A mutation resulted in decreased H3K9me3 at regions encompassing endogenous retroviruses and induced a gain of H3K27ac and nascent transcription. These changes in the chromatin environment unleashed cryptic enhancers, resulting in the activation of distinctive transcriptional programs and culminating in protein expression normally restricted to specialized immune cell types. The H3.3K27A mutant disrupted deposition and spreading of the repressive H3K27me3 mark, particularly impacting bivalent genes with higher basal level of H3.3 at promoters. Therefore, H3.3K9 and K27 crucially orchestrate repressive chromatin states atcis-regulatory elements and bivalent promoters, respectively, and instruct proper transcription in mESCs.

Among the biggest challenges in the post-GWAS (genome-wide association studies) era is the interpretation of disease-associated genetic variants in non-coding genomic regions. Enhancers have emerged as key players in mediating the effect of genetic variants on complex traits and diseases. Their activity is regulated by a combination of transcription factors (TFs), epigenetic changes and genetic variants. Several approaches exist to link enhancers to their target genes, and others that infer TF-gene connections. However, we currently lack a framework that systematically integrates enhancers into TF-gene regulatory networks. Furthermore, we lack an unbiased way of assessing whether inferred regulatory interactions are biologically meaningful. Here we present two methods, implemented as user-friendly R packages: GRaNIE (Gene Regulatory Network Inference including Enhancers) for building enhancer-based gene regulatory networks (eGRNs) and GRaNPA (Gene Regulatory Network Performance Analysis) for evaluating GRNs. GRaNIE jointly infers TF-enhancer, enhancer-gene and TF-gene interactions by integrating open chromatin data such as ATAC-Seq or H3K27ac with RNA-seq across a set of samples (e.g. individuals), and optionally also Hi-C data. GRaNPA is a general framework for evaluating the biological relevance of TF-gene GRNs by assessing their performance for predicting cell-type specific differential expression. We demonstrate the power of our tool-suite by investigating gene regulatory mechanisms in macrophages that underlie their response to infection and cancer, their involvement in common genetic diseases including autoimmune diseases, and identify the TF PURA as putative regulator of pro-inflammatory macrophage polarisation.Availability- GRaNIE: https://bioconductor.org/packages/release/bioc/html/GRaNIE.html- GRaNPA: https://git.embl.de/grp-zaugg/GRaNPAGraphical abstract

Bone marrow mesenchymal stromal cells (BMSCs) can differentiate into adipocytes and osteoblasts, and are important regulators of the haematopoietic system. Ageing associates with an increased ratio of bone marrow adipocytes to osteoblasts and immune dysregulation. Here, we carried out an integrative multiomics analysis of ATAC-Seq, RNA-Seq and proteomics data from primary human BMSCs in a healthy cohort age between 20 - 60. We identified age-sensitive elements uniquely affecting each molecular level where transcription is mostly spared, and characterised the underlying biological pathways, revealing the interplay of age-related gene expression mechanism changes spanning multiple gene regulatory layers. Through data integration with enhancer-mediated gene regulatory network analysis, we discovered that enhancers and transcription factors influence cell differentiation potential in the ageing BMSCs. By combining our results with genome-wide association study data, we found that age-specific changes could contribute to common traits related to BMSC-derived tissues such as bone and adipose tissue, and to immune-related traits on a systemic level such as asthma. We demonstrate here that a multiomics approach is crucial for unravelling complex information, providing new insights on how ageing contributes to bone marrow- and immune-related disorders.

The tumour microenvironment and genetic alterations collectively influence drug efficacy in cancer, but current evidence is limited to small scale studies and systematic analyses are lacking. We chose Chronic Lymphocytic Leukaemia (CLL), the most common leukaemia in adults, as a model disease to study this complex interplay systematically. We performed a combinatorial assay using 12 drugs individually co-applied with each of 17 microenvironmental stimuli in 192 primary CLL samples, generating a comprehensive map of drug-microenvironment interactions in CLL. This data was combined with whole-exome sequencing, DNA-methylation, RNA-sequencing and copy number variant annotation. Our assay identified four distinct CLL subgroups that differed in their responses to the panel of microenvironmental stimuli. These subgroups were characterized by distinct clinical outcomes independently of known prognostic markers. We investigated the effect of CLL- specific recurrent genetic alterations on microenvironmental responses and identified trisomy 12 as an amplifier of multiple microenvironmental stimuli. We further quantified the impact of microenvironmental stimuli on drug response, confirmed known interactions such as Interleukin (IL) 4 mediated resistance to B cell receptor (BCR) inhibitors, and identified new interactions such as Interferon-γ induced resistance to BCR inhibitors. Finally, we identified interactions which were limited to genetic subgroups. Resistance to chemotherapeutics, such as Fludarabine, induced by Toll-Like Receptor (TLR) agonists could be observed in IGHV unmutated patient samples and IGHV mutated samples with trisomy 12. In-vivo relevance was investigated in CLL-infiltrated lymph nodes, which showed increased IL4 and TLR signalling activity compared to healthy samples (pWe provide a publicly available resource (www.dietrichlab.de/CLL_Microenvironment/) which uncovers tumour cell extrinsic influences on drug response and disease progression in CLL, and how these interactions are modulated by cell intrinsic molecular features.

Neuronal activity induced by brain-derived neurotrophic factor (BDNF) triggers gene expression, which is crucial for neuronal survival, differentiation, synaptic plasticity, memory formation, and neurocognitive health. However, its role in chromatin regulation is unclear. Here, using temporal profiling of chromatin accessibility and transcription in mouse primary cortical neurons upon either BDNF stimulation or depolarization (KCl), we identify features that define BDNF-specific chromatin-to-gene expression programs. Enhancer activation is an early event in the regulatory control of BDNF-treated neurons, where the bZIP motif-binding Fos protein pioneered chromatin opening and cooperated with co-regulatory transcription factors (Homeobox, EGRs, and CTCF) to induce transcription. Deleting cis-regulatory sequences decreased BDNF-mediated Arc expression, a regulator of synaptic plasticity. BDNF-induced accessible regions are linked to preferential exon usage by neurodevelopmental disorder-related genes and heritability of neuronal complex traits, which were validated in human iPSC-derived neurons. Thus, we provide a comprehensive view of BDNF-mediated genome regulatory features using comparative genomic approaches to dissect mammalian neuronal activity.

Nucleic acid and histone modifications critically depend on central metabolism for substrates and co-factors. Although a few enzymes related to the formation of these required metabolites have been reported in the nucleus, the corresponding metabolic pathways are considered to function elsewhere in the cell. Here we show that a substantial part of the mitochondrial tricarboxylic acid (TCA) cycle, the biosynthetic hub of epigenetic modification factors, is operational also in the nucleus. Using13C-tracer analysis, we identified activity of glutamine-to-fumarate, citrate-to-succinate, and glutamine-to-aspartate routes in the nuclei ofHeLacells. Proximity labeling mass-spectrometry revealed a spatial vicinity of the involved enzymes with core nuclear proteins, supporting their nuclear location. We further show nuclear localization of aconitase 2 and 2-oxoglutarate dehydrogenase in mouse embryonic stem cells. Together, our results demonstrate operation of an extended metabolic pathway in the nucleus warranting a revision of the canonical view on metabolic compartmentalization and gene expression regulation.

The activation induced cytidine deaminase/apolipoprotein B editing complex (AID/APOBEC) family comprises several nucleic acid editors with roles ranging from antibody diversification to mRNA editing. APOBEC2, an evolutionarily conserved member of this family, has neither an established substrate nor a mechanism of action, however genetic evidence suggests functional relevance in tissues such as muscle. Here, we demonstrate that in muscle, APOBEC2 does not have any of the attributed molecular functions of the AID/APOBEC family, such as RNA editing, DNA demethylation, or DNA mutation. Instead, we show that APOBEC2 occupies chromatin at promoter regions of certain genes, whose expression is repressed during muscle cell differentiation. We further demonstrate that APOBEC2 on one hand binds promoter region DNA directly and in a sequence specific fashion, while on the other it interacts with HDAC transcriptional corepressor complexes. Therefore, APOBEC2, by actively repressing the expression of non-myogenesis pathway genes, plays a key role in enforcing the proper establishment of muscle cell fate.

Regulation of haematopoiesis during human development remains poorly defined. Here, we applied single-cell (sc)RNA-Seq and scATAC-Seq analysis to over 8,000 human immunophenotypic blood cells from foetal liver and bone marrow. We inferred their differentiation trajectory and identified three highly proliferative oligopotent progenitor populations downstream from haematopoietic stem cell/multipotent progenitors (HSC/MPPs). Along this trajectory, we observed opposing patterns of chromatin accessibility and differentiation that coincided with dynamic changes in the activity of distinct lineage-specific transcription factors. Integrative analysis of chromatin accessibility and gene expression revealed extensive epigenetic but not transcriptional priming of HSC/MPPs prior to their lineage commitment. Finally, we refined and functionally validated the sorting strategy for the HSC/MPPs and achieved around 90% enrichment. Our study provides a useful framework for future investigation of human developmental haematopoiesis in the context of blood pathologies and regenerative medicine.

For most biological processes, organisms must respond to extrinsic cues, while maintaining essential gene expression programs. Although studied extensively in single cells, it is still unclear how variation is controlled in multicellular organisms. Here, we used a machine-learning approach to identify genomic features that are predictive of genes with high versus low variation in their expression across individuals, using bulk data to remove stochastic cell-to-cell variation. Using embryonic gene expression across 75 Drosophila isogenic lines, we identify features predictive of expression variation, while controlling for expression level. Genes with low variation fall into two classes, indicating they employ different mechanisms to maintain a robust expression. In contrast, genes with high variation seem to lack both types of stabilizing mechanisms. Applying the framework to human tissues from GTEx revealed similar predictive features, indicating that promoter architecture is an ancient mechanism to control expression variation. Remarkably, expression variation features could also predict differential expression upon stress in both Drosophila and human. Differential gene expression signatures may therefore be partially explained by genetically encoded gene-specific features, unrelated to the studied treatment.

Transcription factor (TF) activity is an important read-out of cellular signalling pathways and thus to assess regulatory differences across conditions. However, current technologies lack the ability to simultaneously assess activity changes for multiple TFs and in particular to determine whether a specific TF acts globally as transcriptional repressor or activator. To this end, we introduce a widely applicable genome-wide methoddiffTFto assess differential TF activity and to classify TFs as activator or repressor (available athttps://git.embl.de/grp-zaugg/diffTF). This is done by integrating any type of genome-wide chromatin accessibility data with RNA-Seq data and in-silico predicted TF binding sites. We corroborated the classification of TFs into repressors and activators by three independent analyses based on enrichments of active/repressive chromatin states, correlation of TF activity with gene expression, and activator-and repressor-specific chromatin footprints. To show the power ofdiffTF, we present two case studies: First, we applieddiffTFin to a large ATAC-Seq/RNA-Seq dataset comparing mutated and unmutated chronic lymphocytic leukemia samples, where we identified dozens of known (40%) and potentially novel (60%) TFs that are differentially active. We were also able to classify almost half of them as either repressor and activator. Second, we applieddiffTFto a small ATAC-Seq/RNA-Seq data set comparing two cell types along the hematopoietic differentiation trajectory (multipotent progenitors – MPP – versus granulocyte-macrophage progenitors – GMP). Here we identified the known drivers of differentiation and found that the majority of the differentially active TFs are transcriptional activators. Overall,diffTFwas able to recover the known TFs in both case studies, additionally identified TFs that have been less well characterized in the given condition, and provides a classification of the TFs into transcriptional activators and repressors.

The epigenetic regulator TET2 is frequently mutated in hematological diseases. Mutations have been shown to arise in hematopoietic stem cells early in disease development, lead to altered DNA methylation landscapes and to an increased risk of hematopoietic malignancy. Here, we show by genome-wide mapping of TET2 binding sites in different cell types that TET2 localizes to regions of open chromatin and cell-type specific enhancers. We find that deletion of Tet2 in native hematopoiesis as well as fully transformed Acute Myeloid Leukemia (AML) results in changes in transcription factor (TF) activity within these regions, and we demonstrate that loss of TET2 leads to enzymatic activity-dependent attenuation of chromatin binding of the hematopoietic TF CDX4. Together, these findings demonstrate that TET2 activity shapes the local chromatin environment at enhancers to facilitate TF binding and provide a compelling example of how epigenetic dysregulation can affect gene expression patterns and drive disease development.

Hypothesis weighting is a powerful approach for improving the power of data analyses that employ multiple testing. However, in general it is not evident how to choose the weights in a data-dependent manner. We describe independent hypothesis weighting (IHW), a method for making use of informative covariates that are independent of the test statistic under the null, but informative of each test’s power or prior probability of the null hypothesis. Covariates can be continuous or categorical and need not fulfill any particular assumptions. The method increases statistical power in applications while controlling the false discovery rate (FDR) and produces additional insight by revealing the covariate-weight relationship. Independent hypothesis weighting is a practical approach to discovery of associations in large datasets.

Nucleosomes play an important role in gene regulation. Molecular studies observed that nucleosome binding in promoters tends to be repressive. In contrast, genomic studies have delivered conflicting results: An analysis of yeast grown on diverse carbon sources reported that nucleosome occupancies remain largely unchanged between conditions, whereas a study of the heat-shock response suggested that nucleosomes get evicted at promoters of genes with increased expression. Consequently, there are few general principles that capture the relationship between chromatin organization and transcriptional regulation. Here, we present a qualitative model for nucleosome positioning in Saccharomyces cerevisiae that helps explain important properties of gene expression. By integrating publicly available data sets, we observe that promoter-bound nucleosomes assume one of four discrete configurations that determine the active and silent transcriptional states of a gene, but not its expression level. In TATA-box-containing promoters, nucleosome architecture indicates the amount of transcriptional noise. We show that >20% of genes switch promoter states upon changes in cellular conditions. The data suggest that DNA-binding transcription factors together with chromatin-remodeling enzymes are primarily responsible for the nucleosome architecture. Our model for promoter nucleosome architecture reconciles genome-scale findings with molecular studies; in doing so, we establish principles for nucleosome positioning and gene expression that apply not only to individual genes, but across the entire genome. The study provides a stepping stone for future models of transcriptional regulation that encompass the intricate interplay between cis- and trans-acting factors, chromatin, and the core transcriptional machinery.