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MYT1L is an autism spectrum disorder (ASD)-associated transcription factor that is expressed in virtually all neurons throughout life. How MYT1L mutations cause neurological phenotypes and whether they can be targeted remains enigmatic. Here, we examine the effects of MYT1L deficiency in human neurons and mice. Mutant mice exhibit neurodevelopmental delays with thinner cortices, behavioural phenotypes, and gene expression changes that resemble those of ASD patients. MYT1L target genes, including WNT and NOTCH, are activated upon MYT1L depletion and their chemical inhibition can rescue delayed neurogenesis in vitro. MYT1L deficiency also causes upregulation of the main cardiac sodium channel, SCN5A, and neuronal hyperactivity, which could be restored by shRNA-mediated knockdown of SCN5A or MYT1L overexpression in postmitotic neurons. Acute application of the sodium channel blocker, lamotrigine, also rescued electrophysiological defects in vitro and behaviour phenotypes in vivo. Hence, MYT1L mutation causes both developmental and postmitotic neurological defects. However, acute intervention can normalise resulting electrophysiological and behavioural phenotypes in adulthood.

Cryo-electron tomograms capture a wealth of structural information on the molecular constituents of cells and tissues. We present DeePiCt (deep picker in context), an open-source deep-learning framework for supervised segmentation and macromolecular complex localization in cryo-electron tomography. To train and benchmark DeePiCt on experimental data, we comprehensively annotated 20 tomograms of Schizosaccharomyces pombe for ribosomes, fatty acid synthases, membranes, nuclear pore complexes, organelles, and cytosol. By comparing DeePiCt to state-of-the-art approaches on this dataset, we show its unique ability to identify low-abundance and low-density complexes. We use DeePiCt to study compositionally distinct subpopulations of cellular ribosomes, with emphasis on their contextual association with mitochondria and the endoplasmic reticulum. Finally, applying pre-trained networks to a HeLa cell tomogram demonstrates that DeePiCt achieves high-quality predictions in unseen datasets from different biological species in a matter of minutes. The comprehensively annotated experimental data and pre-trained networks are provided for immediate use by the community.

Precise control of gene expression requires the coordinated action of multiple factors at cis-regulatory elements. We recently developed single-molecule footprinting to simultaneously resolve the occupancy of multiple proteins including transcription factors, RNA polymerase II and nucleosomes on single DNA molecules genome-wide. The technique combines the use of cytosine methyltransferases to footprint the genome with bisulfite sequencing to resolve transcription factor binding patterns at cis-regulatory elements. DNA footprinting is performed by incubating permeabilized nuclei with recombinant methyltransferases. Upon DNA extraction, whole-genome or targeted bisulfite libraries are prepared and loaded on Illumina sequencers. The protocol can be completed in 4-5 d in any laboratory with access to high-throughput sequencing. Analysis can be performed in 2 d using a dedicated R package and requires access to a high-performance computing system. Our method can be used to analyze how transcription factors cooperate and antagonize to regulate transcription.

Enhancers are genomic sequences that play a key role in regulating tissue-specific gene expression levels. An increasing number of diseases are linked to impaired enhancer function through chromosomal rearrangement, genetic variation within enhancers, or epigenetic modulation. Here, we review how these enhancer disruptions have recently been implicated in congenital disorders, cancers, and common complex diseases and address the implications for diagnosis and treatment. Although further fundamental research into enhancer function, target genes, and context is required, enhancer-targeting drugs and gene editing approaches show great therapeutic promise for a range of diseases.

Progress in the generation of Hematopoietic Stem and Progenitor Cells (HSPCs) in vitro and ex vivo has been built on the knowledge of developmental hematopoiesis, underscoring the importance of understanding this process. HSPCs emerge within the embryonic vasculature through an Endothelial-to-Hematopoietic Transition (EHT). The transcriptional regulator Tal1 exerts essential functions in the earliest stages of blood development, but is considered dispensable for the EHT. Nevertheless, Tal1 is expressed with its binding partner Lmo2 and it homologous Lyl1 in endothelial and transitioning cells at the time of EHT. Here, we investigated the function of these genes using a mouse embryonic-stem cell (mESC)-based differentiation system to model hematopoietic development. We showed for the first time that the expression of TAL1 in endothelial cells is crucial to ensure the efficiency of the EHT process and a sustained hematopoietic output. Our findings uncover an important function of Tal1 during the EHT, thus filling the current gap in the knowledge of the role of this master gene throughout the whole process of hematopoietic development.

The tumour microenvironment and genetic alterations collectively influence drug efficacy in cancer, but current evidence is limited and systematic analyses are lacking. Using chronic lymphocytic leukaemia (CLL) as a model disease, we investigated the influence of 17 microenvironmental stimuli on 12 drugs in 192 genetically characterised patient samples. Based on microenvironmental response, we identified four subgroups with distinct clinical outcomes beyond known prognostic markers. Response to multiple microenvironmental stimuli was amplified in trisomy 12 samples. Trisomy 12 was associated with a distinct epigenetic signature. Bromodomain inhibition reversed this epigenetic profile and could be used to target microenvironmental signalling in trisomy 12 CLL. We quantified the impact of microenvironmental stimuli on drug response and their dependence on genetic alterations, identifying interleukin 4 (IL4) and Toll-like receptor (TLR) stimulation as the strongest actuators of drug resistance. IL4 and TLR signalling activity was increased in CLL-infiltrated lymph nodes compared with healthy samples. High IL4 activity correlated with faster disease progression. The publicly available dataset can facilitate the investigation of cell-extrinsic mechanisms of drug resistance and disease progression.

Physical interactions between distal regulatory elements have a key role in regulating gene expression, but the extent to which these interactions vary between cell types and contribute to cell-type-specific gene expression remains unclear. Here, to address these questions as part of phase III of the Encyclopedia of DNA Elements (ENCODE), we mapped cohesin-mediated chromatin loops, using chromatin interaction analysis by paired-end tag sequencing (ChIA-PET), and analysed gene expression in 24 diverse human cell types, including core ENCODE cell lines. Twenty-eight per cent of all chromatin loops vary across cell types; these variations modestly correlate with changes in gene expression and are effective at grouping cell types according to their tissue of origin. The connectivity of genes corresponds to different functional classes, with housekeeping genes having few contacts, and dosage-sensitive genes being more connected to enhancer elements. This atlas of chromatin loops complements the diverse maps of regulatory architecture that comprise the ENCODE Encyclopedia, and will help to support emerging analyses of genome structure and function., A map of cohesin-mediated chromatin loops in 24 types of human cells identifies loops that show cell-type-specific variation, indicating that chromatin loops may help to specify cell-specific gene expression programs and functions.

Recent high-throughput transcription factor (TF) binding assays revealed that TF cooperativity is a widespread phenomenon. However, a global mechanistic and functional understanding of TF cooperativity is still lacking. To address this, here we introduce a statistical learning framework that provides structural insight into TF cooperativity and its functional consequences based on next generation sequencing data. We identify DNA shape as driver for cooperativity, with a particularly strong effect for Forkhead-Ets pairs. Follow-up experiments reveal a local shape preference at the Ets-DNA-Forkhead interface and decreased cooperativity upon loss of the interaction. Additionally, we discover many functional associations for cooperatively bound TFs. Examination of the link between FOXO1:ETV6 and lymphomas reveals that their joint expression levels improve patient clinical outcome stratification. Altogether, our results demonstrate that inter-family cooperative TF binding is driven by position-specific DNA readout mechanisms, which provides an additional regulatory layer for downstream biological functions., Although transcription factor (TF) cooperativity is widespread, a global mechanistic understanding of the role of TF cooperativity is still lacking. Here the authors introduce a statistical learning framework that provides structural insight into TF cooperativity and its functional consequences based on next generation sequencing data and provide mechanistic insights into TF cooperativity and its impact on protein-phenotype interactions.

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.

Somatic mutations in DNA Methyltransferase 3A (DNMT3A) are among the most frequent alterations in clonal hematopoiesis (CH) and Acute Myeloid Leukemia (AML), with a hotspot in exon 23 at arginine 882 (DNMT3A-R882). Here we demonstrate that DNMT3A-R882H-dependent CH- and AML cells are specifically susceptible to the hypomethylating agent azacytidine (AZA). Addition of AZA to chemotherapy prolonged AML survival solely in patients with DNMT3A-R882 mutation, suggesting its potential as a novel predictive marker for AZA response. AML and CH mouse models confirmed AZA susceptibility specifically in DNMT3A-R882H-expressing cells. Hematopoietic stem and progenitor cells expressing DNMT3A-R882H exhibited cell-autonomous viral mimicry response as a result of focal DNA hypomethylation at retrotransposon sequences. Administration of AZA boosted hypomethylation of retrotransposons specifically in DNMT3A-R882H expressing cells and maintained elevated levels of canonical interferon-stimulated genes (ISGs), thus leading to suppressed protein translation and increased apoptosis.

Precise control of gene expression requires the coordinated action of multiple factors at cis-regulatory elements (CREs). We recently developed Single Molecule Footprinting (SMF) to simultaneously resolve the occupancy of multiple proteins including Transcription Factors (TFs), RNA Pol II (Pol II) and nucleosomes on single DNA molecules genome-wide. The technique combines the use of cytosine methyltransferases to footprint the genome with bisulfite sequencing to resolve TF binding patterns at CREs. DNA footprinting is performed by incubating permeabilized nuclei with recombinant methyltransferases. Upon DNA extraction, whole genome or targeted bisulfite libraries are prepared and loaded on Illumina sequencers. The protocol can be completed in 4-5 days. Analysis can be performed in 2 days using a dedicated R package. The protocol can be executed in any laboratory with access to high- throughput sequencing. Our method can be used to analyse how TFs cooperate and antagonize to regulate transcription.

Summary Regulation of hematopoiesis during human development remains poorly defined. Here we applied single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) to over 8,000 human immunophenotypic blood cells from fetal liver and bone marrow. We inferred their differentiation trajectory and identified three highly proliferative oligopotent progenitor populations downstream of hematopoietic stem cells (HSCs)/multipotent progenitors (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 HSCs/MPPs prior to their lineage commitment. Finally, we refined and functionally validated the sorting strategy for the HSCs/MPPs and achieved around 90% enrichment. Our study provides a useful framework for future investigation of human developmental hematopoiesis in the context of blood pathologies and regenerative medicine., Graphical abstract, Highlights • The epigenetic and transcriptional landscape of human fetal hematopoiesis • Blood stem cells differentiate into three distinct oligopotent progenitor populations • Changes in motif accessibility in blood stem cells precede transcriptional priming • Refined sorting strategy to isolate and enrich for human fetal blood stem cells, Ranzoni et al. provide a detailed transcriptional and chromatin accessibility map of fetal liver and bone marrow hematopoietic stem cells (HSCs). Within HSCs, they revealed extensive epigenetic but not transcriptional priming. They identified transcriptional and functional differences between HSCs from liver and bone marrow.

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.

For most biological processes, organisms must respond to extrinsic cues, while maintaining essential gene expression programmes. 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 (controlling for expression level), many of which are promoter‐related. Genes with low variation fall into two classes reflecting different mechanisms to maintain robust expression, while genes with high variation seem to lack both types of stabilizing mechanisms. Applying this framework to humans revealed similar predictive features, indicating that promoter architecture is an ancient mechanism to control expression variation. Remarkably, expression variation features could also partially predict differential expression after diverse perturbations in both Drosophila and humans. Differential gene expression signatures may therefore be partially explained by genetically encoded gene‐specific features, unrelated to the studied treatment., Conserved genomic features predictive of gene expression variation across individuals are identified in Drosophila and human using a machine‐learning approach. The same features predict differential expression upon perturbation revealing a link between variation and differential expression.

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.

Environmental and epigenetic factors often play an important role in polygenic disorders. However, how such factors affect disease-specific tissues at the molecular level remains to be understood. Here, we address this in pulmonary arterial hypertension (PAH). We obtain pulmonary arterial endothelial cells (PAECs) from lungs of patients and controls (n = 19), and perform chromatin, transcriptomic and interaction profiling. Overall, we observe extensive remodeling at active enhancers in PAH PAECs and identify hundreds of differentially active TFs, yet find very little transcriptomic changes in steady-state. We devise a disease-specific enhancer-gene regulatory network and predict that primed enhancers in PAH PAECs are activated by the differentially active TFs, resulting in an aberrant response to endothelial signals, which could lead to disturbed angiogenesis and endothelial-to-mesenchymal-transition. We validate these predictions for a selection of target genes in PAECs stimulated with TGF-β, VEGF or serotonin. Our study highlights the role of chromatin state and enhancers in disease-relevant cell types of PAH., Pulmonary arterial hypertension (PAH) is a heterogeneous disease, causing severe breathing problems and cardiac morbidity. Here, the authors study chromatin marks in pulmonary arterial endothelial cells from PAH patients and controls and find changes in transcription factor and enhancer activity that suggest an aberrant response to signalling in PAH.

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.

Summary: Transcription factors (TFs) regulate many cellular processes and can therefore serve as readouts of the signaling and regulatory state. Yet for many TFs, the mode of action—repressing or activating transcription of target genes—is unclear. Here, we present diffTF (https://git.embl.de/grp-zaugg/diffTF) to calculate differential TF activity (basic mode) and classify TFs into putative transcriptional activators or repressors (classification mode). In basic mode, it combines genome-wide chromatin accessibility/activity with putative TF binding sites that, in classification mode, are integrated with RNA-seq. We apply diffTF to compare (1) mutated and unmutated chronic lymphocytic leukemia patients and (2) two hematopoietic progenitor cell types. In both datasets, diffTF recovers most known biology and finds many previously unreported TFs. It classifies almost 40% of TFs based on their mode of action, which we validate experimentally. Overall, we demonstrate that diffTF recovers known biology, identifies less well-characterized TFs, and classifies TFs into transcriptional activators or repressors. : Berest et al. present a computational tool (diffTF) to estimate differential TF activity and classify TFs into activators or repressors. It requires active chromatin data (accessibility/ChIP-seq) and integrates with RNA-seq for classification. The authors apply it to two case studies (CLL and hematopoietic differentiation) and validate their predictions experimentally. Keywords: transcription factor, ATAC-seq, CLL, transcriptional activator and repressor, RNA-seq, TF footprint, open chromatin, snakemake, multiomics data integration

Summary Generation of induced oligodendrocyte progenitor cells (iOPCs) from somatic fibroblasts is a strategy for cell-based therapy of myelin diseases. However, iOPC generation is inefficient, and the resulting iOPCs exhibit limited expansion and differentiation competence. Here we overcome these limitations by transducing an optimized transcription factor combination into a permissive donor phenotype, the pericyte. Pericyte-derived iOPCs (PC-iOPCs) are stably expandable and functionally myelinogenic with high differentiation competence. Unexpectedly, however, we found that PC-iOPCs are metastable so that they can produce myelination-competent oligodendrocytes or revert to their original identity in a context-dependent fashion. Phenotypic reversion of PC-iOPCs is tightly linked to memory of their original transcriptome and epigenome. Phenotypic reversion can be disconnected from this donor cell memory effect, and in vivo myelination can eventually be achieved by transplantation of O4+ pre-oligodendrocytes. Our data show that donor cell source and memory can contribute to the fate and stability of directly converted cells.

Understanding how the genome is compacted in a highly ordered structure that fits in the eukaryotic nucleus, while keeping its capacity of orchestrating the functionality of the cell, is one of the long-standing questions in biology. While the recent technological advances in chromosome conformation capture experiments have provided extensive knowledge about the structural organisation of chromatin, our understanding of the functional impact of these arrangements on downstream processes, and how structure translates into function, is just beginning to emerge. In this review we summarize our current knowledge of the three-dimensional chromatin organisation, the mechanisms of how it is established and maintained, and the functional impact it has on gene regulation and complex phenotypes. We will end with a discussion on the future developments of this fast-paced field.

Cellular differentiation requires dramatic changes in chromatin organization, transcriptional regulation, and protein production. To understand the regulatory connections between these processes, we generated proteomic, transcriptomic, and chromatin accessibility data during differentiation of mouse embryonic stem cells (ESCs) into postmitotic neurons and found extensive associations between different molecular layers within and across differentiation time points. We observed that SOX2, as a regulator of pluripotency and neuronal genes, redistributes from pluripotency enhancers to neuronal promoters during differentiation, likely driven by changes in its protein interaction network. We identified ATRX as a major SOX2 partner in neurons, whose co-localization correlated with an increase in active enhancer marks and increased expression of nearby genes, which we experimentally confirmed for three loci. Collectively, our data provide key insights into the regulatory transformation of SOX2 during neuronal differentiation, and we highlight the significance of multi-omic approaches in understanding gene regulation in complex systems.

FLT3, DNMT3A, and NPM1 are the most frequently mutated genes in cytogenetically normal acute myeloid leukemia (AML), but little is known about how these mutations synergize upon cooccurrence. Here we show that triple-mutated AML is characterized by high leukemia stem cell (LSC) frequency, an aberrant leukemia-specific GPR56highCD34low immunophenotype, and synergistic upregulation of Hepatic Leukemia Factor (HLF). Cell sorting based on the LSC marker GPR56 allowed isolation of triple-mutated from DNMT3A/NPM1 double-mutated subclones. Moreover, in DNMT3A R882-mutated patients, CpG hypomethylation at the HLF transcription start site correlated with high HLF mRNA expression, which was itself associated with poor survival. Loss of HLF via CRISPR/Cas9 significantly reduced the CD34+GPR56+ LSC compartment of primary human triple-mutated AML cells in serial xenotransplantation assays. HLF knockout cells were more actively cycling when freshly harvested from mice, but rapidly exhausted when reintroduced in culture. RNA sequencing of primary human triple-mutated AML cells after shRNA-mediated HLF knockdown revealed the NOTCH target Hairy and Enhancer of Split 1 (HES1) and the cyclin-dependent kinase inhibitor CDKN1C/p57 as novel targets of HLF, potentially mediating these effects. Overall, our data establish HLF as a novel LSC regulator in this genetically defined high-risk AML subgroup.

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 method diffTF to assess differential TF activity and to classify TFs as activator or repressor (available at https://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 of diffTF, we present two case studies: First, we applied diffTF in 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 applied diffTF to 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, diffTF was 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.

Backmasking is a recording technique used to hide a sound or message in a music track in reverse, meaning that it is only audible when the record is played backwards. Analogously, the compact yeast genome encodes for diverse sources of information such as overlapping coding and non-coding transcripts, and protein-binding sites on the two complementary DNA strands. Examples are the consensus binding site sequences of the RNA-binding proteins Nrd1 and Nab3 that target non-coding transcripts for degradation. Here, by examining the overlap of stable (SUTs, stable unannotated transcripts) and unstable (CUTs, cryptic unstable transcripts) transcripts with protein-coding genes, we show that the predicted Nrd1 and Nab3-binding site sequences occur at differing frequencies. They are always depleted in the sense direction of protein-coding genes, thus avoiding degradation of the transcript. However in the antisense direction, predicted binding sites occur at high frequencies in genes with overlapping unstable ncRNAs (CUTs), so limiting the availability of non-functional transcripts. In contrast they are depleted in genes with overlapping stable ncRNAs (SUTs), presumably to avoid degrading the non-coding transcript. The protein-coding genes maintain similar amino-acid contents, but they display distinct codon usages so that Nrd1 and Nab3-binding sites can arise at differing frequencies in antisense depending on the overlapping transcript type. Our study demonstrates how yeast has evolved to encode multiple layers of information-protein-coding genes in one strand and the relative chance of degrading antisense RNA in the other strand-in the same regions of a compact genome.

For multiple hypothesis testing in genomics and other large-scale data analyses, the independent hypothesis weighting (IHW) approach uses data-driven P-value weight assignment to improve power while controlling the false discovery rate. Hypothesis weighting improves the power of large-scale multiple testing. We describe independent hypothesis weighting (IHW), a method that assigns weights using covariates independent of the P-values under the null hypothesis but informative of each test's power or prior probability of the null hypothesis ( http://www.bioconductor.org/packages/IHW ). IHW increases power while controlling the false discovery rate and is a practical approach to discovering associations in genomics, high-throughput biology and other large data sets.

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.

SummaryDeciphering the impact of genetic variants on gene regulation is fundamental to understanding human disease. Although gene regulation often involves long-range interactions, it is unknown to what extent non-coding genetic variants influence distal molecular phenotypes. Here, we integrate chromatin profiling for three histone marks in lymphoblastoid cell lines (LCLs) from 75 sequenced individuals with LCL-specific Hi-C and ChIA-PET-based chromatin contact maps to uncover one of the largest collections of local and distal histone quantitative trait loci (hQTLs). Distal QTLs are enriched within topologically associated domains and exhibit largely concordant variation of chromatin state coordinated by proximal and distal non-coding genetic variants. Histone QTLs are enriched for common variants associated with autoimmune diseases and enable identification of putative target genes of disease-associated variants from genome-wide association studies. These analyses provide insights into how genetic variation can affect human disease phenotypes by coordinated changes in chromatin at interacting regulatory elements.

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of regulatory genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single or small sets of tissues. Here, we have reconstructed networks that capture a much more complete set of regulatory relationships, specifically including regulation of relative isoform abundance and splicing, and tissue-specific connections unique to each of a diverse set of tissues. Using the Genotype-Tissue Expression (GTEx) project v6 RNA-sequencing data across 44 tissues in 449 individuals, we evaluated shared and tissue-specific network relationships. First, we developed a framework called Transcriptome Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the complex interplay between the regulation of splicing and transcription. We built TWNs for sixteen tissues, and found that hubs with isoform node neighbors in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome, and providing a set of candidate shared and tissue-specific regulatory hub genes. Next, we used a Bayesian biclustering model that identifies network edges between genes with co-expression in a single tissue to reconstruct tissue-specific networks (TSNs) for 27 distinct GTEx tissues and for four subsets of related tissues. Using both TWNs and TSNs, we characterized gene co-expression patterns shared across tissues. Finally, we found genetic variants associated with multiple neighboring nodes in our networks, supporting the estimated network structures and identifying 33 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships between genes in the human transcriptome, including tissue-specificity of gene co-expression, regulation of splicing, and the coordinated impact of genetic variation on transcription.

Most genomes, including yeast Saccharomyces cerevisiae, are pervasively transcribed producing numerous non-coding RNAs, many of which are unstable and eliminated by nuclear or cytoplasmic surveillance pathways. We previously showed that accumulation of PHO84 antisense RNA (asRNA), in cells lacking the nuclear exosome component Rrp6, is paralleled by repression of sense transcription in a process dependent on the Hda1 histone deacetylase (HDAC) and the H3K4 histone methyl transferase Set1. Here we investigate this process genome-wide and measure the whole transcriptome of various histone modification mutants in a Δrrp6 strain using tiling arrays. We confirm widespread occurrence of potentially antisense-dependent gene regulation and identify three functionally distinct classes of genes that accumulate asRNAs in the absence of Rrp6. These classes differ in whether the genes are silenced by the asRNA and whether the silencing is HDACs and histone methyl transferase-dependent. Among the distinguishing features of asRNAs with regulatory potential, we identify weak early termination by Nrd1/Nab3/Sen1, extension of the asRNA into the open reading frame promoter and dependence of the silencing capacity on Set1 and the HDACs Hda1 and Rpd3 particularly at promoters undergoing extensive chromatin remodelling. Finally, depending on the efficiency of Nrd1/Nab3/Sen1 early termination, asRNA levels are modulated and their capability of silencing is changed.

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.

The CCCTC-binding factor (CTCF) is known to establish long-range DNA contacts that alter the three-dimensional architecture of chromatin, but how the presence of CTCF influences nearby gene expression is still poorly understood. Here, we analyze CTCF chromatin immunoprecipitation sequencing, RNA sequencing, and Hi-C data, together with genotypes from a healthy human cohort, and measure statistical associations between inter-individual variability in CTCF binding and alternative exon usage. We demonstrate that CTCF-mediated chromatin loops between promoters and intragenic regions are prevalent and that when exons are in physical proximity with their promoters, CTCF binding correlates with exon inclusion in spliced mRNA. Genome-wide, CTCF-bound exons are enriched for genes involved in signaling and cellular stress-response pathways. Structural analysis of three specific examples, checkpoint kinase 2 (CHK2), CDC-like kinase 3 (CLK3), and euchromatic histone-lysine N-methyltransferase (EHMT1), suggests that CTCF-mediated exon inclusion is likely to downregulate enzyme activity by disrupting annotated protein domains. In total, our study suggests that alternative exon usage is regulated by CTCF-dependent chromatin structure.

N{sup 5}-Carboxyaminoimidazole ribonucleotide mutase (N{sup 5}-CAIR mutase or PurE) from Escherichia coli catalyzes the reversible interconversion of N{sup 5}-CAIR to carboxyaminoimidazole ribonucleotide (CAIR) with direct CO{sub 2} transfer. Site-directed mutagenesis, a pH-rate profile, DFT calculations, and X-ray crystallography together provide new insight into the mechanism of this unusual transformation. These studies suggest that a conserved, protonated histidine (His45) plays an essential role in catalysis. The importance of proton transfers is supported by DFT calculations on CAIR and N{sup 5}-CAIR analogues in which the ribose 5'-phosphate is replaced with a methyl group. The calculations suggest that the nonaromatic tautomer of CAIR (isoCAIR) is only 3.1 kcal/mol higher in energy than its aromatic counterpart, implicating this species as a potential intermediate in the PurE-catalyzed reaction. A structure of wild-type PurE cocrystallized with 4-nitroaminoimidazole ribonucleotide (NO{sub 2}-AIR, a CAIR analogue) and structures of H45N and H45Q PurEs soaked with CAIR have been determined and provide the first insight into the binding of an intact PurE substrate. A comparison of 19 available structures of PurE and PurE mutants in apo and nucleotide-bound forms reveals a common, buried carboxylate or CO{sub 2} binding site for CAIR and N{sup 5}-CAIR in a hydrophobic pocket in whichmore » the carboxylate or CO{sub 2} interacts with backbone amides. This work has led to a mechanistic proposal in which the carboxylate orients the substrate for proton transfer from His45 to N{sup 5}-CAIR to form an enzyme-bound aminoimidazole ribonucleotide (AIR) and CO{sub 2} intermediate. Subsequent movement of the aminoimidazole moiety of AIR reorients it for addition of CO{sub 2} at C4 to generate isoCAIR. His45 is now in a position to remove a C4 proton to produce CAIR.« less