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Abstract Enhancers play a vital role in gene regulation and are critical in mediating the impact of noncoding genetic variants associated with complex traits. Enhancer activity is a cell‐type‐specific process regulated by transcription factors (TFs), epigenetic mechanisms and genetic variants. Despite the strong mechanistic link between TFs and enhancers, we currently lack a framework for jointly analysing them in cell‐type‐specific gene regulatory networks (GRN). Equally important, we lack an unbiased way of assessing the biological significance of inferred GRNs since no complete ground truth exists. To address these gaps, we present GRaNIE (Gene Regulatory Network Inference including Enhancers) and GRaNPA (Gene Regulatory Network Performance Analysis). GRaNIE ( https://git.embl.de/grp‐zaugg/GRaNIE ) builds enhancer‐mediated GRNs based on covariation of chromatin accessibility and RNA‐seq across samples (e.g. individuals), while GRaNPA ( https://git.embl.de/grp‐zaugg/GRaNPA ) assesses the performance of GRNs for predicting cell‐type‐specific differential expression. We demonstrate their power by investigating gene regulatory mechanisms underlying the response of macrophages to infection, cancer and common genetic traits including autoimmune diseases. Finally, our methods identify the TF PURA as a putative regulator of pro‐inflammatory macrophage polarisation.

Abstract 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.

Abstract Neuronal stimulation induced by the 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 affect 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 the 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 stimulation.

Abstract The heterogeneous response of acute myeloid leukemia (AML) to current anti‐leukemic therapies is only partially explained by mutational heterogeneity. We previously identified GPR56 as a surface marker associated with poor outcome across genetic groups, which characterizes two leukemia stem cell (LSC)‐enriched compartments with different self‐renewal capacities. How these compartments self‐renew remained unclear. Here, we show that GPR56+ LSC compartments are promoted in a complex network involving epithelial‐to‐mesenchymal transition (EMT) regulators besides Rho, Wnt, and Hedgehog (Hh) signaling. Unexpectedly, Wnt pathway inhibition increased the more immature, slowly cycling GPR56+CD34+ fraction and Hh/EMT gene expression, while Wnt activation caused opposite effects. Our data suggest that the crucial role of GPR56 lies in its ability to co‐activate these opposing signals, thus ensuring the constant supply of both LSC subsets. We show that CDK7 inhibitors suppress both LSC‐enriched subsets in vivo and synergize with the Bcl‐2 inhibitor venetoclax. Our data establish reciprocal transition between LSC compartments as a novel concept underlying the poor outcome in GPR56high AML and propose combined CDK7 and Bcl‐2 inhibition as LSC‐directed therapy in this disease.

Abstract 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.

Abstract The recognition of carbon sources and the regulatory adjustments to recognized changes are of particular importance for bacterial survival in fluctuating environments. Despite a thorough knowledge base of Escherichia coli's central metabolism and its regulation, fundamental aspects of the employed sensing and regulatory adjustment mechanisms remain unclear. In this paper, using a differential equation model that couples enzymatic and transcriptional regulation of E. coli's central metabolism, we show that the interplay of known interactions explains in molecular‐level detail the system‐wide adjustments of metabolic operation between glycolytic and gluconeogenic carbon sources. We show that these adaptations are enabled by an indirect recognition of carbon sources through a mechanism we termed distributed sensing of intracellular metabolic fluxes. This mechanism uses two general motifs to establish flux‐signaling metabolites, whose bindings to transcription factors form flux sensors. As these sensors are embedded in global feedback loop architectures, closed‐loop self‐regulation can emerge within metabolism itself and therefore, metabolic operation may adapt itself autonomously (not requiring upstream sensing and signaling) to fluctuating carbon sources.

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.

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.

Ageing causes an inability to replace damaged tissue. Here, the authors perform proteomics analyses of human haematopoietic stem cells and other cells in the bone marrow niche at different ages and show changes in central carbon metabolism, reduced bone marrow niche function, and enhanced myeloid differentiation.

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

Abstract Background Genome wide association studies have identified microtubule associated protein tau (MAPT) H1 haplotype single nucleotide polymorphisms (SNPs) as leading common risk variants for Parkinson’s disease, progressive supranuclear palsy and corticobasal degeneration. The MAPT risk variants fall within a large 1.8 Mb region of high linkage disequilibrium, making it difficult to discern the functionally important risk variants. Here, we leverage the strong haplotype-specific expression of MAPT exon 3 to investigate the functionality of SNPs that fall within this H1 haplotype region of linkage disequilibrium. Methods In this study, we dissect the molecular mechanisms by which haplotype-specific SNPs confer allele-specific effects on the alternative splicing of MAPT exon 3. Firstly, we use haplotype-hybrid whole-locus genomic MAPT vectors studies to identify functional SNPs. Next, we characterise the RNA-protein interactions at two loci by mass spectrometry. Lastly, we knockdown candidate splice factors to determine their effect on MAPT exon 3 using a novel allele-specific qPCR assay. Results Using whole-locus genomic DNA expression vectors to express MAPT haplotype variants, we demonstrate that rs17651213 regulates exon 3 inclusion in a haplotype-specific manner. We further investigated the functionality of this region using RNA-electrophoretic mobility shift assays to show differential RNA-protein complex formation at the H1 and H2 sequence variants of SNP rs17651213 and rs1800547 and subsequently identified candidate trans-acting splicing factors interacting with these functional SNPs sequences by RNA-protein pull-down experiment and mass spectrometry. Finally, gene knockdown of candidate splice factors identified by mass spectrometry demonstrate a role for hnRNP F and hnRNP Q in the haplotype-specific regulation of exon 3 inclusion. Conclusions We identified common splice factors hnRNP F and hnRNP Q regulating the haplotype-specific splicing of MAPT exon 3 through intronic variants rs1800547 and rs17651213. This work demonstrates an integrated approach to characterise the functionality of risk variants in large regions of linkage disequilibrium.

Abstract Histone modifications are associated with distinct transcriptional states, but it is unclear whether they instruct gene expression. To investigate this, we mutate 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 unleash 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 disrupts the deposition and spreading of the repressive H3K27me3 mark, particularly impacting bivalent genes with higher basal levels of H3.3 at promoters. Therefore, H3.3K9 and K27 crucially orchestrate repressive chromatin states at cis-regulatory elements and bivalent promoters, respectively, and instruct proper transcription in mESCs.

Abstract 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.