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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. Synopsis: GRaNIE builds enhancer‐based gene regulatory networks (eGRNs) using chromatin accessibility and RNA‐seq data. GRaNPA assesses the biological significance of GRNs and transcription factors. Together, they provide insights into cell‐type‐specific gene regulation. GRaNIE builds gene regulatory networks that encompass transcription factors, regulatory regions and genes, enabling a comprehensive view of gene regulation.GRaNPA provides an unbiased evaluation method for cell‐type‐specific GRNs by testing their ability to predict cell‐type‐specific differential expression.GRaNPA can identify important transcription factors that drive differential expression, leading to insights into biological mechanisms.GRaNIE and GRaNPA analyses identified PURA as a promising candidate for regulating pro‐inflammatory macrophage polarisation. [ABSTRACT FROM AUTHOR]

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. Synopsis: Combined perturbation by microenvironmental stimuli and drugs of chronic lymphocytic leukaemia cells annotated for genetic alterations reveals distinct response patterns and molecular modulators. CLL samples fall into four subgroups with distinct progression dynamics based on their microenvironmental response.Trisomy 12 enhances the response to microenvironmental stimulation and has a distinct transcription factor activity profile which is inhibited by IBET‐762 treatment.Linear modelling reveals different types of drug ‐ stimuli interactions, the most common being drug resistance induced by microenvironmental stimulation.IL4 and TLR signalling is more active in CLL infiltrated lymph nodes, and higher IL4 signalling activity correlates with faster disease progression. [ABSTRACT FROM AUTHOR]

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. Synopsis: Dynamic multi‐omic profiling and comparative genomics are used to dissect the role of BDNF on neuronal chromatin. A comprehensive description of BDNF‐specific regulatory features is provided, from transcription factor interactions to complex traits.Comparative profiling of mouse neuron stimulation with BDNF or KCl using ATAC‐, RNA‐seq, and proteomics reveals BDNF‐specific gene expression regulatory features.Early enhancer activation is a signature feature of BDNF stimulation that coordinates the transcriptional response, whereas KCl stimulation directly affects promoters with a delayed effect on transcription.BDNF‐responsive chromatin regions conserved between mouse and human display shared neuropsychiatric complex trait associations. [ABSTRACT FROM AUTHOR]

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. Synopsis: 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. Expression variation across individuals is a robust gene‐specific property.Expression variation reflects regulatory properties inherent to genes and discriminates functional gene groups.Promoter architecture and overall gene regulatory complexity are predictive of gene expression variation.Expression variation features could also predict differential expression upon diverse perturbations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 GPR56 high AML and propose combined CDK7 and Bcl-2 inhibition as LSC-directed therapy in this disease., (©2022 The Authors. Published under the terms of the CC BY 4.0 license.)