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Animal genomes are organized into topologically associated domains (TADs). TADs are thought to contribute to gene regulation by facilitating enhancer-promoter (E-P) contacts within a TAD and preventing these contacts across TAD borders. However, the absolute difference in contact frequency across TAD boundaries is usually less than 2-fold, even though disruptions of TAD borders can change gene expression by 10-fold. Existing models fail to explain this hypersensitive response. Here, we propose a futile cycle model of enhancer-mediated regulation that can exhibit hypersensitivity through bistability and hysteresis. Consistent with recent experiments, this regulation does not exhibit strong correlation between E-P contact and promoter activity, even though regulation occurs through contact. Through mathematical analysis and stochastic simulation, we show that this system can create an illusion of E-P biochemical specificity and explain the importance of weak TAD boundaries. It also offers a mechanism to reconcile apparently contradictory results from recent global TAD disruption with local TAD boundary deletion experiments. Together, these analyses advance our understanding of cis-regulatory contacts in controlling gene expression and suggest new experimental directions.

In animals, the sequences for controlling gene expression do not concentrate just at the transcription start site of genes, but are frequently thousands to millions of base pairs distal to it. The interaction of these sequences with one another and their transcription start sites is regulated by factors that shape the three-dimensional (3D) organization of the genome within the nucleus. Over the past decade, indirect tools exploiting high-throughput DNA sequencing have helped to map this 3D organization, have identified multiple key regulators of its structure and, in the process, have substantially reshaped our view of how 3D genome architecture regulates transcription. Now, new tools for high-throughput super-resolution imaging of chromatin have directly visualized the 3D chromatin organization, settling some debates left unresolved by earlier indirect methods, challenging some earlier models of regulatory specificity and creating hypotheses about the role of chromatin structure in transcriptional regulation.This Review discusses how chromosome tracing has deepened our understanding of the role of 3D chromatin topology in transcriptional regulation by helping to resolve open questions and opposing models rising from data generated by sequencing-based approaches, such as 3C and HiC.

The tumour suppressor p53 has a central role in the response to cellular stress. Activated p53 transcriptionally regulates hundreds of genes that are involved in multiple biological processes, including in DNA damage repair, cell cycle arrest, apoptosis and senescence. In the context of DNA damage, p53 is thought to be a decision-making transcription factor that selectively activates genes as part of specific gene expression programmes to determine cellular outcomes. In this Review, we discuss the multiple molecular mechanisms of p53 regulation and how they modulate the induction of apoptosis or cell cycle arrest following DNA damage. Specifically, we discuss how the interaction of p53 with DNA and chromatin affects gene expression, and how p53 post-translational modifications, its temporal expression dynamics and its interactions with chromatin regulators and transcription factors influence cell fate. These multiple layers of regulation enable p53 to execute cellular responses that are appropriate for specific cellular states and environmental conditions.Following DNA damage, the transcription factor p53 determines whether cells undergo apoptosis or cell cycle arrest and DNA repair. To enable different cellular outcomes, p53 is regulated through its temporal expression dynamics and post-translational modification, and by interactions with chromatin, chromatin regulators and transcription factors.

Non-coding variants coordinate transcription factor (TF) binding and chromatin mark enrichment changes over regions spanning >100 kb. These molecularly coordinated regions are named “variable chromatin modules” (VCMs), providing a conceptual framework of how regulatory variation might shape complex traits. To better understand the molecular mechanisms underlying VCM formation, here, we mechanistically dissect a VCM-modulating noncoding variant that is associated with reduced chronic lymphocytic leukemia (CLL) predisposition and disease progression. This common, germline variant constitutes a 5-bp indel that controls the activity of an AXIN2 gene-linked VCM by creating a MEF2 binding site, which, upon binding, activates a super-enhancer-like regulatory element. This triggers a large change in TF binding activity and chromatin state at an enhancer cluster spanning >150 kb, coinciding with subtle, long-range chromatin compaction and robust AXIN2 up-regulation. Our results support a model in which the indel acts as an AXIN2 VCM-activating TF nucleation event, which modulates CLL pathology. Non-coding variants can regulate transcription factor binding and gene expression at variable chromatin modules. Here, the authors show that a germline variant induces transcription factor nucleation through chromatin compaction leading to AXIN2 up-regulation and is associated to better prognosis in chronic lymphocytic leukaemia.

The establishment of cell types during development requires precise interactions between genes and distal regulatory sequences. We have a limited understanding of how these interactions look in three dimensions, vary across cell types in complex tissue, and relate to transcription. Here we describe optical reconstruction of chromatin architecture (ORCA), a method that can trace the DNA path in single cells with nanoscale accuracy and genomic resolution reaching two kilobases. We used ORCA to study a Hox gene cluster in cryosectioned Drosophila embryos and labelled around 30 RNA species in parallel. We identified cell-type-specific physical borders between active and Polycomb-repressed DNA, and unexpected Polycomb-independent borders. Deletion of Polycomb-independent borders led to ectopic enhancer–promoter contacts, aberrant gene expression, and developmental defects. Together, these results illustrate an approach for high-resolution, single-cell DNA domain analysis in vivo, identify domain structures that change with cell identity, and show that border elements contribute to the formation of physical domains in Drosophila . Optical reconstruction of chromatin architecture and multiplex RNA labelling traces the DNA path in single cells and its relationship to transcription.

The mammalian SWI/SNF complex, or BAF complex, has a conserved and direct role in antagonizing Polycomb-mediated repression. Yet, BAF also promotes repression by Polycomb in stem cells and cancer. How BAF both antagonizes and promotes Polycomb-mediated repression remains unknown. Here, we utilize targeted protein degradation to dissect the BAF–Polycomb axis in mouse embryonic stem cells on short timescales. We report that rapid BAF depletion redistributes Polycomb repressive complexes PRC1 and PRC2 from highly occupied domains, like Hox clusters, to weakly occupied sites normally opposed by BAF. Polycomb redistribution from highly repressed domains results in their decompaction, gain of active epigenomic features and transcriptional derepression. Surprisingly, through dose-dependent degradation of PRC1 and PRC2, we identify a conventional role for BAF in Polycomb-mediated repression, in addition to global Polycomb redistribution. These findings provide new mechanistic insight into the highly dynamic state of the Polycomb–Trithorax axis. Chemical genetic dissection of the SWI/SNF–Polycomb axis in mouse stem cells identifies an unexpected role for mSWI/SNF in repression, providing mechanistic insight into the dynamic ‘tug of war’ between transcriptional activation and repression.

p53 oscillations in response to DNA damage lead to oscillatory p53 DNA-binding dynamics, whereas post-transcriptional mechanisms are responsible for the differences in gene expression dynamics. The dynamics of transcription factors play important roles in a variety of biological systems. However, the mechanisms by which these dynamics are decoded into different transcriptional responses are not well understood. Here we focus on the dynamics of the tumor-suppressor protein p53, which exhibits a series of pulses in response to DNA damage. We performed time course RNA sequencing (RNA-seq) and chromatin immunoprecipitation sequencing (ChIP-seq) measurements to determine how p53 oscillations are linked with gene expression genome wide. We discovered multiple distinct patterns of gene expression in response to p53 pulses. Surprisingly, p53-binding dynamics were uniform across all genomic loci, even for genes that exhibited distinct mRNA dynamics. Using a mathematical model, supported by additional experimental measurements in response to sustained p53 input, we determined that p53 binds to and activates transcription of its target genes uniformly, whereas post-transcriptional mechanisms are responsible for the differences in gene expression dynamics.

Transcription factors (TFs) and transcriptional coregulators are emerging therapeutic targets. Gene regulatory networks (GRNs) can evaluate pharmacological agents and identify drivers of disease, but methods that rely solely on gene expression often neglect post-transcriptional modulation of TFs. We present Epiregulon , a method that constructs GRNs from single-cell ATAC-seq and RNA-seq data for accurate prediction of TF activity. This is achieved by considering the co-occurrence of TF expression and chromatin accessibility at TF binding sites in each cell. ChIP-seq data allows motif-agonistic activity inference of transcriptional coregulators or TF harboring neomorphic mutations. Epiregulon accurately predicted the effects of AR inhibition across different drug modalities including an AR antagonist and an AR degrader, delineated the mechanisms of a SMARCA4 degrader by identifying context-dependent interaction partners, and prioritized drivers of lineage reprogramming and tumorigenesis. By mapping gene regulation across various cellular contexts, Epiregulon can accelerate the discovery of therapeutics targeting transcriptional regulators. Transcription factors (TFs) represent an emerging class of therapeutic targets in oncology. Here, the authors develop Epiregulon , a computational method that constructs gene regulatory networks from ChIP-seq, ATAC-seq and RNA-seq data for accurate prediction of TF activity at the single-cell level, thereby facilitating the discovery of therapeutics targeting TFs.

Multiplexed DNA fluorescence in situ hybridization (FISH) imaging technologies have been developed to map the folding of chromatin fibers at tens of nanometers and up to several kilobases in resolution in single cells. However, computational methods to reliably identify chromatin loops from such imaging datasets are still lacking. Here we present a Single-Nucleus Analysis Pipeline for multiplexed DNA FISH (SnapFISH), to process the multiplexed DNA FISH data and identify chromatin loops. SnapFISH can identify known chromatin loops from mouse embryonic stem cells with high sensitivity and accuracy. In addition, SnapFISH obtains comparable results of chromatin loops across datasets generated from diverse imaging technologies. SnapFISH is freely available at https://github.com/HuMingLab/SnapFISH . Multiplexed DNA FISH technologies are powerful tools to reveal chromatin spatial organisation. Here, the authors developed SnapFISH, a computational pipeline to identify chromatin loops from multiplexed DNA FISH data.

Background The tumor suppressor p53 is a major regulator of the DNA damage response and has been suggested to selectively bind and activate cell-type specific gene expression programs. However recent studies and meta-analyses of genomic data propose largely uniform, and condition independent p53 binding and thus question the selective and cell-type dependent function of p53. Results To systematically assess the cell-type specificity of p53, we measured its association with DNA in 12 p53 wild-type cancer cell lines, from a range of epithelial linages, in response to ionizing radiation. We found that the majority of bound sites were occupied across all cell lines, however we also identified a subset of binding sites that were specific to one or a few cell lines. Unlike the shared p53-bound genome, which was not dependent on chromatin accessibility, the association of p53 with these atypical binding sites was well explained by chromatin accessibility and could be modulated by forcing cell state changes such as the epithelial-to-mesenchymal transition. Conclusions Our study reconciles previous conflicting views in the p53 field, by demonstrating that although the majority of p53 DNA binding is conserved across cell types, there is a small set of cell line specific binding sites that depend on cell state.