Super-enhancer interactomes from single cells link clustering and transcription.

Regulation of gene expression hinges on the interplay between enhancers and promoters, traditionally explored through pairwise analyses. Recent advancements in mapping genome folding, like GAM, SPRITE, and multi-contact Hi-C, have uncovered multi-way interactions among super-enhancers (SEs), spanning megabases, yet have not measured their frequency in single cells or the relationship between clustering and transcription. To close this gap, here we used multiplexed imaging to map the 3D positions of 376 SEs across thousands of mammalian nuclei. Notably, our single-cell images reveal that while SE-SE contacts are rare, SEs often form looser associations we termed "communities". These communities, averaging 4-5 SEs, assemble cooperatively under the combined effects of genomic tethers, Pol2 clustering, and nuclear compartmentalization. Larger communities are associated with more frequent and larger transcriptional bursts. Our work provides insights about the SE interactome in single cells that challenge existing hypotheses on SE clustering in the context of transcriptional regulation.

Single-cell chromatin state transitions during epigenetic memory formation.

Repressive chromatin modifications are thought to compact chromatin to silence transcription. However, it is unclear how chromatin structure changes during silencing and epigenetic memory formation. We measured gene expression and chromatin structure in single cells after recruitment and release of repressors at a reporter gene. Chromatin structure is heterogeneous, with open and compact conformations present in both active and silent states. Recruitment of repressors associated with epigenetic memory produces chromatin compaction across 10-20 kilobases, while reversible silencing does not cause compaction at this scale. Chromatin compaction is inherited, but changes molecularly over time from histone methylation (H3K9me3) to DNA methylation. The level of compaction at the end of silencing quantitatively predicts epigenetic memory weeks later. Similarly, chromatin compaction at the Nanog locus predicts the degree of stem-cell fate commitment. These findings suggest that the chromatin state across tens of kilobases, beyond the gene itself, is important for epigenetic memory formation.

SnapFISH: a computational pipeline to identify chromatin loops from multiplexed DNA FISH data.

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 .

Loop stacking organizes genome folding from TADs to chromosomes.

Although population-level analyses revealed significant roles for CTCF and cohesin in mammalian genome organization, their contributions at the single-cell level remain incompletely understood. Here, we used a super-resolution microscopy approach to measure the effects of removal of CTCF or cohesin in mouse embryonic stem cells. Single-chromosome traces revealed cohesin-dependent loops, frequently stacked at their loop anchors forming multi-way contacts (hubs), bridging across TAD boundaries. Despite these bridging interactions, chromatin in intervening TADs was not intermixed, remaining separated in distinct loops around the hub. At the multi-TAD scale, steric effects from loop stacking insulated local chromatin from ultra-long range (>4 Mb) contacts. Upon cohesin removal, the chromosomes were more disordered and increased cell-cell variability in gene expression. Our data revise the TAD-centric understanding of CTCF and cohesin and provide a multi-scale, structural picture of how they organize the genome on the single-cell level through distinct contributions to loop stacking.

The spatial organization of transcriptional control.

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.

A leukemia-protective germline variant mediates chromatin module formation via transcription factor nucleation.

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.

How subtle changes in 3D structure can create large changes in transcription.

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.

mSWI/SNF promotes Polycomb repression both directly and through genome-wide redistribution.

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.

Quantifying the Central Dogma in the p53 Pathway in Live Single Cells.

Transcription factors (TFs) integrate signals to regulate target gene expression, but we generally lack a quantitative understanding of how changes in TF levels regulate mRNA and protein production. Here, we established a system to simultaneously monitor the levels of p53, a TF that shows oscillations following DNA damage, and the transcription and protein levels of its target p21 in individual cells. p21 transcription tracked p53 dynamics, while p21 protein steadily accumulated. p21 transcriptional activation showed bursts of mRNA production, with p53 levels regulating the probability but not magnitude of activation. Variations in p53 levels between cells contributed to heterogeneous p21 transcription while independent p21 alleles exhibited highly correlated behaviors. Pharmacologically elevating p53 increased the probability of p21 transcription with minor effects on its magnitude, leading to a strong increase in p21 protein levels. Our results reveal quantitative mechanisms by which TF dynamics can regulate protein levels of its targets. A record of this paper's transparent peer review process is included in the Supplemental Information.

Identification of universal and cell-type specific p53 DNA binding.

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.

A Comprehensive Drosophila melanogaster Transcription Factor Interactome.

Combinatorial interactions among transcription factors (TFs) play essential roles in generating gene expression specificity and diversity in metazoans. Using yeast 2-hybrid (Y2H) assays on nearly all sequence-specific Drosophila TFs, we identified 1,983 protein-protein interactions (PPIs), more than doubling the number of currently known PPIs among Drosophila TFs. For quality assessment, we validated a subset of our interactions using MITOMI and bimolecular fluorescence complementation assays. We combined our interactome with prior PPI data to generate an integrated Drosophila TF-TF binary interaction network. Our analysis of ChIP-seq data, integrating PPI and gene expression information, uncovered different modes by which interacting TFs are recruited to DNA. We further demonstrate the utility of our Drosophila interactome in shedding light on human TF-TF interactions. This study reveals how TFs interact to bind regulatory elements in vivo and serves as a resource of Drosophila TF-TF binary PPIs for understanding tissue-specific gene regulation.

Visualizing DNA folding and RNA in embryos at single-cell resolution.

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.

The multiple mechanisms that regulate p53 activity and cell fate.

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.

p53 pulses lead to distinct patterns of gene expression albeit similar DNA-binding 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.