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Following the recent isolation of monolayer CrI3 (ref. 1), many more two-dimensional van der Waals magnetic materials have been isolated2–12. Their incorporation in van der Waals heterostructures offers a new platform for spintronics5–9, proximity magnetism13 and quantum spin liquids14. A primary question in this field is how exfoliating crystals to the few-layer limit influences their magnetism. Studies of CrI3 have shown a different magnetic ground state for ultrathin exfoliated films1,5,6 compared with the bulk, but the origin is not yet understood. Here, we use electron tunnelling through few-layer crystals of the layered antiferromagnetic insulator CrCl3 to probe its magnetic order and find a tenfold enhancement of the interlayer exchange compared with bulk crystals. Moreover, temperature- and polarization-dependent Raman spectroscopy reveals that the crystallographic phase transition of bulk crystals does not occur in exfoliated films. This results in a different low-temperature stacking order and, we hypothesize, increased interlayer exchange. Our study provides insight into the connection between stacking order and interlayer interactions in two-dimensional magnets, which may be relevant for correlating stacking faults and mechanical deformations with the magnetic ground states of other more exotic layered magnets such as RuCl3 (ref. 14).

Single-cell analyses have revealed a tremendous variety among cells in the abundance and chemical composition of RNA. Much of this heterogeneity is due to alternative splicing by the spliceosome. Little is known about how many of the resulting isoforms are biologically functional or just provide noise with little to no impact. The dynamic nature of the spliceosome provides numerous opportunities for regulation but is also the source of stochastic fluctuations. We discuss possible origins of splicing stochasticity, the experimental approaches for studying heterogeneity in isoforms, and the potential biological significance of noisy splicing in development and disease.

Cellular messenger RNA levels are achieved by the combinatorial complexity of factors controlling transcription, yet the small number of molecules involved in these pathways fluctuates stochastically. It has not yet been experimentally possible to observe the activity of single polymerases on an endogenous gene to elucidate how these events occur in vivo. Here, we describe a method of fluctuation analysis of fluorescently labeled RNA to measure dynamics of nascent RNA—including initiation, elongation, and termination—at an active yeast locus. We find no transcriptional memory between initiation events, and elongation speed can vary by threefold throughout the cell cycle. By measuring the abundance and intranuclear mobility of an upstream transcription factor, we observe that the gene firing rate is directly determined by trans-activating factor search times.

The role of the spatial organization of chromosomes in directing transcription remains an outstanding question in gene regulation. Here, we analyze two recent single-cell imaging methodologies applied across hundreds of genes to systematically analyze the contribution of chromosome conformation to transcriptional regulation. Those methodologies are (1) single-cell chromatin tracing with super-resolution imaging in fixed cells; and (2) high-throughput labeling and imaging of nascent RNA in living cells. Specifically, we determine the contribution of physical distance to the coordination of transcriptional bursts. We find that individual genes adopt a constrained conformation and reposition toward the centroid of the surrounding chromatin upon activation. Leveraging the variability in distance inherent in single-cell imaging, we show that physical distance – but not genomic distance – between genes on individual chromosomes is the major factor driving co-bursting. By combining this analysis with live-cell imaging, we arrive at a corrected transcriptional correlation of ϕ ≈ 0.3 for genes separated by < 400 nm. We propose that this surprisingly large correlation represents a physical property of human chromosomes and establishes a benchmark for future experimental studies.

Understanding the kinetics of gene expression involves accurate quantitation of gene expression. This is now undertaken by quantifying nascent-RNA levels and relating this indication of transcriptional activity to mRNA abundance in single yeast cells. Combining these measurements with computational modeling indicates that the tested yeast housekeeping genes are probably expressed through single initiation events, whereas a SAGA-transcribed gene shows behavior consistent with transcriptional bursting. Proper execution of transcriptional programs is a key requirement of gene expression regulation, demanding accurate control of timing and amplitude. How precisely the transcription machinery fulfills this task is not known. Using an in situ hybridization approach that detects single mRNA molecules, we measured mRNA abundance and transcriptional activity within single Saccharomyces cerevisiae cells. We found that expression levels for particular genes are higher than initially reported and can vary substantially among cells. However, variability for most constitutively expressed genes is unexpectedly small. Combining single-transcript measurements with computational modeling indicates that low expression variation is achieved by transcribing genes using single transcription-initiation events that are clearly separated in time, rather than by transcriptional bursts. In contrast, PDR5 , a gene regulated by the transcription coactivator complex SAGA, is expressed using transcription bursts, resulting in larger variation. These data directly demonstrate the existence of multiple expression modes used to modulate the transcriptome.

U2 Small Nuclear RNA Auxiliary Factor 1 (U2AF1) forms a heterodimeric complex with U2AF2 that is primarily responsible for 3ʹ splice site selection. U2AF1 mutations have been identified in most cancers but are prevalent in Myelodysplastic Syndrome (MDS) and Acute Myeloid Leukemia (AML), and the most common mutation is a missense substitution of serine-34 to phenylalanine (S34F). The U2AF heterodimer also has a noncanonical function as a translational regulator. Here, we report that the U2AF1-S34F mutation results in specific misregulation of the translation initiation and ribosome biogenesis machinery. The net result is an increase in mRNA translation at the single-cell level. Among the translationally up-regulated targets of U2AF1-S34F is Nucleophosmin 1 (NPM1), which is a major driver of myeloid malignancy. Depletion of NPM1 impairs the viability of the U2AF1-S34F mutant cells and causes ribosomal RNA (rRNA) processing defects, thus indicating an unanticipated synthetic interaction between U2AF1, NPM1, and ribosome biogenesis. Our results establish a unique molecular phenotype for the U2AF1 mutation that recapitulates translational misregulation in myeloid disease.

Key Points Single-molecule and genome-wide studies of transcription reveal the importance of dynamics for understanding the mechanisms of gene regulation. A single gene can be regulated by dozens of factors interacting in a combinatorial manner. Observing all such interactions experimentally is still a daunting task, but computational models of transcription dynamics can provide insight into the underlying mechanisms. Molecular models of transcription often emphasize sequential, ordered recruitment, for example in the formation of a pre-initiation complex at a promoter. These sequential processes are best-described by non-equilibrium thermodynamics, in which kinetics and energy dependence are treated explicitly. Models based on non-equilibrium thermodynamics provide insight into a range of transcription phenomena, including nucleosome positioning, transcriptional bursting, and refractory periods during transcription. Our understanding of transcription is being improved through single-molecule and genome-wide approaches. Quantitative models are also required to provide insights into the underlying mechanisms of transcription, and the authors discuss how experimental results and models can be brought together. Transcriptional regulation is achieved through combinatorial interactions between regulatory elements in the human genome and a vast range of factors that modulate the recruitment and activity of RNA polymerase. Experimental approaches for studying transcription in vivo now extend from single-molecule techniques to genome-wide measurements. Parallel to these developments is the need for testable quantitative and predictive models for understanding gene regulation. These conceptual models must also provide insight into the dynamics of transcription and the variability that is observed at the single-cell level. In this Review, we discuss recent results on transcriptional regulation and also the models those results engender. We show how a non-equilibrium description informs our view of transcription by explicitly considering time- and energy-dependence at the molecular level.

Numerous functions hinge on the spatial arrangement of different genomic loci. Hence, microscopy techniques, such as chromatin tracing, have been developed to localize multiple loci in fixed cells. Depending on the throughput and specifics of the experiment, localization errors can still obscure the true spatial locations. We have developed a post-processing methodology to address this challenge without the need for additional experimentation: Loci Enabled Advanced Resolution (LEAR). By leveraging the fact that localization errors increase the variability of the displacements between loci, and given an approximation of the localization error, we can approximate the ground truth spatial variation for each pair of loci to guide an iterative error correction process. After validating our approach with simulation and experiment, we then applied our approach to existing chromatin tracing data that probed the relation between chromatin organization and Sox2 regulation, where previous work found no clear correlation between enhancer-promoter proximity and transcription bursts in individual cells. We discovered a correlation previously obscured by localization error, clearly demonstrating the need for the methodology. We then investigated the influence of loop-extrusion on higher order multi-way contact frequencies, which dramatically increased with the application of the LEAR method, finding that certain multi-way contacts were only present with loop-extrusion.

Molecular-scale manipulation of electronic and ionic charge accumulation in materials is the backbone of electrochemical energy storage 1 – 4 . Layered van der Waals (vdW) crystals are a diverse family of materials into which mobile ions can electrochemically intercalate into the interlamellar gaps of the host atomic lattice 5 , 6 . The structural diversity of such materials enables the interfacial properties of composites to be optimized to improve ion intercalation for energy storage and electronic devices 7 – 12 . However, the ability of heterolayers to modify intercalation reactions, and their role at the atomic level, are yet to be elucidated. Here we demonstrate the electrointercalation of lithium at the level of individual atomic interfaces of dissimilar vdW layers. Electrochemical devices based on vdW heterostructures 13 of stacked hexagonal boron nitride, graphene and molybdenum dichalcogenide (MoX 2 ; X = S, Se) layers are constructed. We use transmission electron microscopy, in situ magnetoresistance and optical spectroscopy techniques, as well as low-temperature quantum magneto-oscillation measurements and ab initio calculations, to resolve the intermediate stages of lithium intercalation at heterointerfaces. The formation of vdW heterointerfaces between graphene and MoX 2 results in a more than tenfold greater accumulation of charge in MoX 2 when compared to MoX 2 /MoX 2 homointerfaces, while enforcing a more negative intercalation potential than that of bulk MoX 2 by at least 0.5 V. Beyond energy storage, our combined experimental and computational methodology for manipulating and characterizing the electrochemical behaviour of layered systems opens new pathways to control the charge density in two-dimensional electronic and optoelectronic devices. The electrointercalation of lithium into van der Waals heterostructures of graphene, hexagonal boron nitride and molybdenum dichalcogenides is studied at the level of individual atomic interfaces.

We use a data-driven approach to study the magnetic and thermodynamic properties of van der Waals (vdW) layered materials. We investigate monolayers of the form A 2 B 2 X 6 , based on the known material Cr 2 Ge 2 Te 6 , using density functional theory (DFT) calculations and machine learning methods to determine their magnetic properties, such as magnetic order and magnetic moment. We also examine formation energies and use them as a proxy for chemical stability. We show that machine learning tools, combined with DFT calculations, can provide a computationally efficient means to predict properties of such two-dimensional (2D) magnetic materials. Our data analytics approach provides insights into the microscopic origins of magnetic ordering in these systems. For instance, we find that the X site strongly affects the magnetic coupling between neighboring A sites, which drives the magnetic ordering. Our approach opens new ways for rapid discovery of chemically stable vdW materials that exhibit magnetic behavior.