RNA splicing is directed by cis-acting sequence signals interacting with trans-acting factors to remove introns from newly transcribed pre-mRNA, joining exons to generate mature mRNA. Splicing happens far more often than observed exon-exon junctions in mRNA. As one contributing process, the spliceosome progressively removes large introns in small segments by 'recursive splicing', instead of splicing the whole intron at one time. However, the cis-acting sequences associated with recursive splicing have not been identified. Using probabilistic mixture models, we found that recursive splicing occurs more frequently in first introns, which are typically longer, and exhibit a distinct CG-rich sequence feature in the sequences flanking the upstream 5'SS, and depletion of CGs in the downstream polypyrimidine tract. Remarkably, recursive splicing is also more frequent in downstream introns of genes containing first introns with these properties. Mechanistically, these data suggest that early events in RNA synthesis and processing influence the prevalence of recursive splicing for the rest of the transcript. Finally, we developed a sequence-dependent classifier for recursive splicing, which we tested with a novel medium-throughput primer extension assay. In summary, the usage of recursive splicing sites is established at the beginning of RNA synthesis through newly-identified sequence motifs flanking both ends of the first intron.

The mechanisms underlying molecular targeting to mitochondria remain enigmatic, yet this process is crucial for normal cellular function. The RNA-binding proteins U2AF1 and U2AF2 form a heterodimer (U2AF) that shuttles between the nucleus and cytoplasm, regulating splicing in the nucleus and translation in the cytoplasm. Our study in human bronchial epithelial cells (HBECs) identifies an unexpected role for U2AF in mitochondrial function. We demonstrate that U2AF interacts with nuclear-encoded mitochondrial (NE-mt) mRNAs and proteins, inhibits translation, localizes to the mitochondria, and regulates mRNA localization to mitochondria. Moreover, an oncogenic point mutation in U2AF1(S34F) disrupts this regulation, leading to altered mitochondrial structure, increased translation, large changes in the mitochondria proteome, and oxidative phosphorylation (OXPHOS)-dependent metabolic rewiring, recapitulating changes observed in bone marrow progenitors from patients with myelodysplastic syndromes. These findings reveal a non-canonical role for U2AF, where it modulates multiple aspects of mitochondrial function by regulating the translation and mitochondrial localization of nuclear-encoded mRNAs.

Topologically associating domains (TADs) are prominent features of genome organization. A proposed function of TADs is to contribute to gene regulation by promoting chromatin interactions within a TAD and by suppressing interactions between TADs. Here, we directly probe the structure-function relationship of TADs by simultaneously assessing the behavior of TAD boundaries and gene activity at the single-cell and -allele level using high-throughput imaging. We find that while TAD boundaries pair more frequently than non-boundary regions, these interactions are infrequent and are uncorrelated with transcriptional activity of genes within the TAD. Similarly, acute global transcriptional inhibition or gene-specific activation does not alter TAD boundary proximity. Furthermore, while loss of the cohesin component RAD21 alters gene activity, disruption of TAD boundaries by depletion of the architectural chromatin protein CTCF is insufficient to alter expression of genes within the TAD. These results suggest that TAD boundary architecture and gene activity are largely uncoupled.

Increasing cell size drives proteomic changes that impact cell physiology. However, the molecular basis of size-dependent proteome remodeling has remained unclear. Here, we develop an inducible Cyclin D1 expression system in human cells to generate proliferating cells spanning over a 2-fold size range. We use this system to make comprehensive genome-wide measurements of mRNA and protein concentrations and stability. We find that protein and mRNA turnover rates are weakly related to cell size but that mRNA concentrations are strongly size-dependent. This establishes that transcriptional regulation is the basis of proteome remodeling. Live-cell imaging of nascent mRNAs using the MS2 system is used to measure how transcriptional dynamics change with cell size. Larger cells prolong transcriptional bursts but maintain similar burst amplitudes to achieve transcriptional scaling. Together, our results show how transcription is modulated by cell size to remodel the proteome and alter cell physiology.

Topologically associating domains (TADs) are prominent features of genome organization. A proposed function of TADs is to contribute to gene regulation by promoting chromatin interactions within a TAD and by suppressing interactions between TADs. Here, we directly probe the structure-function relationship of TADs by simultaneously assessing TAD boundary architecture and gene activity at the single-cell and -allele level using high-throughput imaging. We find that while TAD boundaries pair more frequently than non-boundary regions, these interactions are infrequent and are uncorrelated with transcriptional activity of genes within the TAD. Similarly, acute global transcriptional inhibition or gene-specific activation does not alter TAD boundary proximity. Furthermore, disruption of TAD boundaries by depletion of the architectural chromatin protein CTCF is insufficient to alter expression of genes within the TAD. These results suggest that TAD boundary architecture and gene activity are largely uncoupled.

Advances in single-cell RNA sequencing (scRNA-seq) and high-resolution imaging techniques, such as single-molecule tracking (SMT) of RNA and transcription factors, allow researchers to quantitatively explore dynamics and variation but have never been integrated into a single coherent model. In this study, we propose a kinetic model that intakes multiple data types, including steady-state and time-resolved datasets, to simulate and fit stochastic models of gene transcription to experimental data. We find that 3-state models provide an essential improvement over the widely used 2-state model for most genes and have the property of kinetic proofreading, which we argue is advantageous in the cellular context. We further identify two dimensionless quantities derived from the rate equations which are broadly conserved across genes. Finally, we extend this model to scRNA-seq datasets to infer kinetic rates under defined perturbations and reveal biochemical insight into the mechanism of action of transcription factors.

The spliceosome is a megadalton protein-RNA complex which removes introns from pre-mRNA, yet the dynamic early assembly steps have not been structurally resolved. Specifically, how the spliceosome selects the correct 3' splice site (3'SS) amongst highly similar non-functional sites is not known. Here, we develop a kinetic model of splice site selection based on single-molecule U2AF heterodimer imaging in vitro and in vivo. The model successfully predicts alternative splicing patterns and indicates that 3'SS commitment occurs while U2AF is in complex with the spliceosome, not during initial binding. This finding indicates the spliceosome operates in a 'partial' kinetic proofreading regime, catalyzed in part by the helicase DDX42, which increases selectivity to the underlying U2AF binding site while still allowing for efficient forward progression.

Advances in single-cell RNA sequencing (scRNA-seq) and high-resolution imaging techniques, such as single-molecule tracking (SMT) of RNA and transcription factors, allow researchers to quantitatively explore dynamics and variation but have never been integrated into a single coherent model. In this study, we propose a kinetic model that intakes multiple data types, including steady-state and time-resolved datasets, to simulate and fit stochastic models of gene transcription to experimental data. We find that 3-state models provide an essential improvement over the widely used 2-state model for most genes and have the property of kinetic proofreading, which we argue is advantageous in the cellular context. We further identify two dimensionless quantities derived from the rate equations which are broadly conserved across genes. Finally, we extend this model to scRNA-seq datasets to infer kinetic rates under defined perturbations and reveal biochemical insight into the mechanism of action of transcription factors.

Differential mRNA expression is essential for driving cell type identity and cell fate transitions during tissue differentiation and organismal development. However, transcription kinetics are seemingly heterogeneous at a cell-to-cell level, occurring in a series of episodic bursts of nascent mRNA synthesis separated by refractory periods. This transcriptional bursting therefore affects both the speed and variability of developmental gene expression. Consequently, how transcription kinetics are modulated to control mRNA expression output remains an outstanding question in the field. This review examines recent literature on how these processes are modulated during differentiation and development, the theoretical models of transcription bursting, and the molecular mechanisms underlying transcription kinetics.

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.

Stochastic transcriptional bursting is a universal property of active genes. While different genes exhibit distinct bursting patterns, the molecular mechanisms that govern gene-specific stochastic bursting are largely unknown. We have developed a high-throughput-imaging-based screening strategy to identify cellular factors that determine the bursting patterns of native genes in human cells. We identify protein acetylation as a prominent effector of burst frequency and burst size acting via decreasing off-times and gene-specific changes in the on-time. These effects are not correlated with promoter acetylation. Instead, we demonstrate acetylation of the Integrator complex as a key determinant of gene bursting that alters Integrator interactions with transcription elongation and RNA processing factors but without affecting pausing. Our results suggest a prominent role for non-histone acetylation of a transcription cofactors as a mechanism for modulation of bursting via a far-downstream checkpoint.

Chromatin organization, facilitated by compartmentalization and loop extrusion, is crucial for proper gene expression and cell viability. Transcription has long been considered important for shaping genome architecture due to its pervasive activity across the genome and impact on the local chromatin environment. Although earlier studies suggested a minimal contribution of transcription to shaping global genome structure, recent insights from high-resolution chromatin contact mapping, polymer simulations, and acute perturbations have revealed its critical role in dynamic chromatin organization at the level of active genes and enhancer-promoter interactions. In this review, we discuss these latest advances, highlighting the direct interplay between transcriptional machinery and loop extrusion. Finally, we explore how transcription of genes and non-coding regulatory elements may contribute to the specificity of gene regulation, focusing on enhancers as sites of targeted cohesin loading.

Fluctuations in the initiation rate of transcription, the first step in gene expression, ensue from the stochastic behavior of the molecular process that controls transcription. In steady state, the regulatory process is often assumed to operate reversibly, i.e., in equilibrium. However, reversibility imposes fundamental limits to information processing. For instance, the assumption of equilibrium is difficult to square with the precision with which the regulatory process executes its task in eukaryotes. Here we provide evidence - from microscopic analyses of the transcription dynamics at a single gene copy of yeast - that the regulatory process for transcription is cyclic and irreversible (out of equilibrium). The necessary coupling to reservoirs of free energy occurs via sequence-specific transcriptional activators and the recruitment, in part, of ATP-dependent chromatin remodelers. Our findings may help explain how eukaryotic cells reconcile the dual but opposing requirements for fast regulatory kinetics and high regulatory specificity.

Discontinuous transcription is evolutionarily conserved and a fundamental feature of gene regulation; yet, the exact mechanisms underlying transcriptional bursting are unresolved. Analyses of bursting transcriptome-wide have focused on the role of cis-regulatory elements, but other factors that regulate this process remain elusive. We applied mathematical modeling to single-cell RNA sequencing data to infer bursting dynamics transcriptome-wide under multiple conditions to identify possible molecular mechanisms. We found that Mediator complex subunit 26 (MED26) primarily regulates frequency, MYC regulates burst size, while cohesin and Bromodomain-containing protein 4 (BRD4) can modulate both. Despite comparable effects on RNA levels among these perturbations, acute depletion of MED26 had the most profound impact on the entire gene regulatory network, acting downstream of chromatin spatial architecture and without affecting TATA box-binding protein (TBP) recruitment. These results indicate that later steps in the initiation of transcriptional bursts are primary nodes for integrating gene networks in single cells.

Enhancers are central for the regulation of metazoan transcription but have proven difficult to study, primarily due to a myriad of interdependent variables shaping their activity. Consequently, synthetic biology has emerged as the main approach for dissecting mechanisms of enhancer function. We start by reviewing simple but highly parallel reporter assays, which have been successful in quantifying the complexity of the activator/coactivator mechanisms at enhancers. We then describe studies that examine how enhancers function in the genomic context and in combination with other enhancers, revealing that they activate genes through a variety of different mechanisms, working together as a system. Here, we primarily focus on synthetic reporter genes that can quantify the dynamics of enhancer biology through time. We end by considering the consequences of having many genes and enhancers within a 'local environment', which we believe leads to correlated gene expression and likely reports on the general principles of enhancer biology.

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.

High-throughput imaging (HTI) generates complex imaging datasets from a large number of experimental perturbations. Commercial HTI software for image analysis workflows does not allow full customization and adoption of new image processing algorithms in the analysis modules. While open-source HTI analysis platforms provide individual modules in the workflow, like nuclei segmentation, spot detection, or cell tracking, they are often limited in integrating novel analysis modules or algorithms. Here, we introduce the High-Throughput Image Processing Software (HiTIPS) to expand the range and customization of existing HTI analysis capabilities. HiTIPS incorporates advanced image processing and machine learning algorithms for automated cell and nuclei segmentation, spot signal detection, nucleus tracking, spot tracking, and quantification of spot signal intensity. Furthermore, HiTIPS features a graphical user interface that is open to integration of new algorithms for existing analysis pipelines and to adding new analysis pipelines through separate plugins. To demonstrate the utility of HiTIPS, we present three examples of image analysis workflows for high-throughput DNA FISH, immunofluorescence (IF), and live-cell imaging of transcription in single cells. Altogether, we demonstrate that HiTIPS is a user-friendly, flexible, and open-source HTI analysis platform for a variety of cell biology applications.

The recognition of polyadenylation signals (PAS) in eukaryotic pre-mRNAs is usually coupled to transcription termination, occurring while pre-mRNA is chromatin-bound. However, for some pre-mRNAs, this 3'-end processing occurs post-transcriptionally, i.e., through a co-transcriptional cleavage (CoTC) event downstream of the PAS, leading to chromatin release and subsequent PAS cleavage in the nucleoplasm. While DNA-damaging agents trigger the shutdown of co-transcriptional chromatin-associated 3'-end processing, specific compensatory mechanisms exist to ensure efficient 3'-end processing for certain pre-mRNAs, including those that encode proteins involved in the DNA damage response, such as the tumor suppressor p53. We show that cleavage at the p53 polyadenylation site occurs in part post-transcriptionally following a co-transcriptional cleavage event. Cells with an engineered deletion of the p53 CoTC site exhibit impaired p53 3'-end processing, decreased mRNA and protein levels of p53 and its transcriptional target p21, and altered cell cycle progression upon UV-induced DNA damage. Using a transcriptome-wide analysis of PAS cleavage, we identify additional pre-mRNAs whose PAS cleavage is maintained in response to UV irradiation and occurring post-transcriptionally. These findings indicate that CoTC-type cleavage of pre-mRNAs, followed by PAS cleavage in the nucleoplasm, allows certain pre-mRNAs to escape 3'-end processing inhibition in response to UV-induced DNA damage.