High-throughput approaches have transformed the study of gene regulation by enabling quantitative, genome-scale analyses in both genomics and imaging. However, applying these methods to intact organisms remains challenging, particularly for high-throughput, 3D imaging. In Caenorhabditis elegans , generalist segmentation models often perform poorly due to rapid changes in nuclear size, shape, and density. To overcome this obstacle, we developed One Click Wonder (OCW) , an automated pipeline that pairs a retrained Cellpose model with stage-specific parameter selection to deliver accurate, high-throughput segmentation of embryos. We further introduce the Biological Annotation and Association Mapper (BAAM) , which integrates segmentation with spot detection, to enable single-cell quantitation. Applied to the pioneer factor pha-4/FoxA , this pipeline revealed distinct cell populations with an eight-fold range in transcriptional burst frequency. These findings demonstrate that OCW and BAAM provide a modular, scalable pipeline for quantitative, single-cell analysis of gene expression in C. elegans embryos.

Heterogeneous NF-κB activation and enhancer features shape transcription in Drosophila immunity.

Mobile elements, particularly long terminal repeat retrotransposons (LTR-RTEs), are abundant and dynamic components of plant genomes. Although viral infections are known to transcriptionally activate retrotransposons, it remains unclear whether such virus-induced activation leads to their mobilization. To address this question, we examined LTR-RTE activation in Arabidopsis thaliana, Brassica napus, and Nicotiana benthamiana following infection with the RNA viruses Tobacco rattle virus (TRV), Potato virus X (PVX), and Tobacco ringspot virus (TRSV). Nanopore cDNA sequencing revealed virus-specific transcriptional responses, with PVX uniquely triggering a strong transcriptional burst of diverse LTR-RTE families in N. benthamiana. To test the role of viral suppressors of RNA silencing (VSRs) in this process, we analyzed extrachromosomal circular DNA (eccDNA) from plants infected with TRV expressing the VSR P19. This analysis identified eccDNA derived from Ty3/Gypsy Galadriel elements, demonstrating that viral infection can promote not only retrotransposon transcription but also eccDNA production, which may indicate the ability of LTR-RTEs to transpose. These findings clearly illustrate that plant–virus interactions can induce not only changes in gene transcription, but also the activation of multiple retrotransposons, highlighting a potential evolutionary interface linking antiviral defense and transposon regulation.

Gene activation and coregulation have been attributed to different mechanisms, such as enhancer-promoter interactions via chromatin looping or the accumulation of transcription factors into hubs or condensates. However, genome-wide studies exploring mechanistic differences in endogenous gene regulation in primary human cells are scarce. Here we dissect the proinflammatory gene expression programme induced by tumor necrosis factor (TNF) in human endothelial cells using sequencing- and imaging-based methods. Our findings, enabled by the co-accessibility analysis of deep-coverage single-cell chromatin accessibility data with our RWireX software, identified two distinct regulatory chromatin modules: autonomous links of co-accessibility (ACs) between separated sites and domains of contiguous co-accessibility (DCs) with increased local transcription factor binding. The TNF-dependent induction timing and strength as well as changes in transcriptional bursting kinetics differed for genes in the AC and DC modules, pointing to functionally distinct regulatory mechanisms. These findings provide a framework for understanding how cells achieve rapid and precise control of gene expression.

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.

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.

BackgroundHuman T-cell leukemia virus type 1 (HTLV-1) infects mainly CD4+ T lymphocytes and causes both malignant and inflammatory diseases: the aggressive malignancy known as Adult T-cell leukemia/lymphoma (ATL) and several chronic inflammatory syndromes. HTLV-1 infection is established by integration of proviral DNA (~9000 bp) into the host genome. In HTLV-1, two viral genes, tax and HBZ, play critical roles in viral transcription and promotion of T-cell proliferation, respectively. The present study was undertaken to test the hypothesis that the higher-order structure of proviral chromatin regulates its transcription on both the plus strand and the minus strand.ResultsATAC-seq analysis identified an open chromatin region in the pol gene of proviral DNA, which we name IPOR, in many ATL cases. Using reporter assays, it was found that the sequence of IPOR suppresses the transcription of the plus strand and activates that of the minus strand. Binding motifs of Eomes and TEAD proteins were predicted in this region, and we confirmed recruitment of the transcription factors to their respective motifs by ChIP-qPCR. A mutant of IPOR which cannot bind the transcription factors weakened the transcriptional activating effects compared with the wild type, suggesting that the IPOR and those transcription factors suppress the 5' long terminal repeat (LTR) but activate the 3'LTR. In addition, a mutant HTLV-1 molecular clone, which possesses the IPOR mutant, produced a higher titer of virus than the wild type. RNA-seq analysis of HTLV-1-infected cell lines, in which Tax expression can be traced after induction, revealed that EOMES expression decreases during the tax transcriptional burst and resumes following termination of the burst. These findings suggested that the expression dynamics of Eomes affect the transient expression of Tax.ConclusionsThe IPOR sequence appears to regulate the transcription from both LTRs, suppressing the 5'LTR but activating the 3'LTR. Recruitment of Eomes to the IPOR is likely to influence the expression of Tax and HBZ. Since both viral genes are involved in diverse mechanisms for viral replication, cellular proliferation, and immune regulation, the IPOR may play a role in fine-tuning the modes of viral persistence in vivo.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12977-025-00671-4.

In recent years, it has become evident that transcription is not always a continuous process. Rather, many genes exhibit bursting behavior characterized by discrete periods of transcriptional activity and inactivity. While transcriptional bursting has been broadly observed across different organisms, from bacteria to mammals, we lack a mechanistic understanding of the molecular events that regulate this widespread process. Specifically, how the expression of a bursty gene is quantitatively determined by different molecular factors such as the concentration of transcription factors (TF) and architecture of the enhancers is not well understood. Here, we introduce a model based on the interplay between chromatin state and TF binding in order to describe bursting dynamics. We leverage the widespread Monod-Wyman-Changeux two-state model to predict the dependence of transcriptional bursting dynamics on TF concentration, binding affinity, and number of TF binding sites. We use the model to qualitatively reproduce the behavior of bursting dynamics observed in the C. elegans gonad. Overall, we provide a tractable model for transcriptional bursting that offers mechanistic insights into the factors regulating transcriptional bursting and generates experimentally testable predictions capable of uncovering the molecular basis of this widespread process.

Circadian transcription factors (TFs) orchestrate daily rhythms in gene expression to drive rhythmic biological functions. In mammals, this system relies on the TF CLOCK:BMAL1, which binds E-boxes to initiate rhythmic transcription. While traditionally viewed as a master activator, CLOCK:BMAL1 is now recognized to engage in additional regulatory functions that are essential for its activity. This perspective focuses on the mammalian circadian clock and integrates genomic, structural, and single-molecule footprinting data to highlight emerging insights into how CLOCK:BMAL1 regulates chromatin architecture, cooperates with other TFs, and coordinates complex enhancer dynamics. We propose an updated framework for how circadian TFs operate within dynamic and multifactorial chromatin landscapes, and prime cis-regulatory elements for rhythmic transcriptional bursts. We also discuss how this framework underlies circadian reprogramming and transcriptional plasticity.

Evolutionary changes to gene expression are understood to be a major driver of phenotypic divergence between species. Researchers have investigated the drivers of this divergence by fitting evolutionary models to multi-species ‘omic’ datasets. It is now apparent that steady-state mRNA expression levels show patterns consistent with evolutionary constraints, likely as a consequence of stabilizing selection. However, as all previous work has used bulk RNA measurements, it has been impossible to determine which of the many cellular processes that contribute to steady-state abundances underlie the divergence between species. Here we develop a novel paradigm for addressing this open problem. Using multi-species single-cell expression data and biophysical models, we estimate mRNA transcriptional burst sizes, splicing rates and decay rates across multiple species. We then derive phylogenetic models that describe the divergence of these rates under alternative evolutionary scenarios and fit these to the comparative data. We find evidence for biophysical constraints on the rates of mRNA decay, such that macroevolutionary divergence in expression is primarily a consequence of variation in transcriptional bursting.

Dynamic spatiotemporal regulation of genetic information flow underlies all cellular processes, yet our current understanding still largely relies on static measurements. Real-time, dynamic recording of genetic information flow along the central dogma is therefore essential to reveal both the processes and molecular mechanisms at play. Recent advances in live-cell imaging, single-molecule fluorescence, super-resolution microscopy, gene editing, and computational analysis have greatly enhanced our ability to visualize genetic information flow across spatial and temporal scales. This review synthesizes the historical development, underlying principles, and technical implementations of dynamic DNA and RNA imaging approaches, comparing their capabilities, limitations, and optimal applications. We highlight key biological insights afforded by these methods-including chromatin dynamics, transcriptional bursting, RNA processing and transport, and localized translation-and discuss how multimodal integration with orthogonal biochemical and genomic techniques strengthens mechanistic interpretation. Finally, we identify current challenges and necessary breakthroughs. A deeper understanding of the fundamental principles governing dynamic genetic information flow could pave the way for deciphering the operational principles of non-equilibrium complex systems, thereby unlocking the organizational logic of complex living systems.

ABSTRACT Chilling temperatures are a major constraint on the early‐season performance of C 4 bioenergy crops in temperate regions. To dissect the temporal architecture of chilling resilience, we conducted an integrative, time‐resolved analysis of two Miscanthus sinensis genotypes contrasting in chilling tolerance, Ms12 (LCT) and Ms16 (HCT). Through stepwise chilling and recovery treatments, we profiled genotype‐specific changes in shoot physiology, hormone accumulation, gene expression, and importantly cell wall composition, a key yet understudied determinant of chilling resilience in perennial grasses. The high chilling‐tolerant genotype (HCT) maintained its shoot growth, photosynthetic performance, and membrane stability by activating a delayed but sustained program involving secondary wall reinforcement, ABA–JA hormonal crosstalk, and raffinose family oligosaccharide (RFO) accumulation in response to the extreme conditions. While, low chilling‐tolerant genotype (LCT) initiated a rapid transcriptional and hormonal response, which lacked persistence and failed to support structural recovery or metabolic buffering. In‐depth transcriptomic profiling revealed divergent dynamics between studied genotypes. The LCT genotype mounted an early transcriptional burst, while the HCT genotype showed prolonged induction of the cell wall biosynthesis, energy metabolism, and stress‐response genes. FTIR (Fourier‐transform infrared spectroscopy) and sugar quantification confirmed genotype‐specific remodeling of cell wall polymers. Moreover, hormone profiling showed that only the HCT genotype sustained ABA and JA signaling through the recovery process. RFOs accumulation, tightly linked to transcriptional activation of GolS (galactinol synthase) and RS (raffinose synthase) genes, was also more pronounced in the HCT genotype. Our findings demonstrate that chilling resilience in M. sinensis depends not on early response magnitude, but on the integration and temporal coordination of stress mitigation and recovery pathways. This work establishes a multiscale framework for identifying traits and regulatory modules underpinning chilling tolerance in perennial grasses, with direct relevance to climate‐resilient biomass plant breeding.

DNA supercoiling (SC), the over- and under-winding of DNA, is generated by transcription as described in the twin-domain model. Conversely, SC also impacts transcription through torsional stress. SC therefore regulates transcription dynamically and independently of transcription factor binding, particularly in the context of chromosomal topological domains and the activity of topoisomerases in bacteria. In this work, we develop numerical simulations of SC-coupled transcription of a single gene within a topological domain, based on a model incorporating stochastic transcription and activities of topoisomerase I and gyrase. We explore the effect of several parameters not systematically assessed in previous works (role of topoisomerase activities, topological domain size, gene expression strength) and compare the simulation results to a diverse set of experimental observations ranging from in vitro transcription assays to transcriptomics datasets from various species. This model recapitulates the non-monotonic dependence of transcription in vitro with the superhelical density of the plasmid template. Simulations of in vivo transcription in a closed domain exhibit a qualitatively different role for the two topoisomerases, as well as qualitatively different regulatory behaviors depending on the promoter strength. Specifically, topoisomerase I is required for strongly expressed genes that may be hindered by stalled RNA Polymerase, whereas gyrase activity favors the expression of all genes by enhancing transcription initiation and modulating the burstiness of transcription. The simulations exhibit a new mechanism for transcription bursting mediated by negative SC accumulating at the promoter region and modulating the initiation rate, resulting in levels of burstiness compatible with values reported in cells. Finally, we analyze several transcriptomics datasets from a range of evolutionarily distant species and show that topoisomerase inhibition is systematically associated with the repression of highly expressed genes. Simulations show this behavior to occur within a limited parameter range and thus indicate a biologically relevant regime for the simulations. Overall, this work provides a more quantitative description of how SC contributes to differential gene regulation and transcriptional bursting in bacteria.

DNA supercoiling (SC), the over- and under-winding of DNA, is generated by transcription as described in the twin-domain model. Conversely, SC also impacts transcription through torsional stress. SC therefore regulates transcription dynamically and independently of transcription factor binding, particularly in the context of chromosomal topological domains and the activity of topoisomerases in bacteria. In this work, we develop numerical simulations of SC-coupled transcription of a single gene within a topological domain, based on a model incorporating stochastic transcription and activities of topoisomerase I and gyrase. We explore the effect of several parameters not systematically assessed in previous works (role of topoisomerase activities, topological domain size, gene expression strength) and compare the simulation results to a diverse set of experimental observations ranging from in vitro transcription assays to transcriptomics datasets from various species. This model recapitulates the non-monotonic dependence of transcription in vitro with the superhelical density of the plasmid template. Simulations of in vivo transcription in a closed domain exhibit a qualitatively different role for the two topoisomerases, as well as qualitatively different regulatory behaviors depending on the promoter strength. Specifically, topoisomerase I is required for strongly expressed genes that may be hindered by stalled RNA Polymerase, whereas gyrase activity favors the expression of all genes by enhancing transcription initiation and modulating the burstiness of transcription. The simulations exhibit a new mechanism for transcription bursting mediated by negative SC accumulating at the promoter region and modulating the initiation rate, resulting in levels of burstiness compatible with values reported in cells. Finally, we analyze several transcriptomics datasets from a range of evolutionarily distant species and show that topoisomerase inhibition is systematically associated with the repression of highly expressed genes. Simulations show this behavior to occur within a limited parameter range and thus indicate a biologically relevant regime for the simulations. Overall, this work provides a more quantitative description of how SC contributes to differential gene regulation and transcriptional bursting in bacteria.

Aberrant chromatin-associated condensates have emerged as drivers of transcriptional dysregulation in cancer. Although extensive studies have elucidated intrinsic protein sequence features governing their formation, how extrinsic factors within the chromatin environment modulate their assembly and pathogenic function remains poorly understood. Gain-of-function mutations in the histone acetylation reader ENL, found in pediatric leukemia and Wilms tumor, drive oncogenesis by inducing condensate formation at highly selective genomic loci. Here, we uncover a critical role for locally produced gene transcripts in reinforcing the nucleation, chromatin engagement, and oncogenic activity of ENL mutant condensates. Mutant ENL binds RNA in part through a conserved basic patch within its YEATS domain, and this interaction enhances condensate formation both in vitro and across diverse cellular contexts. Using a chemically inducible condensate displacement and re-nucleation system, we show that blocking ENL-RNA interactions or transcription impairs condensate reformation at endogenous targets. RNA interactions preferentially enhance mutant ENL occupancy at top-bound, condensate-permissive loci, leading to increased transcriptional bursting and robust gene activation at the single-cell and single-allele level. In mouse models, disrupting ENL-RNA interactions reduces condensate formation and oncogenic transcription in hematopoietic stem and progenitor cells, thereby suppressing ENL mutant-driven leukemogenesis. Together, these findings demonstrate that locally produced RNA transcripts can promote locus-specific nucleation of pathogenic condensates on chromatin, which in turn drive persistent and hyperactive transcription of oncogenic targets and lead to tumorigenesis.

In this study, we apply machine learning to model the spatiotemporal dynamics of gene expression during early Drosophila embryogenesis. By optimizing model architecture, feature selection, and spatial grid resolution, we developed a predictive pipeline capable of accurately classifying active nuclei and forecasting their future distribution in time. We evaluated the model on two reporter constructs for the short gastrulation (sog) gene, sogD and sogD_∆Su(H), allowing us to assess its performance across distinct genetic contexts. The model achieved high accuracy on the wild-type sogD dataset, particularly along the dorsal–ventral (DV) axis during nuclear cycle 14 (NC14), and accurately predicted expression in the central regions of both wild-type and Suppressor of Hairless (Su(H)) mutant enhancers, sogD_∆Su(H). Bootstrap analysis confirmed that the model performed better in the central region than at the edges, where prediction accuracy dropped. Our previous work showed that Su(H) can act both as a repressor at the borders and as a stabilizer of transcriptional bursts in the center of the sog expression domain. This dual function is not unique to Su(H); other broadly expressed transcription factors also exhibit context-dependent regulatory roles, functioning as activators in some regions and repressors in others. These results highlight the importance of spatial context in transcriptional regulation and demonstrate the ability of machine learning to capture such nuanced behavior. Looking ahead, incorporating mechanistic features such as transcriptional bursting parameters into predictive models could enable simulations that forecast not just where genes are expressed but also how their dynamics unfold over time. This form of in silico enhancer mutagenesis would make it possible to predict the effects of specific binding site changes on both spatial expression patterns and underlying transcriptional activity, offering a powerful framework for studying cis-regulatory logic and modeling early developmental processes across diverse genetic backgrounds.

Sex-chromosome dosage poses a challenge for heterogametic species in maintaining the proper balance of gene products across chromosomes in each sex. While therian mammals (XX/XY system) achieve near-perfect balance of X-chromosome mRNAs through X-upregulation and X-inactivation, birds (ZW/ZZ system) have been found to lack efficient compensation at RNA level, challenging the necessity of resolving major gene-dosage asymmetries in avian cells. Through comprehensive allele-resolved multiome analyses, we examine dosage compensation in female (ZW), male (ZZ), and rare intersex (ZZW) chicken. Our data reveal that females upregulate their single Z chromosome through increased transcriptional burst frequency, mirroring mammalian X upregulation. Z-protein levels are further balanced in females through enhanced translation efficiency. Additionally, we present a global analysis of promoter elements regulating transcriptional burst kinetics in birds, revealing evolutionary conservation of the genomic encoding of burst kinetics between birds and mammals. Our study provides insights into the regulation of avian dosage compensation, and when considering all regulatory layers collectively, an unexpected similarity between avian and mammalian dosage compensation becomes apparent.

Gene expression noise, the inherent randomness in protein levels, plays a crucial role in cellular heterogeneity and diverse responses to environmental conditions. While transcriptional bursts and their impact on noise have been extensively studied over the past two decades, recent experiments suggest that mRNA folding-unfolding kinetics can also create bursts in gene translation. This means mRNA can switch between active and inactive states, while gene translation occurs only when mRNA is in the active state. However, the combined influence of transcriptional and translational bursts on gene expression noise remains largely unexplored. To address this, we present a gene expression model that integrates both transcriptional and translational bursting phenomena to provide a detailed understanding of the factors governing protein noise. Using the generating function technique, we solve the model and derive analytical expressions for mean protein levels and noise in protein copy numbers. Our findings show that translational bursting significantly contributes to overall noise and the noise from transcriptional bursts further amplifies the relative contribution of translational noise. We also find that translation efficiency, defined as the rate of protein synthesis from a single mRNA transcript, increases the overall noise of gene expression at fixed protein levels. This dependence of gene expression noise on translation efficiency suggests that both translation and transcription kinetics are required to be tuned simultaneously to achieve specific protein levels and gene expression noise. Thus, this study improves our understanding of the factors regulating gene expression noise, providing insights into how transcriptional and translational bursting shape this noise.

Long noncoding RNA-dependent control of Myc transcriptional bursting.

Drought-activated BZR1 reprograms flavonoid metabolism via transcriptional cascades to amplify baicalin biosynthesis in Scutellaria baicalensis.