Most advanced melanomas initially respond to targeted therapy but eventually relapse. Rather than acquiring new mutations, resistance is driven by drug-tolerant persister cells that enter a reversible drug-refractory state. We developed MeRLin, a high-resolution lineage tracing platform integrating cellular barcoding, single-cell transcriptomics, RNA fluorescence in situ hybridization (FISH), and computational analyses to track clonal and transcriptional dynamics in patient-derived melanoma models during prolonged therapy. Clonal dynamics revealed that persister subpopulations first responded to treatment but persisted and expanded during minimal residual disease, ultimately leading to tumor recurrence. Pre-treatment melanoma populations diversified into four conserved persister states characterized by stress-like, lipid metabolism, PI3K signaling, and extracellular matrix remodeling programs associated with adaptive resistance. Spatial transcriptomics showed the organization of these adaptive programs and a complex signaling network of autocrine and paracrine interactions among persister subpopulations. Barcoded RNA-FISH enabled spatial mapping of clonal identity and gene expression, revealing in situ co-localization of a dominant resistant clone with SLC2A1 expression. MeRLin provides a robust framework for dissecting cancer heterogeneity and identifying vulnerabilities in persister populations.

Transcription of ribosomal RNAs (rRNAs) from rDNA repeats is the first step of ribosome biogenesis, accounting for a major portion of all cellular transcription. Often regarded as a housekeeping process, its cell-type-specific regulation in complex organ systems is largely neglected. We used rRNA FISH-Flow to profile nascent and mature rRNA levels in detail across mouse hematopoiesis, and observed that rRNA abundance is a cell-type-specific property, largely uncoupled from cell cycling or protein synthesis rates. Absolute quantification of rRNA molecules unexpectedly revealed that 28S rRNA is in excess in all cell types, most prominently in the normal myeloid lineage. In acute myeloid leukemia (AML), leukemic progenitors showed notably higher nascent and mature rRNA levels than matched normal counterparts. Across contexts of hematopoiesis, broad trends in rRNA transcription paralleled changes in accessibility but not methylation of rDNA repeats. Collectively, our work provides a detailed map of the complex dynamics of rRNAs within and between normal and leukemic hematopoiesis.

The NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3) inflammasome is a multiprotein signaling complex that triggers pyroptotic cell death and interleukin (IL)-1 family cytokine release during infection and cell injury. Its assembly is driven by the adaptor protein, apoptosis-associated speck-like protein containing a CARD (ASC), whose filamentation forms a supramolecular speck upon NLRP3 activation to amplify inflammasome signaling. While the NLRP3 inflammasome is well appreciated as a sensor of environmental danger and damage, little is known about how homeostatic environmental factors like dietary metabolites regulate its activity. Here, we find that environmental availability of the branched-chain amino acids (BCAAs), leucine, isoleucine, and valine, controls NLRP3 inflammasome assembly. While ASC is typically viewed as a constitutively expressed, unregulated inflammasome component, we find that Toll-like receptor 4 (TLR4) activation triggers localization of ASC mRNA to the perinuclear space. Moreover, our data demonstrate that ASC undergoes TLR4-driven translational bursting from polyribosomes during inflammasome priming. This translational engagement is dependent on BCAA availability and mechanistic target of rapamycin (mTOR) activity, which regulate the kinetics of inflammasome assembly. In contrast, the translation of NLRP3 and caspase-1 is largely insensitive to these inputs. Furthermore, we find that BCAAs regulate NLRP3 inflammasome activation in both mouse and human macrophages, in the context of bacterial infection, and during lipopolysaccharide (LPS)-induced sepsis in vivo. Altogether, this work unveils a novel inflammasome priming event governed by the amino acid environment. These findings further highlight how the activity of proteins maintained in equilibrium like ASC can be dynamically regulated through rapid changes in mRNA translation.

Embryonic development typically requires precise coordination among cells to achieve reproducible outcomes, leading to the assumption that cellular heterogeneity must be minimized or buffered against. Using fluorescence-based lineage tracing in combination with spatial transcriptomics, we show that, in the gastruloid model of early development, pre-existing heterogeneity promotes proper axial organization through division of labor among stem cell clones. Individual clones isolated from a common population exhibit consistent spatial propensities for anterior or posterior fates. While pure clones generate elongated structures less frequently than a polyclonal population, mixing clones restores proper axial elongation. Spatial transcriptomics reveals that pure clones show disrupted gene expression with inappropriate coexpression of anterior and posterior markers, while clone combinations restore proper spatial organization. Using RNA-seq, ATAC-seq, and perturbations to key developmental signaling pathways, we further profile differences among clones and suggest a model whereby developmental precision emerges from the coordinated action of intrinsically biased clonal populations.

Resistance to targeted therapies is a significant clinical problem, but eliminating resistant cancer cells has proven difficult. One potential reason for this difficulty is heterogeneity in the resistant population: even genetically homogeneous cancer cell populations can give rise to many resistant subtypes, each potentially with specific second-line drug vulnerabilities. Using high-throughput drug screening of genetically-identical resistant clones with varying transcriptomes and morphologies, we show that each clone had a distinct drug sensitivity profile. These results suggested that there are drugs that are effective against only subsets of resistant populations but in combination eliminate a large proportion of the resistant population. Using the individual clone sensitivity profiles, we prospectively identified combinations that were highly effective at eliminating most of the resistant population. Our results demonstrate the effectiveness of "subpopulation-directed synergy", showing that considering population heterogeneity can reveal therapeutic opportunities otherwise masked by population averages, offering new strategies to combat therapy resistance.

Innate immune memory (also termed trained immunity) is defined in part by its ability to cross-protect against heterologous pathogens, and can be generated by many different stimuli, suggesting a "universal" trained state. However, different stimuli could form distinct memories, leading to stimulus-specific trained responses. Here, we use primary human monocyte-derived macrophages to demonstrate phenotypic and epigenetic stimulus specificity of innate immune memory six days after initial exposure. Quantification of cytokine production with single-molecule RNA imaging demonstrates stimulus-specific patterns of response to restimulation at the single cell level. Differential licensing of inflammatory transcription factors is associated with encoding of specificities in chromatin. Trained cells show stronger responses to secondary stimuli that are more similar to the initial stimulus they experienced, suggesting a functional role for these stimulus-specific memories. Rather than activating a universal training state, our findings demonstrate that different stimuli impart specific memories that generate distinct training phenotypes in macrophages.

Objective: To investigate whether oral treatment with 12.5 mg iodine additional to standard of care is effective in reducing mortality and clinical deterioration of patients hospitalized with COVID-19. Methods: A single center, randomized clinical trial (EudraCT 2020-001852-16) enrolled patients with severe covid-19 requiring hospitalization, randomized into two groups. The first group received 12.5 mg oral iodine for 8 days; the second group received standard care only. Primary endpoints were disease deterioration defined as transfer to intensive care unit (ICU) or death. Additional parameters followed WHO recommendations from early pandemic period. The inclusion phase ran from October 2020 to April 2022. In vitro validations were also performed. Results: Analysis of 141 participants revealed no significant differences in mortality or ICU transfers between the iodine-treated group (67 patients) and control group (74 patients). Exploratory analysis found patients receiving oral iodine had significantly shorter ICU stays (p=0.016). In vitro validations showed increased virus-induced type I interferon responses upon iodine administration in pulmonary cells. Conclusion: While iodine does not reduce mortality or ICU admissions, it may enhance antiviral immunity through increased type I interferon responses, contributing to shorter ICU stays in COVID-19 patients. The role of iodine in enhancing IFN-I mediated antiviral immunity warrants future research.

Individual cells within a given population exhibit striking variability in viral susceptibility, but it remains unknown whether this heterogeneity reflects memories encoded into the cellular lineage or true probabilistic variability. We used multi-color lineage tracing in a human primary organotypic skin model to reveal that viral resistance is encoded within specific cellular lineages. These lineages create distinct boundaries that block viral spread. Our lineage analyses in vitro confirmed that viral susceptibility exhibits strong heritability across cell generations, with siblings and cousins displaying remarkably similar infection outcomes. ATAC and proteomics profiling of resistant and susceptible clones revealed distinct epigenomic and proteomic states, with the transcription factor AP-1 emerging as a potential central regulator of lineage-encoded viral resistance. Inducing AP-1 activity with PMA rendered cells resistant to viral infection, suggesting a causative role in mediating resistance memory. Our findings demonstrate that antiviral resistance in human skin cells is encoded within cellular lineages and preserved through cell divisions, revealing how cell memory may shape infection dynamics and viral containment in tissues.

The intestinal epithelium exhibits zonated gene expression along the crypt-villus axis, with distinct transcriptional programs in enterocytes at the villus top versus bottom. However, the mechanisms establishing these spatial patterns remain unclear. Three models could explain zonation: external gradients, cell-intrinsic temporal programs, or local self-organization. Using spatial transcriptomics and perturbations of two-dimensional intestinal organoids, we show that zonation emerges via spontaneous self-organization without mesenchymal, neural, or vascular inputs. Cell-intrinsic models were eliminated by transplanting cells into established monolayers; transplanted cells progressively adopted zonation profiles matching their new location, with strongly zonated genes showing the greatest adaptive responses. Pharmacological inhibition of EphA2 receptors disrupted zonation, revealing a previously unknown role for epithelial EphA-ephrin-A signaling in regulating enterocyte zonation. These findings demonstrate that self-organization through local epithelial cell-cell communication generates spatial patterns independently of external positional cues or cell-autonomous programs.

In metazoans, gene duplication has given rise to paralogous transcription factors, which have functionally diversified to control cellular differentiation. While the majority of paralogous TFs are dispersed across different chromosomes, some remain clustered raising the question of whether genomic proximity confers any evolutionary advantage for TF clusters. To address this, we investigated a ~1 Mbp locus containing two ETS family paralogs, Ets1 and Fli1. Using a sub-diffraction sequential imaging technique called Optical Reconstruction of Chromatin Architecture (ORCA), we traced the 3D organization of this region in single alleles of T cells from genetically engineered mice with targeted deletions of key regulatory elements. In wild-type T cells, the predominant chromatin conformation spatially links Ets1 to its proximal super-enhancer, segregating Ets1 from Fli1. This topology correlates with high Ets1 and low Fli1 expression. Deletion of the Ets1 super-enhancer abolishes this configuration, triggering locus-wide architectural rewiring that increases Ets1-Fli1 promoter-promoter interactions and subsequently the co-expression of two genes within individual cells. Remarkably, this compensatory interaction bypasses insulated chromatin domains, sustaining Ets1 levels necessary for T cell development despite enhancer loss. Our results reveal that genomic clustering of TF paralogs enables dynamic architectural plasticity: while a super-enhancer fine-tunes paralog expression balance in wild-type contexts, its deletion unmasks latent promoter-driven coordination, suggesting that proximity safeguards functional redundancy and transcriptional resilience critical for cellular fitness.

Gastruloids are three-dimensional stem-cell-based models that recapitulate key aspects of mammalian gastrulation, including formation of an anterior-posterior (AP) axis. However, we do not have detailed spatial information about gene expression and cell type organization, particularly at the level of individual gastruloids. Here, we report a spatially resolved, single-cell molecular catalog of the transcriptomes of 26 individual gastruloids. We found that cell type composition and spatial organization were remarkably consistent across gastruloids. Posterior cell types formed distinct, organized clusters, while anterior cell types were more disorganized. To distinguish progressive differentiation from cell type differences, we developed the L-metric, a parameter-free quantification of mutually exclusive gene expression. This analysis revealed spatial organization without explicit encoding, recapitulated known cell type relationships, and identified novel gene expression states and spatial subclusters within cell types. We confirmed that in gastruloids, NMP differentiation occurred through a continuous, spatially-coordinated process. We also showed that endothelial precursors exhibited unique spatial organization and had distinct gene expression profiles dependent on their association with anterior somitic or posterior endodermal tissues. This work enables the rigorous use of gastruloids as models for studying the molecular mechanisms underlying mammalian development and tissue organization, and introduces novel computational tools for analyzing spatially-resolved single-cell datasets.

Cellular responses to environmental stimuli are typically thought to be governed by genetically encoded programs. We demonstrate that melanoma cells can form and maintain cellular memories during the acquisition of therapy resistance that exhibit characteristics of cellular learning and are dependent on the transcription factor AP-1. We show that cells exposed to a low dose of therapy adapt to become resistant to a high dose, demonstrating that resistance was not purely selective. The application of therapy itself results in the encoding of transient gene expression into cellular memory and that this encoding occurs for both transiently induced and probabilistically arising expression. Chromatin accessibility showed concomitant persistence. A two-color AP-1 reporter system showed that these memories are encoded in cis, constituting an example of activating cis epigenetics. Our findings establish the formation and maintenance of cellular memories as a critical aspect of gene regulation during the development of therapy resistance.

Trained immunity (a form of innate immune memory), defined in part by heightened responses to pathogen restimulation, can be generated by many different stimuli. However, both the quantitative differences in trained states generated by different stimuli and the downstream consequences of those differences remain unclear. Here, we used primary human monocyte-derived macrophages to demonstrate phenotypic and molecular stimulus specificity of trained immunity six days after initial exposure. Quantification of cytokine production with single-molecule RNA imaging demonstrated stimulus-specific patterns of response to restimulation, with trained cells showed stronger responses to secondary stimuli more similar to their initial stimulation. Differential licensing of inflammatory transcription factors was associated with encoding of specificities in chromatin six days after training, while memory of some, but not all, training stimuli is lost by eleven days post-training in vitro. Overall, our findings demonstrate that different training stimuli can impart specific memories which generate distinct training phenotypes.

Infectious diseases remain a global health challenge, driven by increasing antimicrobial resistance and the threat of emerging epidemics. *Mycobacterium tuberculosis* and *Staphylococcus aureus* are leading causes of mortality worldwide. Trained immunity — a form of innate immune memory — offers a promising approach to enhance pathogen clearance. Here, we demonstrate that IFN-γ induces trained immunity in human monocytes through a mechanism involving mTORC1 activation, glutaminolysis, and epigenetic remodeling. Macrophages derived from IFN-γ–trained monocytes exhibited increased glycolytic activity with enhanced cytokine and chemokine responses upon stimulation or infection. Crucially, trained macrophages had increased production of reactive oxygen species, which mediated enhanced bactericidal activity against methicillin-resistant *S*. *aureus* and *M*. *tuberculosis*. Furthermore, ATAC-sequencing analysis of IFN-γ–trained macrophages revealed increased chromatin accessibility in regions associated with host defense. Last, IFN-γ training restored impaired innate responses in macrophages from individuals homozygous for the *TIRAP* 180L polymorphism, a genetic variant associated with increased susceptibility to infection. These findings establish IFN-γ as a potent inducer of trained immunity in human monocytes and support its potential as a host-directed strategy to strengthen antimicrobial defenses, particularly in genetically susceptible individuals and high-risk clinical contexts.

Imaging has been critical to biological discoveries for centuries. Throughout, one of the primary challenges has been the quantitative analysis of these images. The solutions to date have largely involved custom software in combination with software packages such as ImageJ, napari, CellProfiler, MATLAB, and others. However, there remains a need for users to interact with their data even if they lack the ability to code. New machine-learning algorithms have the potential to scale our ability to accurately quantify imaging data, but the technical expertise required to deploy these tools puts them out of reach for many users. Here, we introduce NimbusImage, a software package that addresses these challenges. NimbusImage brings advancements in image analysis to users who may otherwise find such tools difficult to use, all in an easy-to-use web-based platform. Key features include cloud-based deployment, an intuitive interface that enables direct interaction with data, an extensible API (application programming interface), and plug-ins that combine conventional analytical methods with newer deep-learning techniques.

Macrophages can remember prior activation and subsequently augment their response to restimulation through trained immunity. However, it remains uncertain how trained immunity phenotypes manifest in individual cells. Here, we leverage highly quantitative single-molecule RNA imaging across 90,857 individual macrophages from 26 human donors to reveal inflammatory response dynamics in trained versus untrained populations at single-cell resolution. Different inflammatory response genes showed distinct single-cell behavior in trained populations upon restimulation. Although training increased transcription of these response genes early after restimulation, untrained populations eventually "caught up" to the transcriptional output of trained populations, highlighting the importance of sampling timescale when interpreting transcriptional assays of training. Training did not significantly alter the relationship between transcriptional activation of different genes within the same single cell, and any single cell appeared to be capable of training. Overall, these results revealed gene-specific single-cell transcriptional changes that generate population-wide training phenotypes in macrophages.

Resistance to cancer therapy is driven by both cell-intrinsic and microenvironmental factors. We use spatial transcriptomics and single-cell RNA sequencing to uncover distinct resistance programs in melanoma cells shaped by intrinsic cellular states and the tumor microenvironment. Consensus non-negative matrix factorization reveals shared intrinsic resistance programs across cell lines. In patient samples, these resistance programs coexist within individual tumors and associate with diverse immune signatures. Single-cell resolution spatial transcriptomics in xenograft models reveals both intrinsically determined and extrinsically influenced resistant fates. This work demonstrates that therapy-resistant fates coexist within distinct microenvironments and that tissue features influence which fate is adopted.

Nuclear speckles are dynamic nuclear bodies with high concentrations of RNA production factors. Here we identify two main speckle signatures in human cancer: one similar to healthy tissue and another aberrant state. Aberrant speckles display altered nuclear positioning, elevated TREX RNA export complex levels, and correlate with poorer outcomes in clear cell renal cell carcinoma (ccRCC). We reveal that the HIF-2α transcription factor promotes physical association of target genes with speckles through specific protein motifs. Similar motifs appear in other transcription factors, suggesting DNA-speckle targeting operates as a general regulatory mechanism. Functional, genomic, and imaging analyses demonstrate that HIF-2α regulatory programs are influenced by speckle state and HIF-2α-driven speckle targeting disruption. In ccRCC, nuclear speckles functionally modulate select HIF-2α-regulated genes affecting patient outcomes. Across tumors broadly, speckle states correlate with altered pathways and expression of speckle-associated genes, establishing a general connection between nuclear speckles and gene expression dysregulation in cancer.

Single-molecule RNA fluorescence in situ hybridization (RNA FISH)-based spatial transcriptomics methods have enabled the accurate quantification of gene expression at single-cell resolution by visualizing transcripts as diffraction-limited spots. Although these methods generally scale to large samples, image analysis remains challenging, often requiring manual parameter tuning. We present Piscis, a fully automatic deep learning algorithm for spot detection trained using a loss function, the SmoothF1 loss, that approximates the F1 score to directly penalize false positives and false negatives but remains differentiable and hence usable for training by deep learning approaches. Piscis was trained and tested on a diverse dataset composed of 358 manually annotated experimental RNA FISH images representing multiple cell types and 240 additional synthetic images. Piscis outperforms other state-of-the-art spot detection methods, enabling accurate, high-throughput analysis of RNA FISH-derived imaging data without the need for manual parameter tuning.

The ability of a virus to infect a cell is partly determined by host factors required for the viral life cycle. However, not every cell of a given type is equally susceptible to infection. Profiling susceptible subsets of cells could reveal additional host factors, but viral infection obscures and remodels the state of these cells prior to infection. We used single-cell clone tracing to retrospectively identify cells that were highly susceptible to infection with SARS-CoV-2. Depletion of certain factors identified by our approach revealed roles in viral entry, whereas others exerted control over the infectable cell state itself. Patient lung samples revealed heterogeneous expression of these factors in vivo, with heightened expression in particular inflammatory pathologies. We further found a distinct cell state that was susceptible to the influenza A virus. Thus, intrinsic variability in state is a major determinant of whether individual cells can be infected by a virus.

Imaging-based spatial transcriptomics methods allow for the measurement of spatial determinants of cellular phenotypes but are incompatible with random barcode-based clone-tracing methods, preventing the simultaneous detection of clonal and spatial drivers. Here we report SpaceBar, which enables simultaneous clone tracing and spatial gene expression profiling with standard imaging-based spatial transcriptomics pipelines. Our approach uses a library of 96 synthetic barcode sequences that combinatorially labels each cell. Thus, SpaceBar can distinguish between clonal dynamics and environmentally driven transcriptional regulation in complex tissue contexts.

Splicing is the stepwise molecular process by which introns are removed from pre-mRNA and exons are joined together to form mature mRNA sequences. The ordering and spatial distribution of these steps remain controversial, with opposing models suggesting splicing occurs either during or after transcription. We used single-molecule RNA FISH, expansion microscopy, and live-cell imaging to reveal the spatiotemporal distribution of nascent transcripts in mammalian cells. At super-resolution levels, we found that pre-mRNA formed clouds around the transcription site. These clouds indicate the existence of a transcription-site-proximal zone through which RNA move more slowly than in the nucleoplasm. Full-length pre-mRNA undergo continuous splicing as they move through this zone following transcription, suggesting a model in which splicing can occur post-transcriptionally but still within the proximity of the transcription site, thus seeming co-transcriptional by most assays. These results may unify conflicting reports of co-transcriptional versus post-transcriptional splicing.

Pluripotency can be induced in somatic cells by expressing OCT4, KLF4, SOX2, and MYC. Usually only a rare subset of cells reprogram, and the molecular characteristics of this subset remain unknown. We apply retrospective clone tracing to identify and characterize the rare human fibroblasts primed for reprogramming. These fibroblasts showed markers of increased cell cycle speed and decreased fibroblast activation. Knockdown of a fibroblast activation factor identified by our analysis increased the reprogramming efficiency. We provide evidence for a unified model in which cells can move into and out of the primed state over time, explaining how reprogramming appears deterministic at short timescales and stochastic at long timescales. Furthermore, inhibiting the activity of LSD1 enlarged the pool of cells that were primed for reprogramming. Thus, even homogeneous cell populations can exhibit heritable molecular variability that can dictate whether individual rare cells will reprogram or not.

Sustained responses to transient environmental stimuli are important for survival. The mechanisms underlying long-term adaptations to temporary shifts in abiotic factors remain incompletely understood. Here, we find that transient cold exposure leads to sustained transcriptional and metabolic adaptations in brown adipose tissue, which improve thermogenic responses to secondary cold encounter. Primary thermogenic challenge triggers the delayed induction of a lipid biosynthesis programme even after cessation of the original stimulus, which protects from subsequent exposures. Single-nucleus RNA sequencing and spatial transcriptomics reveal that this response is driven by a lipogenic subpopulation of brown adipocytes localized along the perimeter of Ucp1hi adipocytes. This lipogenic programme is associated with the production of acylcarnitines, and supplementation of acylcarnitines is sufficient to recapitulate improved secondary cold responses. Overall, our data highlight the importance of heterogenous brown adipocyte populations for 'thermogenic memory', which may have therapeutic implications for leveraging short-term thermogenesis to counteract obesity.

Clustering cells based on their high-dimensional profiles is an important data reduction process by which researchers infer distinct cellular states. The advent of cellular barcoding, however, provides an alternative means by which to group cells: by their clonal origin. We developed ClonoCluster, a computational method that combines both clone and transcriptome information to create hybrid clusters that weight both kinds of data with a tunable parameter. We generated hybrid clusters across six independent datasets and found that ClonoCluster generated qualitatively different clusters in all cases. The markers of these hybrid clusters were different but had equivalent fidelity to transcriptome-only clusters. The genes most strongly associated with the rearrangements in hybrid clusters were ribosomal function and extracellular matrix genes. We also developed the complementary tool Warp Factor that incorporates clone information in popular 2D visualization techniques like UMAP. Integrating ClonoCluster and Warp Factor revealed biologically relevant markers of cell identity.

Even among genetically identical cancer cells, resistance to therapy frequently emerges from a small subset of those cells. Molecular differences in rare individual cells in the initial population enable certain cells to become resistant to therapy; however, comparatively little is known about the variability in the resistance outcomes. Here we develop and apply FateMap, a framework that combines DNA barcoding with single-cell RNA sequencing, to reveal the fates of hundreds of thousands of clones exposed to anti-cancer therapies. We show that resistant clones emerging from single-cell-derived cancer cells adopt molecularly, morphologically and functionally distinct resistant types. These resistant types are largely predetermined by molecular differences between cells before drug addition and not by extrinsic factors. Changes in the dose and type of drug can switch the resistant type of an initial cell, resulting in the generation and elimination of certain resistant types. Samples from patients show evidence for the existence of these resistant types in a clinical context. We observed diversity in resistant types across several single-cell-derived cancer cell lines and cell types treated with a variety of drugs. The diversity of resistant types as a result of the variability in intrinsic cell states may be a generic feature of responses to external cues.

Metastasis occurs when tumor cells leave the primary tumor site and disseminate to distal organs. Even though most cells remain in the primary tumor, the circumstances by which a small fraction of them disseminate remain unclear. Here, we show that a rare, highly invasive subpopulation of melanoma cells can be detected within clonal cell lines due to non-genetic fluctuations in gene expression. The highly invasive phenotype was intrinsic to the cells, independent of their environment, and was marked by transiently high levels of SEMA3C expression, as revealed by RNA-sequencing analysis. Furthermore, the invasive subpopulation drove the bulk dissemination of tumor cells to distal locations in a mouse model of melanoma. The transcription factor NKX2.2 regulated the proportion of invasive cells in the melanoma 1205Lu cell line. Furthermore, an overall tradeoff between proliferation and invasion in single cells was observed. Our results suggest that phenotypes like metastasis may arise from intrinsic differences stemming from non-genetic fluctuations between single cells.

Genetic networks face a fundamental challenge: they must respond to signals while filtering out random fluctuations. This study develops a mathematical framework showing that allelic correlation and noise transmission correspond across model parameters and network architectures. The research reveals an inherent trade-off -- reducing noise transmission decreases responsiveness to signals, while maintaining signal responsiveness necessarily permits some noise to propagate. Within responsive systems, cells can minimize noise by sacrificing response speed. Analysis of single-cell RNA sequencing data indicates upstream regulatory factors exhibit higher allelic correlation than downstream targets, suggesting they experience stricter regulation. The findings suggest noise transmission is an unavoidable consequence of signal responsiveness but can be minimized through slower response kinetics.

Cardiac differentiation of human-induced pluripotent stem (hiPS) cells consistently produces a mixed population of cardiomyocytes and non-cardiac cell types, even when using well-characterized protocols. We sought to determine whether different cell types might result from intrinsic differences in hiPS cells prior to the onset of differentiation. By associating individual differentiated cells that share a common hiPS cell precursor, we tested whether expression variability is predetermined from the hiPS cell state. In a single experiment, cells that shared a progenitor were more transcriptionally similar to each other than to other cells in the differentiated population. However, when the same hiPS cells were differentiated in parallel, we did not observe high transcriptional similarity across differentiations. Additionally, we found that substantial cell death occurs during differentiation in a manner that suggested all cells were equally likely to survive or die, suggesting that there is no intrinsic selection bias for cells descended from particular hiPS cell progenitors. We thus wondered how cells grow spatially during differentiation, so we labeled cells by expression of marker genes and found that cells expressing the same marker tended to occur in patches. Our results suggest that cell type determination across multiple cell types, once initiated, is maintained in a cell-autonomous manner for multiple divisions. Altogether, our results show that while substantial heterogeneity exists in the initial hiPS cell population, it is not responsible for the variability observed in differentiated outcomes; instead, factors specifying the various cell types likely act during a window that begins shortly after the seeding of hiPS cells for differentiation.

A major goal in transcriptional regulation is mapping transcription factor binding changes to resulting gene expression alterations. This study investigated chromatin accessibility and gene expression concordance using ATAC-seq and RNA-seq in MCF-7 breast cancer cells treated with retinoic acid and TGF-beta. The researchers identified two gene classes: those exhibiting expression changes with corresponding chromatin accessibility modifications, and those showing significant expression changes despite minimal accessibility alterations. Genes in the first group had lower baseline accessibility before signal exposure. Notably, focusing analysis on peaks containing transcription factor motifs relevant to these signaling pathways did not substantially improve the observed correspondence. Comparisons with hematopoietic differentiation data revealed much stronger concordance in that context, suggesting multifactorial biological processes like differentiation produce accessibility changes reflecting altered transcriptional status, whereas single-factor perturbations can drive expression changes independently of local chromatin accessibility modifications.

RNA labeling in situ has enormous potential to visualize transcripts and quantify their levels in single cells, but it remains challenging to produce high levels of signal while also enabling multiplexed detection of multiple RNA species simultaneously. Here, we describe clampFISH 2.0, a method that uses an inverted padlock design to efficiently detect many RNA species and exponentially amplify their signals at once, while also reducing the time and cost compared with the prior clampFISH method. We leverage the increased throughput afforded by multiplexed signal amplification and sequential detection to detect 10 different RNA species in more than 1 million cells. We also show that clampFISH 2.0 works in tissue sections. We expect that the advantages offered by clampFISH 2.0 will enable many applications in spatial transcriptomics.

Transcription at most promoters is divergent, initiating at closely spaced oppositely oriented core promoters to produce sense transcripts along with often unstable upstream antisense transcripts (uasTrx). How antisense transcription is regulated and to what extent it is coordinated with sense transcription is not well understood. Here, by combining acute degradation of the multi-functional transcription factor CTCF and nascent transcription measurements, we find that CTCF specifically suppresses antisense but not sense transcription at hundreds of divergent promoters. Primary transcript RNA-FISH shows that CTCF lowers burst fraction but not burst intensity of uasTrx and that co-bursting of sense and antisense transcripts is disfavored. Genome editing, chromatin conformation studies and high-resolution transcript mapping revealed that precisely positioned CTCF directly suppresses the initiation of uasTrx, in a manner independent of its architectural function. In sum, CTCF shapes the transcriptional landscape in part by suppressing upstream antisense transcription.

Organoids recapitulate complex 3D organ structures and represent a unique opportunity to probe the principles of self-organization. While we can alter an organoid's morphology by manipulating the culture conditions, the morphology of an organoid often resembles that of its original organ, suggesting that organoid morphologies are governed by a set of tissue-specific constraints. Here, we establish a framework to identify constraints on an organoid's morphological features by quantifying them from microscopy images of organoids exposed to a range of perturbations. We apply this framework to Madin-Darby canine kidney cysts and show that they obey a number of constraints taking the form of scaling relationships or caps on certain parameters. For example, we found that the number, but not size, of cells increases with increasing cyst size. We also find that these constraints vary with cyst age and can be altered by varying the culture conditions. We observed similar sets of constraints in intestinal organoids. This quantitative framework for identifying constraints on organoid morphologies may inform future efforts to engineer organoids.

Cellular plasticity describes the ability of cells to transition from one set of phenotypes to another. In melanoma, transient fluctuations in the molecular state of tumor cells mark the formation of rare cells primed to survive BRAF inhibition and reprogram into a stably drug-resistant fate. However, the biological processes governing cellular priming remain unknown. We used CRISPR-Cas9 genetic screens to identify genes that affect cell fate decisions by altering cellular plasticity. We found that many factors can independently affect cellular priming and fate decisions. We discovered a new plasticity-based mode of increasing resistance to BRAF inhibition that pushes cells towards a more differentiated state. Manipulating cellular plasticity through inhibition of DOT1L before the addition of the BRAF inhibitor resulted in more therapy resistance than concurrent administration. Our results indicate that modulating cellular plasticity can alter cell fate decisions and may prove useful for treating drug resistance in other cancers.

Nuclear speckles are prominent nuclear bodies that contain proteins and RNA involved in gene expression. Although links between nuclear speckles and gene activation are emerging, the mechanisms regulating association of genes with speckles are unclear. We find that speckle association of p53 target genes is driven by the p53 transcription factor. Focusing on p21, a key p53 target, we demonstrate that speckle association boosts expression by elevating nascent RNA amounts. p53-regulated speckle association did not depend on p53 transactivation functions but required an intact proline-rich domain and direct DNA binding, providing mechanisms within p53 for regulating gene-speckle association. Beyond p21, a substantial subset of p53 targets have p53-regulated speckle association. Strikingly, speckle-associating p53 targets are more robustly activated and occupy a distinct niche of p53 biology compared with non-speckle-associating p53 targets. Together, our findings illuminate regulated speckle association as a mechanism used by a transcription factor to boost gene expression.

Identifying the particular transcription factors that maintain cell type in vitro is important for manipulating cell type. Identifying such transcription factors by their cell-type-specific expression or their involvement in developmental regulation has had limited success. We hypothesized that because cell type is often resilient to perturbations, the transcriptional response to perturbations would reveal identity-maintaining transcription factors. We developed perturbation panel profiling (P3) as a framework for perturbing cells across many conditions and measuring gene expression responsiveness transcriptome-wide. In human iPSC-derived cardiac myocytes, P3 showed that transcription factors important for cardiac myocyte differentiation and maintenance were among the most frequently upregulated (most responsive). We reasoned that one function of responsive genes may be to maintain cellular identity. We identified responsive transcription factors in fibroblasts using P3 and found that suppressing their expression led to enhanced reprogramming. We propose that responsiveness to perturbations is a property of transcription factors that help maintain cellular identity in vitro.

Molecular differences between individual cells can lead to dramatic differences in cell fate, such as death versus survival of cancer cells upon drug treatment. These originating differences remain largely hidden due to difficulties in determining precisely what variable molecular features lead to which cellular fates. Thus, we developed Rewind, a methodology that combines genetic barcoding with RNA fluorescence in situ hybridization to directly capture rare cells that give rise to cellular behaviors of interest. Applying Rewind to BRAFV600E melanoma, we trace drug-resistant cell fates back to single-cell gene expression differences in their drug-naive precursors (initial frequency of ~1:1,000-1:10,000 cells) and relative persistence of MAP kinase signaling soon after drug treatment. Within this rare subpopulation, we uncover a rich substructure in which molecular differences among several distinct subpopulations predict future differences in phenotypic behavior, such as proliferative capacity of distinct resistant clones after drug treatment. Our results reveal hidden, rare-cell variability that underlies a range of latent phenotypic outcomes upon drug exposure.

Non-genetic transcriptional variability is a potential mechanism for therapy resistance in melanoma. Specifically, rare subpopulations of cells occupy a transient pre-resistant state characterized by coordinated high expression of several genes and survive therapy. How might these rare states arise and disappear within the population? It is unclear whether the canonical models of probabilistic transcriptional pulsing can explain this behavior, or if it requires special, hitherto unidentified mechanisms. We show that a minimal model of transcriptional bursting and gene interactions can give rise to rare coordinated high expression states. These states occur more frequently in networks with low connectivity and depend on three parameters. While entry into these states is initiated by a long transcriptional burst that also triggers entry of other genes, the exit occurs through independent inactivation of individual genes. Together, we demonstrate that established principles of gene regulation are sufficient to describe this behavior and argue for its more general existence.

Two different cell signals often affect transcription of the same gene. In such cases, it is natural to ask how the combined transcriptional response compares to the individual responses. The most commonly used mechanistic models predict additive or multiplicative combined responses, but a systematic genome-wide evaluation of these predictions is not available. Here, we analyzed the transcriptional response of human MCF-7 cells to retinoic acid and TGF-beta, applied individually and in combination. The combined transcriptional responses of induced genes exhibited a range of behaviors, but clearly favored both additive and multiplicative outcomes. We performed paired chromatin accessibility measurements and found that increases in accessibility were largely additive. There was some association between super-additivity of accessibility and multiplicative or super-multiplicative combined transcriptional responses, while sub-additivity of accessibility associated with additive transcriptional responses. Our findings suggest that mechanistic models of combined transcriptional regulation must be able to reproduce a range of behaviors.

Genetics significantly influences autoimmune disease susceptibility. We investigated whether genome organization provides protection or vulnerability to sequence variations in type 1 diabetes (T1D). We created high-resolution maps of linear and 3D genome organization in thymocytes from NOD mice (a T1D model) and diabetes-resistant C57BL/6 mice. Key findings showed that while both strains formed multi-enhancer interactions at regions containing genes crucial for T cell development, diabetes risk-conferring loci coalesced enhancers and promoters in NOD, but not C57BL/6 thymocytes. 3D genome mapping of hybrid F1 thymocytes revealed this structural misfolding occurs in cis in NOD mice. Additionally, immune cells infiltrating pancreases in humans with T1D displayed increased expression of genes located at misfolded loci identified in mice. These results demonstrate that genetic variation produces altered three-dimensional chromatin architecture and associated gene expression changes potentially underlying autoimmune pathology.

Non-genetic factors can cause individual cells to fluctuate substantially in gene expression levels over time. It remains unclear whether these fluctuations can persist for much longer than the time of one cell division. Current methods for measuring gene expression in single cells mostly rely on single time point measurements, making the duration of gene expression fluctuations or cellular memory difficult to measure. Here, we combined Luria and Delbruck's fluctuation analysis with population-based RNA sequencing (MemorySeq) for identifying genes transcriptome-wide whose fluctuations persist for several divisions. MemorySeq revealed multiple gene modules that expressed together in rare cells within otherwise homogeneous clonal populations. These rare cell subpopulations were associated with biologically distinct behaviors like proliferation in the face of anti-cancer therapeutics. The identification of non-genetic, multigenerational fluctuations can reveal new forms of biological memory in single cells and suggests that non-genetic heritability of cellular state may be a quantitative property.

Extensive cell-to-cell variation exists even among putatively identical cells, and there is great interest in understanding how the properties of transcription relate to this heterogeneity. Differential expression from the two gene copies in diploid cells could potentially contribute, yet our ability to measure from which gene copy individual RNAs originated remains limited, particularly in the context of tissues. Here, we demonstrate quantitative, single molecule allele-specific RNA FISH adapted for use on tissue sections, allowing us to determine the chromosome of origin of individual RNA molecules in formaldehyde-fixed tissues. We used this method to visualize the allele-specific expression of Xist and multiple autosomal genes in mouse kidney. By combining these data with mathematical modeling, we evaluated models for allele-specific heterogeneity, in particular demonstrating that apparent expression from only one of the alleles in single cells can arise as a consequence of low-level mRNA abundance and transcriptional bursting.

In the postgenomic era, the human genome encodes thousands of long noncoding RNAs (lncRNAs). RNA imaging (e.g., RNA fluorescence in situ hybridization [RNA-FISH]) has been instrumental in identifying powerful roles for lncRNAs based on their subcellular localization patterns. This review explores how these imaging technologies illuminate when, where, and how lncRNAs function by synthesizing underlying principles through landmark studies that have revealed key insights into lncRNA biology.

Mammalian genomes are folded into tens of thousands of long-range looping interactions. The cause-and-effect relationship between looping and genome function is poorly understood, and the extent to which loops are dynamic on short time scales remains an unanswered question. Here, we engineer a new class of synthetic architectural proteins for directed rearrangement of the three-dimensional genome using blue light. We target our light-activated-dynamic-looping (LADL) system to two genomic anchors with CRISPR guide RNAs and induce their spatial colocalization via light-induced heterodimerization of cryptochrome 2 and a dCas9-CIBN fusion protein. We apply LADL to redirect a stretch enhancer (SE) away from its endogenous Klf4 target gene and to the Zfp462 promoter. Using single-molecule RNA-FISH, we demonstrate that de novo formation of the Zfp462-SE loop correlates with a modest increase in Zfp462 expression. LADL facilitates colocalization of genomic loci without exogenous chemical cofactors and will enable future efforts to engineer reversible and oscillatory loops on short time scales.

Transcriptional regulation occurs via changes to rates of different biochemical steps of transcription, but it remains unclear which rates are subject to change upon biological perturbation. We combined Pol II ChIP-seq with single-molecule RNA FISH to measure transcriptional burst parameters and Pol II occupancy at the same loci across the genome. We found that burst initiation precedes polymerase recruitment. Testing various regulatory perturbations, we found that biological stimuli modified both burst initiation and polymerase pause release rates, but did not alter polymerase recruitment rates. Our findings indicate that transcriptional regulation primarily functions through modulation of burst initiation frequency and pause release dynamics.

Methods for detecting single nucleic acids in cell and tissues, such as fluorescence in situ hybridization (FISH), are limited by relatively low signal intensity and nonspecific probe binding. Here we present click-amplifying FISH (clampFISH), a method for fluorescence detection of nucleic acids that achieves high specificity and high-gain (>400-fold) signal amplification. ClampFISH probes form a 'C' configuration upon hybridization to the sequence of interest in a double helical manner. The ends of the probes are ligated together using bio-orthogonal click chemistry, effectively locking the probes around the target. Iterative rounds of hybridization and click amplify the fluorescence intensity. We show that clampFISH enables the detection of RNA species with low-magnification microscopy and in RNA-based flow cytometry. Additionally, we show that the modular design of clampFISH probes allows multiplexing of RNA and DNA detection, that the locking mechanism prevents probe detachment in expansion microscopy, and that clampFISH can be applied in tissue samples.

Single-cell RNA sequencing (scRNA-seq) enables quantification of each gene's expression distribution across cells, thus allowing the assessment of the dispersion, nonzero fraction, and other aspects of its distribution beyond the mean. These statistical characterizations of the gene expression distribution are critical for understanding expression variation and for selecting marker genes for population heterogeneity. However, scRNA-seq data are noisy, with each cell typically sequenced at low coverage, thus making it difficult to infer properties of the gene expression distribution from raw counts. Based on a reexamination of nine public datasets, we propose a simple technical noise model for scRNA-seq data with unique molecular identifiers (UMI). We develop DESCEND (deconvolution of single-cell expression distribution), a method that deconvolves the true cross-cell gene expression distribution from observed scRNA-seq counts, yielding improved estimates of distribution properties such as dispersion and nonzero fraction. DESCEND adjusts for cell-level covariates including cell size, cell cycle, and batch effects, and provides reliable estimates for downstream analyses such as identifying differentially expressed genes, determining cell types, and selecting differentiation markers.

The tumor microenvironment plays a significant role in the pathogenesis of multiple cancer types, particularly upper gastrointestinal cancers. Cancer-associated fibroblasts (CAF) are an essential component of the tumor microenvironment, contributing to tumorigenesis by secreting growth factors, modifying the extracellular matrix, supporting angiogenesis, and suppressing antitumor immune responses. Through an unbiased approach, we established that IL-6 mediates cross-talk between tumor cells and CAF not only by supporting tumor cell growth, but also by promoting fibroblast activation. IL-6 loss suppressed tumorigenesis in physiologically relevant three-dimensional organotypic and tumoroid models and murine models of esophageal cancer. Tocilizumab, an anti-IL6R-alpha antibody, reduced tumor growth through STAT3 and MEK/ERK signaling inhibition. These findings suggest that IL-6 is a major contributor to the dynamic cross-talk between tumor cells and CAF, providing rationale for IL6R-alpha inhibition as novel targeted therapy in upper gastrointestinal cancers.

We describe Quanti.us, a crowd-based image-annotation platform that provides an accurate alternative to computational algorithms for difficult image-analysis problems. We used Quanti.us for a variety of medium-throughput image-analysis tasks and achieved 10-50x savings in analysis time compared with that required for the same task by a single expert annotator. We show equivalent deep learning performance for Quanti.us-derived and expert-derived annotations, which should allow scalable integration with tailored machine learning algorithms.

Although single-cell RNA sequencing can reliably detect large-scale transcriptional programs, it is unclear whether it accurately captures the behavior of individual genes, especially those that express only in rare cells. We used single-molecule RNA fluorescence in situ hybridization as a reference standard to evaluate trade-offs in single-cell RNA-sequencing data for detecting rare cell expression variability. We analyzed 26 genes ranging from ubiquitous to rarely expressed and found that correspondence between platforms improved with greater transcriptome coverage and more cells analyzed. When analyzing a limited number of genes for specific biological questions, transcriptome coverage becomes more critical than cell sample size. These findings provide practical guidance for establishing quality thresholds in single-cell RNA-sequencing experiments focused on rare cell analysis.

Physical changes in skin are among the most visible signs of aging. We found that young dermal fibroblasts secrete high levels of extracellular matrix (ECM) constituents, including proteoglycans, glycoproteins, and cartilage-linking proteins. The most abundantly secreted was HAPLN1, a hyaluronic and proteoglycan link protein. HAPLN1 was lost in aged fibroblasts, resulting in a more aligned ECM that promoted metastasis of melanoma cells. Reconstituting HAPLN1 inhibited metastasis in an aged microenvironment, in 3-D skin reconstruction models, and in vivo. Intriguingly, aged fibroblast-derived matrices had the opposite effect on the migration of T cells, inhibiting their motility. HAPLN1 treatment of aged fibroblasts restored motility of mononuclear immune cells, while impeding that of polymorphonuclear immune cells, which in turn affected regulatory T-cell recruitment. These data suggest that although age-related physical changes in the ECM can promote tumor cell motility, they may adversely affect the motility of some immune cells, resulting in an overall change in the immune microenvironment. Understanding the physical changes in aging skin may provide avenues for more effective therapy for older patients with melanoma.

In single-cell RNA sequencing (scRNA-seq) studies, only a small fraction of the transcripts present in each cell are sequenced. This leads to unreliable quantification of genes with low or moderate expression levels, which hinders downstream analysis. We introduce SAVER (single-cell analysis via expression recovery), an expression recovery method for unique molecular identifier (UMI)-based scRNA-seq data that borrows information across genes and cells to provide accurate expression estimates for all genes.

Early responses mounted by both tissue-resident and recruited innate immune cells are essential for host defense against bacterial pathogens. In particular, both neutrophils and Ly6Chi monocytes are rapidly recruited to sites of infection. While neutrophils and monocytes produce bactericidal molecules, such as reactive nitrogen and oxygen species, both cell types are also capable of synthesizing overlapping sets of cytokines important for host defense. Whether neutrophils and monocytes perform redundant or non-redundant functions in the generation of anti-microbial cytokine responses remains elusive. Here, we sought to define the contributions of neutrophils and Ly6Chi monocytes to cytokine production and host defense during pulmonary infection with Legionella pneumophila, responsible for the severe pneumonia Legionnaires' disease. We found that both neutrophils and monocytes are critical for host defense against L. pneumophila. Both monocytes and neutrophils contribute to maximal IL-12 and IFN-gamma responses, and monocytes are also required for TNF production. Moreover, natural killer (NK) cells, NKT cells, and gamma-delta T cells are sources of IFN-gamma, and monocytes direct IFN-gamma production by these cell types. Thus, neutrophils and monocytes cooperate in eliciting an optimal cytokine response that promotes effective control of bacterial infection.

Therapies that target signalling molecules that are mutated in cancers can often have substantial short-term effects, but the emergence of resistant cancer cells is a major barrier to full cures. Resistance can result from secondary mutations, but in other cases there is no clear genetic cause, raising the possibility of non-genetic rare cell variability. Here we show that human melanoma cells can display profound transcriptional variability at the single-cell level that predicts which cells will ultimately resist drug treatment. This variability involves infrequent, semi-coordinated transcription of a number of resistance markers at high levels in a very small percentage of cells. The addition of drug then induces epigenetic reprogramming in these cells, converting the transient transcriptional state to a stably resistant state. This reprogramming begins with a loss of SOX10-mediated differentiation followed by activation of new signalling pathways, partially mediated by the activity of the transcription factors JUN and/or AP-1 and TEAD. Our work reveals the multistage nature of the acquisition of drug resistance and provides a framework for understanding resistance dynamics in single cells. We find that other cell types also exhibit sporadic expression of many of these same marker genes, suggesting the existence of a general program in which expression is displayed in rare subpopulations of cells.

A system that introduces random modifications to barcode sequences embedded in cells' DNA allows lineage relationships between cells to be discerned, while preserving the cells' spatial relationships.

Bromodomain and extraterminal motif (BET) proteins are pharmacologic targets for the treatment of diverse diseases, yet the roles of individual BET family members remain unclear. We find that BRD2, but not BRD4, co-localizes with the architectural/insulator protein CCCTC-binding factor (CTCF) genome-wide. CTCF recruits BRD2 to co-bound sites whereas BRD2 is dispensable for CTCF occupancy. Disruption of a CTCF/BRD2-occupied element positioned between two unrelated genes enables regulatory influence to spread from one gene to another, suggesting that CTCF and BRD2 form a transcriptional boundary. Accordingly, single-molecule mRNA fluorescence in situ hybridization (FISH) reveals that, upon site-specific CTCF disruption or BRD2 depletion, expression of the two genes becomes increasingly correlated. HiC shows that BRD2 depletion weakens boundaries co-occupied by CTCF and BRD2, but not those that lack BRD2. These findings indicate that BRD2 supports boundary activity, and they raise the possibility that pharmacologic BET inhibitors can influence gene expression in part by perturbing domain boundary function.

Conversion of adenosine to inosine is a frequent type of RNA editing, but important details about the biology of this conversion remain unknown because of a lack of imaging tools. We developed inoFISH to directly visualize and quantify adenosine-to-inosine-edited transcripts in situ. We found that editing of the GRIA2, EIF2AK2, and NUP43 transcripts is uncorrelated with nuclear localization and paraspeckle association. Further, NUP43 exhibits constant editing levels between single cells, while GRIA2 editing levels vary.

During mitosis, RNA polymerase II and transcription factors leave chromatin, halting transcription globally. We tracked RNA polymerase II across the genome as cells progressed from mitosis through late G1 phase. Remarkably, approximately 50% of active genes and distal enhancers displayed a transcriptional spike during early reactivation, surpassing levels seen later in G1. While enhancer-promoter contacts were depleted during mitosis and restored upon G1 entry, they did not spike. Histone H3 acetylation at individual loci best predicted transcriptional activity during the mitosis-G1 transition. Single-molecule imaging demonstrated that this transcriptional spike may represent maximum activity per DNA copy throughout the cell cycle. The spike occurred unevenly across cells and led to heterogeneity in mature mRNA expression, suggesting passage through mitosis-G1 may cause cells to diverge in gene expression states.

Mammalian genes transcribe RNA not continuously, but in bursts. Transcriptional output can be modulated by altering burst fraction or burst size, but how regulatory elements control bursting parameters remains unclear. Single-molecule RNA FISH experiments revealed that the beta-globin enhancer (LCR) predominantly augments transcriptional burst fraction of the beta-globin gene with modest stimulation of burst size. To specifically measure the impact of long-range chromatin contacts on transcriptional bursting, we forced an LCR-beta-globin promoter chromatin loop. We observed that raising contact frequencies increases burst fraction but not burst size. In cells in which two developmentally distinct LCR-regulated globin genes are cotranscribed in cis, burst sizes of both genes are comparable. However, allelic co-transcription of both genes is statistically disfavored, suggesting mutually exclusive LCR-gene contacts. These results are consistent with competition between the beta-type globin genes for LCR contacts and suggest that LCR-promoter loops are formed and released with rapid kinetics.

The ability to image RNA identity and location with nanoscale precision in intact tissues is of great interest for defining cell types and states in normal and pathological biological settings. Here, we present a strategy for expansion microscopy of RNA. We developed a small-molecule linker that enables RNA to be covalently attached to a swellable polyelectrolyte gel synthesized throughout a biological specimen. Then, postexpansion, fluorescent in situ hybridization (FISH) imaging of RNA can be performed with high yield and specificity as well as single-molecule precision in both cultured cells and intact brain tissue. Expansion FISH (ExFISH) separates RNAs and supports amplification of single-molecule signals (i.e., via hybridization chain reaction) as well as multiplexed RNA FISH readout. ExFISH thus enables super-resolution imaging of RNA structure and location with diffraction-limited microscopes in thick specimens, such as intact brain tissue and other tissues of importance to biology and medicine.

Understanding gene expression across the diverse metazoan cell types during development is critical to understanding their function and regulation. However, most cell types have not been assayed for expression genome-wide. We employed a technique called POP-Seq using RNA-seq to examine transcriptomes across embryonic cell populations in C. elegans. This method identified numerous transcripts with differential expression and revealed over 100 sets of coexpressed genes showing distinct cell-type-specific patterns. We also identified candidate regulatory genes through transcription factor motif enrichment analysis. Our analysis provides new insight into embryonic gene regulation, and provides a resource for improving our knowledge of tissue-specific expression and its regulation throughout C. elegans development.

Mesenchymal stem cells (MSCs) display substantial cell-to-cell heterogeneity, complicating their use in regenerative medicine. Using single-molecule RNA FISH to measure mRNA expression of differentiation markers in single cells, we found that both chondrocytes and chondrogenically induced MSCs exhibit substantial mRNA expression heterogeneity. Sister cell pairs have high levels of mRNA variability, suggesting that marker expression is not heritable. Surprisingly, this variability does not correlate with cell-to-cell differences in cartilage-like matrix production. Genome-wide transcriptome analysis indicated that no combination of markers could reliably predict functional capacity. De-differentiating chondrocytes similarly demonstrated a disconnect between aggrecan expression and matrix accumulation. These results suggest that instantaneous mRNA levels of canonical markers have only a tenuous relationship to chondrogenic phenotype at the single-cell level, and that sorting cells based on these markers would provide minimal enrichment for superior matrix-producing cells.

Neutrophils, eosinophils and 'classical' monocytes collectively account for about 70% of human blood leukocytes and are among the shortest-lived cells in the body. Precise regulation of the lifespan of these myeloid cells is critical to maintain protective immune responses and minimize the deleterious consequences of prolonged inflammation. However, how the lifespan of these cells is strictly controlled remains largely unknown. Here we identify a long non-coding RNA that we termed Morrbid, which tightly controls the survival of neutrophils, eosinophils and classical monocytes in response to pro-survival cytokines in mice. To control the lifespan of these cells, Morrbid regulates the transcription of the neighbouring pro-apoptotic gene, Bcl2l11 (also known as Bim), by promoting the enrichment of the PRC2 complex at the Bcl2l11 promoter to maintain this gene in a poised state. Notably, Morrbid regulates this process in cis, enabling allele-specific control of Bcl2l11 transcription. Thus, in these highly inflammatory cells, changes in Morrbid levels provide a locus-specific regulatory mechanism that allows rapid control of apoptosis in response to extracellular pro-survival signals. As MORRBID is present in humans and dysregulated in individuals with hypereosinophilic syndrome, this long non-coding RNA may represent a potential therapeutic target for inflammatory disorders characterized by aberrant short-lived myeloid cell lifespan.

Recent analysis demonstrates that the HIV-1 Long Terminal Repeat (HIV LTR) promoter exhibits a range of possible transcriptional burst sizes and frequencies for any mean-expression level. However, these results have also been interpreted as demonstrating that cell-to-cell expression variability (noise) and mean are uncorrelated, a significant deviation from previous results. Here, we re-examine the available mRNA and protein abundance data for the HIV LTR and find that noise in mRNA and protein expression scales inversely with the mean along analytically predicted transcriptional burst-size manifolds. We then experimentally perturb transcriptional activity to test a prediction of the multiple burst-size model: that increasing burst frequency will cause mRNA noise to decrease along given burst-size lines as mRNA levels increase. The data show that mRNA and protein noise decrease as mean expression increases, supporting the canonical inverse correlation between noise and mean.

Imprinting is a classic mammalian epigenetic phenomenon that results in expression from a single parental allele. Imprinting defects can lead to inappropriate expression from the normally silenced allele, but it remains unclear whether every cell in a mutant organism follows the population average, which would have profound implications for human imprinting disorders. Here, we apply a new fluorescence in situ hybridization method that measures allele-specific expression in single cells to address this question in mutants exhibiting aberrant H19/Igf2 imprinting. We show that mutant primary embryonic mouse fibroblasts are comprised of two subpopulations: one expressing both H19 alleles and another expressing only the maternal copy. Only in the latter cell population is Igf2 expression detected. Furthermore, the two subpopulations are stable in that cells do not interconvert between the two expression patterns. Combined small input methylation analysis and transcriptional imaging revealed that these two mutant subpopulations exhibit distinct methylation patterns at their imprinting control regions. Consistently, pharmacological inhibition of DNA methylation reduced the proportion of monoallelic cells. Importantly, we observed that the same two subpopulations are also present in vivo within murine cardiac tissue. Our results establish that imprinting disorders can display striking single-cell heterogeneity in their molecular phenotypes and suggest that such heterogeneity may underlie epigenetic mosaicism in human imprinting disorders.

The field of single-cell biology has morphed from a philosophical digression at its inception, to a playground for quantitative biologists, to a major area of biomedical research. The last several years have witnessed an explosion of new technologies, allowing us to apply even more of the modern molecular biology toolkit to single cells. Conceptual progress, however, has been comparatively slow. Here, we provide a framework for classifying both the origins of the differences between individual cells and the consequences of those differences. We discuss how the concept of "random" differences is context dependent, and propose that rigorous definitions of inputs and outputs may bring clarity to the discussion. We also categorize ways in which probabilistic behavior may influence cellular function, highlighting studies that point to exciting future directions in the field.

Enhancers govern transcription through multiple mechanisms, including the regulation of elongation by RNA polymerase II (RNAPII). We characterized the dynamics of looped enhancer contacts during synchronous transcription elongation. We found that two model enhancers form stable contacts with their target promoters during the entire interval of elongation. Notably, we detected additional dynamic enhancer contacts throughout the gene bodies that track with elongating RNAPII and the leading edge of RNA synthesis. These results support a model in which the gene body changes its position relative to a stable enhancer-promoter complex, which has broad ramifications for enhancer function and architectural models of transcriptional elongation.

Small-scale molecular systems biology assumes that cellular regulation is arranged in a circuit-like structure, but findings from the omics revolution reveal high interconnectivity that challenges this vision. We outline limitations of small-scale approaches using examples from genetic algorithms, genetics, transcriptional network analysis, and genomics. We discuss difficulties in deriving understanding from large datasets and propose that intelligent computational tools may offer a path forward, suggesting that developing a true understanding via molecular systems biology will require a fundamental rethinking of our approach.

Populations of cultured mouse embryonic stem cells (ESCs) exhibit a subfraction of cells expressing uncharacteristically low levels of pluripotency markers such as Nanog. We investigated whether Nanog-negative cells represent truly differentiated populations or merely primed states. Through transcriptomic analysis, we found these cells express differentiation-associated genes more prominently than cells exposed to one-day differentiation conditions. Interestingly, long non-coding RNAs showed greater expression changes in induced differentiation than in Nanog-negative populations. Single-cell analysis revealed substantial heterogeneity, with progressively nested cell subsets displaying low Nanog, then low Oct4, followed by intensive lineage marker expression. The findings suggest the observed enrichment of lineage-specific marker gene expression in Nanog-negative cells is associated with spontaneous differentiation rather than reversible lineage priming, indicating these populations contain both differentiated and lineage-primed cell subsets.

Stimulation of the antiviral response depends on the sensing of viral pathogen-associated molecular patterns (PAMPs) by specialized cellular proteins. We identify a critical RNA motif (DVG(70-114)) in Sendai virus immunostimulatory defective viral genomes that enhances immune recognition. This motif strengthens RIG-I binding to viral RNA and promotes polymerization, activating the antiviral response independently of complementary RNA sequences. When transferred to otherwise inactive viral RNA, the motif retains its immunostimulatory capacity. The findings characterize a natural viral PAMP enhancer that could inform vaccine adjuvant and antiviral therapeutic development.

Long non-coding RNAs (lncRNAs) have been implicated in diverse biological processes. In contrast to extensive genomic annotation of lncRNA transcripts, far fewer have been characterized for subcellular localization and cell-to-cell variability. Addressing this requires systematic, direct visualization of lncRNAs in single cells at single-molecule resolution. We use single-molecule RNA-FISH to systematically quantify and categorize the subcellular localization patterns of a representative set of 61 lncRNAs in three different cell types. Our survey yields high-resolution quantification and stringent validation of the number and spatial positions of these lncRNA, with an mRNA set for comparison. Using this highly quantitative image-based dataset, we observe a variety of subcellular localization patterns, ranging from bright sub-nuclear foci to almost exclusively cytoplasmic localization. We also find that the low abundance of lncRNAs observed from cell population measurements cannot be explained by high expression in a small subset of 'jackpot' cells. Additionally, nuclear lncRNA foci dissolve during mitosis and become widely dispersed, suggesting these lncRNAs are not mitotic bookmarking factors. Moreover, we see that divergently transcribed lncRNAs do not always correlate with their cognate mRNA, nor do they have a characteristic localization pattern. Our systematic, high-resolution survey of lncRNA localization reveals aspects of lncRNAs that are similar to mRNAs, such as cell-to-cell variability, but also several distinct properties. These characteristics may correspond to particular functional roles. Our study also provides a quantitative description of lncRNAs at the single-cell level and a universally applicable framework for future study and validation of lncRNAs.

Viral infections are a major cause of human disease, but many require molecular assays for conclusive diagnosis. Current assays typically rely on RT-PCR or ELISA; however, these tests often have limited speed, sensitivity or specificity. Here, we demonstrate that rapid RNA FISH is a viable alternative method that could improve upon these limitations. We describe a platform beginning with software to generate RNA FISH probes both for distinguishing related strains of virus (even those different by a single base) and for capturing large numbers of strains simultaneously. Next, we present a simple fluidic device for reliably performing RNA FISH assays in an automated fashion. Finally, we describe an automated image processing pipeline to robustly identify uninfected and infected samples. Together, our results establish RNA FISH as a methodology with potential for viral point-of-care diagnostics.

Hematopoietic lineage commitment is regulated by cytokines and master transcription factors, but it remains unclear how a progenitor cell chooses a lineage in the face of conflicting cues. We examined megakaryocyte-erythroid progenitors undergoing red blood cell development and discovered that pro-erythropoiesis factors (EKLF and EpoR) showed inverse expression patterns compared to pro-megakaryopoiesis factors (FLI-1 and TpoR). During erythrocyte commitment, EpoR increased while TpoR was substantially reduced, effectively amplifying red blood cell signals while suppressing competing signals. We proposed a model for lineage decision-making that incorporates external cues and validated predictions about gene expression variability in committing cells. Our findings suggest that lineage-specific receptor levels can modulate potencies of cues to achieve robust commitment decisions.

Individual mammalian cells show large variability in cellular volume despite having identical DNA content, requiring compensation to maintain constant gene expression product concentrations. Using single-molecule counting and computational analysis, we demonstrated that transcript abundance correlates with cellular volume due to increased global transcription in larger cells. Cell fusion experiments confirmed that increased cellular material can directly boost transcription. The study identified a mechanism measuring the ratio of cellular volume to DNA content, likely through transcriptional factor sequestration to DNA. Additionally, analysis of transcriptional bursts revealed a separate mechanism for gene dosage compensation following DNA replication, enabling proper transcriptional output during S phase. These findings provide quantitative understanding of relationships among DNA content, cell size, and gene expression variability in individual cells.

While many transcriptional regulators of pluripotent and terminally differentiated states have been identified, regulation of intermediate progenitor states is less well understood. Previous high throughput cellular resolution expression studies identified dozens of transcription factors with lineage-specific expression patterns in C. elegans embryos that could regulate progenitor identity. In this study we identified a broad embryonic role for the C. elegans OTX transcription factor ceh-36, which was previously shown to be required for the terminal specification of four neurons. ceh-36 is expressed in progenitors of over 30% of embryonic cells, yet is not required for embryonic viability. Quantitative phenotyping by computational analysis of time-lapse movies of ceh-36 mutant embryos identified cell cycle or cell migration defects in over 100 of these cells, but most defects were low-penetrance, suggesting redundancy. Expression of ceh-36 partially overlaps with that of the PITX transcription factor unc-30. unc-30 single mutants are viable but loss of both ceh-36 and unc-30 causes 100% lethality, and double mutants have significantly higher frequencies of cellular developmental defects in the cells where their expression normally overlaps. These factors are also required for robust expression of the downstream developmental regulator mls-2/HMX. This work provides the first example of genetic redundancy between the related yet evolutionarily distant OTX and PITX families of bicoid class homeodomain factors and demonstrates the power of quantitative developmental phenotyping in C. elegans to identify developmental regulators acting in progenitor cells.

Single-molecule RNA fluorescence in situ hybridization is a technique that holds great potential for the study of long noncoding RNA. Here we present a protocol for the application of single-molecule fluorescence in situ hybridization.

Aberrant de novo methylation of DNA is considered an important mediator of tumorigenesis. We investigated Dnmt3a's function in intestinal tumor development using murine and human samples. Key findings showed elevated Dnmt3a expression in colon adenomas and colorectal cancer, particularly in Lgr5-positive stem/progenitor cells. When Dnmt3a was conditionally deleted in APC(Min/+) mice, tumor numbers decreased by approximately 40%. Remaining tumors contained non-inactivated Dnmt3a alleles exclusively. DNA methylation decreased at specific promoter regions (Oct4, Nanog, Tff2, Cdkn1c), while tumor-suppressor genes Tff2 and Cdkn1c showed increased expression. The study concludes that Dnmt3a expression predominates in the stem/progenitor cell compartment of tumors and that removing Dnmt3a inhibits early-stage intestinal tumor development.

The p53-regulated long noncoding RNA lincRNA-p21 has been proposed to act in trans via several mechanisms ranging from repressing genes in the p53 transcriptional network to regulating mRNA translation and protein stability. We created a conditional knockout mouse model and discovered that lincRNA-p21 predominantly functions nearby its genomic location to activate expression of the neighboring p21 gene. The mechanism involves lincRNA-p21 working with hnRNP-K as a coactivator for p53-dependent p21 transcription. Loss of lincRNA-p21 resulted in diminished p21 levels, leading to several consequences: deregulated expression and altered chromatin state of certain Polycomb target genes, a defective G1/S checkpoint, increased proliferation rates, and enhanced reprogramming efficiency. The findings indicate that lincRNA-p21 affects global gene expression and influences the p53 tumor suppressor pathway by acting in cis as a locus-restricted coactivator for p53-mediated p21 expression.

Mammals express thousands of long noncoding (lnc) RNAs, yet the entire repertoire of lncRNAs in most tissues and species is not defined. We used RNA sequencing to identify 1,109 polyadenylated lncRNAs in mouse erythroid and megakaryocytic cells, plus 594 in human erythroblasts. Over half were previously unannotated. The analysis revealed approximately 75% originate from promoters and 25% from enhancers, regulated by transcription factors including GATA1 and TAL1. While erythroid lncRNA expression remained largely conserved among 8 different mouse strains, only 15% of mouse lncRNAs were expressed in humans, reflecting dramatic species-specificity. RNA interference studies of 21 abundant erythroid-specific murine lncRNAs identified 7 whose knockdown inhibited terminal erythroid maturation. Notably, at least 6 of these 7 functional lncRNAs have no detectable expression in human erythroblasts, suggesting that lack of cross-species conservation does not necessarily predict functional irrelevance.

In response to infection, the innate immune system rapidly activates an elaborate and tightly orchestrated gene expression program to induce critical antimicrobial genes. While many key players in this program have been identified in disparate biological systems, it is clear that there are additional uncharacterized mechanisms at play. Our previous studies revealed that a rapidly-induced antiviral gene expression program is active against disparate human arthropod-borne viruses in Drosophila, with one-half of this program regulated at the level of transcriptional pausing. We found that Nup98, a virus-induced gene, was antiviral against a panel of viruses both in cells and adult flies since its depletion significantly enhanced viral infection. Mechanistically, we found that Nup98 promotes antiviral gene expression in Drosophila at the level of transcription. Expression profiling revealed that the virus-induced activation of 36 genes was abrogated upon loss of Nup98; a subset of these Nup98-dependent genes were antiviral. These Nup98-dependent virus-induced genes are Cdk9-dependent and translation-independent suggesting that these are rapidly induced primary response genes. Biochemically, we demonstrate that Nup98 is directly bound to the promoters of virus-induced genes, and that it promotes occupancy of the initiating form of RNA polymerase II at these promoters, which are rapidly induced on viral infection to restrict human arboviruses in insects.

Heterogeneous expression of the transcription factor NANOG has been linked to the existence of various functional states in pluripotent stem cells. This heterogeneity seems to arise from fluctuations of Nanog expression in individual cells, but a thorough characterization of these fluctuations and their impact on the pluripotent state is still lacking. Here, we have used a novel fluorescent reporter to investigate the temporal dynamics of NANOG expression in mouse embryonic stem cells (mESCs), and to dissect the lineage potential of mESCs at different NANOG states. Our results show that stochastic NANOG fluctuations are widespread in mESCs, with essentially all expressing cells showing fluctuations in NANOG levels, even when cultured in ground-state conditions (2i media). We further show that fluctuations have similar kinetics when mESCs are cultured in standard conditions (serum plus leukemia inhibitory factor) or ground-state conditions, implying that NANOG fluctuations are inherent to the pluripotent state. We have then compared the developmental potential of low-NANOG and high-NANOG mESCs, grown in different conditions, and confirm that mESCs are more susceptible to enter differentiation at the low-NANOG state. Further analysis by gene expression profiling reveals that low-NANOG cells have marked expression of lineage-affiliated genes, with variable profiles according to the signalling environment. By contrast, high-NANOG cells show a more stable expression profile in different environments, with minimal expression of lineage markers. Altogether, our data support a model in which stochastic NANOG fluctuations provide opportunities for mESCs to explore multiple lineage options, modulating their probability to change functional state.

RNA, including long noncoding RNA (lncRNA), is known to be an abundant and important structural component of the nuclear matrix. However, the molecular identities, functional roles and localization dynamics of lncRNAs that influence nuclear architecture remain poorly understood. Here, we describe one lncRNA, Firre, that interacts with the nuclear-matrix factor hnRNPU through a 156-bp repeating sequence and localizes across an approximately 5-Mb domain on the X chromosome. We further observed Firre localization across five distinct trans-chromosomal loci, which reside in spatial proximity to the Firre genomic locus on the X chromosome. Both genetic deletion of the Firre locus and knockdown of hnRNPU resulted in loss of colocalization of these trans-chromosomal interacting loci. Thus, our data suggest a model in which lncRNAs such as Firre can interface with and modulate nuclear architecture across chromosomes.

Tumor endothelial marker 1 (TEM1; also known as endosialin or CD248) is a protein found on tumor vasculature and in tumor stroma. Here, we tested whether TEM1 has potential as a therapeutic target for cancer immunotherapy by immunizing immunocompetent mice with Tem1 cDNA fused to the minimal domain of the C fragment of tetanus toxoid (referred to herein as Tem1-TT vaccine). Tem1-TT vaccination elicited CD8+ and/or CD4+ T cell responses against immunodominant TEM1 protein sequences. Prophylactic immunization of animals with Tem1-TT prevented or delayed tumor formation in several murine tumor models. Therapeutic vaccination of tumor-bearing mice reduced tumor vascularity, increased infiltration of CD3+ T cells into the tumor, and controlled progression of established tumors. Tem1-TT vaccination also elicited CD8+ cytotoxic T cell responses against murine tumor-specific antigens. Effective Tem1-TT vaccination did not affect angiogenesis-dependent physiological processes, including wound healing and reproduction. Based on these data and the widespread expression of TEM1 on the vasculature of different tumor types, we conclude that targeting TEM1 has therapeutic potential in cancer immunotherapy.

Several of the thousands of human long non-coding RNAs (lncRNAs) have been functionally characterized; however, potential roles for lncRNAs in somatic tissue differentiation remain poorly understood. Here we show that a 3.7-kilobase lncRNA, terminal differentiation-induced ncRNA (TINCR), controls human epidermal differentiation by a post-transcriptional mechanism. TINCR is required for high messenger RNA abundance of key differentiation genes, many of which are mutated in human skin diseases, including FLG, LOR, ALOXE3, ALOX12B, ABCA12, CASP14 and ELOVL3. TINCR-deficient epidermis lacked terminal differentiation ultrastructure, including keratohyalin granules and intact lamellar bodies. Genome-scale RNA interactome analysis revealed that TINCR interacts with a range of differentiation mRNAs. TINCR-mRNA interaction occurs through a 25-nucleotide 'TINCR box' motif that is strongly enriched in interacting mRNAs and required for TINCR binding. A high-throughput screen to analyse TINCR binding capacity to approximately 9,400 human recombinant proteins revealed direct binding of TINCR RNA to the staufen1 (STAU1) protein. STAU1-deficient tissue recapitulated the impaired differentiation seen with TINCR depletion. Loss of UPF1 and UPF2, both of which are required for STAU1-mediated RNA decay, however, did not have differentiation effects. Instead, the TINCR-STAU1 complex seems to mediate stabilization of differentiation mRNAs, such as KRT80. These data identify TINCR as a key lncRNA required for somatic tissue differentiation, which occurs through lncRNA binding to differentiation mRNAs to ensure their expression.

Cell differentiation and proliferation are coordinated during animal development, but the link between them remains uncharacterized. We combined imaging techniques to study transcriptional timing in C. elegans embryos. Our findings revealed that slowing development through temperature changes or mutations caused both cell division and transcription to slow proportionally, suggesting coordination. However, using specific cell cycle mutants, we discovered that the order between cell divisions and expression onset can switch, demonstrating that gene expression is not strictly dependent on cell division occurring. The work indicates expression and proliferation are independently entrained to a separate clock-like process, with changes in timing affecting which cells express particular genes. These results constrain the possible mechanisms ensuring proper developmental timing during normal embryogenesis.

Recently, researchers have uncovered the presence of many long noncoding RNAs (lncRNAs) in embryonic stem cells and believe they are important regulators of the differentiation process. However, there are only a few examples explicitly linking lncRNA activity to transcriptional regulation. Here, we used transcript counting and spatial localization to characterize a lncRNA (dubbed linc-HOXA1) located approximately 50 kb from the Hoxa gene cluster in mouse embryonic stem cells. Single-cell transcript counting revealed that linc-HOXA1 and Hoxa1 RNA are highly variable at the single-cell level and that whenever linc-HOXA1 RNA abundance was high, Hoxa1 mRNA abundance was low and vice versa. Knockdown analysis revealed that depletion of linc-HOXA1 RNA at its site of transcription increased transcription of the Hoxa1 gene cis to the chromosome and that exposure of cells to retinoic acid can disrupt this interaction. We further showed that linc-HOXA1 RNA represses Hoxa1 by recruiting the protein PURB as a transcriptional cofactor. Our results highlight the power of transcript visualization to characterize lncRNA function and also suggest that PURB can facilitate lncRNA-mediated transcriptional regulation.

Recently, we developed an oligonucleotide-based probe, ratiometric bimolecular beacon (RBMB), which generates a detectable fluorescent signal in living cells that express the target RNA. We demonstrate that RBMBs can image individual RNA transcripts in living cells when the target RNA contains as few as four hybridization sites. We validated our measurements against single-molecule fluorescence in situ hybridization, confirming RBMBs accurately quantify RNA transcript numbers within individual cells. Key findings include rapid measurements (within 30 minutes) across diverse RBMB concentrations and successful application in multiple cell lines (HT-1080 and CHO). These results highlight RBMBs as robust tools for RNA imaging in live cells and suggest new possibilities for RNA research applications.

We report intron chromosomal expression FISH (iceFISH), a multiplex imaging method for measuring gene expression and chromosome structure simultaneously on single chromosomes. We find substantial differences in transcriptional frequency between genes on a translocated chromosome and the same genes in their normal chromosomal context in the same cell. Correlations between genes on a single chromosome pointed toward a cis chromosome-level transcriptional interaction spanning 14.3 megabases.

Advances in RNA fluorescence in situ hybridization (RNA FISH) have allowed practitioners to detect individual RNA molecules in single cells via fluorescence microscopy, enabling highly accurate and sensitive quantification of gene expression. However, current methods typically employ hybridization times on the order of 2-16 hours, limiting its potential in applications like rapid diagnostics. We present here a set of conditions for RNA FISH (dubbed Turbo RNA FISH) that allow us to make accurate measurements with no more than 5 minutes of hybridization time and 3 minutes of washing, and show that hybridization times can go as low as 30 seconds while still producing quantifiable images. We further show that rapid hybridization is compatible with our recently developed iceFISH and SNP FISH variants of RNA FISH that enable chromosome and single base discrimination, respectively. Our method is simple and cost effective, and has the potential to dramatically increase the throughput and realm of applicability of RNA FISH.

With the advent of quantitative tools for measuring gene expression in single cells, researchers have made the discovery that in many contexts, messenger RNA and protein levels can vary widely from cell to cell, often because of inherently stochastic events associated with gene expression. Scientists now study cellular individuality through technological development and theoretical analysis. This review focuses on using expression variability as a mechanism to understand gene regulation, examining how it functions as a natural systems-level perturbation and helps characterize biological processes underlying transcription. Additionally, it discusses its role in discovering novel gene regulatory interactions, arguing that this variability-based approach provides valuable biological insights into transcriptional control mechanisms.

We present a FISH-based method for detecting single-nucleotide variants (SNVs) in exons and introns on individual RNA transcripts with high efficiency. We used this method to quantify allelic expression in cell populations and in single cells, and also to distinguish maternal from paternal chromosomes in single cells.

The secondary structure of RNA is necessary for its maturation, regulation, processing, and function. However, the global influence of RNA folding in eukaryotes is still unclear. Here, we use a high-throughput, sequencing-based, structure-mapping approach to identify the paired (double-stranded RNA) and unpaired (single-stranded RNA) components of the Drosophila melanogaster and Caenorhabditis elegans transcriptomes, which allows us to identify conserved features of RNA secondary structure in metazoans. From this analysis, we find that ssRNAs and dsRNAs are significantly correlated with specific epigenetic modifications. Additionally, we find key structural patterns across protein-coding transcripts that indicate that RNA folding demarcates regions of protein translation and likely affects microRNA-mediated regulation of mRNAs in animals. Finally, we identify and characterize 546 mRNAs whose folding pattern is significantly correlated between these metazoans, suggesting that their structure has some function. Overall, our findings provide a global assessment of RNA folding in animals.

ComK transcriptionally controls competence for the uptake of transforming DNA in Bacillus subtilis. Only 10-20% of the cells in a clonal population are randomly selected for competence. Because ComK activates its own promoter, cells exceeding a threshold amount of ComK trigger a positive feedback loop, transitioning to the competence ON state. The transition rate increases to a maximum during the approach to stationary phase and then decreases, with most cells remaining OFF. The average basal rate of comK transcription increases transiently, defining a window of opportunity for transitions and accounting for the heterogeneity of competent populations. We show that as the concentration of the response regulator Spo0A~P increases during the entry to stationary phase it first induces comK promoter activity and then represses it by direct binding. Spo0A~P activates by antagonizing the repressor, Rok. This amplifies an inherent increase in basal level comK promoter activity that takes place during the approach to stationary phase and is a general feature of core promoters, serving to couple the probability of competence transitions to growth rate. Competence transitions are thus regulated by growth rate and temporally controlled by the complex mechanisms that govern the formation of Spo0A~P. On the level of individual cells, the fate-determining noise for competence is intrinsic to the comK promoter. This overall mechanism has been stochastically simulated and shown to be plausible. Thus, a deterministic mechanism modulates an inherently stochastic process.

Human cancer cells frequently have regions of their DNA hypermethylated, which results in transcriptional silencing of affected genes and promotion of tumor formation. Transgenic expression of DNA methyltransferase 3b (Dnmt3b) in mouse colon initiates de novo DNA methylation of genes remarkably similar to those methylated in human colon cancer. This indicates that aberrant methylation in cancer may result from targeted sequences by Dnmt3b rather than random methylation followed by clonal selection. Additionally, Dnmt3b-induced aberrant DNA methylation persisted in regenerating tissue even without continuous Dnmt3b expression, supporting the concept that transient stressors can cause permanent epigenetic changes in somatic stem cells that accumulate throughout an organism's lifetime, paralleling DNA mutations.

This protocol describes a method to image individual mRNA molecules in situ. About 50 oligonucleotides complementary to different regions of a target mRNA species are used simultaneously. Each probe is labeled with a single fluorescent moiety. When these probes bind to their target, each mRNA molecule becomes so intensely fluorescent that it can be seen as a fine fluorescent spot. Several different mRNA species can be detected in multiplex imaging using differently colored probe sets for each species. An automated image-processing program is used to count the number of mRNA molecules of each species that are expressed in each cell, thus yielding single-cell gene expression profiles.

Measurements of gene expression within single cells have revealed startling variability otherwise hidden in bulk measurements. Here, we present an in situ hybridization method capable of detecting individual mRNA molecules, thus permitting the accurate quantification and localization of mRNA within fixed sample. Our in situ protocol involves probing the target mRNA using a series of singly labeled oligonucleotide probes. This method is simple to implement and is applicable to a variety of biological samples. We also discuss some aspects of image processing required for analyzing the resulting data.

The phenotypic differences between individual organisms can often be ascribed to underlying genetic and environmental variation. However, even genetically identical organisms in homogeneous environments vary, indicating that randomness in developmental processes such as gene expression may also generate diversity. To examine the consequences of gene expression variability in multicellular organisms, we studied intestinal specification in the nematode Caenorhabditis elegans in which wild-type cell fate is invariant and controlled by a small transcriptional network. Mutations in elements of this network can have indeterminate effects: some mutant embryos fail to develop intestinal cells, whereas others produce intestinal precursors. By counting transcripts of the genes in this network in individual embryos, we show that the expression of an otherwise redundant gene becomes highly variable in the mutants and that this variation is subjected to a threshold, producing an ON/OFF expression pattern of the master regulatory gene of intestinal differentiation. Our results demonstrate that mutations in developmental networks can expose otherwise buffered stochastic variability in gene expression, leading to pronounced phenotypic variation.

We recently showed that the mammalian genome encodes >1,000 large intergenic noncoding (linc)RNAs that are clearly conserved across mammals and, thus, functional. Gene expression patterns have implicated these lincRNAs in diverse biological processes, including cell-cycle regulation, immune surveillance, and embryonic stem cell pluripotency. However, the mechanism by which these lincRNAs function is unknown. Here, we expand the catalog of human lincRNAs to approximately 3,300 by analyzing chromatin-state maps of various human cell types. Inspired by the observation that the well-characterized lincRNA HOTAIR binds the polycomb repressive complex (PRC)2, we tested whether many lincRNAs are physically associated with PRC2. Remarkably, we observe that approximately 20% of lincRNAs expressed in various cell types are bound by PRC2, and that additional lincRNAs are bound by other chromatin-modifying complexes. Also, we show that siRNA-mediated depletion of certain lincRNAs associated with PRC2 leads to changes in gene expression, and that the up-regulated genes are enriched for those normally silenced by PRC2. We propose a model in which some lincRNAs guide chromatin-modifying complexes to specific genomic loci to regulate gene expression.

Both the transcription of mRNAs from genes and their subsequent translation into proteins are inherently stochastic biochemical events, and this randomness can lead to substantial cell-to-cell variability in mRNA and protein numbers in otherwise identical cells. Recently, a number of studies have greatly enhanced our understanding of stochastic processes in gene expression by utilizing new methods capable of counting individual mRNAs and proteins in cells. In this review, we examine the insights that these studies have yielded in the field of stochastic gene expression. In particular, we discuss how these studies have played in understanding the properties of bursts in gene expression. We also compare the array of different methods that have arisen for single mRNA and protein detection, highlighting their relative strengths and weaknesses. In conclusion, we point out further areas where single-molecule techniques applied to gene expression may lead to new discoveries.

We describe a method for imaging individual mRNA molecules in fixed cells by probing each mRNA species with 48 or more short, singly labeled oligonucleotide probes. This makes each mRNA molecule visible as a computationally identifiable fluorescent spot by fluorescence microscopy. We demonstrate simultaneous detection of three mRNA species in single cells and mRNA detection in yeast, nematodes, fruit fly wing discs, and mammalian cell lines and neurons.

Gene expression is a fundamentally stochastic process, with randomness in transcription and translation leading to cell-to-cell variations in mRNA and protein levels. This variation appears in organisms ranging from microbes to metazoans, and its characteristics depend both on the biophysical parameters governing gene expression and on gene network structure. Stochastic gene expression has important consequences for cellular function, being beneficial in some contexts and harmful in others. These situations include the stress response, metabolism, development, the cell cycle, circadian rhythms, and aging.

Random cell-to-cell variations in gene expression within an isogenic population can lead to transitions between alternative states of gene expression. Little is known about how these variations (noise) in natural systems affect such transitions. In Bacillus subtilis, noise in ComK, the protein that regulates competence for DNA uptake, is thought to cause cells to transition to the competent state in which genes encoding DNA uptake proteins are expressed. We demonstrate that noise in comK expression selects cells for competence and that experimental reduction of this noise decreases the number of competent cells. We also show that transitions are limited temporally by a reduction in comK transcription. These results illustrate how such stochastic transitions are regulated in a natural system and suggest that noise characteristics are subject to evolutionary forces.

Individual cells in genetically homogeneous populations have been found to express different numbers of molecules of specific proteins. We investigated the origins of these variations in mammalian cells by counting individual molecules of mRNA produced from a reporter gene that was stably integrated into the cell's genome. We found that there are massive variations in the number of mRNA molecules present in each cell. These variations occur because mRNAs are synthesized in short but intense bursts of transcription beginning when the gene transitions from an inactive to an active state and ending when they transition back to the inactive state. We show that these transitions are intrinsically random and not due to global, extrinsic factors such as the levels of transcriptional activators. Moreover, the gene activation causes burst-like expression of all genes within a wider genomic locus. We further found that bursts are also exhibited in the synthesis of natural genes. The bursts of mRNA expression can be buffered at the protein level by slow protein degradation rates. A stochastic model of gene activation and inactivation was developed to explain the statistical properties of the bursts. The model showed that increasing the level of transcription factors increases the average size of the bursts rather than their frequency. These results demonstrate that gene expression in mammalian cells is subject to large, intrinsically random fluctuations and raise questions about how cells are able to function in the face of such noise.

The role of protein flexibility in molecular motor function has previously been studied by considering a Brownian ratchet motor that is connected to its cargo by an elastic spring, with the result that the average velocity of the motor/cargo system is increased by reducing the stiffness of the linkage. Here, we extend this investigation to the case of chromosome transport during anaphase A, in which the relevant flexibility is not primarily in the motor/cargo linkage but rather in the cargo itself, i.e., in the chromosome. We model the motor mechanism as an imperfect Brownian ratchet with a built-in opposing load and the chromosome as a collection of discrete segments linked by an elastic energy function that discretizes the potential energy of an elastic rod. Thermal fluctuations are produced in the model by random forces, as in Brownian dynamics. All of the parameters that characterize the chromosome are known or can be estimated from experimental data, as can all but one of the motor parameters, which is adjusted to give the correct transport velocity of normal-length chromosomes. With the parameters so determined, we then reproduce the experimental finding of Nicklas that chromosome speed is essentially independent of chromosome length, even though our model contains no "velocity governor." We find instead that this effect is a consequence of chromosome flexibility, as it disappears when stiffer than normal chromosomes are considered.

The mechanism of transport of mRNA-protein (mRNP) complexes from transcription sites to nuclear pores has been the subject of many studies. Using molecular beacons to track single mRNA molecules in living cells, we have characterized the diffusion of mRNP complexes in the nucleus. The mRNP complexes move freely by Brownian diffusion at a rate that assures their dispersion throughout the nucleus before they exit into the cytoplasm, even when the transcription site is located near the nuclear periphery. The diffusion of mRNP complexes is restricted to the extranucleolar, interchromatin spaces. When mRNP complexes wander into dense chromatin, they tend to become stalled. Although the movement of mRNP complexes occurs without the expenditure of metabolic energy, ATP is required for the complexes to resume their motion after they become stalled. This finding provides an explanation for a number of observations in which mRNA transport appeared to be an enzymatically facilitated process.

We have surveyed all high-speed (>250 km/s) flows detected by Wind during its 17 perigee passes across the near-Earth (x_GSE = -25 to 0 R_E) plasma sheet in the period between 1995 and 1997. We classified high-speed flow events by ion distribution characteristics rather than plasma moments, discovering two categories: bulk flows and field-aligned beams. Bulk flows exhibit single drifting populations with peak occurrence at the neutral sheet, accompanied by magnetic field fluctuations and energetic particle increases. Field-aligned beams show sharp low-energy cutoffs and occur in steady conditions away from the neutral sheet. Bulk flows are perpendicular to magnetic fields at the neutral sheet but develop field-aligned components at higher latitudes. No single moment-based parameter or threshold can serve to cleanly separate beam from bulk flow distributions. Analysis identified perpendicular flow speed v_perp > 250 km/s and plasma beta_xy > 2 as optimal selection criteria. Additionally, the survey confirmed a dawn-dusk asymmetry, with most bulk flow events occurring in the premidnight sector, while field-aligned beams showed no such bias.

For certain classes of fractal differential equations on the Sierpinski gasket, built using the Kigami Laplacian, we describe how to approximate solutions using the finite element method based on piecewise harmonic or piecewise biharmonic splines. We give theoretical error estimates, and compare these with experimental data obtained using a computer implementation of the method (available at the web site http://mathlab.cit.cornell.edu/~gibbons). We also explain some interesting structure concerning the spectrum of the Laplacian that became apparent from the experimental data.