Genome-wide kinetic properties of transcriptional bursting in mouse embryonic stem cells

Epigenomic states contribute to coordinated allelic transcriptional bursting in iPSC reprogramming

Two alleles of a gene can be transcribed independently or coordinatedly, which can lead to temporal expression heterogeneity with potentially distinct impacts on cell fate. Here, we profiled genome-wide allelic transcriptional burst kinetics during the reprogramming of MEF to induced pluripotent stem cells. We show that the degree of coordination of allelic bursting differs among genes, and alleles of many reprogramming-related genes burst in a highly coordinated fashion. Notably, we show that the chromatin accessibility of the two alleles of highly coordinated genes is similar, unlike the semi-coordinated or independent genes, suggesting the degree of coordination of allelic bursting is linked to allelic chromatin accessibility. Consistently, we show that many transcription factors have differential binding affinity between alleles of semi-coordinated or independent genes. We show that highly coordinated genes are enriched with chromatin accessibility regulators such as H3K4me3, H3K4me1, H3K36me3, H3K27ac, histone variant H3.3, and BRD4. Finally, we demonstrate that enhancer elements are highly enriched in highly coordinated genes. Our study demonstrates that epigenomic states contribute to coordinated allelic bursting to fine-tune gene expression during induced pluripotent stem cell reprogramming.

Power-law behavior of transcriptional bursting regulated by enhancer-promoter communication

Revealing how transcriptional bursting kinetics are genomically encoded is challenging because genome structures are stochastic at the organization level and are suggestively linked to gene transcription. To address this challenge, we develop a generic theoretical framework that integrates chromatin dynamics, enhancer-promoter (E-P) communication, and gene-state switching to study transcriptional bursting. The theory predicts that power law can be a general rule to quantitatively describe bursting modulations by E-P spatial communication. Specifically, burst frequency and burst size are up-regulated by E-P communication strength, following power laws with positive exponents. Analysis of the scaling exponents further reveals that burst frequency is preferentially regulated. Bursting kinetics are down-regulated by E-P genomic distance with negative power-law exponents, and this negative modulation desensitizes at large distances. The mutual information between burst frequency (or burst size) and E-P spatial distance further reveals essential characteristics of the information transfer from E-P communication to transcriptional bursting kinetics. These findings, which are in agreement with experimental observations, not only reveal fundamental principles of E-P communication in transcriptional bursting but also are essential for understanding cellular decision-making.

De novo hematopoietic (stem) cell generation - A differentiation or stochastic process?

The hematopoietic system is one of the earliest tissues to develop. De novo generation of hematopoietic progenitor and stem cells occurs through a transdifferentiation of (hemogenic) endothelial cells to hematopoietic identity, resulting in the formation of intra-aortic hematopoietic cluster (IAHC) cells. Heterogeneity of IAHC cell phenotypes and functions has stymied the field in its search for the transcriptional program of emerging hematopoietic stem cells (HSCs), given that an individual IAHC cannot be simultaneously examined for function and transcriptome. Several models could account for this heterogeneity, including a novel model suggesting that the transcriptomes of individual emerging IAHC cells are in an unstable/metastable state, with pivotal hematopoietic transcription factors expressed dynamically due to transcriptional pulsing and combinatorial activities. The question remains - how is functional hematopoietic cell fate established - is the process stochastic? This article touches upon these important issues, which may be relevant to the field's inability to make HSCs ex vivo.

4D nucleome equation predicts gene expression controlled by long-range enhancer-promoter interaction

Recent experimental evidence strongly supports that three-dimensional (3D) long-range enhancer-promoter (E-P) interactions have important influences on gene-expression dynamics, but it is unclear how the interaction information is translated into gene expression over time (4D). To address this question, we developed a general theoretical framework (named as a 4D nucleome equation), which integrates E-P interactions on chromatin and biochemical reactions of gene transcription. With this equation, we first present the distribution of mRNA counts as a function of the E-P genomic distance and then reveal a power-law scaling of the expression level in this distance. Interestingly, we find that long-range E-P interactions can induce bimodal and trimodal mRNA distributions. The 4D nucleome equation also allows for model selection and parameter inference. When this equation is applied to the mouse embryonic stem cell smRNA-FISH data and the E-P genomic-distance data, the predicted E-P contact probability and mRNA distribution are in good agreement with experimental results. Further statistical inference indicates that the E-P interactions prefer to modulate the mRNA level by controlling promoter activation and transcription initiation rates. Our model and results provide quantitative insights into both spatiotemporal gene-expression determinants (i.e., long-range E-P interactions) and cellular fates during development.

Mechanical stimulation from the surrounding tissue activates mitochondrial energy metabolism in Drosophila differentiating germ cells

In multicellular lives, the differentiation of stem cells and progenitor cells is often accompanied by a transition from glycolysis to mitochondrial oxidative phosphorylation (OXPHOS). However, the underlying mechanism of this metabolic transition remains largely unknown. In this study, we investigate the role of mechanical stress in activating OXPHOS during differentiation of the female germline cyst in Drosophila. We demonstrate that the surrounding somatic cells flatten the 16-cell differentiating cyst, resulting in an increase of the membrane tension of germ cells inside the cyst. This mechanical stress is necessary to maintain cytosolic Ca2+ concentration in germ cells through a mechanically activated channel, transmembrane channel-like. The sustained cytosolic Ca2+ triggers a CaMKI-Fray-JNK signaling relay, leading to the transcriptional activation of OXPHOS in differentiating cysts. Our findings demonstrate a molecular link between cell mechanics and mitochondrial energy metabolism, with implications for other developmentally orchestrated metabolic transitions in mammals.

Single-cell nascent RNA sequencing using click-chemistry unveils coordinated transcription

Transcription is the primary regulatory step in gene expression. Divergent transcription initiation from promoters and enhancers produces stable RNAs from genes and unstable RNAs from enhancers1-5. Nascent RNA capture and sequencing assays simultaneously measure gene and enhancer activity in cell populations6-9. However, fundamental questions in the temporal regulation of transcription and enhancer-gene synchrony remain unanswered primarily due to the absence of a single-cell perspective on active transcription. In this study, we present scGRO-seq - a novel single-cell nascent RNA sequencing assay using click-chemistry - and unveil the coordinated transcription throughout the genome. scGRO-seq demonstrates the episodic nature of transcription, and estimates burst size and frequency by directly quantifying transcribing RNA polymerases in individual cells. It reveals the co-transcription of functionally related genes and leverages the replication-dependent non-polyadenylated histone genes transcription to elucidate cell-cycle dynamics. The single-nucleotide spatial and temporal resolution of scGRO-seq identifies networks of enhancers and genes and indicates that the bursting of transcription at super-enhancers precedes the burst from associated genes. By imparting insights into the dynamic nature of transcription and the origin and propagation of transcription signals, scGRO-seq demonstrates its unique ability to investigate the mechanisms of transcription regulation and the role of enhancers in gene expression.

The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian

Gene expression inherently gives rise to stochastic variation ("noise") in the production of gene products. Minimizing noise is crucial for ensuring reliable cellular functions. However, noise cannot be suppressed below a certain intrinsic limit. For constitutively expressed genes, this limit is typically assumed to be Poissonian noise, wherein the variance in mRNA numbers is equal to their mean. Here, we demonstrate that several cell division genes in fission yeast exhibit mRNA variances significantly below this limit. The reduced variance can be explained by a gene expression model incorporating multiple transcription and mRNA degradation steps. Notably, in this sub-Poissonian regime, distinct from Poissonian or super-Poissonian regimes, cytoplasmic noise is effectively suppressed through a higher mRNA export rate. Our findings redefine the lower limit of eukaryotic gene expression noise and uncover molecular requirements for achieving ultralow noise, which is expected to be important for vital cellular functions.

Organization of transcription and 3D genome as revealed by live-cell imaging

Higher-order genomic structures play a critical role in regulating gene expression by influencing the spatial proximity of promoters and enhancers. Live-cell imaging studies have demonstrated that three-dimensional genome structures undergo dynamic changes over time. Transcription is also dynamic, with genes frequently switching between active and inactive states. Recent observations suggest that the formation of condensates, composed of transcription-related factors, RNA, and RNA-binding proteins, around genes can regulate transcription. Advancements in technology have facilitated the visualization of the intricate spatiotemporal relationship between higher-order genomic structures, condensate formation, and transcriptional activity in living cells.

Variability of the innate immune response is globally constrained by transcriptional bursting

Transcription of almost all mammalian genes occurs in stochastic bursts, however the fundamental control mechanisms that allow appropriate single-cell responses remain unresolved. Here we utilise single cell genomics data and stochastic models of transcription to perform global analysis of the toll-like receptor (TLR)-induced gene expression variability. Based on analysis of more than 2000 TLR-response genes across multiple experimental conditions we demonstrate that the single-cell, gene-by-gene expression variability can be empirically described by a linear function of the population mean. We show that response heterogeneity of individual genes can be characterised by the slope of the mean-variance line, which captures how cells respond to stimulus and provides insight into evolutionary differences between species. We further demonstrate that linear relationships theoretically determine the underlying transcriptional bursting kinetics, revealing different regulatory modes of TLR response heterogeneity. Stochastic modelling of temporal scRNA-seq count distributions demonstrates that increased response variability is associated with larger and more frequent transcriptional bursts, which emerge via increased complexity of transcriptional regulatory networks between genes and different species. Overall, we provide a methodology relying on inference of empirical mean-variance relationships from single cell data and new insights into control of innate immune response variability.

Synergising single-cell resolution and 4sU labelling boosts inference of transcriptional bursting

Despite the recent rise of RNA-seq datasets combining single-cell (sc) resolution with 4-thiouridine (4sU) labelling, analytical methods exploiting their power to dissect transcriptional bursting are lacking. Here, we present a mathematical model and Bayesian inference implementation to facilitate genome-wide joint parameter estimation and confidence quantification (R package: burstMCMC). We demonstrate that, unlike conventional scRNA-seq, 4sU scRNA-seq resolves temporal parameters and furthermore boosts inference of dimensionless parameters via a synergy between single-cell resolution and 4sU labelling. We apply our method to published 4sU scRNA-seq data and linked with ChIP-seq data, we uncover previously obscured associations between different parameters and histone modifications.

Low-level repressive histone marks fine-tune gene transcription in neural stem cells

Coordinated regulation of gene activity by transcriptional and translational mechanisms poise stem cells for a timely cell-state transition during differentiation. Although important for all stemness-to-differentiation transitions, mechanistic understanding of the fine-tuning of gene transcription is lacking due to the compensatory effect of translational control. We used intermediate neural progenitor (INP) identity commitment to define the mechanisms that fine-tune stemness gene transcription in fly neural stem cells (neuroblasts). We demonstrate that the transcription factor FruitlessC (FruC) binds cis-regulatory elements of most genes uniquely transcribed in neuroblasts. Loss of fruC function alone has no effect on INP commitment but drives INP dedifferentiation when translational control is reduced. FruC negatively regulates gene expression by promoting low-level enrichment of the repressive histone mark H3K27me3 in gene cis-regulatory regions. Identical to fruC loss-of-function, reducing Polycomb Repressive Complex 2 activity increases stemness gene activity. We propose low-level H3K27me3 enrichment fine-tunes gene transcription in stem cells, a mechanism likely conserved from flies to humans.

Inferring transcriptional bursting kinetics from single-cell snapshot data using a generalized telegraph model

Gene expression has inherent stochasticity resulting from transcription's burst manners. Single-cell snapshot data can be exploited to rigorously infer transcriptional burst kinetics, using mathematical models as blueprints. The classical telegraph model (CTM) has been widely used to explain transcriptional bursting with Markovian assumptions. However, growing evidence suggests that the gene-state dwell times are generally non-exponential, as gene-state switching is a multi-step process in organisms. Therefore, interpretable non-Markovian mathematical models and efficient statistical inference methods are urgently required in investigating transcriptional burst kinetics. We develop an interpretable and tractable model, the generalized telegraph model (GTM), to characterize transcriptional bursting that allows arbitrary dwell-time distributions, rather than exponential distributions, to be incorporated into the ON and OFF switching process. Based on the GTM, we propose an inference method for transcriptional bursting kinetics using an approximate Bayesian computation framework. This method demonstrates an efficient and scalable estimation of burst frequency and burst size on synthetic data. Further, the application of inference to genome-wide data from mouse embryonic fibroblasts reveals that GTM would estimate lower burst frequency and higher burst size than those estimated by CTM. In conclusion, the GTM and the corresponding inference method are effective tools to infer dynamic transcriptional bursting from static single-cell snapshot data.

The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian

Stochastic variation in gene products ("noise") is an inescapable by-product of gene expression. Noise must be minimized to allow for the reliable execution of cellular functions. However, noise cannot be suppressed beyond an intrinsic lower limit. For constitutively expressed genes, this limit is believed to be Poissonian, meaning that the variance in mRNA numbers cannot be lower than their mean. Here, we show that several cell division genes in fission yeast have mRNA variances significantly below this limit, which cannot be explained by the classical gene expression model for low-noise genes. Our analysis reveals that multiple steps in both transcription and mRNA degradation are essential to explain this sub-Poissonian variance. The sub-Poissonian regime differs qualitatively from previously characterized noise regimes, a hallmark being that cytoplasmic noise is reduced when the mRNA export rate increases. Our study re-defines the lower limit of eukaryotic gene expression noise and identifies molecular requirements for ultra-low noise which are expected to support essential cell functions.

Probing transient memory of cellular states using single-cell lineages

The inherent stochasticity in the gene product levels can drive single cells within an isoclonal population to different phenotypic states. The dynamic nature of this intercellular variation, where individual cells can transition between different states over time, makes it a particularly hard phenomenon to characterize. We reviewed recent progress in leveraging the classical Luria-Delbrück experiment to infer the transient heritability of the cellular states. Similar to the original experiment, individual cells were first grown into cell colonies, and then, the fraction of cells residing in different states was assayed for each colony. We discuss modeling approaches for capturing dynamic state transitions in a growing cell population and highlight formulas that identify the kinetics of state switching from the extent of colony-to-colony fluctuations. The utility of this method in identifying multi-generational memory of the both expression and phenotypic states is illustrated across diverse biological systems from cancer drug resistance, reactivation of human viruses, and cellular immune responses. In summary, this fluctuation-based methodology provides a powerful approach for elucidating cell-state transitions from a single time point measurement, which is particularly relevant in situations where measurements lead to cell death (as in single-cell RNA-seq or drug treatment) or cause an irreversible change in cell physiology.

From structure to molecular condensates: emerging mechanisms for Mediator function

Mediator is a large modular protein assembly whose function as a coactivator of transcription is conserved in all eukaryotes. The Mediator complex can integrate and relay signals from gene-specific activators bound at enhancers to activate the general transcription machinery located at promoters. It has thus been described as a bridge between these elements during initiation of transcription. Here, we review recent studies on Mediator relating to its structure, gene specificity and general requirement, roles in chromatin architecture as well as novel concepts involving phase separation and transcriptional bursting. We revisit the mechanism of action of Mediator and ultimately put forward models for its mode of action in gene activation.

STREAMING-Tag System: Technology to Enable Visualization of Transcriptional Activity and Subnuclear Localization of Specific Endogenous Genes

The Spliced TetO REpeAt, MS2 repeat, and INtein sandwiched reporter Gene tag (STREAMING-tag) system enables imaging of nuclear localization as well as the transcription activity of a specific endogenous gene at sub-100-nm resolution in living cells. The use of this system combined with imaging of epigenome states enables a detailed analysis of the impact of epigenome status on transcriptional dynamics. In this chapter, we describe a method for quantifying distances between Nanog gene and clusters of cofactor BRD4 using the STREAMING-tag system in mouse embryonic stem cells.

Genome-wide inference reveals that feedback regulations constrain promoter-dependent transcriptional burst kinetics

Gene expression in mammalian cells is highly variable and episodic, resulting in a series of discontinuous bursts of mRNAs. A challenge is to understand how static promoter architecture and dynamic feedback regulations dictate bursting on a genome-wide scale. Although single-cell RNA sequencing (scRNA-seq) provides an opportunity to address this challenge, effective analytical methods are scarce. We developed an interpretable and scalable inference framework, which combined experimental data with a mechanistic model to infer transcriptional burst kinetics (sizes and frequencies) and feedback regulations. Applying this framework to scRNA-seq data generated from embryonic mouse fibroblast cells, we found Simpson's paradoxes, i.e. genome-wide burst kinetics exhibit different characteristics in two cases without and with distinguishing feedback regulations. We also showed that feedbacks differently modulate burst frequencies and sizes and conceal the effects of transcription start site distributions on burst kinetics. Notably, only in the presence of positive feedback, TATA genes are expressed with high burst frequencies and enhancer-promoter interactions mainly modulate burst frequencies. The developed inference method provided a flexible and efficient way to investigate transcriptional burst kinetics and the obtained results would be helpful for understanding cell development and fate decision.

Retention of ERK in the cytoplasm mediates the pluripotency of embryonic stem cells

The dynamic subcellular localization of ERK1/2 plays an important role in regulating cell fate. Differentiation of mouse embryonic stem cells (mESCs) involves inductive stimulation of ERK1/2, and therefore, inhibitors of the ERK cascade are used to maintain pluripotency. Interestingly, we found that in pluripotent mESCs, ERK1/2 do not translocate to the nucleus either before or after stimulation. This inhibition of nuclear translocation may be dependent on a lack of stimulated ERK1/2 interaction with importin7 rather than a lack of ERK1/2 phosphorylation activating translocation. At late stages of naive-to-primed transition, the action of the translocating machinery is restored, leading to elevation in ERK1/2-importin7 interaction and their nuclear translocation. Importantly, forcing ERK2 into the naive cells' nuclei accelerates their early differentiation, while prevention of the translocation restores stem cells' pluripotency. These results indicate that prevention of nuclear ERK1/2 translocation serves as a safety mechanism for keeping pluripotency of mESCs.

STREAMING-tag system reveals spatiotemporal relationships between transcriptional regulatory factors and transcriptional activity

Transcription is a dynamic process. To detect the dynamic relationship among protein clusters of RNA polymerase II and coactivators, gene loci, and transcriptional activity, we insert an MS2 repeat, a TetO repeat, and inteins with a selection marker just downstream of the transcription start site. By optimizing the individual elements, we develop the Spliced TetO REpeAt, MS2 repeat, and INtein sandwiched reporter Gene tag (STREAMING-tag) system. Clusters of RNA polymerase II and BRD4 are observed proximal to the transcription start site of Nanog when the gene is transcribed in mouse embryonic stem cells. In contrast, clusters of MED19 and MED22 tend to be located near the transcription start site, even without transcription activity. Thus, the STREAMING-tag system reveals the spatiotemporal relationships between transcriptional activity and protein clusters near the gene. This powerful tool is useful for quantitatively understanding transcriptional regulation in living cells.

Transcriptional enhancers at 40: evolution of a viral DNA element to nuclear architectural structures

Gene regulation by transcriptional enhancers is the dominant mechanism driving cell type- and signal-specific transcriptional diversity in metazoans. However, over four decades since the original discovery, how enhancers operate in the nuclear space remains largely enigmatic. Recent multidisciplinary efforts combining real-time imaging, genome sequencing, and biophysical strategies provide insightful but conflicting models of enhancer-mediated gene control. Here, we review the discovery and progress in enhancer biology, emphasizing the recent findings that acutely activated enhancers assemble regulatory machinery as mesoscale architectural structures with distinct physical properties. These findings help formulate novel models that explain several mysterious features of the assembly of transcriptional enhancers and the mechanisms of spatial control of gene expression.

Tracking the Activation of Heat Shock Signaling in Cellular Protection and Damage

Heat Shock (HS) signaling is activated in response to various types of cellular stress. This activation serves to protect cells from immediate threats in the surrounding environment. However, activation of HS signaling occurs in a heterogeneous manner within each cell population and can alter the epigenetic state of the cell, ultimately leading to long-term abnormalities in body function. Here, we summarize recent research findings obtained using molecular and genetic tools to track cells where HS signaling is activated. We then discuss the potential further applications of these tools, their limitations, and the necessary caveats in interpreting data obtained with these tools.

Live imaging of transcription sites using an elongating RNA polymerase II-specific probe

In eukaryotic nuclei, most genes are transcribed by RNA polymerase II (RNAP2), whose regulation is a key to understanding the genome and cell function. RNAP2 has a long heptapeptide repeat (Tyr1-Ser2-Pro3-Thr4-Ser5-Pro6-Ser7), and Ser2 is phosphorylated on an elongation form. To detect RNAP2 Ser2 phosphorylation (RNAP2 Ser2ph) in living cells, we developed a genetically encoded modification-specific intracellular antibody (mintbody) probe. The RNAP2 Ser2ph-mintbody exhibited numerous foci, possibly representing transcription “factories,” and foci were diminished during mitosis and in a Ser2 kinase inhibitor. An in vitro binding assay using phosphopeptides confirmed the mintbody’s specificity. RNAP2 Ser2ph-mintbody foci were colocalized with proteins associated with elongating RNAP2 compared with factors involved in the initiation. These results support the view that mintbody localization represents the sites of RNAP2 Ser2ph in living cells. RNAP2 Ser2ph-mintbody foci showed constrained diffusional motion like chromatin, but they were more mobile than DNA replication domains and p300-enriched foci, suggesting that the elongating RNAP2 complexes are separated from more confined chromatin domains.

Inference of trajectory presence by tree dimension and subset specificity by subtree cover

The complexity of biological processes such as cell differentiation is reflected in dynamic transitions between cellular states. Trajectory inference arranges the states into a progression using methodologies propelled by single-cell biology. However, current methods, all returning a best trajectory, do not adequately assess statistical significance of noisy patterns, leading to uncertainty in inferred trajectories. We introduce a tree dimension test for trajectory presence in multivariate data by a dimension measure of Euclidean minimum spanning tree, a test statistic, and a null distribution. Computable in linear time to tree size, the tree dimension measure summarizes the extent of branching more effectively than globally insensitive number of leaves or tree diameter indifferent to secondary branches. The test statistic quantifies trajectory presence and its null distribution is estimated under the null hypothesis of no trajectory in data. On simulated and real single-cell datasets, the test outperformed the intuitive number of leaves and tree diameter statistics. Next, we developed a measure for the tissue specificity of the dynamics of a subset, based on the minimum subtree cover of the subset in a minimum spanning tree. We found that tissue specificity of pathway gene expression dynamics is conserved in human and mouse development: several signal transduction pathways including calcium and Wnt signaling are most tissue specific, while genetic information processing pathways such as ribosome and mismatch repair are least so. Neither the tree dimension test nor the subset specificity measure has any user parameter to tune. Our work opens a window to prioritize cellular dynamics and pathways in development and other multivariate dynamical systems.

Modern biology now routinely studies transcriptome profiles during development. This practice demands computational methods to quantify dynamical changes in cellular states and their heterogeneity. Many methods process single-cell transcriptome data to reconstruct cellular trajectories, which are orderings of cells as they progress from an early to a late developmental stage. Due to noise in transcriptome data, there is a great need to quantify how likely observed data present a trajectory-like pattern due to chance. To address this need, we developed a tree dimension test to quantify evidence for trajectory presence in multivariate data based on graph-theoretical concepts. By this test, one may reject trajectory presence due to low data quality, or accept a trajectory with high statistical significance. Now one can rank biological pathways by their trajectory quality. We also introduce a subset specificity measure to quantify how cellular or pathway dynamics are tissue specific. We found that pathway tissue specificity is highly conserved between human and mouse. Trajectory presence testing and subset specificity offer a unique informatics tool set to study developmental biology.

Dynamic modulation of enhancer responsiveness by core promoter elements in living Drosophila embryos

Regulatory interactions between enhancers and core promoters are fundamental for the temporal and spatial specificity of gene expression in development. The central role of core promoters is to initiate productive transcription in response to enhancer's activation cues. However, it has not been systematically assessed how individual core promoter elements affect the induction of transcriptional bursting by enhancers. Here, we provide evidence that each core promoter element differentially modulates functional parameters of transcriptional bursting in developing Drosophila embryos. Quantitative live imaging analysis revealed that the timing and the continuity of burst induction are common regulatory steps on which core promoter elements impact. We further show that the upstream TATA also affects the burst amplitude. On the other hand, Inr, MTE and DPE mainly contribute to the regulation of the burst frequency. Genome editing analysis of the pair-rule gene fushi tarazu revealed that the endogenous TATA and DPE are both essential for its correct expression and function during the establishment of body segments in early embryos. We suggest that core promoter elements serve as a key regulatory module in converting enhancer activity into transcription dynamics during animal development.

Inter- and Intrapopulational Heterogeneity of Characteristic Markers in Adult Human Neural Crest-derived Stem Cells

Adult human neural crest-derived stem cells (NCSCs) are found in a variety of adult tissues and show an extraordinary broad developmental potential. Despite their great differentiation capacity, increasing evidence suggest a remaining niche-dependent variability between different NCSC-populations regarding their differentiation behavior and expression signatures. In the present study, we extended the view on heterogeneity of NCSCs by identifying heterogeneous expression levels and protein amounts of characteristic markers even between NCSCs from the same niche of origin. In particular, populations of neural crest-derived inferior turbinate stem cells (ITSCs) isolated from different individuals showed significant variations in characteristic NCSC marker proteins Nestin, S100 and Slug in a donor-dependent manner. Notably, increased nuclear protein amounts of Slug were accompanied by a significantly elevated level of nuclear NF-κB-p65 protein, suggesting an NF-κB-dependent regulation of NCSC-makers. In addition to this interpopulational genetic heterogeneity of ITSC-populations from different donors, single ITSCs also revealed a strong heterogeneity regarding the protein amounts of Nestin, S100, Slug and NF-κB-p65 even within the same clonal culture. Our present findings therefor strongly suggest ITSC-heterogeneity to be at least partly based on an interpopulational genetic heterogeneity dependent on the donor accompanied by a stochastic intrapopulational heterogeneity between single cells. We propose this stochastic intrapopulational heterogeneity to occur in addition to the already described genetic variability between clonal NCSC-cultures and the niche-dependent plasticity of NCSCs. Our observations offer a novel perspective on NCSC-heterogeneity, which may build the basis to understand heterogeneous NCSC-behavior.

A Comprehensive Characterization of Monoallelic Expression During Hematopoiesis and Leukemogenesis via Single-Cell RNA-Sequencing

Single-cell RNA-sequencing (scRNA-seq) is becoming a powerful tool to investigate monoallelic expression (MAE) in various developmental and pathological processes. However, our knowledge of MAE during hematopoiesis and leukemogenesis is limited. In this study, we conducted a systematic interrogation of MAEs in bone marrow mononuclear cells (BMMCs) at single-cell resolution to construct a MAE atlas of BMMCs. We identified 1,020 constitutive MAEs in BMMCs, which included imprinted genes such as MEG8, NAP1L5, and IRAIN. We classified the BMMCs into six cell types and identified 74 cell type specific MAEs including MTSS1, MOB1A, and TCF12. We further identified 114 random MAEs (rMAEs) at single-cell level, with 78.1% single-allele rMAE and 21.9% biallelic mosaic rMAE. Many MAEs identified in BMMCs have not been reported and are potentially hematopoietic specific, supporting MAEs are functional relevance. Comparison of BMMC samples from a leukemia patient with multiple clinical stages showed the fractions of constitutive MAE were correlated with fractions of leukemia cells in BMMCs. Further separation of the BMMCs into leukemia cells and normal cells showed that leukemia cells have much higher constitutive MAE and rMAEs than normal cells. We identified the leukemia cell-specific MAEs and relapsed leukemia cell-specific MAEs, which were enriched in immune-related functions. These results indicate MAE is prevalent and is an important gene regulation mechanism during hematopoiesis and leukemogenesis. As the first systematical interrogation of constitutive MAEs, cell type specific MAEs, and rMAEs during hematopoiesis and leukemogenesis, the study significantly increased our knowledge about the features and functions of MAEs.

PRC1 drives Polycomb-mediated gene repression by controlling transcription initiation and burst frequency

The Polycomb repressive system plays a fundamental role in controlling gene expression during mammalian development. To achieve this, Polycomb repressive complexes 1 and 2 (PRC1 and PRC2) bind target genes and use histone modification-dependent feedback mechanisms to form Polycomb chromatin domains and repress transcription. The inter-relatedness of PRC1 and PRC2 activity at these sites has made it difficult to discover the specific components of Polycomb chromatin domains that drive gene repression and to understand mechanistically how this is achieved. Here, by exploiting rapid degron-based approaches and time-resolved genomics, we kinetically dissect Polycomb-mediated repression and discover that PRC1 functions independently of PRC2 to counteract RNA polymerase II binding and transcription initiation. Using single-cell gene expression analysis, we reveal that PRC1 acts uniformly within the cell population and that repression is achieved by controlling transcriptional burst frequency. These important new discoveries provide a mechanistic and conceptual framework for Polycomb-dependent transcriptional control.

Semicoordinated allelic-bursting shape dynamic random monoallelic expression in pregastrulation embryos

Recently, allele-specific single-cell RNA-seq analysis has demonstrated widespread dynamic random monoallelic expression of autosomal genes (aRME) in different cell types. However, the prevalence of dynamic aRME during pregastrulation remains unknown. Here, we show that dynamic aRME is widespread in different lineages of pregastrulation embryos. Additionally, the origin of dynamic aRME remains elusive. It is believed that independent transcriptional bursting from each allele leads to dynamic aRME. Here, we show that allelic burst is not perfectly independent; instead it happens in a semicoordinated fashion. Importantly, we show that semicoordinated allelic bursting of genes, particularly with low burst frequency, leads to frequent asynchronous allelic bursting, thereby contributing to dynamic aRME. Furthermore, we found that coordination of allelic bursting is lineage specific and genes regulating the development have a higher degree of coordination. Altogether, our study provides significant insights into the prevalence and origin of dynamic aRME and their developmental relevance during early development.

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Dynamic aRME is widespread in different lineages of pregastrulation embryos

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Semicoordinated bursting of genes with low burst frequency leads to dynamic aRME

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Degree of coordination of allelic bursting is lineage specific

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Developmental genes have higher degree of coordination of allelic bursting

Transcription factor binding kinetics and transcriptional bursting: What do we really know?

In eukaryotes, transcription is a discontinuous process with mRNA being generated in bursts, after the binding of transcription factors (TFs) to regulatory elements on the genome. Live-cell single-molecule microscopy has highlighted that transcriptional bursting can be controlled by tuning TF/DNA binding kinetics. Yet the timescales of these two processes seem disconnected with TF/DNA interactions typically lasting orders of magnitude shorter than transcriptional bursts. To test models that could reconcile these discrepancies, reliable measurements of TF binding kinetics are needed, also accounting for the current limitations in performing these single-molecule measurements at specific regulatory elements. Here, we review the recent studies linking TF binding kinetics to transcriptional bursting and outline some current and future challenges that need to be addressed to provide a microscopic description of transcriptional regulation kinetics.

Decoding the dynamics of multilayered stochastic antiviral IFN-I responses

Type I Interferon (IFN-I) responses were first recognized for their role in antiviral immunity, but it is now widely appreciated that IFN-Is have many immunomodulatory functions, influencing antitumor responses, autoimmune manifestations, and antimicrobial defenses. Given these pivotal roles, it may be surprising that multilayered stochastic events create highly heterogeneous, but tightly regulated, all-or-nothing cellular decisions. Recently, mathematical models have provided crucial insights into the stochastic nature of antiviral IFN-I responses, which we critically evaluate in this review. In this context, we emphasize the need for innovative single-cell technologies combined with mathematical models to further reveal, understand, and predict the complexity of the IFN-I system in physiological and pathological conditions that may be relevant to a plethora of diseases.

Deciphering transcriptional and functional heterogeneity in hematopoiesis with single-cell genomics

PURPOSE OF REVIEW

Single-cell genomic approaches have uncovered cell fate biases and heterogeneity within hematopoietic subpopulations. However, standard single-cell transcriptomics suffers from high sampling noise, which particularly skews the distribution of lowly expressed genes, such as transcription factors (TFs). This might preclude the identification of rare transcripts that define cell identity and demarcate cell fate biases. Moreover, these studies need to go hand in hand with relevant functional assays to ensure that observed gene expression changes represent biologically meaningful alterations.

RECENT FINDINGS

Single-cell lineage tracing and functional validation studies have uncovered cell fate bias within transcriptionally distinct hematopoietic stem and progenitor subpopulations. Novel markers identified using these strategies have been proposed to prospectively isolate functionally distinct subpopulations, including long-term hematopoietic stem cells for ex vivo applications. Furthermore, the continuous nature of hematopoiesis has prompted the study of the relationship between stochastic transcriptional noise in hematopoietic TFs and cell fate determination.

SUMMARY

An understanding of the limitations of single-cell genomic approaches and follow-up functional assays is critical to discern the technical and biological contribution of noise in hematopoietic heterogeneity, to identify rare gene expression states, and to uncover functionally distinct subpopulations within hematopoiesis.

SUPPLEMENTARY VIDEO

http://links.lww.com/COH/A23.

Between Fate Choice and Self-Renewal-Heterogeneity of Adult Neural Crest-Derived Stem Cells

Stem cells of the neural crest (NC) vitally participate to embryonic development, but also remain in distinct niches as quiescent neural crest-derived stem cell (NCSC) pools into adulthood. Although NCSC-populations share a high capacity for self-renewal and differentiation resulting in promising preclinical applications within the last two decades, inter- and intrapopulational differences exist in terms of their expression signatures and regenerative capability. Differentiation and self-renewal of stem cells in developmental and regenerative contexts are partially regulated by the niche or culture condition and further influenced by single cell decision processes, making cell-to-cell variation and heterogeneity critical for understanding adult stem cell populations. The present review summarizes current knowledge of the cellular heterogeneity within NCSC-populations located in distinct craniofacial and trunk niches including the nasal cavity, olfactory bulb, oral tissues or skin. We shed light on the impact of intrapopulational heterogeneity on fate specifications and plasticity of NCSCs in their niches in vivo as well as during in vitro culture. We further discuss underlying molecular regulators determining fate specifications of NCSCs, suggesting a regulatory network including NF-κB and NC-related transcription factors like SLUG and SOX9 accompanied by Wnt- and MAPK-signaling to orchestrate NCSC stemness and differentiation. In summary, adult NCSCs show a broad heterogeneity on the level of the donor and the donors' sex, the cell population and the single stem cell directly impacting their differentiation capability and fate choices in vivo and in vitro. The findings discussed here emphasize heterogeneity of NCSCs as a crucial parameter for understanding their role in tissue homeostasis and regeneration and for improving their applicability in regenerative medicine.

Interplay between genetic, epigenetic, and gene expression variability: Considering complexity in evolvability

Genetic variability, epigenetic variability, and gene expression variability (noise) are generally considered independently in their relationship with phenotypic variation. However, they appear to be intrinsically interconnected and influence it in combination. The study of the interplay between genetic and epigenetic variability has the longest history. This article rather considers the introduction of gene expression variability in its relationships with the two others and reviews for the first time experimental evidences over the four relationships connected to gene expression noise. They show how introducing this third source of variability complicates the way of thinking evolvability and the emergence of biological novelty. Finally, cancer cells are proposed to be an ideal model to decipher the dynamic interplay between genetic, epigenetic, and gene expression variability when one of them is either experimentally increased or therapeutically targeted. This interplay is also discussed in an evolutionary perspective in the context of cancer cell drug resistance.

Nebulosa recovers single cell gene expression signals by kernel density estimation

SUMMARY

Data sparsity in single-cell experiments prevents an accurate assessment of gene expression when visualised in a low-dimensional space. Here, we introduce Nebulosa, an R package that uses weighted kernel density estimation to recover signals lost through drop-out or low expression.

AVAILABILITY AND IMPLEMENTATION

Nebulosa can be easily installed from www.github.com/powellgenomicslab/Nebulosa.

SUPPLEMENTARY INFORMATION

Supplementary data are available online.

Capturing and Understanding the Dynamics and Heterogeneity of Gene Expression in the Living Cell

The regulation of gene expression is a fundamental process enabling cells to respond to internal and external stimuli or to execute developmental programs. Changes in gene expression are highly dynamic and depend on many intrinsic and extrinsic factors. In this review, we highlight the dynamic nature of transient gene expression changes to better understand cell physiology and development in general. We will start by comparing recent in vivo procedures to capture gene expression in real time. Intrinsic factors modulating gene expression dynamics will then be discussed, focusing on chromatin modifications. Furthermore, we will dissect how cell physiology or age impacts on dynamic gene regulation and especially discuss molecular insights into acquired transcriptional memory. Finally, this review will give an update on the mechanisms of heterogeneous gene expression among genetically identical individual cells. We will mainly focus on state-of-the-art developments in the yeast model but also cover higher eukaryotic systems.

Buffering noise: KAT2A modular contributions to stabilization of transcription and cell identity in cancer and development

KAT2A is a histone acetyltransferase recently identified as a vulnerability in at least some forms of Acute Myeloid Leukemia (AML). Its loss or inhibition prompts leukemia stem cells out of self-renewal and into differentiation with ultimate exhaustion of the leukemia pool. We have recently linked the Kat2a requirement in AML to control of transcriptional noise, reflecting an evolutionary-conserved role of Kat2a in promoting burst-like promoter activity and stabilizing gene expression. We suggest that through this role, Kat2a contributes to preservation of cell identity. KAT2A exerts its acetyltransferase activity in the context of two macromolecular complexes, Spt-Ada-Gcn5-Acetyltransferase (SAGA) and Ada-Two-A-Containing (ATAC), but the specific contribution of each complex to stabilization of gene expression is currently unknown. By reviewing specific gene targets and requirements of the two complexes in cancer and development, we suggest that SAGA regulates lineage-specific programs, and ATAC maintains biosynthetic activity through control of ribosomal protein and translation-associated genes, on which cells may be differentially dependent. While our data suggest that KAT2A-mediated regulation of transcriptional noise in AML may be exerted through ATAC, we discuss potential caveats and probe general vs. complex-specific contributions of KAT2A to transcriptional stability, with implications for control and perturbation of cell identity.