Flipping between Polycomb repressed and active transcriptional states introduces noise in gene expression

Molecular models of bidirectional promoter regulation

Approximately 11% of human genes are transcribed by a bidirectional promoter (BDP), defined as two genes with <1 kb between their transcription start sites. Despite their evolutionary conservation and enrichment for housekeeping genes and oncogenes, the regulatory role of BDPs remains unclear. BDPs have been suggested to facilitate gene coregulation and/or decrease expression noise. This review discusses these potential regulatory functions through the context of six prospective underlying mechanistic models: a single nucleosome free region, shared transcription factor/regulator binding, cooperative negative supercoiling, bimodal histone marks, joint activation by enhancer(s), and RNA-mediated recruitment of regulators. These molecular mechanisms may act independently and/or cooperatively to facilitate the coregulation and/or decreased expression noise predicted of BDPs.

Contributions of transcriptional noise to leukaemia evolution: KAT2A as a case-study

Transcriptional noise is proposed to participate in cell fate changes, but contributions to mammalian cell differentiation systems, including cancer, remain associative. Cancer evolution is driven by genetic variability, with modulatory or contributory participation of epigenetic variants. Accumulation of epigenetic variants enhances transcriptional noise, which can facilitate cancer cell fate transitions. Acute myeloid leukaemia (AML) is an aggressive cancer with strong epigenetic dependencies, characterized by blocked differentiation. It constitutes an attractive model to probe links between transcriptional noise and malignant cell fate regulation. Gcn5/KAT2A is a classical epigenetic transcriptional noise regulator. Its loss increases transcriptional noise and modifies cell fates in stem and AML cells. By reviewing the analysis of KAT2A-depleted pre-leukaemia and leukaemia models, I discuss that the net result of transcriptional noise is diversification of cell fates secondary to alternative transcriptional programmes. Cellular diversification can enable or hinder AML progression, respectively, by differentiation of cell types responsive to mutations, or by maladaptation of leukaemia stem cells. KAT2A-dependent noise-responsive genes participate in ribosome biogenesis and KAT2A loss destabilizes translational activity. I discuss putative contributions of perturbed translation to AML biology, and propose KAT2A loss as a model for mechanistic integration of transcriptional and translational control of noise and fate decisions. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

VarID2 quantifies gene expression noise dynamics and unveils functional heterogeneity of ageing hematopoietic stem cells

Variability of gene expression due to stochasticity of transcription or variation of extrinsic signals, termed biological noise, is a potential driving force of cellular differentiation. Utilizing single-cell RNA-sequencing, we develop VarID2 for the quantification of biological noise at single-cell resolution. VarID2 reveals enhanced nuclear versus cytoplasmic noise, and distinct regulatory modes stratified by correlation between noise, expression, and chromatin accessibility. Noise levels are minimal in murine hematopoietic stem cells (HSCs) and increase during differentiation and ageing. Differential noise identifies myeloid-biased Dlk1+ long-term HSCs in aged mice with enhanced quiescence and self-renewal capacity. VarID2 reveals noise dynamics invisible to conventional single-cell transcriptome analysis.

Dual functions of TET1 in germ layer lineage bifurcation distinguished by genomic context and dependence on 5-methylcytosine oxidation

Gastrulation begins when the epiblast forms the primitive streak or becomes definitive ectoderm. During this lineage bifurcation, the DNA dioxygenase TET1 has bipartite functions in transcriptional activation and repression, but the mechanisms remain unclear. By converting mouse embryonic stem cells (ESCs) into neuroprogenitors, we defined how Tet1-/- cells switch from neuroectoderm fate to form mesoderm and endoderm. We identified the Wnt repressor Tcf7l1 as a TET1 target that suppresses Wnt/β-catenin and Nodal signalling. ESCs expressing catalytic dead TET1 retain neural potential but activate Nodal and subsequently Wnt/β-catenin pathways to generate also mesoderm and endoderm. At CpG-poor distal enhancers, TET1 maintains accessible chromatin at neuroectodermal loci independently of DNA demethylation. At CpG-rich promoters, DNA demethylation by TET1 affects the expression of bivalent genes. In ESCs, a non-catalytic TET1 cooperation with Polycomb represses primitive streak genes; post-lineage priming, the interaction becomes antagonistic at neuronal genes, when TET1's catalytic activity is further involved by repressing Wnt signalling. The convergence of repressive DNA and histone methylation does not inhibit neural induction in Tet1-deficient cells, but some DNA hypermethylated loci persist at genes with brain-specific functions. Our results reveal versatile switching of non-catalytic and catalytic TET1 activities based on genomic context, lineage and developmental stage.

Mapping Multi-factor-mediated Chromatin Interactions to Assess Dysregulation of Lung Cancer-related Genes

Studies on the lung cancer genome are indispensable for developing a cure for lung cancer. Whole-genome resequencing, genome-wide association studies, and transcriptome sequencing have greatly improved our understanding of the cancer genome. However, dysregulation of long-range chromatin interactions in lung cancer remains poorly described. To better understand the three-dimensional (3D) genomic interaction features of the lung cancer genome, we used the A549 cell line as a model system and generated high-resolution chromatin interactions associated with RNA polymerase II (RNAPII), CCCTC-binding factor (CTCF), enhancer of zeste homolog 2 (EZH2), and histone 3 lysine 27 trimethylation (H3K27me3) using long-read chromatin interaction analysis by paired-end tag sequencing (ChIA-PET). Analysis showed that EZH2/H3K27me3-mediated interactions further repressed target genes, either through loops or domains, and their distributions along the genome were distinct from and complementary to those associated with RNAPII. Cancer-related genes were highly enriched with chromatin interactions, and chromatin interactions specific to the A549 cell line were associated with oncogenes and tumor suppressor genes, such as additional repressive interactions on FOXO4 and promoter-promoter interactions between NF1 and RNF135. Knockout of an anchor associated with chromatin interactions reversed the dysregulation of cancer-related genes, suggesting that chromatin interactions are essential for proper expression of lung cancer-related genes. These findings demonstrate the 3D landscape and gene regulatory relationships of the lung cancer genome.

Making use of noise in biological systems

Disorder and noise are inherent in biological systems. They are required to provide systems with the advantages required for proper functioning. Noise is a part of the flexibility and plasticity of biological systems. It provides systems with increased routes, improves information transfer, and assists in response triggers. This paper reviews recent studies on noise at the genome, cellular, and whole organ levels. We focus on the need to use noise in system engineering. We present some of the challenges faced in studying noise. Optimizing the efficiency of complex systems requires a degree of variability in their functions within certain limits. Constrained noise can be considered a method for improving system robustness by regulating noise levels in continuously dynamic settings. The digital pill-based artificial intelligence (AI)-based platform is the first to implement second-generation AI comprising variability-based signatures. This platform enhances the efficacy of the therapeutic regimens. Systems requiring variability and mechanisms regulating noise are mandatory for understanding biological functions.

Molecular versatility during pluripotency progression

A challenge during development is to ensure lineage segregation while preserving plasticity. Using pluripotency progression as a paradigm, we review how developmental transitions are coordinated by redeployments, rather than global resettings, of cellular components. We highlight how changes in response to extrinsic cues (FGF, WNT, Activin/Nodal, Netrin-1), context- and stoichiometry-dependent action of transcription factors (Oct4, Nanog) and reconfigurations of epigenetic regulators (enhancers, promoters, TrxG, PRC) may confer robustness to naïve to primed pluripotency transition. We propose the notion of Molecular Versatility to regroup mechanisms by which molecules are repurposed to exert different, sometimes opposite, functions in close stem cell configurations.

Regulation, functions and transmission of bivalent chromatin during mammalian development

Cells differentiate and progress through development guided by a dynamic chromatin landscape that mediates gene expression programmes. During development, mammalian cells display a paradoxical chromatin state: histone modifications associated with gene activation (trimethylated histone H3 Lys4 (H3K4me3)) and with gene repression (trimethylated H3 Lys27 (H3K27me3)) co-occur at promoters of developmental genes. This bivalent chromatin modification state is thought to poise important regulatory genes for expression or repression during cell-lineage specification. In this Review, we discuss recent work that has expanded our understanding of the molecular basis of bivalent chromatin and its contributions to mammalian development. We describe the factors that establish bivalency, especially histone-lysine N-methyltransferase 2B (KMT2B) and Polycomb repressive complex 2 (PRC2), and consider evidence indicating that PRC1 shapes bivalency and may contribute to its transmission between generations. We posit that bivalency is a key feature of germline and embryonic stem cells, as well as other types of stem and progenitor cells. Finally, we discuss the relevance of bivalent chromtin to human development and cancer, and outline avenues of future research.

Mother–Fetus Immune Cross-Talk Coordinates “Extrinsic”/“Intrinsic” Embryo Gene Expression Noise and Growth Stability

Developmental instability (DI) is thought to be inversely related to a capacity of an organism to buffer its development against random genetic and environmental perturbations. DI is represented by a trait’s inter- and intra-individual variabilities. The inter-individual variability (inversely referred to as canalization) indicates the capability of organisms to reproduce a trait from individual to individual. The intra-individual variability reflects an organism’s capability to stabilize a trait internally under the same conditions, and, for symmetric traits, it is expressed as fluctuating asymmetry (FA). When representing a trait as a random variable conditioned on environmental fluctuations, it is clear that, in statistical terms, the DI partitions into “extrinsic” (canalization) and “intrinsic” (FA) components of a trait’s variance/noise. We established a simple statistical framework to dissect both parts of a symmetric trait variance/noise using a PCA (principal component analysis) projection of the left/right measurements on eigenvectors followed by GAMLSS (generalized additive models for location scale and shape) modeling of eigenvalues. The first eigenvalue represents “extrinsic” and the second—“intrinsic” DI components. We applied this framework to investigate the impact of mother–fetus major histocompatibility complex (MHC)-mediated immune cross-talk on gene expression noise and developmental stability. We showed that “intrinsic” gene noise for the entire transcriptional landscape could be estimated from a small subset of randomly selected genes. Using a diagnostic set of genes, we found that allogeneic MHC combinations tended to decrease “extrinsic” and “intrinsic” gene noise in C57BL/6J embryos developing in the surrogate NOD-SCID and BALB/c mothers. The “intrinsic” gene noise was negatively correlated with growth (embryonic mass) and the levels of placental growth factor (PLGF), but not vascular endothelial growth factor (VEGF). However, it was positively associated with phenotypic growth instability and noise in PLGF. In mammals, the mother–fetus MHC interaction plays a significant role in development, contributing to the fitness of the offspring. Our results demonstrate that a positive impact of distant MHC combinations on embryonic growth could be mediated by the reduction of “intrinsic” gene noise followed by the developmental stabilization of growth.

Polycomb Directed Cell Fate Decisions in Development and Cancer

The polycomb group (PcG) proteins are a subset of transcription regulators highly conserved throughout evolution. Their principal role is to epigenetically modify chromatin landscapes and control the expression of master transcriptional programs to determine cellular identity. The two mayor PcG protein complexes that have been identified in mammals to date are Polycomb Repressive Complex 1 (PRC1) and 2 (PRC2). These protein complexes selectively repress gene expression via the induction of covalent post-translational histone modifications, promoting chromatin structure stabilization. PRC2 catalyzes the histone H3 methylation at lysine 27 (H3K27me1/2/3), inducing heterochromatin structures. This activity is controlled by the formation of a multi-subunit complex, which includes enhancer of zeste (EZH2), embryonic ectoderm development protein (EED), and suppressor of zeste 12 (SUZ12). This review will summarize the latest insights into how PRC2 in mammalian cells regulates transcription to orchestrate the temporal and tissue-specific expression of genes to determine cell identity and cell-fate decisions. We will specifically describe how PRC2 dysregulation in different cell types can promote phenotypic plasticity and/or non-mutational epigenetic reprogramming, inducing the development of highly aggressive epithelial neuroendocrine carcinomas, including prostate, small cell lung, and Merkel cell cancer. With this, EZH2 has emerged as an important actionable therapeutic target in such cancers.

Inferring gene regulation from stochastic transcriptional variation across single cells at steady state

Regulatory relationships between transcription factors (TFs) and their target genes lie at the heart of cellular identity and function; however, uncovering these relationships is often labor-intensive and requires perturbations. Here, we propose a principled framework to systematically infer gene regulation for all TFs simultaneously in cells at steady state by leveraging the intrinsic variation in the transcriptional abundance across single cells. Through modeling and simulations, we characterize how transcriptional bursts of a TF gene are propagated to its target genes, including the expected ranges of time delay and magnitude of maximum covariation. We distinguish these temporal trends from the time-invariant covariation arising from cell states, and we delineate the experimental and technical requirements for leveraging these small but meaningful cofluctuations in the presence of measurement noise. While current technology does not yet allow adequate power for definitively detecting regulatory relationships for all TFs simultaneously in cells at steady state, we investigate a small-scale dataset to inform future experimental design. This study supports the potential value of mapping regulatory connections through stochastic variation, and it motivates further technological development to achieve its full potential.

The molecular principles of gene regulation by Polycomb repressive complexes

Precise control of gene expression is fundamental to cell function and development. Although ultimately gene expression relies on DNA-binding transcription factors to guide the activity of the transcription machinery to genes, it has also become clear that chromatin and histone post-translational modification have fundamental roles in gene regulation. Polycomb repressive complexes represent a paradigm of chromatin-based gene regulation in animals. The Polycomb repressive system comprises two central protein complexes, Polycomb repressive complex 1 (PRC1) and PRC2, which are essential for normal gene regulation and development. Our early understanding of Polycomb function relied on studies in simple model organisms, but more recently it has become apparent that this system has expanded and diverged in mammals. Detailed studies are now uncovering the molecular mechanisms that enable mammalian PRC1 and PRC2 to identify their target sites in the genome, communicate through feedback mechanisms to create Polycomb chromatin domains and control transcription to regulate gene expression. In this Review, we discuss and contextualize the emerging principles that define how this fascinating chromatin-based system regulates gene expression in mammals.

Cell-type specialization is encoded by specific chromatin topologies

The three-dimensional (3D) structure of chromatin is intrinsically associated with gene regulation and cell function1-3. Methods based on chromatin conformation capture have mapped chromatin structures in neuronal systems such as in vitro differentiated neurons, neurons isolated through fluorescence-activated cell sorting from cortical tissues pooled from different animals and from dissociated whole hippocampi4-6. However, changes in chromatin organization captured by imaging, such as the relocation of Bdnf away from the nuclear periphery after activation7, are invisible with such approaches8. Here we developed immunoGAM, an extension of genome architecture mapping (GAM)2,9, to map 3D chromatin topology genome-wide in specific brain cell types, without tissue disruption, from single animals. GAM is a ligation-free technology that maps genome topology by sequencing the DNA content from thin (about 220 nm) nuclear cryosections. Chromatin interactions are identified from the increased probability of co-segregation of contacting loci across a collection of nuclear slices. ImmunoGAM expands the scope of GAM to enable the selection of specific cell types using low cell numbers (approximately 1,000 cells) within a complex tissue and avoids tissue dissociation2,10. We report cell-type specialized 3D chromatin structures at multiple genomic scales that relate to patterns of gene expression. We discover extensive 'melting' of long genes when they are highly expressed and/or have high chromatin accessibility. The contacts most specific of neuron subtypes contain genes associated with specialized processes, such as addiction and synaptic plasticity, which harbour putative binding sites for neuronal transcription factors within accessible chromatin regions. Moreover, sensory receptor genes are preferentially found in heterochromatic compartments in brain cells, which establish strong contacts across tens of megabases. Our results demonstrate that highly specific chromatin conformations in brain cells are tightly related to gene regulation mechanisms and specialized functions.

Chromatin Network Analyses: Towards Structure-Function Relationships in Epigenomics

Recent technological advances have allowed us to map chromatin conformation and uncover the genome’s spatial organization of the genome inside the nucleus. These experiments have revealed the complexities of genome folding, characterized by the presence of loops and domains at different scales, which can change across development and in different cell types. There is strong evidence for a relationship between the topological properties of chromatin contacts and cellular phenotype. Chromatin can be represented as a network, in which genomic fragments are the nodes and connections represent experimentally observed spatial proximity of two genomically distant regions in a specific cell type or biological condition. With this approach we can consider a variety of chromatin features in association with the 3D structure, investigating how nuclear chromatin organization can be related to gene regulation, replication, malignancy, phenotypic variability and plasticity. We briefly review the results obtained on genome architecture through network theoretic approaches. As previously observed in protein-protein interaction networks and many types of non-biological networks, external conditions could shape network topology through a yet unidentified structure-function relationship. Similar to scientists studying the brain, we are confronted with a duality between a spatially embedded network of physical contacts, a related network of correlation in the dynamics of network nodes and, finally, an abstract definition of function of this network, related to phenotype. We summarise major developments in the study of networks in other fields, which we think can suggest a path towards better understanding how 3D genome configuration can impact biological function and adaptation to the environment.

Pioneer factors in development and cancer

Transcription factors (TFs) are essential mediators of epigenetic regulation and modifiers of penetrance. Studies from the past decades have revealed a sub-class of TF that is capable of remodeling closed chromatin states through targeting nucleosomal motifs. This pioneer factor (PF) class of chromatin remodeler is ATP independent in its roles in epigenetic initiation, with nucleosome-motif recognition and association with repressive chromatin regions. Increasing evidence suggests that the fundamental properties of PFs can be coopted in human cancers. We explore the role of PFs in the larger context of tissue-specific epigenetic regulation. Moreover, we highlight an emerging class of chimeric PF derived from translocation partners in human disease and PFs associated with rare tumors. In the age of site-directed genome editing and targeted protein degradation, increasing our understanding of PFs will provide access to next-generation therapy for human disease driven from altered transcriptional circuitry.

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.

Does transcriptional heterogeneity facilitate the development of genetic drug resistance?

Non-genetic forms of antimicrobial (drug) resistance can result from cell-to-cell variability that is not encoded in the genetic material. Data from recent studies also suggest that non-genetic mechanisms can facilitate the development of genetic drug resistance. We speculate on how the interplay between non-genetic and genetic mechanisms may affect microbial adaptation and evolution during drug treatment. We argue that cellular heterogeneity arising from fluctuations in gene expression, epigenetic modifications, as well as genetic changes contribute to drug resistance at different timescales, and that the interplay between these mechanisms enhance pathogen resistance. Accordingly, developing a better understanding of the role of non-genetic mechanisms in drug resistance and how they interact with genetic mechanisms will enhance our ability to combat antimicrobial resistance. Also see the video abstract here: https://youtu.be/aefGpdh-bgU.

Polycomb Repressive Complex 2 and KRYPTONITE regulate pathogen-induced programmed cell death in Arabidopsis

The Polycomb Repressive Complex 2 (PRC2) is well-known for its role in controlling developmental transitions by suppressing the premature expression of key developmental regulators. Previous work revealed that PRC2 also controls the onset of senescence, a form of developmental programmed cell death (PCD) in plants. Whether the induction of PCD in response to stress is similarly suppressed by the PRC2 remained largely unknown. In this study, we explored whether PCD triggered in response to immunity- and disease-promoting pathogen effectors is associated with changes in the distribution of the PRC2-mediated histone H3 lysine 27 trimethylation (H3K27me3) modification in Arabidopsis thaliana. We furthermore tested the distribution of the heterochromatic histone mark H3K9me2, which is established, to a large extent, by the H3K9 methyltransferase KRYPTONITE, and occupies chromatin regions generally not targeted by PRC2. We report that effector-induced PCD caused major changes in the distribution of both repressive epigenetic modifications and that both modifications have a regulatory role and impact on the onset of PCD during pathogen infection. Our work highlights that the transition to pathogen-induced PCD is epigenetically controlled, revealing striking similarities to developmental PCD.

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.

Quantifying the Stability of Coupled Genetic and Epigenetic Switches With Variational Methods

The Waddington landscape provides an intuitive metaphor to view development as a ball rolling down the hill, with distinct phenotypes as basins and differentiation pathways as valleys. Since, at a molecular level, cell differentiation arises from interactions among the genes, a mathematical definition for the Waddington landscape can, in principle, be obtained by studying the gene regulatory networks. For eukaryotes, gene regulation is inextricably and intimately linked to histone modifications. However, the impact of such modifications on both landscape topography and stability of attractor states is not fully understood. In this work, we introduced a minimal kinetic model for gene regulation that combines the impact of both histone modifications and transcription factors. We further developed an approximation scheme based on variational principles to solve the corresponding master equation in a second quantized framework. By analyzing the steady-state solutions at various parameter regimes, we found that histone modification kinetics can significantly alter the behavior of a genetic network, resulting in qualitative changes in gene expression profiles. The emerging epigenetic landscape captures the delicate interplay between transcription factors and histone modifications in driving cell-fate decisions.

Identifying chromatin features that regulate gene expression distribution

Gene expression variability, differences in the number of mRNA per cell across a population of cells, is ubiquitous across diverse organisms with broad impacts on cellular phenotypes. The role of chromatin in regulating average gene expression has been extensively studied. However, what aspects of the chromatin contribute to gene expression variability is still underexplored. Here we addressed this problem by leveraging chromatin diversity and using a systematic investigation of randomly integrated expression reporters to identify what aspects of chromatin microenvironment contribute to gene expression variability. Using DNA barcoding and split-pool decoding, we created a large library of isogenic reporter clones and identified reporter integration sites in a massive and parallel manner. By mapping our measurements of reporter expression at different genomic loci with multiple epigenetic profiles including the enrichment of transcription factors and the distance to different chromatin states, we identified new factors that impact the regulation of gene expression distributions.

Microbial metabolic noise

From the time a cell was first placed under the microscope, it became apparent that identifying two clonal cells that "look" identical is extremely challenging. Since then, cell-to-cell differences in shape, size, and protein content have been carefully examined, informing us of the ultimate limits that hinder two cells from occupying an identical phenotypic state. Here, we present recent experimental and computational evidence that similar limits emerge also in cellular metabolism. These limits pertain to stochastic metabolic dynamics and, thus, cell-to-cell metabolic variability, including the resulting adapting benefits. We review these phenomena with a focus on microbial metabolism and conclude with a brief outlook on the potential relationship between metabolic noise and adaptive evolution. This article is categorized under: Metabolic Diseases > Computational Models Metabolic Diseases > Biomedical Engineering.

Identification of Genes Involved in the Differentiation of R7y and R7p Photoreceptor Cells in Drosophila

The R7 and R8 photoreceptor cells of the Drosophila compound eye mediate color vision. Throughout the majority of the eye, these cells occur in two principal types of ommatidia. Approximately 35% of ommatidia are of the pale type and express Rh3 in R7 cells and Rh5 in R8 cells. The remaining 65% are of the yellow type and express Rh4 in R7 cells and Rh6 in R8 cells. The specification of an R8 cell in a pale or yellow ommatidium depends on the fate of the adjacent R7 cell. However, pale and yellow R7 cells are specified by a stochastic process that requires the genes spineless, tango and klumpfuss. To identify additional genes involved in this process we performed genetic screens using a collection of 480 P{EP} transposon insertion strains. We identified genes in gain of function and loss of function screens that significantly altered the percentage of Rh3 expressing R7 cells (Rh3%) from wild-type. 36 strains resulted in altered Rh3% in the gain of function screen where the P{EP} insertion strains were crossed to a sevEP-GAL4 driver line. 53 strains resulted in altered Rh3% in the heterozygous loss of function screen. 4 strains showed effects that differed between the two screens, suggesting that the effect found in the gain of function screen was either larger than, or potentially masked by, the P{EP} insertion alone. Analyses of homozygotes validated many of the candidates identified. These results suggest that R7 cell fate specification is sensitive to perturbations in mRNA transcription, splicing and localization, growth inhibition, post-translational protein modification, cleavage and secretion, hedgehog signaling, ubiquitin protease activity, GTPase activation, actin and cytoskeletal regulation, and Ser/Thr kinase activity, among other diverse signaling and cell biological processes.

Functions of Polycomb Proteins on Active Targets

Chromatin regulators of the Polycomb group of genes are well-known by their activities as transcriptional repressors. Characteristically, their presence at genomic sites occurs with specific histone modifications and sometimes high-order chromatin structures correlated with silencing of genes involved in cell differentiation. However, evidence gathered in recent years, on flies and mammals, shows that in addition to these sites, Polycomb products bind to a large number of active regulatory regions. Occupied sites include promoters and also intergenic regions, containing enhancers and super-enhancers. Contrasting with occupancies at repressed targets, characteristic histone modifications are low or undetectable. Functions on active targets are dual, restraining gene expression at some targets while promoting activity at others. Our aim here is to summarize the evidence available and discuss the convenience of broadening the scope of research to include Polycomb functions on active targets.

Mechanistic models of signaling pathways deconvolute the glioblastoma single-cell functional landscape

Single-cell RNA sequencing is revealing an unexpectedly large degree of heterogeneity in gene expression levels across cell populations. However, little is known on the functional consequences of this heterogeneity and the contribution of individual cell fate decisions to the collective behavior of the tissues these cells are part of. Here, we use mechanistic modeling of signaling circuits, which reveals a complex functional landscape at single-cell level. Different clusters of neoplastic glioblastoma cells have been defined according to their differences in signaling circuit activity profiles triggering specific cancer hallmarks, which suggest different functional strategies with distinct degrees of aggressiveness. Moreover, mechanistic modeling of effects of targeted drug inhibitions at single-cell level revealed, how in some cells, the substitution of VEGFA, the target of bevacizumab, by other expressed proteins, like PDGFD, KITLG and FGF2, keeps the VEGF pathway active, insensitive to the VEGFA inhibition by the drug. Here, we describe for the first time mechanisms that individual cells use to avoid the effect of a targeted therapy, providing an explanation for the innate resistance to the treatment displayed by some cells. Our results suggest that mechanistic modeling could become an important asset for the definition of personalized therapeutic interventions.

Probing Mechanisms of Transcription Elongation Through Cell-to-Cell Variability of RNA Polymerase

The process of transcription initiation and elongation are primary points of control in the regulation of gene expression. Although biochemical studies have uncovered the mechanisms involved in controlling transcription at each step, how these mechanisms manifest in vivo at the level of individual genes is still unclear. Recent experimental advances have enabled single-cell measurements of RNA polymerase (RNAP) molecules engaged in the process of transcribing a gene of interest. In this article, we use Gillespie simulations to show that measurements of cell-to-cell variability of RNAP numbers and interpolymerase distances can reveal the prevailing mode of regulation of a given gene. Mechanisms of regulation at each step, from initiation to elongation dynamics, produce qualitatively distinct signatures, which can further be used to discern between them. Most intriguingly, depending on the initiation kinetics, stochastic elongation can either enhance or suppress cell-to-cell variability at the RNAP level. To demonstrate the value of this framework, we analyze RNAP number distribution data for ribosomal genes in Saccharomyces cerevisiae from three previously published studies and show that this approach provides crucial mechanistic insights into the transcriptional regulation of these genes.

Epigenetic control in Kaposi sarcoma-associated herpesvirus infection and associated disease

Kaposi sarcoma-associated herpesvirus (KSHV) is the etiologic agent of several malignancies of endothelial and B-cell origin. The fact that latently infected tumor cells in these malignancies do not express classical viral oncogenes suggests that pathogenesis of KSHV-associated disease results from multistep processes that, in addition to constitutive viral gene expression, may require accumulation of cellular alterations. Heritable changes of the epigenome have emerged as an important co-factor that contributes to the pathogenesis of many non-viral cancers. Since KSHV encodes a number of factors that directly or indirectly manipulate host cell chromatin, it is an intriguing possibility that epigenetic reprogramming also contributes to the pathogenesis of KSHV-associated tumors. The fact that heritable histone modifications have also been shown to regulate viral gene expression programs in KSHV-infected tumor cells underlines the importance of epigenetic control during latency and tumorigenesis. We here review what is presently known about the role of epigenetic regulation of viral and host chromatin in KSHV infection and discuss how viral manipulation of these processes may contribute to the development of KSHV-associated disease.

Fighting Against Promoter DNA Hyper-Methylation: Protective Histone Modification Profiles of Stress-Resistant Intestinal Stem Cells

Aberrant DNA methylation in stem cells is a hallmark of aging and tumor development. Recently, we have suggested that promoter DNA hyper-methylation originates in DNA repair and that even successful DNA repair might confer this kind of epigenetic long-term change. Here, we ask for interrelations between promoter DNA methylation and histone modification changes observed in the intestine weeks after irradiation and/or following Msh2 loss. We focus on H3K4me3 recruitment to the promoter of H3K27me3 target genes. By RNA- and histone ChIP-sequencing, we demonstrate that this recruitment occurs without changes of the average gene transcription and does not involve H3K9me3. Applying a mathematical model of epigenetic regulation of transcription, we show that the recruitment can be explained by stronger DNA binding of H3K4me3 and H3K27me3 histone methyl-transferases as a consequence of lower DNA methylation. This scenario implicates stable transcription despite of H3K4me3 recruitment, in agreement with our RNA-seq data. Following several kinds of stress, including moderate irradiation, stress-sensitive intestinal stem cell (ISCs) are known to become replaced by more resistant populations. Our simulation results suggest that the stress-resistant ISCs are largely protected against promoter hyper-methylation of H3K27me3 target genes.

Bivalent promoter hypermethylation in cancer is linked to the H327me3/H3K4me3 ratio in embryonic stem cells

BACKGROUND

Thousands of mammalian promoters are defined by co-enrichment of the histone tail modifications H3K27me3 (repressive) and H3K4me3 (activating) and are thus termed bivalent. It was previously observed that bivalent genes in human ES cells (hESC) are frequent targets for hypermethylation in human cancers, and depletion of DNA methylation in mouse embryonic stem cells has a marked impact on H3K27me3 distribution at bivalent promoters. However, only a fraction of bivalent genes in stem cells are targets of hypermethylation in cancer, and it is currently unclear whether all bivalent promoters are equally sensitive to DNA hypomethylation and whether H3K4me3 levels play a role in the interplay between DNA methylation and H3K27me3.

RESULTS

We report the sub-classification of bivalent promoters into two groups-promoters with a high H3K27me3:H3K4me3 (hiBiv) ratio or promoters with a low H3K27me3:H3K4me3 ratio (loBiv). HiBiv are enriched in canonical Polycomb components, show a higher degree of local intrachromosomal contacts and are highly sensitive to DNA hypomethylation in terms of H3K27me3 depletion from broad Polycomb domains. In contrast, loBiv promoters are enriched in non-canonical Polycomb components, show lower intrachromosomal contacts and are less sensitive to DNA hypomethylation at the same genomic resolution. Multiple systems reveal that hiBiv promoters are more depleted of Polycomb complexes than loBiv promoters following a reduction in DNA methylation, and we demonstrate that H3K27me3 re-accumulates at promoters when DNA methylation is restored. In human cancer, we show that hiBiv promoters lose H3K27me3 and are more susceptible to DNA hypermethylation than loBiv promoters.

CONCLUSION

We conclude that bivalency as a general term to describe mammalian promoters is an over-simplification and our sub-classification has revealed novel insights into the interplay between the largely antagonistic presence of DNA methylation and Polycomb systems at bivalent promoters. This approach redefines molecular pathologies underlying disease in which global DNA methylation is aberrant or where Polycomb mutations are present.

Genomic organization of Polycomb Response Elements and its functional implication in Drosophila and other insects

The epigenetic memory is an essential aspect of multicellular organisms to maintain several cell types and their gene expression pattern. This complex process uses a number of protein factors and specific DNA elements within the developmental cues to achieve this. The protein factors involved in the process are the Polycomb group (PcG) members, and, accordingly, the DNA sequences that interact with these proteins are called Polycomb Response Elements (PREs). Since the PcG proteins are highly conserved among higher eukaryotes, including insects, and function at thousands of sites in the genomes, it is expected that PREs mayalso be present across the genome.However, the studies on PREs in insect species, other thanDrosophila, is currently lacking.We took a bioinformatics approach to develop an inclusive PRE prediction tool, 'PRE Mapper', to address this need. By applying this tool on the Drosophila melanogaster genome, we predicted greater than 20,000 PREs.When comparedwith the available PRE prediction methods, this tool shows far better performance by correctly identifying the in vivo binding sites of PcG proteins, identified by genome-scale ChIP experiments. Further analysis of the predicted PREs shows their cohabitation with chromatin domain boundary elements at several places in the Drosophila genome, possibly defining a composite epigenetic module.We analysed 10 insect genomes in this context and find several conserved features in PREs across the insect species with some variations in their occurrence frequency. These analyses leading to the identification of PREin insect genomes contribute to our understanding of epigenetic mechanisms in these organisms.

Regulation of Latency in the Human T Cell Leukemia Virus, HTLV-1

The human T cell leukemia virus persists in vivo in 10³ to 10⁶ clones of T lymphocytes that appear to survive for the lifetime of the host. The plus strand of the provirus is typically transcriptionally silent in freshly isolated lymphocytes, but the strong, persistently activated cytotoxic T lymphocyte (CTL) response to the viral antigens indicates that the virus is not constantly latent in vivo. There is now evidence that the plus strand is transcribed in intense intermittent bursts that are triggered by cellular stress, modulated by hypoxia and glycolysis, and inhibited by polycomb repressive complex 1 (PRC1). The minus-strand gene hbz is transcribed at a lower, more constant level but is silent in a proportion of infected cells at a given time. Viral genes in the sense and antisense strands of the provirus play different respective roles in latency and de novo infection: Expression of the plus-strand gene tax is essential for de novo infection, whereas hbz appears to facilitate survival of the infected T cell clone in vivo.

Challenges in measuring and understanding biological noise

Biochemical reactions are intrinsically stochastic, leading to variation in the production of mRNAs and proteins within cells. In the scientific literature, this source of variation is typically referred to as 'noise'. The observed variability in molecular phenotypes arises from a combination of processes that amplify and attenuate noise. Our ability to quantify cell-to-cell variability in numerous biological contexts has been revolutionized by recent advances in single-cell technology, from imaging approaches through to 'omics' strategies. However, defining, accurately measuring and disentangling the stochastic and deterministic components of cell-to-cell variability is challenging. In this Review, we discuss the sources, impact and function of molecular phenotypic variability and highlight future directions to understand its role.

Polycomb Assemblies Multitask to Regulate Transcription

The Polycomb system is made of an evolutionary ancient group of proteins, present throughout plants and animals. Known initially from developmental studies with the fly Drosophila melanogaster, they were associated with stable sustainment of gene repression and maintenance of cell identity. Acting as multiprotein assemblies with an ability to modify chromatin, through chemical additions to histones and organization of topological domains, they have been involved subsequently in control of developmental transitions and in cell homeostasis. Recent work has unveiled an association of Polycomb components with transcriptionally active loci and the promotion of gene expression, in clear contrast with conventional recognition as repressors. Focusing on mammalian models, I review here advances concerning roles in transcriptional control. Among new findings highlighted is the regulation of their catalytic properties, recruiting to targets, and activities in chromatin organization and compartmentalization. The need for a more integrated approach to the study of the Polycomb system, given its fundamental complexity and its adaptation to cell context, is discussed.

Simulating multiple faceted variability in single cell RNA sequencing

The abundance of new computational methods for processing and interpreting transcriptomes at a single cell level raises the need for in silico platforms for evaluation and validation. Here, we present SymSim, a simulator that explicitly models the processes that give rise to data observed in single cell RNA-Seq experiments. The components of the SymSim pipeline pertain to the three primary sources of variation in single cell RNA-Seq data: noise intrinsic to the process of transcription, extrinsic variation indicative of different cell states (both discrete and continuous), and technical variation due to low sensitivity and measurement noise and bias. We demonstrate how SymSim can be used for benchmarking methods for clustering, differential expression and trajectory inference, and for examining the effects of various parameters on their performance. We also show how SymSim can be used to evaluate the number of cells required to detect a rare population under various scenarios.

Simulated single cell RNA sequencing data is useful for method development and comparison. Here, the authors developed SymSim, a simulator that explicitly models the main factors of variation in single cell data.

Theoretical analysis of Polycomb-Trithorax systems predicts that poised chromatin is bistable and not bivalent

Polycomb (PcG) and Trithorax (TrxG) group proteins give stable epigenetic memory of silent and active gene expression states, but also allow poised states in pluripotent cells. Here we systematically address the relationship between poised, active and silent chromatin, by integrating 73 publications on PcG/TrxG biochemistry into a mathematical model comprising 144 nucleosome modification states and 8 enzymatic reactions. Our model predicts that poised chromatin is bistable and not bivalent. Bivalent chromatin, containing opposing active and silent modifications, is present as an unstable background population in all system states, and different subtypes co-occur with active and silent chromatin. In contrast, bistability, in which the system switches frequently between stable active and silent states, occurs under a wide range of conditions at the transition between monostable active and silent system states. By proposing that bistability and not bivalency is associated with poised chromatin, this work has implications for understanding the molecular nature of pluripotency.

Polycomb and Trithorax group proteins regulate silent and active gene expression states, but also allow poised states in pluripotent cells. Here the authors present a mathematical model that integrates data on Polycomb/ Trithorax biochemistry into a single coherent framework which predicts that poised chromatin is not bivalent as previously proposed, but is bistable, meaning that the system switches frequently between stable active and silent states.

Enabling cell-type-specific behavioral epigenetics in Drosophila: a modified high-yield INTACT method reveals the impact of social environment on the epigenetic landscape in dopaminergic neurons

BACKGROUND

Epigenetic mechanisms play fundamental roles in brain function and behavior and stressors such as social isolation can alter animal behavior via epigenetic mechanisms. However, due to cellular heterogeneity, identifying cell-type-specific epigenetic changes in the brain is challenging. Here, we report the first use of a modified isolation of nuclei tagged in specific cell type (INTACT) method in behavioral epigenetics of Drosophila melanogaster, a method we call mini-INTACT.

RESULTS

Using ChIP-seq on mini-INTACT purified dopaminergic nuclei, we identified epigenetic signatures in socially isolated and socially enriched Drosophila males. Social experience altered the epigenetic landscape in clusters of genes involved in transcription and neural function. Some of these alterations could be predicted by expression changes of four transcription factors and the prevalence of their binding sites in several clusters. These transcription factors were previously identified as activity-regulated genes, and their knockdown in dopaminergic neurons reduced the effects of social experience on sleep.

CONCLUSIONS

Our work enables the use of Drosophila as a model for cell-type-specific behavioral epigenetics and establishes that social environment shifts the epigenetic landscape in dopaminergic neurons. Four activity-related transcription factors are required in dopaminergic neurons for the effects of social environment on sleep.

Chromatin folding and nuclear architecture: PRC1 function in 3D

Embryonic development requires the intricate balance between the expansion and specialisation of defined cell types in time and space. The gene expression programmes that underpin this balance are regulated, in part, by modulating the chemical and structural state of chromatin. Polycomb repressive complexes (PRCs), a family of essential developmental regulators, operate at this level to stabilise or perpetuate a repressed but transcriptionally poised chromatin configuration. This dynamic state is required to control the timely initiation of productive gene transcription during embryonic development. The two major PRCs cooperate to target the genome, but it is PRC1 that appears to be the primary effector that controls gene expression. In this review I will discuss recent findings relating to how PRC1 alters chromatin accessibility, folding and global 3D nuclear organisation to control gene transcription.

Buffering and Amplifying Transcriptional Noise During Cell Fate Specification

The molecular processes that drive gene transcription are inherently noisy. This noise often manifests in the form of transcriptional bursts, producing fluctuations in gene activity over time. During cell fate specification, this noise is often buffered to ensure reproducible developmental outcomes. However, sometimes noise is utilized as a “bet-hedging” mechanism to diversify functional roles across a population of cells. Studies of bacteria, yeast, and cultured cells have provided insights into the nature and roles of noise in transcription, yet we are only beginning to understand the mechanisms by which noise influences the development of multicellular organisms. Here we discuss the sources of transcriptional noise and the mechanisms that either buffer noise to drive reproducible fate choices or amplify noise to randomly specify fates.

CpG island composition differences are a source of gene expression noise indicative of promoter responsiveness

BACKGROUND

Population phenotypic variation can arise from genetic differences between individuals, or from cellular heterogeneity in an isogenic group of cells or organisms. The emergence of gene expression differences between genetically identical cells is referred to as gene expression noise, the sources of which are not well understood.

RESULTS

In this work, by studying gene expression noise between multiple cell lineages and mammalian species, we find consistent evidence of a role for CpG islands as sources of gene expression noise. Variation in noise among CpG island promoters can be partially attributed to differences in island size, in which short islands have noisier gene expression. Building on these findings, we investigate the potential for short CpG islands to act as fast response elements to environmental stimuli. Specifically, we find that these islands are enriched amongst primary response genes in SWI/SNF-independent stimuli, suggesting that expression noise is an indicator of promoter responsiveness.

CONCLUSIONS

Thus, through the integration of single-cell RNA expression profiling, chromatin landscape and temporal gene expression dynamics, we have uncovered a role for short CpG island promoters as fast response elements.

Epigenetic and Transcriptional Variability Shape Phenotypic Plasticity

Epigenetic and transcriptional variability contribute to the vast diversity of cellular and organismal phenotypes and are key in human health and disease. In this review, we describe different types, sources, and determinants of epigenetic and transcriptional variability, enabling cells and organisms to adapt and evolve to a changing environment. We highlight the latest research and hypotheses on how chromatin structure and the epigenome influence gene expression variability. Further, we provide an overview of challenges in the analysis of biological variability. An improved understanding of the molecular mechanisms underlying epigenetic and transcriptional variability, at both the intra- and inter-individual level, provides great opportunity for disease prevention, better therapeutic approaches, and personalized medicine.

RNA polymerase II primes Polycomb-repressed developmental genes throughout terminal neuronal differentiation

Polycomb repression in mouse embryonic stem cells (ESCs) is tightly associated with promoter co‐occupancy of RNA polymerase II (RNAPII) which is thought to prime genes for activation during early development. However, it is unknown whether RNAPII poising is a general feature of Polycomb repression, or is lost during differentiation. Here, we map the genome‐wide occupancy of RNAPII and Polycomb from pluripotent ESCs to non‐dividing functional dopaminergic neurons. We find that poised RNAPII complexes are ubiquitously present at Polycomb‐repressed genes at all stages of neuronal differentiation. We observe both loss and acquisition of RNAPII and Polycomb at specific groups of genes reflecting their silencing or activation. Strikingly, RNAPII remains poised at transcription factor genes which are silenced in neurons through Polycomb repression, and have major roles in specifying other, non‐neuronal lineages. We conclude that RNAPII poising is intrinsically associated with Polycomb repression throughout differentiation. Our work suggests that the tight interplay between RNAPII poising and Polycomb repression not only instructs promoter state transitions, but also may enable promoter plasticity in differentiated cells.

A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications

RNA sequencing (RNA-seq) is a genomic approach for the detection and quantitative analysis of messenger RNA molecules in a biological sample and is useful for studying cellular responses. RNA-seq has fueled much discovery and innovation in medicine over recent years. For practical reasons, the technique is usually conducted on samples comprising thousands to millions of cells. However, this has hindered direct assessment of the fundamental unit of biology-the cell. Since the first single-cell RNA-sequencing (scRNA-seq) study was published in 2009, many more have been conducted, mostly by specialist laboratories with unique skills in wet-lab single-cell genomics, bioinformatics, and computation. However, with the increasing commercial availability of scRNA-seq platforms, and the rapid ongoing maturation of bioinformatics approaches, a point has been reached where any biomedical researcher or clinician can use scRNA-seq to make exciting discoveries. In this review, we present a practical guide to help researchers design their first scRNA-seq studies, including introductory information on experimental hardware, protocol choice, quality control, data analysis and biological interpretation.

Single-Cell Landscape of Transcriptional Heterogeneity and Cell Fate Decisions during Mouse Early Gastrulation

The mouse inner cell mass (ICM) segregates into the epiblast and primitive endoderm (PrE) lineages coincident with implantation of the embryo. The epiblast subsequently undergoes considerable expansion of cell numbers prior to gastrulation. To investigate underlying regulatory principles, we performed systematic single-cell RNA sequencing (seq) of conceptuses from E3.5 to E6.5. The epiblast shows reactivation and subsequent inactivation of the X chromosome, with Zfp57 expression associated with reactivation and inactivation together with other candidate regulators. At E6.5, the transition from epiblast to primitive streak is linked with decreased expression of polycomb subunits, suggesting a key regulatory role. Notably, our analyses suggest elevated transcriptional noise at E3.5 and within the non-committed epiblast at E6.5, coinciding with exit from pluripotency. By contrast, E6.5 primitive streak cells became highly synchronized and exhibit a shortened G1 cell-cycle phase, consistent with accelerated proliferation. Our study systematically charts transcriptional noise and uncovers molecular processes associated with early lineage decisions.

Computational approaches for interpreting scRNA-seq data

The recent developments in high‐throughput single‐cell RNA sequencing technology (scRNA‐seq) have enabled the generation of vast amounts of transcriptomic data at cellular resolution. With these advances come new modes of data analysis, building on high‐dimensional data mining techniques. Here, we consider biological questions for which scRNA‐seq data is used, both at a cell and gene level, and describe tools available for these types of analyses. This is an exciting and rapidly evolving field, where clustering, pseudotime inference, branching inference and gene‐level analyses are particularly informative areas of computational analysis.