Buffering and Amplifying Transcriptional Noise During Cell Fate Specification

Multifunctional histone variants in genome function

Histones are integral components of eukaryotic chromatin that have a pivotal role in the organization and function of the genome. The dynamic regulation of chromatin involves the incorporation of histone variants, which can dramatically alter its structural and functional properties. Contrary to an earlier view that limited individual histone variants to specific genomic functions, new insights have revealed that histone variants exert multifaceted roles involving all aspects of genome function, from governing patterns of gene expression at precise genomic loci to participating in genome replication, repair and maintenance. This conceptual change has led to a new understanding of the intricate interplay between chromatin and DNA-dependent processes and how this connection translates into normal and abnormal cellular functions.

Histone deacetylase Hos2 regulates protein expression noise by potentially modulating the protein translation machinery

Non-genetic variations derived from expression noise at transcript or protein levels can result in cell-to-cell heterogeneity within an isogenic population. Although cells have developed strategies to reduce noise in some cellular functions, this heterogeneity can also facilitate varying levels of regulation and provide evolutionary benefits in specific environments. Despite several general characteristics of cellular noise having been revealed, the detailed molecular pathways underlying noise regulation remain elusive. Here, we established a dual-fluorescent reporter system in Saccharomyces cerevisiae and performed experimental evolution to search for mutations that increase expression noise. By analyzing evolved cells using bulk segregant analysis coupled with whole-genome sequencing, we identified the histone deacetylase Hos2 as a negative noise regulator. A hos2 mutant down-regulated multiple ribosomal protein genes and exhibited partially compromised protein translation, indicating that Hos2 may regulate protein expression noise by modulating the translation machinery. Treating cells with translation inhibitors or introducing mutations into several Hos2-regulated ribosomal protein genes-RPS9A, RPS28B and RPL42A-enhanced protein expression noise. Our study provides an effective strategy for identifying noise regulators and also sheds light on how cells regulate non-genetic variation through protein translation.

How Transcription Factor Clusters Shape the Transcriptional Landscape

In eukaryotic cells, gene transcription typically occurs in discrete periods of promoter activity, interspersed with intervals of inactivity. This pattern deviates from simple stochastic events and warrants a closer examination of the molecular interactions that activate the promoter. Recent studies have identified transcription factor (TF) clusters as key precursors to transcriptional bursting. Often, these TF clusters form at chromatin segments that are physically distant from the promoter, making changes in chromatin conformation crucial for promoter-TF cluster interactions. In this review, I explore the formation and constituents of TF clusters, examining how the dynamic interplay between chromatin architecture and TF clustering influences transcriptional bursting. Additionally, I discuss techniques for visualizing TF clusters and provide an outlook on understanding the remaining gaps in this field.

Living in a noisy world-origins of gene expression noise and its impact on cellular decision-making

The expression level of a gene can vary between genetically identical cells under the same environmental condition-a phenomenon referred to as gene expression noise. Several studies have now elucidated a central role of transcription factors in the generation of expression noise. Transcription factors, as the key components of gene regulatory networks, drive many important cellular decisions in response to cellular and environmental signals. Therefore, a very relevant question is how expression noise impacts gene regulation and influences cellular decision-making. In this Review, we summarize the current understanding of the molecular origins of expression noise, highlighting the role of transcription factors in this process, and discuss the ways in which noise can influence cellular decision-making. As advances in single-cell technologies open new avenues for studying expression noise as well as gene regulatory circuits, a better understanding of the influence of noise on cellular decisions will have important implications for many biological processes.

Analysis of developmental gene expression using smFISH and in silico staging of C. elegans embryos

Regulation of transcription during embryogenesis is key to development and differentiation. To study transcript expression throughout Caenorhabditis elegans embryogenesis at single-molecule resolution, we developed a high-throughput single-molecule fluorescence in situ hybridization (smFISH) method that relies on computational methods to developmentally stage embryos and quantify individual mRNA molecules in single embryos. We applied our system to sdc-2, a zygotically transcribed gene essential for hermaphrodite development and dosage compensation. We found that sdc-2 is rapidly activated during early embryogenesis by increasing both the number of mRNAs produced per transcription site and the frequency of sites engaged in transcription. Knockdown of sdc-2 and dpy-27, a subunit of the dosage compensation complex (DCC), increased the number of active transcription sites for the X chromosomal gene dpy-23 but not the autosomal gene mdh-1, suggesting that the DCC reduces the frequency of dpy-23 transcription. The temporal resolution from in silico staging of embryos showed that the deletion of a single DCC recruitment element near the dpy-23 gene causes higher dpy-23 mRNA expression after the start of dosage compensation, which could not be resolved using mRNAseq from mixed-stage embryos. In summary, we have established a computational approach to quantify temporal regulation of transcription throughout C. elegans embryogenesis and demonstrated its potential to provide new insights into developmental gene regulation.

Cis-regulatory control of transcriptional timing and noise in response to estrogen

Cis-regulatory elements control transcription levels, temporal dynamics, and cell-cell variation or transcriptional noise. However, the combination of regulatory features that control these different attributes is not fully understood. Here, we used single-cell RNA-seq during an estrogen treatment time course and machine learning to identify predictors of expression timing and noise. We found that genes with multiple active enhancers exhibit faster temporal responses. We verified this finding by showing that manipulation of enhancer activity changes the temporal response of estrogen target genes. Analysis of transcriptional noise uncovered a relationship between promoter and enhancer activity, with active promoters associated with low noise and active enhancers linked to high noise. Finally, we observed that co-expression across single cells is an emergent property associated with chromatin looping, timing, and noise. Overall, our results indicate a fundamental tradeoff between a gene's ability to quickly respond to incoming signals and maintain low variation across cells.

Transcriptional priming and chromatin regulation during stochastic cell fate specification

Stochastic cell fate specification, in which a cell chooses between two or more fates with a set probability, diversifies cell subtypes in development. Although this is a vital process across species, a common mechanism for these cell fate decisions remains elusive. This review examines two well-characterized stochastic cell fate decisions to identify commonalities between their developmental programmes. In the fly eye, two subtypes of R7 photoreceptors are specified by the stochastic ON/OFF expression of a transcription factor, spineless. In the mouse olfactory system, olfactory sensory neurons (OSNs) randomly select to express one copy of an olfactory receptor (OR) gene out of a pool of 2800 alleles. Despite the differences in these sensory systems, both stochastic fate choices rely on the dynamic interplay between transcriptional priming, chromatin regulation and terminal gene expression. The coupling of transcription and chromatin modifications primes gene loci in undifferentiated neurons, enabling later expression during terminal differentiation. Here, we compare these mechanisms, examine broader implications for gene regulation during development and posit key challenges moving forward. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

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'.

Cis-regulatory control of transcriptional timing and noise in response to estrogen

Cis-regulatory elements control transcription levels, temporal dynamics, and cell-cell variation or transcriptional noise. However, the combination of regulatory features that control these different attributes is not fully understood. Here, we used single cell RNA-seq during an estrogen treatment time course and machine learning to identify predictors of expression timing and noise. We find that genes with multiple active enhancers exhibit faster temporal responses. We verified this finding by showing that manipulation of enhancer activity changes the temporal response of estrogen target genes. Analysis of transcriptional noise uncovered a relationship between promoter and enhancer activity, with active promoters associated with low noise and active enhancers linked to high noise. Finally, we observed that co-expression across single cells is an emergent property associated with chromatin looping, timing, and noise. Overall, our results indicate a fundamental tradeoff between a gene's ability to quickly respond to incoming signals and maintain low variation across cells.

Broad H3K4me3 domains: Maintaining cellular identity and their implication in super-enhancer hijacking

The human and mouse genomes are complex from a genomic standpoint. Each cell has the same genomic sequence, yet a wide array of cell types exists due to the presence of a plethora of regulatory elements in the non-coding genome. Recent advances in epigenomic profiling have uncovered non-coding gene proximal promoters and distal enhancers of transcription genome-wide. Extension of promoter-associated H3K4me3 histone mark across the gene body, known as a broad H3K4me3 domain (H3K4me3-BD), is a signature of constitutive expression of cell-type-specific regulation and of tumour suppressor genes in healthy cells. Recently, it has been discovered that the presence of H3K4me3-BDs over oncogenes is a cancer-specific feature associated with their dysregulated gene expression and tumourigenesis. Moreover, it has been shown that the hijacking of clusters of enhancers, known as super-enhancers (SE), by proto-oncogenes results in the presence of H3K4me3-BDs over the gene body. Therefore, H3K4me3-BDs and SE crosstalk in healthy and cancer cells therefore represents an important mechanism to identify future treatments for patients with SE driven cancers.

Transcriptional Stochasticity as a Key Aspect of HIV-1 Latency

This review summarizes current advances in the role of transcriptional stochasticity in HIV-1 latency, which were possible in a large part due to the development of single-cell approaches. HIV-1 transcription proceeds in bursts of RNA production, which stem from the stochastic switching of the viral promoter between ON and OFF states. This switching is caused by random binding dynamics of transcription factors and nucleosomes to the viral promoter and occurs at several time scales from minutes to hours. Transcriptional bursts are mainly controlled by the core transcription factors TBP, SP1 and NF-κb, the chromatin status of the viral promoter and RNA polymerase II pausing. In particular, spontaneous variability in the promoter chromatin creates heterogeneity in the response to activators such as TNF-α, which is then amplified by the Tat feedback loop to generate high and low viral transcriptional states. This phenomenon is likely at the basis of the partial and stochastic response of latent T cells from HIV-1 patients to latency-reversing agents, which is a barrier for the development of shock-and-kill strategies of viral eradication. A detailed understanding of the transcriptional stochasticity of HIV-1 and the possibility to precisely model this phenomenon will be important assets to develop more effective therapeutic strategies.

The epithelial-mesenchymal plasticity landscape: principles of design and mechanisms of regulation

Epithelial-mesenchymal plasticity (EMP) enables cells to interconvert between several states across the epithelial-mesenchymal landscape, thereby acquiring hybrid epithelial/mesenchymal phenotypic features. This plasticity is crucial for embryonic development and wound healing, but also underlies the acquisition of several malignant traits during cancer progression. Recent research using systems biology and single-cell profiling methods has provided novel insights into the main forces that shape EMP, which include the microenvironment, lineage specification and cell identity, and the genome. Additionally, key roles have emerged for hysteresis (cell memory) and cellular noise, which can drive stochastic transitions between cell states. Here, we review these forces and the distinct but interwoven layers of regulatory control that stabilize EMP states or facilitate epithelial-mesenchymal transitions (EMTs) and discuss the therapeutic potential of manipulating the EMP landscape.

Using Constrained-Disorder Principle-Based Systems to Improve the Performance of Digital Twins in Biological Systems

Digital twins are computer programs that use real-world data to create simulations that predict the performance of processes, products, and systems. Digital twins may integrate artificial intelligence to improve their outputs. Models for dealing with uncertainties and noise are used to improve the accuracy of digital twins. Most currently used systems aim to reduce noise to improve their outputs. Nevertheless, biological systems are characterized by inherent variability, which is necessary for their proper function. The constrained-disorder principle defines living systems as having a disorder as part of their existence and proper operation while kept within dynamic boundaries. In the present paper, we review the role of noise in complex systems and its use in bioengineering. We describe the use of digital twins for medical applications and current methods for dealing with noise and uncertainties in modeling. The paper presents methods to improve the accuracy and effectiveness of digital twin systems by continuously implementing variability signatures while simultaneously reducing unwanted noise in their inputs and outputs. Accounting for the noisy internal and external environments of complex biological systems is necessary for the future design of improved, more accurate digital twins.

The impact of cell size on morphogen gradient precision

Tissue patterning during embryonic development is remarkably precise. Here, we numerically determine the impact of the cell diameter, gradient length and the morphogen source on the variability of morphogen gradients. We show that the positional error increases with the gradient length relative to the size of the morphogen source, and with the square root of the cell diameter and the readout position. We provide theoretical explanations for these relationships, and show that they enable high patterning precision over developmental time for readouts that scale with expanding tissue domains, as observed in the Drosophila wing disc. Our analysis suggests that epithelial tissues generally achieve higher patterning precision with small cross-sectional cell areas. An extensive survey of measured apical cell areas shows that they are indeed small in developing tissues that are patterned by morphogen gradients. Enhanced precision may thus have led to the emergence of pseudostratification in epithelia, a phenomenon for which the evolutionary benefit had so far remained elusive.

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.

Mechanisms of robustness in gene regulatory networks involved in neural development

The functions of living organisms are affected by different kinds of perturbation, both internal and external, which in many cases have functional effects and phenotypic impact. The effects of these perturbations become particularly relevant for multicellular organisms with complex body patterns and cell type heterogeneity, where transcriptional programs controlled by gene regulatory networks determine, for example, the cell fate during embryonic development. Therefore, an essential aspect of development in these organisms is the ability to maintain the functionality of their genetic developmental programs even in the presence of genetic variation, changing environmental conditions and biochemical noise, a property commonly termed robustness. We discuss the implication of different molecular mechanisms of robustness involved in neurodevelopment, which is characterized by the interplay of many developmental programs at a molecular, cellular and systemic level. We specifically focus on processes affecting the function of gene regulatory networks, encompassing transcriptional regulatory elements and post-transcriptional processes such as miRNA-based regulation, but also higher order regulatory organization, such as gene network topology. We also present cases where impairment of robustness mechanisms can be associated with neurodevelopmental disorders, as well as reasons why understanding these mechanisms should represent an important part of the study of gene regulatory networks driving neural development.

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.

Promoter sequence and architecture determine expression variability and confer robustness to genetic variants

Genetic and environmental exposures cause variability in gene expression. Although most genes are affected in a population, their effect sizes vary greatly, indicating the existence of regulatory mechanisms that could amplify or attenuate expression variability. Here, we investigate the relationship between the sequence and transcription start site architectures of promoters and their expression variability across human individuals. We find that expression variability can be largely explained by a promoter's DNA sequence and its binding sites for specific transcription factors. We show that promoter expression variability reflects the biological process of a gene, demonstrating a selective trade-off between stability for metabolic genes and plasticity for responsive genes and those involved in signaling. Promoters with a rigid transcription start site architecture are more prone to have variable expression and to be associated with genetic variants with large effect sizes, while a flexible usage of transcription start sites within a promoter attenuates expression variability and limits genotypic effects. Our work provides insights into the variable nature of responsive genes and reveals a novel mechanism for supplying transcriptional and mutational robustness to essential genes through multiple transcription start site regions within a promoter.

Game of clones: Battles in the field of carcinogenesis

Recent advances in bulk sequencing approaches as well as genomic decoding at the single-cell level have revealed surprisingly high somatic mutational burdens in normal tissues, as well as increased our understanding of the landscape of "field cancerization", that is, molecular and immune alterations in mutagen-exposed normal-appearing tissues that recapitulated those present in tumors. Charting the somatic mutational landscapes in normal tissues can have strong implications on our understanding of how tumors arise from mutagenized epithelium. Making sense of those mutations to understand the progression along the pathologic continuum of normal epithelia, preneoplasias, up to malignant tissues will help pave way for identification of ideal targets that can guide new strategies for preventing or eliminating cancers at their earliest stages of development. In this review, we will provide a brief history of field cancerization and its implications on understanding early stages of cancer pathogenesis and deviation from the pathologically "normal" state. The review will provide an overview of how mutations accumulating in normal tissues can lead to a patchwork of mutated cell clones that compete while maintaining an overall state of functional homeostasis. The review also explores the role of clonal competition in directing the fate of normal tissues and summarizes multiple mechanisms elicited in this phenomenon and which have been linked to cancer development. Finally, we highlight the importance of understanding mutations in normal tissues, as well as clonal competition dynamics (in both the epithelium and the microenvironment) and their significance in exploring new approaches to combatting cancer.

Transcriptional bursts and heterogeneity among cardiomyocytes in hypertrophic cardiomyopathy

Transcriptional bursting is a common expression mode for most genes where independent transcription of alleles leads to different ratios of allelic mRNA from cell to cell. Here we investigated burst-like transcription and its consequences in cardiac tissue from Hypertrophic Cardiomyopathy (HCM) patients with heterozygous mutations in the sarcomeric proteins cardiac myosin binding protein C (cMyBP-C, MYBPC3) and cardiac troponin I (cTnI, TNNI3). Using fluorescence in situ hybridization (RNA-FISH) we found that both, MYBPC3 and TNNI3 are transcribed burst-like. Along with that, we show unequal allelic ratios of TNNI3-mRNA among single cardiomyocytes and unequally distributed wildtype cMyBP-C protein across tissue sections from heterozygous HCM-patients. The mutations led to opposing functional alterations, namely increasing (cMyBP-C_c.927−2A>G) or decreasing (cTnI_R145W) calcium sensitivity. Regardless, all patients revealed highly variable calcium-dependent force generation between individual cardiomyocytes, indicating contractile imbalance, which appears widespread in HCM-patients. Altogether, we provide strong evidence that burst-like transcription of sarcomeric genes can lead to an allelic mosaic among neighboring cardiomyocytes at mRNA and protein level. In HCM-patients, this presumably induces the observed contractile imbalance among individual cardiomyocytes and promotes HCM-development.

From developmental to atavistic bet-hedging: How cancer cells pervert the exploitation of random single-cell phenotypic fluctuations

Stochastic gene expression plays a leading developmental role through its contribution to cell differentiation. It is also proposed to promote phenotypic diversification in malignant cells. However, it remains unclear if these two forms of cellular bet-hedging are identical or rather display distinct features. Here we argue that bet-hedging phenomena in cancer cells are more similar to those occurring in unicellular organisms than to those of normal metazoan cells. We further propose that the atavistic bet-hedging strategies in cancer originate from a hijacking of the normal developmental bet-hedging of metazoans. Finally, we discuss the constraints that may shape the atavistic bet-hedging strategies of cancer cells.

G-quadruplex DNA structures in human stem cells and differentiation

The establishment of cell identity during embryonic development involves the activation of specific gene expression programmes and is underpinned by epigenetic factors including DNA methylation and histone post-translational modifications. G-quadruplexes are four-stranded DNA secondary structures (G4s) that have been implicated in transcriptional regulation and cancer. Here, we show that G4s are key genomic structural features linked to cellular differentiation. We find that G4s are highly abundant in human embryonic stem cells and are lost during lineage specification. G4s are prevalent in enhancers and promoters. G4s that are found in common between embryonic and downstream lineages are tightly linked to transcriptional stabilisation of genes involved in essential cellular functions as well as transitions in the histone post-translational modification landscape. Furthermore, the application of small molecules that stabilise G4s causes a delay in stem cell differentiation, keeping cells in a more pluripotent-like state. Collectively, our data highlight G4s as important epigenetic features that are coupled to stem cell pluripotency and differentiation.

Transcriptional repression in stochastic gene expression, patterning, and cell fate specification

Development is often driven by signaling and lineage-specific cues, yielding highly uniform and reproducible outcomes. Development also involves mechanisms that generate noise in gene expression and random patterns across tissues. Cells sometimes randomly choose between two or more cell fates in a mechanism called stochastic cell fate specification. This process diversifies cell types in otherwise homogenous tissues. Stochastic mechanisms have been extensively studied in prokaryotes where noisy gene activation plays a pivotal role in controlling cell fates. In eukaryotes, transcriptional repression stochastically limits gene expression to generate random patterns and specify cell fates. Here, we review our current understanding of repressive mechanisms that produce random patterns of gene expression and cell fates in flies, plants, mice, and humans.

Topoisomerase 1 activity during mitotic transcription favors the transition from mitosis to G1

As cells enter mitosis, chromatin compacts to facilitate chromosome segregation yet remains transcribed. Transcription supercoils DNA to levels that can impede further progression of RNA polymerase II (RNAPII) unless it is removed by DNA topoisomerase 1 (TOP1). Using ChIP-seq on mitotic cells, we found that TOP1 is required for RNAPII translocation along genes. The stimulation of TOP1 activity by RNAPII during elongation allowed RNAPII clearance from genes in prometaphase and enabled chromosomal segregation. Disruption of the TOP1-RNAPII interaction impaired RNAPII spiking at promoters and triggered defects in the post-mitotic transcription program. This program includes factors necessary for cell growth, and cells with impaired TOP1-RNAPII interaction are more sensitive to inhibitors of mTOR signaling. We conclude that TOP1 is necessary for assisting transcription during mitosis with consequences for growth and gene expression long after mitosis is completed. In this sense, TOP1 ensures that cellular memory is preserved in subsequent generations.

Oncogenic Viruses as Entropic Drivers of Cancer Evolution

Viral infection is an indisputable causal factor for nearly 17% of all human cancers. However, the diversity and complexity of oncogenic mechanisms raises new questions as to the mechanistic role of viruses in cancer. Classical viral oncogenes have been identified for all tumor-associated viruses. These oncogenes can have multiple oncogenic activities that may or may not be utilized in a particular tumor cell. In addition, stochastic events, like viral mutation and integration, as well as heritable host susceptibilities and immune deficiencies are also implicated in tumorigenesis. A more contemporary view of tumor biology highlights the importance of evolutionary forces that select for phenotypes better adapted to a complex and changing environment. Given the challenges of prioritizing singular mechanistic causes, it may be necessary to integrate concepts from evolutionary theory and systems biology to better understand viral cancer-driving forces. Here, we propose that viral infection provides a biological “entropy” that increases genetic variation and phenotypic plasticity, accelerating the main driving forces of cancer cell evolution. Viruses can also influence the evolutionary selection criteria by altering the tumor microenvironment and immune signaling. Utilizing concepts from cancer cell evolution, population genetics, thermodynamics, and systems biology may provide new perspectives on viral oncogenesis and identify novel therapeutic strategies for treating viruses and cancer.

Regulation of gene expression via translational buffering

Translation of an mRNA represents a critical step during the expression of protein-coding genes. As mechanisms governing post-transcriptional regulation of gene expression are progressively unveiled, it is becoming apparent that transcriptional programs are not fully reflected in the proteome. Herein, we highlight a previously underappreciated post-transcriptional mode of regulation of gene expression termed translational buffering. In principle, translational buffering opposes the impact of alterations in mRNA levels on the proteome. We further describe three types of translational buffering: compensation, which maintains protein levels e.g. across species or individuals; equilibration, which retains pathway stoichiometry; and offsetting, which acts as a reversible mechanism that maintains the levels of selected subsets of proteins constant despite genetic alteration and/or stress-induced changes in corresponding mRNA levels. While mechanisms underlying compensation and equilibration have been reviewed elsewhere, the principal focus of this review is on the less-well understood mechanism of translational offsetting. Finally, we discuss potential roles of translational buffering in homeostasis and disease.

Different Patterns of mRNA Nuclear Retention during Meiotic Prophase in Larch Microsporocytes

Recent studies show a crucial role of post-transcriptional processes in the regulation of gene expression. Our research has shown that mRNA retention in the nucleus plays a significant role in such regulation. We studied larch microsporocytes during meiotic prophase, characterized by pulsatile transcriptional activity. After each pulse, the transcriptional activity is silenced, but the transcripts synthesized at this time are not exported immediately to the cytoplasm but are retained in the cell nucleus and especially in Cajal bodies, where non-fully-spliced transcripts with retained introns are accumulated. Analysis of the transcriptome of these cells and detailed analysis of the nuclear retention and transport dynamics of several mRNAs revealed two main patterns of nuclear accumulation and transport. The majority of studied transcripts followed the first one, consisting of a more extended retention period and slow release to the cytoplasm. We have shown this in detail for the pre-mRNA and mRNA encoding RNA pol II subunit 10. In this pre-mRNA, a second (retained) intron is posttranscriptionally spliced at a precisely defined time. Fully mature mRNA is then released into the cytoplasm, where the RNA pol II complexes are produced. These proteins are necessary for transcription in the next pulse to occur.mRNAs encoding translation factors and SERRATE followed the second pattern, in which the retention period was shorter and transcripts were rapidly transferred to the cytoplasm. The presence of such a mechanism in various cell types from a diverse range of organisms suggests that it is an evolutionarily conserved mechanism of gene regulation.

Alteration of Proteotranscriptomic Landscape Reveals the Transcriptional Regulatory Circuits Controlling Key-Signaling Pathways and Metabolic Reprogramming During Tumor Evolution

The proteotranscriptomic landscape depends on the transcription, mRNA-turnover, translation, and regulated-destruction of proteins. Gene-specific mRNA-to-protein correlation is the consequence of the dynamic interplays of the different regulatory processes of proteotranscriptomic landscape. So far, the critical impact of mRNA and protein stability on their subsequent correlation on a global scale remained unresolved. Whether the mRNA-to-protein correlations are constrained by their stability and conserved across mammalian species including human is unknown. Moreover, whether the stability-dependent correlation pattern is altered in the tumor has not been explored. To establish the quantitative relationship between stability and correlation between mRNA and protein levels, we performed a multi-omics data integration study across mammalian systems including diverse types of human tissues and cell lines in a genome-wide manner. The current study illuminated an important aspect of the mammalian proteotranscriptomic landscape by providing evidence that stability-constrained mRNA-to-protein correlation follows a hierarchical pattern that remains conserved across different tissues and mammalian species. By analyzing the tumor and non-tumor tissues, we further illustrated that mRNA-to-protein correlations deviate in tumor tissues. By gene-centric analysis, we harnessed the hierarchical correlation patterns to identify altered mRNA-to-protein correlation in tumors and characterized the tumor correlation-enhancing and -repressing genes. We elucidated the transcriptional regulatory circuits controlling the correlation-enhancing and -repressing genes that are associated with metabolic reprogramming and cancer-associated pathways in tumor tissue. By tightly controlling the mRNA-to-protein correlation of specific genes, the transcriptional regulatory circuits may enable the tumor cells to evolve in varying tumor microenvironment. The mRNA-to-protein correlation analysis thus can serve as a unique approach to identify the pathways prioritized by the tumor cells at different clinical stages. The component of transcriptional regulatory circuits identified by the current study can serve as potential candidates for stage-dependent anticancer therapy.

Interdependent regulation of stereotyped and stochastic photoreceptor fates in the fly eye

Diversification of neuronal subtypes often requires stochastic gene regulatory mechanisms. How stochastically expressed transcription factors interact with other regulators in gene networks to specify cell fates is poorly understood. The random mosaic of color-detecting R7 photoreceptor subtypes in Drosophila is controlled by the stochastic on/off expression of the transcription factor Spineless (Ss). In Ss^ON R7s, Ss induces expression of Rhodopsin 4 (Rh4), whereas in Ss^OFF R7s, the absence of Ss allows expression of Rhodopsin 3 (Rh3). Here, we find that the transcription factor Runt, which is initially expressed in all R7s, is sufficient to promote stochastic Ss expression. Later, as R7s develop, Ss negatively feeds back onto Runt to prevent repression of Rh4 and ensure proper fate specification. Together, stereotyped and stochastic regulatory inputs are integrated into feedforward and feedback mechanisms to control cell fate.

Perspective: Controlling Epidermal Terminal Differentiation with Transcriptional Bursting and RNA Bodies

The outer layer of the skin, the epidermis, is the principal barrier to the external environment: post-mitotic cells terminally differentiate to form a tough outer cornified layer of enucleate and flattened cells that confer the majority of skin barrier function. Nuclear degradation is required for correct cornified envelope formation. This process requires mRNA translation during the process of nuclear destruction. In this review and perspective, we address the biology of transcriptional bursting and the formation of ribonuclear particles in model organisms including mammals, and then examine the evidence that these phenomena occur as part of epidermal terminal differentiation.

Theoretical study of the impact of adaptation on cell-fate heterogeneity and fractional killing

Fractional killing illustrates the cell propensity to display a heterogeneous fate response over a wide range of stimuli. The interplay between the nonlinear and stochastic dynamics of biochemical networks plays a fundamental role in shaping this probabilistic response and in reconciling requirements for heterogeneity and controllability of cell-fate decisions. The stress-induced fate choice between life and death depends on an early adaptation response which may contribute to fractional killing by amplifying small differences between cells. To test this hypothesis, we consider a stochastic modeling framework suited for comprehensive sensitivity analysis of dose response curve through the computation of a fractionality index. Combining bifurcation analysis and Langevin simulation, we show that adaptation dynamics enhances noise-induced cell-fate heterogeneity by shifting from a saddle-node to a saddle-collision transition scenario. The generality of this result is further assessed by a computational analysis of a detailed regulatory network model of apoptosis initiation and by a theoretical analysis of stochastic bifurcation mechanisms. Overall, the present study identifies a cooperative interplay between stochastic, adaptation and decision intracellular processes that could promote cell-fate heterogeneity in many contexts.

Gene Transcription as a Limiting Factor in Protein Production and Cell Growth

Cell growth is driven by the synthesis of proteins, genes, and other cellular components. Defining processes that limit biosynthesis rates is fundamental for understanding the determinants of cell physiology. Here, we analyze the consequences of engineering cells to express extremely high levels of mCherry proteins, as a tool to define limiting processes that fail to adapt upon increasing biosynthetic demands. Protein-burdened cells were transcriptionally and phenotypically similar to mutants of the Mediator, a transcription coactivator complex. However, our binding data suggest that the Mediator was not depleted from endogenous promoters. Burdened cells showed an overall increase in the abundance of the majority of endogenous transcripts, except for highly expressed genes. Our results, supported by mathematical modeling, suggest that wild-type cells transcribe highly expressed genes at the maximal possible rate, as defined by the transcription machinery’s physical properties. We discuss the possible cellular benefit of maximal transcription rates to allow a coordinated optimization of cell size and cell growth.

Stochasticity and determinism in cell fate decisions

During development, cells need to make decisions about their fate in order to ensure that the correct numbers and types of cells are established at the correct time and place in the embryo. Such cell fate decisions are often classified as deterministic or stochastic. However, although these terms are clearly defined in a mathematical sense, they are sometimes used ambiguously in biological contexts. Here, we provide some suggestions on how to clarify the definitions and usage of the terms stochastic and deterministic in biological experiments. We discuss the frameworks within which such clear definitions make sense and highlight when certain ambiguity prevails. As an example, we examine how these terms are used in studies of neuronal cell fate decisions and point out areas in which definitions and interpretations have changed and matured over time. We hope that this Review will provide some clarification and inspire discussion on the use of terminology in relation to fate decisions.

Stochastic allelic expression as trigger for contractile imbalance in hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM), the most common inherited cardiac disease, is caused by several mostly heterozygous mutations in sarcomeric genes. Hallmarks of HCM are cardiomyocyte and myofibrillar disarray and hypertrophy and fibrosis of the septum and the left ventricle. To date, a pathomechanism common to all mutations remains elusive. We have proposed that contractile imbalance, an unequal force generation of neighboring cardiomyocytes, may contribute to development of HCM hallmarks. At the same calcium concentration, we found substantial differences in force generation between individual cardiomyocytes from HCM patients with mutations in β-MyHC (β-myosin heavy chain). Variability among cardiomyocytes was significantly larger in HCM patients as compared with donor controls. We assume that this heterogeneity in force generation among cardiomyocytes may lead to myocardial disarray and trigger hypertrophy and fibrosis. We provided evidence that burst-like transcription of the MYH7-gene, encoding for β-MyHC, is associated with unequal fractions of mutant per wild-type mRNA from cell to cell (cell-to-cell allelic imbalance). This will presumably lead to unequal fractions of mutant per wild-type protein from cell to cell which may underlie contractile imbalance. In this review, we discuss molecular mechanisms of burst-like transcription with regard to contractile imbalance and disease development in HCM.

Enhancement of gene expression noise from transcription factor binding to genomic decoy sites

The genome contains several high-affinity non-functional binding sites for transcription factors (TFs) creating a hidden and unexplored layer of gene regulation. We investigate the role of such “decoy sites” in controlling noise (random fluctuations) in the level of a TF that is synthesized in stochastic bursts. Prior studies have assumed that decoy-bound TFs are protected from degradation, and in this case decoys function to buffer noise. Relaxing this assumption to consider arbitrary degradation rates for both bound/unbound TF states, we find rich noise behaviors. For low-affinity decoys, noise in the level of unbound TF always monotonically decreases to the Poisson limit with increasing decoy numbers. In contrast, for high-affinity decoys, noise levels first increase with increasing decoy numbers, before decreasing back to the Poisson limit. Interestingly, while protection of bound TFs from degradation slows the time-scale of fluctuations in the unbound TF levels, the decay of bound TFs leads to faster fluctuations and smaller noise propagation to downstream target proteins. In summary, our analysis reveals stochastic dynamics emerging from nonspecific binding of TFs and highlights the dual role of decoys as attenuators or amplifiers of gene expression noise depending on their binding affinity and stability of the bound TF.

A Synchronous IRF4-Dependent Gene Regulatory Network in B and Helper T Cells Orchestrating the Antibody Response

Control of diverse pathogens requires an adaptive antibody response, dependent on cellular division of labor to allocate antigen-dependent B- and CD4⁺ T-cell fates that collaborate to control the quantity and quality of antibody. This is orchestrated by the dynamic action of key transcriptional regulators mediating gene expression programs in response to pathogen-specific environmental inputs. We describe a conserved, likely ancient, gene regulatory network that intriguingly operates contemporaneously in B and CD4⁺ T cells to control their cell fate dynamics and thus, the character of the antibody response. The remarkable output of this network derives from graded expression, designated by antigen receptor signal strength, of a pivotal transcription factor that regulates alternate cell fate choices.

Short Residence Times of DNA-Bound Transcription Factors Can Reduce Gene Expression Noise and Increase the Transmission of Information in a Gene Regulation System

Gene expression noise is not just ubiquitous but also variable, and we still do not understand some of the most elementary factors that affect it. Among them is the residence time of a transcription factor (TF) on DNA, the mean time that a DNA-bound TF remains bound. Here, we use a stochastic model of transcriptional regulation to study how residence time affects the gene expression noise that arises when a TF induces gene expression. We find that the effect of residence time on gene expression noise depends on the TF’s concentration and its affinity to DNA, which determine the level of induction of the gene. At high levels of induction, residence time has no effect on gene expression noise. However, as the level of induction decreases, short residence times reduce gene expression noise. The reason is that fast on-off TF binding dynamics prevent long periods where proteins are predominantly synthesized or degraded, which can cause excessive fluctuations in gene expression. As a consequence, short residence times can help a gene regulation system acquire information about the cellular environment it operates in. Our predictions are consistent with the observation that experimentally measured residence times are usually modest and lie between seconds to minutes.

Obstacles to detecting isoforms using full-length scRNA-seq data

BACKGROUND

Early single-cell RNA-seq (scRNA-seq) studies suggested that it was unusual to see more than one isoform being produced from a gene in a single cell, even when multiple isoforms were detected in matched bulk RNA-seq samples. However, these studies generally did not consider the impact of dropouts or isoform quantification errors, potentially confounding the results of these analyses.

RESULTS

In this study, we take a simulation based approach in which we explicitly account for dropouts and isoform quantification errors. We use our simulations to ask to what extent it is possible to study alternative splicing using scRNA-seq. Additionally, we ask what limitations must be overcome to make splicing analysis feasible. We find that the high rate of dropouts associated with scRNA-seq is a major obstacle to studying alternative splicing. In mice and other well-established model organisms, the relatively low rate of isoform quantification errors poses a lesser obstacle to splicing analysis. We find that different models of isoform choice meaningfully change our simulation results.

CONCLUSIONS

To accurately study alternative splicing with single-cell RNA-seq, a better understanding of isoform choice and the errors associated with scRNA-seq is required. An increase in the capture efficiency of scRNA-seq would also be beneficial. Until some or all of the above are achieved, we do not recommend attempting to resolve isoforms in individual cells using scRNA-seq.

Loss of Kat2a enhances transcriptional noise and depletes acute myeloid leukemia stem-like cells

Acute Myeloid Leukemia (AML) is an aggressive hematological malignancy with abnormal progenitor self-renewal and defective white blood cell differentiation. Its pathogenesis comprises subversion of transcriptional regulation, through mutation and by hijacking normal chromatin regulation. Kat2a is a histone acetyltransferase central to promoter activity, that we recently associated with stability of pluripotency networks, and identified as a genetic vulnerability in AML. Through combined chromatin profiling and single-cell transcriptomics of a conditional knockout mouse, we demonstrate that Kat2a contributes to leukemia propagation through preservation of leukemia stem-like cells. Kat2a loss impacts transcription factor binding and reduces transcriptional burst frequency in a subset of gene promoters, generating enhanced variability of transcript levels. Destabilization of target programs shifts leukemia cell fate out of self-renewal into differentiation. We propose that control of transcriptional variability is central to leukemia stem-like cell propagation, and establish a paradigm exploitable in different tumors and distinct stages of cancer evolution.

Optogenetic approaches to investigate spatiotemporal signaling during development

Embryogenesis is coordinated by signaling pathways that pattern the developing organism. Many aspects of this process are not fully understood, including how signaling molecules spread through embryonic tissues, how signaling amplitude and dynamics are decoded, and how multiple signaling pathways cooperate to pattern the body plan. Optogenetic approaches can be used to address these questions by providing precise experimental control over a variety of biological processes. Here, we review how these strategies have provided new insights into developmental signaling and discuss how they could contribute to future investigations.

HLH-2/E2A Expression Links Stochastic and Deterministic Elements of a Cell Fate Decision during C. elegans Gonadogenesis

Stochastic mechanisms diversify cell fate in organisms ranging from bacteria to humans [1-4]. In the anchor cell/ventral uterine precursor cell (AC/VU) fate decision during C. elegans gonadogenesis, two "α cells," each with equal potential to be an AC or a VU, interact via LIN-12/Notch and its ligand LAG-2/DSL [5, 6]. This LIN-12/Notch-mediated interaction engages feedback mechanisms that amplify a stochastic initial difference between the two α cells, ensuring that the cell with higher lin-12 activity becomes the VU while the other becomes the AC [7-9]. The initial difference between the α cells was originally envisaged as a random imbalance from "noise" in lin-12 expression/activity [6]. However, subsequent evidence that the relative birth order of the α cells biases their fates suggested other factors may be operating [7]. Here, we investigate the nature of the initial difference using high-throughput lineage analysis [10]; GFP-tagged endogenous LIN-12, LAG-2, and HLH-2, a conserved transcription factor that orchestrates AC/VU development [7, 11]; and tissue-specific hlh-2 null alleles. We identify two stochastic elements: relative birth order, which largely originates at the beginning of the somatic gonad lineage three generations earlier, and onset of HLH-2 expression, such that the α cell whose parent expressed HLH-2 first is biased toward the VU fate. We find that these elements are interrelated, because initiation of HLH-2 expression is linked to the birth of the parent cell. Finally, we provide a potential deterministic mechanism for the HLH-2 expression bias by showing that hlh-2 is required for LIN-12 expression in the α cells.

Post-Transcriptional Noise Control

Recent evidence indicates that transcriptional bursts are intrinsically amplified by messenger RNA cytoplasmic processing to generate large stochastic fluctuations in protein levels. These fluctuations can be exploited by cells to enable probabilistic bet-hedging decisions. But large fluctuations in gene expression can also destabilize cell-fate commitment. Thus, it is unclear if cells temporally switch from high to low noise, and what mechanisms enable this switch. Here, the discovery of a post-transcriptional mechanism that attenuates noise in HIV is reviewed. Early in its life cycle, HIV amplifies transcriptional fluctuations to probabilistically select alternate fates, whereas at late times, HIV utilizes a post-transcriptional feedback mechanism to commit to a specific fate. Reanalyzing various reported post-transcriptional negative feedback architectures reveals that they attenuate noise more efficiently than classic transcriptional autorepression, leading to the derivation of an assay to detect post-transcriptional motifs. It is hypothesized that coupling transcriptional and post-transcriptional autoregulation enables efficient temporal noise control to benefit developmental bet-hedging decisions.

A single-cell transcriptomic atlas of the developing chicken limb

BACKGROUND

Through precise implementation of distinct cell type specification programs, differentially regulated in both space and time, complex patterns emerge during organogenesis. Thanks to its easy experimental accessibility, the developing chicken limb has long served as a paradigm to study vertebrate pattern formation. Through decades' worth of research, we now have a firm grasp on the molecular mechanisms driving limb formation at the tissue-level. However, to elucidate the dynamic interplay between transcriptional cell type specification programs and pattern formation at its relevant cellular scale, we lack appropriately resolved molecular data at the genome-wide level. Here, making use of droplet-based single-cell RNA-sequencing, we catalogue the developmental emergence of distinct tissue types and their transcriptome dynamics in the distal chicken limb, the so-called autopod, at cellular resolution.

RESULTS

Using single-cell RNA-sequencing technology, we sequenced a total of 17,628 cells coming from three key developmental stages of chicken autopod patterning. Overall, we identified 23 cell populations with distinct transcriptional profiles. Amongst them were small, albeit essential populations like the apical ectodermal ridge, demonstrating the ability to detect even rare cell types. Moreover, we uncovered the existence of molecularly distinct sub-populations within previously defined compartments of the developing limb, some of which have important signaling functions during autopod pattern formation. Finally, we inferred gene co-expression modules that coincide with distinct tissue types across developmental time, and used them to track patterning-relevant cell populations of the forming digits.

CONCLUSIONS

We provide a comprehensive functional genomics resource to study the molecular effectors of chicken limb patterning at cellular resolution. Our single-cell transcriptomic atlas captures all major cell populations of the developing autopod, and highlights the transcriptional complexity in many of its components. Finally, integrating our data-set with other single-cell transcriptomics resources will enable researchers to assess molecular similarities in orthologous cell types across the major tetrapod clades, and provide an extensive candidate gene list to functionally test cell-type-specific drivers of limb morphological diversification.