Gene expression variability as a unifying element of the pluripotency network

Detection of genes with differential expression dispersion unravels the role of autophagy in cancer progression

The majority of gene expression studies focus on the search for genes whose mean expression is different between two or more populations of samples in the so-called "differential expression analysis" approach. However, a difference in variance in gene expression may also be biologically and physiologically relevant. In the classical statistical model used to analyze RNA-sequencing (RNA-seq) data, the dispersion, which defines the variance, is only considered as a parameter to be estimated prior to identifying a difference in mean expression between conditions of interest. Here, we propose to evaluate four recently published methods, which detect differences in both the mean and dispersion in RNA-seq data. We thoroughly investigated the performance of these methods on simulated datasets and characterized parameter settings to reliably detect genes with a differential expression dispersion. We applied these methods to The Cancer Genome Atlas datasets. Interestingly, among the genes with an increased expression dispersion in tumors and without a change in mean expression, we identified some key cellular functions, most of which were related to catabolism and were overrepresented in most of the analyzed cancers. In particular, our results highlight autophagy, whose role in cancerogenesis is context-dependent, illustrating the potential of the differential dispersion approach to gain new insights into biological processes and to discover new biomarkers.

A dynamic actin-dependent nucleoskeleton and cell identity

Actin is an essential regulator of cellular functions. In the eukaryotic cell nucleus, actin regulates chromatin as a bona fide component of chromatin remodelling complexes, it associates with nuclear RNA polymerases to regulate transcription and is involved in co-transcriptional assembly of nascent RNAs into ribonucleoprotein complexes. Actin dynamics are, therefore, emerging as a major regulatory factor affecting diverse cellular processes. Importantly, the involvement of actin dynamics in nuclear functions is redefining the concept of nucleoskeleton from a rigid scaffold to a dynamic entity that is likely linked to the three-dimensional organization of the nuclear genome. In this review, we discuss how nuclear actin, by regulating chromatin structure through phase separation may contribute to the architecture of the nuclear genome during cell differentiation and facilitate the expression of specific gene programs. We focus specifically on mitochondrial genes and how their dysregulation in the absence of actin raises important questions about the role of cytoskeletal proteins in regulating chromatin structure. The discovery of a novel pool of mitochondrial actin that serves as 'mitoskeleton' to facilitate organization of mtDNA supports a general role for actin in genome architecture and a possible function of distinct actin pools in the communication between nucleus and mitochondria.

Paf1c defects challenge the robustness of flower meristem termination in Arabidopsis thaliana

Although accumulating evidence suggests that gene regulation is highly stochastic, genetic screens have successfully uncovered master developmental regulators, questioning the relationship between transcriptional noise and intrinsic robustness of development. To identify developmental modules that are more or less resilient to large-scale genetic perturbations, we used the Arabidopsis polymerase II-associated factor 1 complex (Paf1c) mutant vip3, which is impaired in several RNA polymerase II-dependent transcriptional processes. We found that the control of flower termination was not as robust as classically pictured. In angiosperms, the floral female organs, called carpels, display determinate growth: their development requires the arrest of stem cell maintenance. In vip3 mutant flowers, carpels displayed a highly variable morphology, with different degrees of indeterminacy defects up to wild-type size inflorescence emerging from carpels. This phenotype was associated with variable expression of two key regulators of flower termination and stem cell maintenance in flowers, WUSCHEL and AGAMOUS. The phenotype was also dependent on growth conditions. Together, these results highlight the surprisingly plastic nature of stem cell maintenance in plants and its dependence on Paf1c.

Summary: Using a mutant with increased transcriptional noise, we reveal that stem cell maintenance is not as robust as anticipated in plants, even leading to major defects in essential developmental processes such as flower indeterminacy.

AKIRIN1: A Potential New Reference Gene in Human Natural Killer Cells and Granulocytes in Sepsis

Timely and reliable distinction of sepsis from non-infectious systemic inflammatory response syndrome (SIRS) supports adequate antimicrobial therapy and saves lives but is clinically challenging. Blood transcriptional profiling promises to deliver insights into the pathomechanisms of SIRS and sepsis and to accelerate the discovery of urgently sought sepsis biomarkers. However, suitable reference genes for normalizing gene expression in these disease conditions are lacking. In addition, variability in blood leukocyte subtype composition complicates gene profile interpretation. Here, we aimed to identify potential reference genes in natural killer (NK) cells and granulocytes from patients with SIRS and sepsis on intensive care unit (ICU) admission. Discovery by a two-step probabilistic selection from microarray data followed by validation through branched DNA assays in independent patients revealed several candidate reference genes in NK cells including AKIRIN1, PPP6R3, TAX1BP1, and ADRBK1. Initially, no candidate genes could be validated in patient granulocytes. However, we determined highly similar AKIRIN1 expression also in SIRS and sepsis granulocytes and no change by in vitro LPS challenge in granulocytes from healthy donors. Inspection of external neutrophil transcriptome datasets further support unchanged AKIRIN1 expression in human systemic inflammation. As a potential new reference gene in NK cells and granulocytes in infectious and inflammatory diseases, AKIRIN1 may improve our pathomechanistic understanding of SIRS and sepsis and help identifying new sepsis biomarkers.

Gene expression variability: the other dimension in transcriptome analysis

Transcriptome sequencing is a powerful technique to study molecular changes that underlie the differences in physiological conditions and disease progression. A typical question that is posed in such studies is finding genes with significant changes between sample groups. In this respect expression variability is regarded as a nuisance factor that is primarily of technical origin and complicates the data analysis. However, it is becoming apparent that the biological variation in gene expression might be an important molecular phenotype that can affect physiological parameters. In this review we explore the recent literature on technical and biological variability in gene expression, sources of expression variability, (epi-)genetic hallmarks, and evolutionary constraints in genes with robust and variable gene expression. We provide an overview of recent findings on effects of external cues, such as diet and aging, on expression variability and on other biological phenomena that can be linked to it. We discuss metrics and tools that were developed for quantification of expression variability and highlight the importance of future studies in this direction. To assist the adoption of expression variability analysis, we also provide a detailed description and computer code, which can easily be utilized by other researchers. We also provide a reanalysis of recently published data to highlight the value of the analysis method.

Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling

Schizophrenia (SCZ) is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells). Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70) by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM) was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology of SCZ.

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.

Genetically unmatched human iPSC and ESC exhibit equivalent gene expression and neuronal differentiation potential

The potential uniformity between differentiation and therapeutic potential of human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs) remains debatable. We studied the gene expression profiles, pathways analysis and the ability to differentiated into neural progenitor cells (NPCs) and motor neurons (MNs) of genetically unmatched integration-free hiPSC versus hESC to highlight possible differences/similarities between them at the molecular level. We also provided the functional information of the neurons derived from the different hESCs and hiPSCs lines using the Neural Muscular Junction (NMJ) Assay. The hiPSC line was generated by transfecting human epidermal fibroblasts (HEF) with episomal DNAs expressing Oct4, Sox2, Klf4, Nanog, L-Myc and shRNA against p53. For the hESCs line, we used the NIH-approved H9 cell line. Using unsupervised clustering both hESCs and hiPSCs were clustered together implying homogeneous genetic states. The genetic profiles of hiPSCs and hESCs were clearly similar but not identical. Collectively, our data indicate close molecular similarities between genetically unmatched hESCs and hiPS in term of gene expression, and signaling pathways. Moreover, both cell types exhibited similar cholinergic motor neurons differentiation potential with marked ability of the differentiated hESCs and hiPSCs-derived MNs to induce contraction of myotubes after 4 days of co-culture.

pathVar: a new method for pathway-based interpretation of gene expression variability

Identifying the pathways that control a cellular phenotype is the first step to building a mechanistic model. Recent examples in developmental biology, cancer genomics, and neurological disease have demonstrated how changes in the variability of gene expression can highlight important genes that are under different degrees of regulatory control. Simple statistical tests exist to identify differentially-variable genes; however, methods for investigating how changes in gene expression variability in the context of pathways and gene sets are under-explored. Here we present pathVar, a new method that provides functional interpretation of gene expression variability changes at the level of pathways and gene sets. pathVar is based on a multinomial exact test, or an asymptotic Chi-squared test as a more computationally-efficient alternative. The method can be used for gene expression studies from any technology platform in all biological settings either with a single phenotypic group, or two-group comparisons. To demonstrate its utility, we applied the method to a diverse set of diseases, species and samples. Results from pathVar are benchmarked against analyses based on average expression and two methods of GSEA, and demonstrate that analyses using both statistics are useful for understanding transcriptional regulation. We also provide recommendations for the choice of variability statistic that have been informed through analyses on simulations and real data. Based on the datasets selected, we show how pathVar can be used to gain insight into expression variability of single cell versus bulk samples, different stem cell populations, and cancer versus normal tissue comparisons.

Prospective purification and characterization of Müller glia in the mouse retina regeneration assay

Reactive gliosis is an umbrella term for various glia functions in neurodegenerative diseases and upon injury. Specifically, Müller glia (MG) in some species readily regenerate retinal neurons to restore vision loss after insult, whereas mammalian MG respond by reactive gliosis-a heterogeneous response which frequently includes cell hypertrophy and proliferation. Limited regeneration has been stimulated in mammals, with a higher propensity in young MG, and in vitro compared to in vivo, but the underlying processes are unknown. To facilitate studies on the mechanisms regulating and limiting glia functions, we developed a strategy to purify glia and their progeny by fluorescence-activated cell sorting. Dual-transgenic nuclear reporter mice, which label neurons and glia with red and green fluorescent proteins, respectively, have enabled MG enrichment up to 93% purity. We applied this approach to MG in a mouse retina regeneration ex vivo assay. Combined cell size and cell cycle analysis indicates that most MG hypertrophy and a subpopulation proliferates which, over time, become even larger in cell size than the ones that do not proliferate. MG undergo timed differential genomic changes in genes controlling stemness and neurogenic competence; and glial markers are downregulated. Genes that are potentially required for, or associated with, regeneration and reactive gliosis are differentially regulated by retina explant culture time, epidermal growth factor stimulation, and animal age. Thus, MG enrichment facilitates cellular and molecular studies which, in combination with the mouse retina regeneration assay, provide an experimental approach for deciphering mechanisms that possibly regulate reactive gliosis and limit regeneration in mammals.

Transcriptome-Level Signatures in Gene Expression and Gene Expression Variability during Bacterial Adaptive Evolution

Antibiotic-resistant bacteria are an increasingly serious public health concern, as strains emerge that demonstrate resistance to almost all available treatments. One factor that contributes to the crisis is the adaptive ability of bacteria, which exhibit remarkable phenotypic and gene expression heterogeneity in order to gain a survival advantage in damaging environments. This high degree of variability in gene expression across biological populations makes it a challenging task to identify key regulators of bacterial adaptation. Here, we research the regulation of adaptive resistance by investigating transcriptome profiles of Escherichia coli upon adaptation to disparate toxins, including antibiotics and biofuels. We locate potential target genes via conventional gene expression analysis as well as using a new analysis technique examining differential gene expression variability. By investigating trends across the diverse adaptation conditions, we identify a focused set of genes with conserved behavior, including those involved in cell motility, metabolism, membrane structure, and transport, and several genes of unknown function. To validate the biological relevance of the observed changes, we synthetically perturb gene expression using clustered regularly interspaced short palindromic repeat (CRISPR)-dCas9. Manipulation of select genes in combination with antibiotic treatment promotes adaptive resistance as demonstrated by an increased degree of antibiotic tolerance and heterogeneity in MICs. We study the mechanisms by which identified genes influence adaptation and find that select differentially variable genes have the potential to impact metabolic rates, mutation rates, and motility. Overall, this work provides evidence for a complex nongenetic response, encompassing shifts in gene expression and gene expression variability, which underlies adaptive resistance. IMPORTANCE Even initially sensitive bacteria can rapidly thwart antibiotic treatment through stress response processes known as adaptive resistance. Adaptive resistance fosters transient tolerance increases and the emergence of mutations conferring heritable drug resistance. In order to extend the applicable lifetime of new antibiotics, we must seek to hinder the occurrence of bacterial adaptive resistance; however, the regulation of adaptation is difficult to identify due to immense heterogeneity emerging during evolution. This study specifically seeks to generate heterogeneity by adapting bacteria to different stresses and then examines gene expression trends across the disparate populations in order to pinpoint key genes and pathways associated with adaptive resistance. The targets identified here may eventually inform strategies for impeding adaptive resistance and prolonging the effectiveness of antibiotic treatment.

Stably Expressed Genes Involved in Basic Cellular Functions

Stably Expressed Genes (SEGs) whose expression varies within a narrow range may be involved in core cellular processes necessary for basic functions. To identify such genes, we re-analyzed existing RNA-Seq gene expression profiles across 11 organs at 4 developmental stages (from immature to old age) in both sexes of F344 rats (n = 4/group; 320 samples). Expression changes (calculated as the maximum expression / minimum expression for each gene) of >19000 genes across organs, ages, and sexes ranged from 2.35 to >10⁹-fold, with a median of 165-fold. The expression of 278 SEGs was found to vary ≤4-fold and these genes were significantly involved in protein catabolism (proteasome and ubiquitination), RNA transport, protein processing, and the spliceosome. Such stability of expression was further validated in human samples where the expression variability of the homologous human SEGs was significantly lower than that of other genes in the human genome. It was also found that the homologous human SEGs were generally less subject to non-synonymous mutation than other genes, as would be expected of stably expressed genes. We also found that knockout of SEG homologs in mouse models was more likely to cause complete preweaning lethality than non-SEG homologs, corroborating the fundamental roles played by SEGs in biological development. Such stably expressed genes and pathways across life-stages suggest that tight control of these processes is important in basic cellular functions and that perturbation by endogenous (e.g., genetics) or exogenous agents (e.g., drugs, environmental factors) may cause serious adverse effects.

Epigenetics of cell fate reprogramming and its implications for neurological disorders modelling

The reprogramming of human induced pluripotent stem cells (hiPSCs) proceeds in a stepwise manner with reprogramming factors binding and epigenetic composition changes during transition to maintain the epigenetic landscape, important for pluripotency. There arises a question as to whether the aberrant epigenetic state after reprogramming leads to epigenetic defects in induced stem cells causing unpredictable long term effects in differentiated cells. In this review, we present a comprehensive view of epigenetic alterations accompanying reprogramming, cell maintenance and differentiation as factors that influence applications of hiPSCs in stem cell based technologies. We conclude that sample heterogeneity masks DNA methylation signatures in subpopulations of cells and thus believe that beside a genetic evaluation, extensive epigenomic screening should become a standard procedure to ensure hiPSCs state before they are used for genome editing and differentiation into neurons of interest. In particular, we suggest that exploitation of the single-cell composition of the epigenome will provide important insights into heterogeneity within hiPSCs subpopulations to fast forward development of reliable hiPSC-based analytical platforms in neurological disorders modelling and before completed hiPSC technology will be implemented in clinical approaches.

Modeling heterogeneity in the pluripotent state: A promising strategy for improving the efficiency and fidelity of stem cell differentiation

Pluripotency can be considered a functional characteristic of pluripotent stem cells (PSCs) populations and their niches, rather than a property of individual cells. In this view, individual cells within the population independently adopt a variety of different expression states, maintained by different signaling, transcriptional, and epigenetics regulatory networks. In this review, we propose that generation of integrative network models from single cell data will be essential for getting a better understanding of the regulation of self-renewal and differentiation. In particular, we suggest that the identification of network stability determinants in these integrative models will provide important insights into the mechanisms mediating the transduction of signals from the niche, and how these signals can trigger differentiation. In this regard, the differential use of these stability determinants in subpopulation-specific regulatory networks would mediate differentiation into different cell fates. We suggest that this approach could offer a promising avenue for the development of novel strategies for increasing the efficiency and fidelity of differentiation, which could have a strong impact on regenerative medicine.

Retinal Organoids from Pluripotent Stem Cells Efficiently Recapitulate Retinogenesis

The plasticity of pluripotent stem cells provides new possibilities for studying development, degeneration, and regeneration. Protocols for the differentiation of retinal organoids from embryonic stem cells have been developed, which either recapitulate complete eyecup morphogenesis or maximize photoreceptor genesis. Here, we have developed a protocol for the efficient generation of large, 3D-stratified retinal organoids that does not require evagination of optic-vesicle-like structures, which so far limited the organoid yield. Analysis of gene expression in individual organoids, cell birthdating, and interorganoid variation indicate efficient, reproducible, and temporally regulated retinogenesis. Comparative analysis of a transgenic reporter for PAX6, a master regulator of retinogenesis, shows expression in similar cell types in mouse in vivo, and in mouse and human retinal organoids. Early or late Notch signaling inhibition forces cell differentiation, generating organoids enriched with cone or rod photoreceptors, respectively, demonstrating the power of our improved organoid system for future research in stem cell biology and regenerative medicine.

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Efficient protocol for pluripotent stem cell-derived retinal organoidogenesis

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Temporal gene-expression profile analysis of individual organoids

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Comparative hPAX6GFP expression in murine retinal organoids and mouse retina

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Timed Notch inhibition results in cone- or rod-photoreceptor-enriched organoids

Gene expression variability in mammalian embryonic stem cells using single cell RNA-seq data

BACKGROUND

Gene expression heterogeneity contributes to development as well as disease progression. Due to technological limitations, most studies to date have focused on differences in mean expression across experimental conditions, rather than differences in gene expression variance. The advent of single cell RNA sequencing has now made it feasible to study gene expression heterogeneity and to characterise genes based on their coefficient of variation.

METHODS

We collected single cell gene expression profiles for 32 human and 39 mouse embryonic stem cells and studied correlation between diverse characteristics such as network connectivity and coefficient of variation (CV) across single cells. We further systematically characterised properties unique to High CV genes.

RESULTS

Highly expressed genes tended to have a low CV and were enriched for cell cycle genes. In contrast, High CV genes were co-expressed with other High CV genes, were enriched for bivalent (H3K4me3 and H3K27me3) marked promoters and showed enrichment for response to DNA damage and DNA repair.

CONCLUSIONS

Taken together, this analysis demonstrates the divergent characteristics of genes based on their CV. High CV genes tend to form co-expression clusters and they explain bivalency at least in part.

TBX3 Knockdown Decreases Reprogramming Efficiency of Human Cells

TBX3 is a member of the T-box transcription factor family and is involved in the core pluripotency network. Despite this role in the pluripotency network, its contribution to the reprogramming process during the generation of human induced pluripotent stem cells remains elusive. In this respect, we performed reprogramming experiments applying TBX3 knockdown in human fibroblasts and keratinocytes. Knockdown of TBX3 in both somatic cell types decreased the reprogramming efficiencies in comparison to control cells but with unchanged reprogramming kinetics. The resulting iPSCs were indistinguishable from control cells and displayed a normal in vitro differentiation capacity by generating cells of all three germ layers comparable to the controls.

Variability of Gene Expression Identifies Transcriptional Regulators of Early Human Embryonic Development

An analysis of gene expression variability can provide an insightful window into how regulatory control is distributed across the transcriptome. In a single cell analysis, the inter-cellular variability of gene expression measures the consistency of transcript copy numbers observed between cells in the same population. Application of these ideas to the study of early human embryonic development may reveal important insights into the transcriptional programs controlling this process, based on which components are most tightly regulated. Using a published single cell RNA-seq data set of human embryos collected at four-cell, eight-cell, morula and blastocyst stages, we identified genes with the most stable, invariant expression across all four developmental stages. Stably-expressed genes were found to be enriched for those sharing indispensable features, including essentiality, haploinsufficiency, and ubiquitous expression. The stable genes were less likely to be associated with loss-of-function variant genes or human recessive disease genes affected by a DNA copy number variant deletion, suggesting that stable genes have a functional impact on the regulation of some of the basic cellular processes. Genes with low expression variability at early stages of development are involved in regulation of DNA methylation, responses to hypoxia and telomerase activity, whereas by the blastocyst stage, low-variability genes are enriched for metabolic processes as well as telomerase signaling. Based on changes in expression variability, we identified a putative set of gene expression markers of morulae and blastocyst stages. Experimental validation of a blastocyst-expressed variability marker demonstrated that HDDC2 plays a role in the maintenance of pluripotency in human ES and iPS cells. Collectively our analyses identified new regulators involved in human embryonic development that would have otherwise been missed using methods that focus on assessment of the average expression levels; in doing so, we highlight the value of studying expression variability for single cell RNA-seq data.

Cell Cycle-Driven Heterogeneity: On the Road to Demystifying the Transitions between "Poised" and "Restricted" Pluripotent Cell States

Cellular heterogeneity is now considered an inherent property of most stem cell types, including pluripotent stem cells, somatic stem cells, and cancer stem cells, and this heterogeneity can exist at the epigenetic, transcriptional, and posttranscriptional levels. Several studies have indicated that the stochastic activation of signaling networks may promote heterogeneity and further that this heterogeneity may be reduced by their inhibition. But why different cells in the same culture respond in a nonuniform manner to the identical exogenous signals has remained unclear. Recent studies now demonstrate that the cell cycle position directly influences lineage specification and specifically that pluripotent stem cells initiate their differentiation from the G1 phase. These studies suggest that cells in G1 are uniquely "poised" to undergo cell specification. G1 cells are therefore more prone to respond to differentiation cues, which may explain the heterogeneity of developmental factors, such as Gata6, and pluripotency factors, such as Nanog, in stem cell cultures. Overall, this raises the possibility that G1 serves as a "Differentiation Induction Point." In this review, we will reexamine the literature describing heterogeneity of pluripotent stem cells, while highlighting the role of the cell cycle as a major determinant.