Regulatory States Research Articles

Tetrahydrobiopterin and Nitric Oxide Synthase Recouplers.

Generation of nitric oxide (NO) by the nitric oxide synthase (NOS) enzymes plays multiple signalling roles in every organ system, with crucial roles in the cardiovascular system, mediated by endothelial nitric oxide synthase (eNOS, encoded by NOS3) and neuronal nitric oxide synthase (nNOS, encoded by NOS1) in regulation of blood pressure, flow, oxygen delivery and cardiac function. Loss of normal NO-mediated functions in cardiovascular disease state is associated with changes in nitroso-redox signalling that are not dependent solely upon altered NO generation, but increased generation of reactive oxygen species (ROS). The NOS enzymes can also generate ROS, in a catalytic mode whereby the generation of NO from L-arginine is 'uncoupled' from the reduction of molecular oxygen. NOS uncoupling is determined by several factors, including the availability and oxidation state of the required NOS cofactor, tetrahydrobiopterin (BH4). The duality of NOS functions as enzymes that generate both NO and ROS under different regulatory states has emerged as an important pathophysiologic mechanism, and is a potential therapeutic target, via agents that can maintain or restore NOS coupling, for example via effects on BH4 availability.

Network architecture and regulatory logic in neural crest development.

The neural crest is an ectodermal cell population that gives rise to over 30 cell types during vertebrate embryogenesis. These stem cells are formed at the border of the developing central nervous system and undergo extensive migration before differentiating into components of multiple tissues and organs. Neural crest formation and differentiation is a multistep process, as these cells transition through sequential regulatory states before adopting their adult phenotype. Such changes are governed by a complex gene regulatory network (GRN) that integrates environmental and cell-intrinsic inputs to regulate cell identity. Studies of neural crest cells in a variety of vertebrate models have elucidated the function and regulation of dozens of the molecular players that are part of this network. The neural crest GRN has served as a platform to explore the molecular control of multipotency, cell differentiation, and the evolution of vertebrates. In this review, we employ this genetic program as a stepping-stone to explore the architecture and the regulatory principles of developmental GRNs. We also discuss how modern genomic approaches can further expand our understanding of genetic networks in this system and others. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Biological Mechanisms > Cell Fates Developmental Biology > Lineages Models of Systems Properties and Processes > Cellular Models.

Direct prediction of regulatory elements from partial data without imputation.

Genome segmentation approaches allow us to characterize regulatory states in a given cell type using combinatorial patterns of histone modifications and other regulatory signals. In order to analyze regulatory state differences across cell types, current genome segmentation approaches typically require that the same regulatory genomics assays have been performed in all analyzed cell types. This necessarily limits both the numbers of cell types that can be analyzed and the complexity of the resulting regulatory states, as only a small number of histone modifications have been profiled across many cell types. Data imputation approaches that aim to estimate missing regulatory signals have been applied before genome segmentation. However, this approach is computationally costly and propagates any errors in imputation to produce incorrect genome segmentation results downstream. We present an extension to the IDEAS genome segmentation platform which can perform genome segmentation on incomplete regulatory genomics dataset collections without using imputation. Instead of relying on imputed data, we use an expectation-maximization approach to estimate marginal density functions within each regulatory state. We demonstrate that our genome segmentation results compare favorably with approaches based on imputation or other strategies for handling missing data. We further show that our approach can accurately impute missing data after genome segmentation, reversing the typical order of imputation/genome segmentation pipelines. Finally, we present a new 2D genome segmentation analysis of 127 human cell types studied by the Roadmap Epigenomics Consortium. By using an expanded set of chromatin marks that have been profiled in subsets of these cell types, our new segmentation results capture a more complex picture of combinatorial regulatory patterns that appear on the human genome.

The Essence, Significance, and Problems of the Trans-Pacific Partnership

The Trans-Pacific Partnership (TPP) is the first fully formed attempt at a new type of geopolitical and economic ordering project we call megaregulation. This introduction draws on the thirty further chapters in our edited volume 'Megaregulation Contested: Global Economic Ordering after TPP' (OUP, 2019) to distill TPP’s essence and critically appraise its significance in the Asia-Pacific and beyond. TPP’s megaregulatory project uses the treaty-institutional form to open space for transnational business operations and prescribe liberal-type reforms of regulatory states and of their relations to markets. It also carries glimmers of a megaregionalism, but one largely lacking in imagination of a shared social or ecological future. TPP’s extensive coverage implicates, but TPP does not very much address, concerns over distribution, inequality, labor, environment, development, and national futures and nationalism which became more and more evident in national and international politics during and after the years of its negotiation. Drawing together themes from the book sheds some light on thinking about possible futures of economic ordering.

A Stochastic Multiscale Model of Cardiac Thin Filament Activation Using Brownian-Langevin Dynamics

We use Brownian-Langevin dynamics principles to derive a coarse-graining multiscale myofilament model that can describe the thin-filament activation process during contraction. The model links atomistic molecular simulations of protein-protein interactions in the thin-filament regulatory unit to sarcomere-level activation dynamics. We first calculate the molecular interaction energy between tropomyosin and actin surface using Brownian dynamics simulations. This energy profile is then generalized to account for the observed tropomyosin transitions between its regulatory stable states. The generalized energy landscape then served as a basis for developing a filament-scale model using Langevin dynamics. This integrated analysis, spanning molecular to thin-filament scales, is capable of tracking the events of the tropomyosin conformational changes as it moves over the actin surface. The tropomyosin coil with flexible overlap regions between adjacent tropomyosins is represented in the model as a system of coupled stochastic ordinary differential equations. The proposed multiscale approach provides a more detailed molecular connection between tropomyosin dynamics, the trompomyosin-actin interaction-energy landscape, and the generated force by the sarcomere.

Evidence against tetrapod-wide digit identities and for a limited frame shift in bird wings

In crown group tetrapods, individual digits are homologized in relation to a pentadactyl ground plan. However, testing hypotheses of digit homology is challenging because it is unclear whether digits represent distinct and conserved gene regulatory states. Here we show dramatic evolutionary dynamism in the gene expression profiles of digits, challenging the notion that five digits have conserved developmental identities across amniotes. Transcriptomics shows diversity in the patterns of gene expression differentiation of digits, although the anterior-most digit of the pentadactyl limb has a unique, conserved expression profile. Further, we identify a core set of transcription factors that are differentially expressed among the digits of amniote limbs; their spatial expression domains, however, vary between species. In light of these results, we reevaluate the frame shift hypothesis of avian wing evolution and conclude only the identity of the anterior-most digit has shifted position, suggesting a 1,3,4 digit identity in the bird wing.

Abstract 4558: Mapping tolerized T cell states to exhaustion phenotypes in NSCLC

Abstract The promise of checkpoint blockade treatment has yet to be fully realized in part due to a lack of knowledge of immune exhaustion and its efficient characterization, especially in the context of immunosuppressive tumor microenvironments which effectively tolerize the immune system. We hypothesized that mapping expression signatures defining regulatory T-cell states to previously studied and characterized exhaustion phenotypes of infiltrating T cells in NSCLC would reveal points of contact between T cell tolerization and exhaustion. Concretely, we profiled the gene expression and directly inferred CDR3/1 clonality between tolerized and immunized states in purified CD4+ T-Cells from 10 patients with ovarian or peritoneal and non-small cell lung cancer. The samples were taken before and during immunization therapy for the antigens MAGE-A3 or NY-ESO-1 over a period of 13 weeks, in the presence and absence of adjuvant to emulate the tolerized and immunized states. Further, by modeling the regulatory T-cell states as an interaction between the tolerized and immunized with time and type of antigen allowed us to identify significant differentially expressed gene clusters and their correlation to clonality. We then projected these signatures onto single cell RNAseq data from NSCLC-TCGA to compare the identified clusters to previously identified exhaustion phenotypes. We show that antigen vaccination is immunostimulating and induces lymphocyte activation, leading to a proinflammatory environment. During an immunized stated an increase in cytokine activity, including IL2, 4, 9, 10, 13 and 17, whereas tolerized T Cells, we observe an increase in clonality, BIRC6 and IL20 apart from alterations in chromosome organization pathways and cell cycle including senescence. In conclusion, we detail how the differences between tolerized and immunized states help unravel exhaustion mechanisms, which will ultimately identify molecular markers for exhaustion to assist during treatment and prognosis in clinical settings. Citation Format: Edgar Kozlova, Shingo Eikawa, Sacha Gnjatic, Bojan Losic. Mapping tolerized T cell states to exhaustion phenotypes in NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4558.

Abstract 5095: Statistical modeling of transcriptional regulatory states in single-cell RNA-Seq data of tumor and infiltrated immune cells

Abstract Single-cell RNA-seq of tumor tissue has greatly strengthened our understanding of tumor development as well as the heterogeneous tissue micro-environment. Many models are dedicated to detect deferentially expressed genes among single cells of different conditions, or to discover (novel) sub-cell types via various clustering methods. However, current statistical models often neglect the zero/low expressions, and use one single modality to fit the rest of the non-zero ones. We believe that zero and low expressions are observed partly due to limited experimental resolution; on the other hand, occasionally, low expressions are falsely observed as non-zero due to the existence of incompletely degraded mRNA. In addition, the severe heterogeneity and fast dynamics of single cells makes it invalid to fit their expressions in one single modality. Here, we propose a left truncated mixture Gaussian (LTMG) distribution to uncover the multimodality in single cells’ gene expression while properly handling the zero and low expressions. LTMG is motivated by the kinetic relationships among the mRNA abundance, transcriptional regulatory signals (TRSs), and mRNA metabolism in a cell. Specifically, observations of a gene’s expression are fitted as mixture Gaussian distributions which assumes zero and low expressions as left censored data. By treating each mixing component as one state of the transcriptional regulators, we combined our LTMG model and our in-house bi-clustering algorithm to infer modules of genes co-regulated by certain (unknown) transcriptional regulatory signal, which is only shared by a subset of all the single cells. Application of the method to three high quality single-cell RNA-seq data sets of T cells extracted from liver, colon and lung cancer micro-environments, identified varied transcriptional regulations specific to subclasses of T cells. Citation Format: Changlin Wan, Wennan Chang, Xiaoyu Lu, Yifan Sun, Kaman So, Sha Cao, Xiongbin Lu, Chi Zhang. Statistical modeling of transcriptional regulatory states in single-cell RNA-Seq data of tumor and infiltrated immune cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 5095.

DREF Genetically Counteracts Mi-2 and Caf1 to Regulate Adult Stem Cell Maintenance.

Active adult stem cells maintain a bipotential state with progeny able to either self-renew or initiate differentiation depending on extrinsic signals from the surrounding microenvironment. However, the intrinsic gene regulatory networks and chromatin states that allow adult stem cells to make these cell fate choices are not entirely understood. Here we show that the transcription factor DNA Replication-related Element Factor (DREF) regulates adult stem cell maintenance in the Drosophila male germline. A temperature-sensitive allele of DREF described in this study genetically separated a role for DREF in germline stem cell self-renewal from the general roles of DREF in cell proliferation. The DREF temperature-sensitive allele caused defects in germline stem cell self-renewal but allowed viability and division of germline stem cells as well as cell viability, growth and division of somatic cyst stem cells in the testes and cells in the Drosophila eye. Germline stem cells mutant for the temperature sensitive DREF allele exhibited lower activation of a TGF-beta reporter, and their progeny turned on expression of the differentiation factor Bam prematurely. Results of genetic interaction analyses revealed that Mi-2 and Caf1/p55, components of the Nucleosome Remodeling and Deacetylase (NuRD) complex, genetically antagonize the role of DREF in germline stem cell maintenance. Taken together, these data suggest that DREF contributes to intrinsic components of the germline stem cell regulatory network that maintains competence to self-renew.

An epigenetic link between the gut microbiome and immune responses in atopy

Abstract Atopy is the most common childhood disease in developed countries. Dysbiosis of the microbiome is now understood to be a driving force behind the development and severity of allergy/atopy. We previously showed that antibiotic treatment of newborn mice leads to a life-long perturbation of the gut microbiome marked by reduced bacterial production of the short chain fatty acid, butyrate. These mice exhibit a striking pro-inflammatory phenotype, marked by a heightened Th2 response, that was completely reversible with dietary supplementation of butyrate. Butyrate is known to exert its effects on target cells via inhibition of histone deacetylases that have long term effects on gene expression. Consistent with a role for epigenetic skewing on the hematopoietic compartment of antibiotic treated mice, we found that bone marrow transplantation was sufficient to transfer the pro Th2 inflammatory phenotype into chimeric mice. Strikingly, we found unique regulatory states (H3K27ac) in purified hematopoietic stem and progenitor cells of these Th2 skewed mice. Single cell sequence analyses identified a distinct stem/progenitor cell transcriptomic signature in butyrate depleted mice that was reversed by butyrate supplementation. We identified a metagenomic gene signature present in fecal microbiome samples of 3-month-old children who subsequently developed atopy. Consistent with our observations in mice, this signature included depletion of the bacterial genes required for breakdown of indigestible carbohydrates in breast milk and the loss of genes required for butyrate fermentation. This work provides novel evidence for a butyrate-driven epigenetic process that links the fetal microbiome to long term sculpting of the immune response.

Regulatory relationships across levels of multilevel governance systems: From collaboration to competition

The European Union and the United States are paradigmatic examples of multilevel governance systems that are also regulatory states. In both settings, informal networks of regulators preceded and existed alongside supranational (federal) regulatory agencies. The literature understood their rationale as preparatory to the creation of higher level agencies. This approach, however, cannot explain why informal regulatory networks still exist, years after the establishment of higher level agencies. What explains the persistence of informal regulatory networks? The argument of this article is that in multilevel governance systems, the relationship between regulatory networks and the supranational level of governance is coevolutionary and embodies struggles for autonomy and authority: as the multilevel governance system consolidates, the character of this relationship evolves from collaborative to competitive. The argument relies on a comparative historical analysis of two voluntary networks of energy regulators from the European Union and the United States, based on 27 interviews and archival research.

The Pulse-Respiration Quotient: A Powerful but Untapped Parameter for Modern Studies About Human Physiology and Pathophysiology.

A specific and unique aspect of cardiorespiratory activity can be captured by dividing the heart rate (HR) by the respiration rate (RR), giving the pulse-respiration quotient (PRQ = HR/RR). In this review article, we summarize the main findings of studies using and investigating the PRQ. We describe why the PRQ is a powerful parameter that captures complex regulatory states of the cardiorespiratory system, and we highlight the need to re-introduce the use of this parameter into modern studies about human physiology and pathophysiology. In particular, we show that the PRQ (i) changes during human development, (ii) is time-dependent (ultradian, circadian, and infradian rhythms), (iii) shows specific patterns during sleep, (iv) changes with physical activity and body posture, (v) is linked with psychophysical and cognitive activity, (vi) is sex-dependent, and (vii) is determined by the individual physiological constitution. Furthermore, we discuss the medical aspects of the PRQ in terms of applications for disease classification and monitoring. Finally, we explain why there should be a revival in the use of the PRQ for basic research about human physiology and for applications in medicine, and we give recommendations for the use of the PRQ in studies and medical applications.

In situ 10-cell RNA sequencing in tissue and tumor biopsy samples

Single-cell transcriptomic methods classify new and existing cell types very effectively, but alternative approaches are needed to quantify the individual regulatory states of cells in their native tissue context. We combined the tissue preservation and single-cell resolution of laser capture with an improved preamplification procedure enabling RNA sequencing of 10 microdissected cells. This in situ 10-cell RNA sequencing (10cRNA-seq) can exploit fluorescent reporters of cell type in genetically engineered mice and is compatible with freshly cryoembedded clinical biopsies from patients. Through recombinant RNA spike-ins, we estimate dropout-free technical reliability as low as ~250 copies and a 50% detection sensitivity of ~45 copies per 10-cell reaction. By using small pools of microdissected cells, 10cRNA-seq improves technical per-cell reliability and sensitivity beyond existing approaches for single-cell RNA sequencing (scRNA-seq). Detection of low-abundance transcripts by 10cRNA-seq is comparable to random 10-cell groups of scRNA-seq data, suggesting no loss of gene recovery when cells are isolated in situ. Combined with existing approaches to deconvolve small pools of cells, 10cRNA-seq offers a reliable, unbiased, and sensitive way to measure cell-state heterogeneity in tissues and tumors.

Long non-coding RNAs discriminate the stages and gene regulatory states of human humoral immune response

lncRNAs make up a majority of the human transcriptome and have key regulatory functions. Here we perform unbiased de novo annotation of transcripts expressed during the human humoral immune response to find 30% of the human genome transcribed during this process, yet 58% of these transcripts manifest striking differential expression, indicating an lncRNA phylogenetic relationship among cell types that is more robust than that of coding genes. We provide an atlas of lncRNAs in naive and GC B-cells that indicates their partition into ten functionally categories based on chromatin features, DNase hypersensitivity and transcription factor localization, defining lncRNAs classes such as enhancer-RNAs (eRNA), bivalent-lncRNAs, and CTCF-associated, among others. Specifically, eRNAs are transcribed in 8.6% of regular enhancers and 36.5% of super enhancers, and are associated with coding genes that participate in critical immune regulatory pathways, while plasma cells have uniquely high levels of circular-RNAs accounted for by and reflecting the combinatorial clonal state of the Immunoglobulin loci.

Abstract B054: Single-cell analysis illuminates the gradients of immune cell functional states within human melanoma tumors, and facilitates characterization of tumor-reactive T-cells

Abstract Checkpoint blockade therapies that aim to reactivate antitumor immune responses have revolutionized cancer treatment, resulting in durable responses in a significant proportion of patients with advanced tumor progression. Nevertheless, many patients fail to reach long-term clinical benefit due to lack of response or acquired resistance. Inconsistency in therapy outcomes may be explained in part by recent findings suggesting that immune cell infiltrates in tumors are highly heterogeneous among patients. Therefore, comprehensive characterization of the diverse functional states exhibited by immune cell infiltrates is critical for the development of more effective immunotherapies. Here, we characterized immune cell infiltrates within tumors derived from 28 metastatic melanoma patients by single-cell RNA-seq of ~100,000 immune cells, and parallel T-cell receptor (TCR) sequencing, thereby generating an unbiased map of the expression signatures of immune cells, as well as clonality of T-cells within and between metastases. We identified within the tumor infiltrates naïve, semi- and fully-activated effector, dysfunctional, and regulatory T-cells, as well as NK cells, and various myeloid subsets. While various immune cell types and cellular states are shared among patients, their frequency in each is highly heterogeneous even among similar tumor progression stages and treatment background. We noticed that clonally expanded T-cells predominantly adapted similar expression profiles. The frequencies of certain sub-populations were found to be correlated; notably, dysfunctional CD8 T-cell states were associated with prevalence of regulatory T-cells and follicular helper cells. The high-resolution map demonstrated gradient transitions between activation and dysfunctional states of CD8 T-cells, as well as variability within regulatory T-cell states. We used computational modeling to find the key transcription factors driving these gradients of expression states. Our analysis also puts forward novel candidate genes, which are highly correlate with known checkpoint targets within specific single-cell clusters, and may prove to be effective targets for checkpoint blockade. In order to validate our results, we performed in vitro reactivity assays (for available samples), which allowed us to determine autologous-tumor reactive and nonreactive TCRs, adding the reactive potential of T-cells as another layer of information to the single-cell expression signatures, facilitating inference of the functionality of clonally expanded T-cell populations in the tumor. Linking autologous tumor reactivity with single-cell expression profiles, we found that T-cells presenting reactive capability in vitro show a highly dysfunctional signature in the original tumor. The lack or presence of such reactive CD8 T-cells was also associated with patient response to immunotherapy (n=10). In conclusion, we present an atlas of immune cell infiltrates of human melanoma, revealing intra- and inter-patient heterogeneity of tumor immune infiltrates, highlighting regulatory circuits underlying different immune populations and their interactions. Our findings demonstrate how single-cell analysis may serve in the future as a tool for predicting response to therapy, provide rapid and effective tumor-immune state characterization, and ultimately lead to optimization of personalized immunotherapy. Citation Format: do Yofe, Hanjie Li, Anne van der Leun, Yaniv Lubling, Dikla Gelbard, Alexander C. J. van Akkooi, Amos Tanay, Ton N.M. Schumacher, Ido Amit. Single-cell analysis illuminates the gradients of immune cell functional states within human melanoma tumors, and facilitates characterization of tumor-reactive T-cells [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B054.

Transcription factor binding site clusters identify target genes with similar tissue-wide expression and buffer against mutations

Background: The distribution and composition of cis-regulatory modules composed of transcription factor (TF) binding site (TFBS) clusters in promoters substantially determine gene expression patterns and TF targets. TF knockdown experiments have revealed that TF binding profiles and gene expression levels are correlated. We use TFBS features within accessible promoter intervals to predict genes with similar tissue-wide expression patterns and TF targets. Methods: Genes with correlated expression patterns across 53 tissues and TF targets were respectively identified from Bray-Curtis Similarity and TF knockdown experiments. Corresponding promoter sequences were reduced to DNase I-accessible intervals; TFBSs were then identified within these intervals using information theory-based position weight matrices for each TF (iPWMs) and clustered. Features from information-dense TFBS clusters predicted these genes with machine learning classifiers, which were evaluated for accuracy, specificity and sensitivity. Mutations in TFBSs were analyzed to in silico examine their impact on cluster densities and the regulatory states of target genes. Results: We initially chose the glucocorticoid receptor gene ( NR3C1), whose regulation has been extensively studied, to test this approach. SLC25A32 and TANK were found to exhibit the most similar expression patterns to NR3C1. A Decision Tree classifier exhibited the largest area under the Receiver Operating Characteristic (ROC) curve in detecting such genes. Target gene prediction was confirmed using siRNA knockdown of TFs, which was found to be more accurate than those predicted after CRISPR/CAS9 inactivation. In-silico mutation analyses of TFBSs also revealed that one or more information-dense TFBS clusters in promoters are required for accurate target gene prediction. Conclusions: Machine learning based on TFBS information density, organization, and chromatin accessibility accurately identifies gene targets with comparable tissue-wide expression patterns. Multiple information-dense TFBS clusters in promoters appear to protect promoters from effects of deleterious binding site mutations in a single TFBS that would otherwise alter regulation of these genes.

The Limits of Phenotypic Plasticity in the Actin Cytoskeleton Revealed by Unbiased Chemical Perturbation

Numerous proteins and pathways regulate F-actin organisation, meaning that, in combinatorial terms, an almost unlimited number of regulatory states are conceivable. Consequently, the potential for plasticity in F-actin phenotypes appears virtually unbounded. To estimate the actual limits of F-actin phenotype plasticity, we used a library of 114,400 structurally diverse compounds to induce unbiased chemical perturbations. Remarkably, just 25 distinct, recurrent F-actin phenotypes emerged. Correspondingly, select compounds with distinct molecular mechanisms induced equivalent phenotypes, suggesting that these recurring phenotypes reflect a low number of equilibrium or attractor states in actin organisation. This was supported by dynamic analyses comparing phenotype trajectories over time, showing how initially divergent phenotypes ultimately converged into equivalent end-states. We propose that infrequent attractor states in the actin phenotypic landscape reflect a channelling of high perturbative diversity into low phenotypic variety and consider how this may suppress chaotic outcomes during the evolution of this complex, functionally integral system.

Integrative analysis of single-cell expression data reveals distinct regulatory states in bidirectional promoters

BackgroundBidirectional promoters (BPs) are prevalent in eukaryotic genomes. However, it is poorly understood how the cell integrates different epigenomic information, such as transcription factor (TF) binding and chromatin marks, to drive gene expression at BPs. Single-cell sequencing technologies are revolutionizing the field of genome biology. Therefore, this study focuses on the integration of single-cell RNA-seq data with bulk ChIP-seq and other epigenetics data, for which single-cell technologies are not yet established, in the context of BPs.ResultsWe performed integrative analyses of novel human single-cell RNA-seq (scRNA-seq) data with bulk ChIP-seq and other epigenetics data. scRNA-seq data revealed distinct transcription states of BPs that were previously not recognized. We find associations between these transcription states to distinct patterns in structural gene features, DNA accessibility, histone modification, DNA methylation and TF binding profiles.ConclusionsOur results suggest that a complex interplay of all of these elements is required to achieve BP-specific transcriptional output in this specialized promoter configuration. Further, our study implies that novel statistical methods can be developed to deconvolute masked subpopulations of cells measured with different bulk epigenomic assays using scRNA-seq data.

Emergence of form in embryogenesis.

The development of form in an embryo is the result of a series of topological and informational symmetry breakings. We introduce the vector–reaction–diffusion–drift (VRDD) system where the limit cycle of spatial dynamics is morphogen concentrations with Dirac delta-type distributions. This is fundamentally different from the Turing reaction–diffusion system, as VRDD generates system-wide broken symmetry. We developed ‘fundamental forms’ from spherical blastula with a single organizing axis (rotational symmetry), double axis (mirror symmetry) and triple axis (no symmetry operator in three dimensions). We then introduced dynamics for cell differentiation, where genetic regulatory states are modelled as a finite-state machine (FSM). The state switching of an FSM is based on local morphogen concentrations as epigenetic information that changes dynamically. We grow complicated forms hierarchically in spatial subdomains using the FSM model coupled with the VRDD system. Using our integrated simulation model with four layers (topological, physical, chemical and regulatory), we generated life-like forms such as hydra. Genotype–phenotype mapping was investigated with continuous and jump mutations. Our study can have applications in morphogenetic engineering, soft robotics and biomimetic design.

Canonical and non-canonical Wnt signaling pathways define the expression domains of Frizzled 5/8 and Frizzled 1/2/7 along the early anterior-posterior axis in sea urchin embryos

The spatiotemporal expression of Frizzled receptors is critical for patterning along the early anterior-posterior axis during embryonic development in many animal species. However, the molecular mechanisms that regulate the expression of Frizzled receptors are incompletely understood in any species. In this study, I examine how the expression of two Frizzled receptors, Fzl1/2/7 and Fzl5/8, is controlled by the Wnt signaling network which directs specification and positioning of early regulatory states along the anterior-posterior (AP) axis of sea urchin embryos. I used a combination of morpholino- and dominant negative-mediated interference to knock down each Wnt signaling pathway involved in the AP Wnt signaling network. I found that the expression of zygotic fzl5/8 as well as that of the anterior neuroectoderm gene regulatory network (ANE GRN) is activated by an unknown broadly expressed regulatory state and that posterior Wnt/β-catenin signaling is necessary to down regulate fzl5/8's expression in posterior blastomeres. I show that zygotic expression of fzl1/2/7 in the equatorial ectodermal belt is dependent on an uncharacterized regulatory mechanism that works in the same cells receiving the TGF-β signals patterning this territory along the dorsal-ventral axis. In addition, my data indicate that Fzl1/2/7 signaling represses its own expression in a negative feedback mechanism. Finally, we discovered that a balance between the activities of posterior Wnt8 and anterior Dkk1 is necessary to establish the correct spatial expression of zygotic fzl12/7 expression in the equatorial ectodermal domain during blastula and gastrula stages. Together, these studies lead to a better understanding of the complex interactions among the three Wnt signaling pathway governing AP axis specification and patterning in sea urchin embryos.