Mesoscale modeling reveals formation of an epigenetically driven HOXC gene hub.
Ontology highlight
ABSTRACT:
SUBMITTER: Bascom GD
PROVIDER: S-EPMC6421463 | biostudies-literature | 2019 Mar
REPOSITORIES: biostudies-literature
Publications
Mesoscale modeling reveals formation of an epigenetically driven HOXC gene hub.
Bascom Gavin D GD Myers Christopher G CG Schlick Tamar T
Proceedings of the National Academy of Sciences of the United States of America 20190204 11
Gene expression is orchestrated at the structural level by nucleosome positioning, histone tail acetylation, and linker histone (LH) binding. Here, we integrate available data on nucleosome positioning, nucleosome-free regions (NFRs), acetylation islands, and LH binding sites to "fold" in silico the 55-kb HOXC gene cluster and investigate the role of each feature on the gene's folding. The gene cluster spontaneously forms a dynamic connection hub, characterized by hierarchical loops which accomm ...[more]
Similar Datasets
Project description:While it is well-recognized that chromatin loops play an important role in gene regulation, structural details regarding higher order chromatin loops are only emerging. Here we present a systematic study of restrained chromatin loops ranging from 25 to 427 nucleosomes (fibers of 5-80 Kb DNA in length), mimicking gene elements studied by 3C contact data. We find that hierarchical looping represents a stable configuration that can effectively bring distant regions of the GATA-4 gene together, satisfying connections reported by 3C experiments. Additionally, we find that restrained chromatin fibers larger than 100 nucleosomes (∼20Kb) form closed plectonemes, whereas fibers shorter than 100 nucleosomes form simple hairpin loops. By studying the dependence of loop structures on internal parameters, we show that loop features are sensitive to linker histone concentration, loop length, divalent ions, and DNA linker length. Specifically, increasing loop length, linker histone concentration, and divalent ion concentration are associated with increased persistence length (or decreased bending), while varying DNA linker length in a manner similar to experimentally observed "nucleosome free regions" (found near transcription start sites) disrupts intertwining and leads to loop opening and increased persistence length in linker histone depleted (-LH) fibers. Chromatin fiber structure sensitivity to these parameters, all of which vary throughout the cell cycle, tissue type, and species, suggests that caution is warranted when using uniform polymer models to fit chromatin conformation capture genome-wide data. Furthermore, the folding geometry we observe near the transcription initiation site of the GATA-4 gene suggests that hierarchical looping provides a structural mechanism for gene inhibition, and offers tunable parameters for design of gene regulation elements.
| S-EPMC6268121 | biostudies-literature
Project description:Recent advances in brain imaging techniques, measurement approaches, and storage capacities have provided an unprecedented supply of high temporal resolution neural data. These data present a remarkable opportunity to gain a mechanistic understanding not just of circuit structure, but also of circuit dynamics, and its role in cognition and disease. Such understanding necessitates a description of the raw observations, and a delineation of computational models and mathematical theories that accurately capture fundamental principles behind the observations. Here we review recent advances in a range of modeling approaches that embrace the temporally-evolving interconnected structure of the brain and summarize that structure in a dynamic graph. We describe recent efforts to model dynamic patterns of connectivity, dynamic patterns of activity, and patterns of activity atop connectivity. In the context of these models, we review important considerations in statistical testing, including parametric and non-parametric approaches. Finally, we offer thoughts on careful and accurate interpretation of dynamic graph architecture, and outline important future directions for method development.
| S-EPMC5738302 | biostudies-literature
Project description:ABSTRACTAfter decades of debate about the existence of non‐genetic inheritance, the focus is now slowly shifting towards dissecting its underlying mechanisms. Here, we propose a new mechanism that, by integrating non‐genetic and genetic inheritance, may help build the long‐sought inclusive vision of evolution. After briefly reviewing the wealth of evidence documenting the existence and ubiquity of non‐genetic inheritance in a table, we review the categories of mechanisms of parent–offspring resemblance that underlie inheritance. We then review several lines of argument for the existence of interactions between non‐genetic and genetic components of inheritance, leading to a discussion of the contrasting timescales of action of non‐genetic and genetic inheritance. This raises the question of how the fidelity of the inheritance system can match the rate of environmental variation. This question is central to understanding the role of different inheritance systems in evolution. We then review and interpret evidence indicating the existence of shifts from inheritance systems with low to higher transmission fidelity. Based on results from different research fields we propose a conceptual hypothesis linking genetic and non‐genetic inheritance systems. According to this hypothesis, over the course of generations, shifts among information systems allow gradual matching between the rate of environmental change and the inheritance fidelity of the corresponding response. A striking conclusion from our review is that documented shifts between types of inherited non‐genetic information converge towards epigenetics (i.e. inclusively heritable molecular variation in gene expression without change in DNA sequence). We then interpret the well‐documented mutagenicity of epigenetic marks as potentially generating a final shift from epigenetic to genetic encoding. This sequence of shifts suggests the existence of a relay in inheritance systems from relatively labile ones to gradually more persistent modes of inheritance, a relay that could constitute a new mechanistic basis for the long‐proposed, but still poorly documented, hypothesis of genetic assimilation. A profound difference between the genocentric and the inclusive vision of heredity revealed by the genetic assimilation relay proposed here lies in the fact that a given form of inheritance can affect the rate of change of other inheritance systems. To explore the consequences of such inter‐connection among inheritance systems, we briefly review published theoretical models to build a model of genetic assimilation focusing on the shift in the engraving of environmentally induced phenotypic variation into the DNA sequence. According to this hypothesis, when environmental change remains stable over a sufficient number of generations, the relay among inheritance systems has the potential to generate a form of genetic assimilation. In this hypothesis, epigenetics appears as a hub by which non‐genetically inherited environmentally induced variation in traits can become genetically encoded over generations, in a form of epigenetically facilitated mutational assimilation. Finally, we illustrate some of the major implications of our hypothetical framework, concerning mutation randomness, the central dogma of molecular biology, concepts of inheritance and the curing of inherited disorders, as well as for the emergence of the inclusive evolutionary synthesis.
| S-EPMC6378602 | biostudies-other
Project description:Formation of bacterial colonies as biofilm on the surface/interface of various objects has the potential to impact not only human health and disease but also energy and environmental considerations. Biofilms can be regarded as soft materials, and comprehension of their shear response to external forces is a key element to the fundamental understanding. A mesoscale model has been presented in this article based on digitization of a biofilm microstructure. Its response under externally applied shear load is analyzed. Strain stiffening type behavior is readily observed under high strain loads due to the unfolding of chains within soft polymeric substrate. Sustained shear loading of the biofilm network results in strain localization along the diagonal direction. Rupture of the soft polymeric matrix can potentially reduce the intercellular interaction between the bacterial cells. Evolution of stiffness within the biofilm network under shear reveals two regimes: a) initial increase in stiffness due to strain stiffening of polymer matrix, and b) eventual reduction in stiffness because of tear in polymeric substrate.
| S-EPMC5091762 | biostudies-literature
Project description:Retinoblastoma (Rb) is the most common childhood malignancy initiated by biallelic mutation in RB1 gene and driven by various epigenetic events including DNA methylation and microRNA dysregulation. Hence, understanding the key genes that are critically modulated by epigenetic modifications in RB1 -/- cells is very important to identify prominent biomarkers and therapeutic targets of Rb. In this study, we for the first time have integrated various Rb microarray NCBI-GEO datasets including DNA Methylation (GSE57362), miRNA (GSE7072) and mRNA (GSE110811) to comprehensively investigate the epigenetic consequences of RB loss in retinoblastoma tumors and identify genes with the potential to serve as early diagnostic markers and therapeutic targets for Rb. Interestingly, the GEO2R and co-expression network analysis have identified three genes namely E2F3, ESR1, and UNC5D that are significantly deregulated by modified DNA methylation, mRNA and microRNA expression in Rb tumors. Due to their recognition in all epigenetic, transcriptomic, and miRNA datasets, we have termed these genes as "common genes". The results of our integrative bioinformatics analysis were validated in vitro by studying the gene and protein expression of these common genes in Y79, WERI-Rb-1, Rb cell lines and non-tumorigenic retinal pigment epithelial cell line (hTERT-RPE). The expression of E2F3 and UNC5D were up-regulated and that of ESR1 was down-regulated in Rb tumor cells when compared to that in non-tumorigenic hTERT-RPE cells. More importantly, UNC5D, a potent tumor suppressor gene in most cancers is significantly up-regulated in Y79 and Weri Rb1 cells, which, in turn, questions its anti-cancer properties. Together, our study shows that E2F3, ESR1, and UNC5D may be crucially involved in Rb tumorigenesis and possess the potential to act as early diagnostic biomarkers and therapeutic targets of Rb.
| S-EPMC8960645 | biostudies-literature
Project description:High-performance solution-processed organic semiconductors maintain macroscopic functionality even in the presence of microscopic disorder. Here we show that the functional robustness of certain organic materials arises from the ability of molecules to create connected mesoscopic electrical networks, even in the absence of periodic order. The hierarchical network structures of two families of important organic photovoltaic acceptors, functionalized fullerenes and perylene diimides, are analyzed using a newly developed graph methodology. The results establish a connection between network robustness and molecular topology, and also demonstrate that solubilizing moieties play a large role in disrupting the molecular networks responsible for charge transport. A clear link is established between the success of mono and bis functionalized fullerene acceptors in organic photovoltaics and their ability to construct mesoscopically connected electrical networks over length scales of 10 nm.
| S-EPMC4104918 | biostudies-literature
Project description:Chemical synapses exhibit a diverse array of internal mechanisms that affect the dynamics of transmission efficacy. Many of these processes, such as release of neurotransmitter and vesicle recycling, depend strongly on activity-dependent influx and accumulation of Ca2+. To model how each of these processes may affect the processing of information in neural circuits, and how their dysfunction may lead to disease states, requires a computationally efficient modelling framework, capable of generating accurate phenomenology without incurring a heavy computational cost per synapse. Constructing a phenomenologically realistic model requires the precise characterization of the timing and probability of neurotransmitter release. Difficulties arise in that functional forms of instantaneous release rate can be difficult to extract from noisy data without running many thousands of trials, and in biophysical synapses, facilitation of per-vesicle release probability is confounded by depletion. To overcome this, we obtained traces of free Ca2+ concentration in response to various action potential stimulus trains from a molecular MCell model of a hippocampal Schaffer collateral axon. Ca2+ sensors were placed at varying distance from a voltage-dependent calcium channel (VDCC) cluster, and Ca2+ was buffered by calbindin. Then, using the calcium traces to drive deterministic state vector models of synaptotagmin 1 and 7 (Syt-1/7), which respectively mediate synchronous and asynchronous release in excitatory hippocampal synapses, we obtained high-resolution profiles of instantaneous release rate, to which we applied functional fits. Synchronous vesicle release occurred predominantly within half a micron of the source of spike-evoked Ca2+ influx, while asynchronous release occurred more consistently at all distances. Both fast and slow mechanisms exhibited multi-exponential release rate curves, whose magnitudes decayed exponentially with distance from the Ca2+ source. Profile parameters facilitate on different time scales according to a single, general facilitation function. These functional descriptions lay the groundwork for efficient mesoscale modelling of vesicular release dynamics.
| S-EPMC9119629 | biostudies-literature
Project description:BackgroundOne of the most frequent malignancies is lung carcinoma which poses heavy burden on the global health. The link among differentially expressed genes (DEGs) and lung cancer patients' clinical outcomes was still missing. In this study, we integrated transcriptome data with clinical data to investigate the relationship between them in lung carcinoma patients.MethodsTo begin, DEGs were identified using the Gene Expression Omnibus (GEO) gene expression pattern (GSE180347). Then, these DEGs are being searched in the TCGA database using the DEGs collected in the preceding phase. The Kaplan-Meier plotter was then used to assess the predictive value of these DEGs in patients with lung cancer.ResultsOur study revealed a total of 45 DEGs, 15 of which were up-regulated and 30 of which were down-regulated. These DEGs were mostly enriched in cytokine receptor binding and cytokine activity, according to GO enrichment analysis. These DEGs were mostly enriched in cytokine-cytokine receptor interaction, according to KEGG enrichment analysis. Based on the PPI network, which comprises of 12 DEGs, a major module was discovered. They are mostly interested in cytotoxicity mediated by natural killer cells. Among all 45 DEGs, the mutations of NCAM1 account for the most cases in TCGA database with a percentage above 15%. Among the 12 DEGs in the significant module, higher expression of FAS, GPR29, HAVCR2, and NCAM1 exhibits longer survival time with hazard ratio and 95% confident interval of 0.79 (0.69-0.89), 0.80 (0.70-0.90), 0.71 (0.60-0.84), and 0.73 (0.62-0.86), respectively. However, higher expression of FCGR3A and IFNG exhibits shorter survival time with hazard ratio and 95% confident interval of 1.50 (1.32-1.71) and 1.15 (1.02-1.31), respectively.ConclusionOur results demonstrate significant correlation between some DEGs and the survival outcome in lung adenocarcinomas patients, providing a comprehensive bioinformatics study in anticipation of future molecular mechanisms and biomarker studies.
| S-EPMC9276499 | biostudies-literature
Project description:BackgroundImmunoglobulin A nephropathy (IgAN) is the most common primary glomerulopathy worldwide. However, the molecular events underlying IgAN remain to be fully elucidated. This study aimed to identify novel biomarkers of IgAN through bioinformatics analysis and elucidate the possible molecular mechanism.MethodsBased on the microarray datasets GSE93798 and GSE37460 downloaded from the Gene Expression Omnibus database, the differentially expressed genes (DEGs) between IgAN samples and normal controls were identified. Using the DEGs, we further performed a series of functional enrichment analyses. Protein-protein interaction (PPI) networks of the DEGs were constructed using the STRING online search tool and were visualized using Cytoscape. Next, hub genes were identified and the most important module among the DEGs, Biological Networks Gene Ontology tool (BiNGO), was used to elucidate the molecular mechanism of IgAN.ResultsIn total, 148 DEGs were identified, comprising 53 upregulated genes and 95 downregulated genes. Gene Ontology (GO) analysis indicated that the DEGs for IgAN were mainly enriched in extracellular exosome, region and space, fibroblast growth factor stimulus, inflammatory response, and innate immunity. Module analysis showed that genes in the top 1 significant module of the PPI network were mainly associated with innate immune response, integrin-mediated signaling pathway and inflammatory response. The top 10 hub genes were constructed in the PPI network, which could well distinguish the IgAN and control group in monocyte and tissue samples. We finally identified the integrin subunit beta 2 (ITGB2) and Fc fragment of IgE receptor Ig (FCER1G) genes that may play important roles in the development of IgAN.ConclusionsWe identified key genes along with the pathways that were most closely related to IgAN initiation and progression. Our results provide a more detailed molecular mechanism for the development of IgAN and novel candidate gene targets of IgAN.
| S-EPMC7487908 | biostudies-literature
Project description:An emerging view regarding neurodegenerative diseases is that discreet seeding of misfolded proteins leads to widespread pathology. However, the mechanisms by which misfolded proteins seed distinct brain regions and cause differential whole-brain pathology remain elusive. We used whole-brain tissue clearing and high-resolution imaging to longitudinally map pathology in an α-synuclein pre-formed fibril injection model of Parkinson's disease. Cleared brains at different time points of disease progression were quantitatively segmented and registered to a standardized atlas, revealing distinct phases of spreading and decline. We then fit a computational model with parameters that represent α-synuclein pathology spreading, aggregation, decay, and gene expression pattern to this longitudinal dataset. Remarkably, our model can generalize to predicting α-synuclein spreading patterns from several distinct brain regions and can even estimate their origins. This model empowers mechanistic understanding and accurate prediction of disease progression, paving the way for the development and testing of therapeutic interventions.
| S-EPMC10840492 | biostudies-literature