scholarly journals Data-driven polymer model for mechanistic exploration of diploid genome organization

2020 ◽  
Author(s):  
Yifeng Qi ◽  
Alejandro Reyes ◽  
Sarah E. Johnstone ◽  
Martin J. Aryee ◽  
Bradley E. Bernstein ◽  
...  
Keyword(s):  
Nuclear Localization ◽  
Genome Organization ◽  
Large Scale ◽  
Transcriptional Activity ◽  
Molecular Mechanisms ◽  
Mechanistic Model ◽  
Genome Structure ◽  
Data Driven ◽  
Experimental Measurements ◽  
Polymer Model

AbstractChromosomes are positioned non-randomly inside the nucleus to coordinate with their transcriptional activity. The molecular mechanisms that dictate the global genome organization and the nuclear localization of individual chromosomes are not fully understood. We introduce a polymer model to study the organization of the diploid human genome: it is data-driven as all parameters can be derived from Hi-C data; it is also a mechanistic model since the energy function is explicitly written out based on a few biologically motivated hypotheses. These two features distinguish the model from existing approaches and make it useful both for reconstructing genome structures and for exploring the principles of genome organization. We carried out extensive validations to show that simulated genome structures reproduce a wide variety of experimental measurements, including chromosome radial positions and spatial distances between homologous pairs. Detailed mechanistic investigations support the importance of both specific inter-chromosomal interactions and centromere clustering for chromosome positioning. We anticipate the polymer model, when combined with Hi-C experiments, to be a powerful tool for investigating large scale rearrangements in genome structure upon cell differentiation and tumor progression.

scholarly journals Data-Driven Polymer Model for Mechanistic Exploration of Diploid Genome Organization

2020 ◽  
Vol 119 (9) ◽  
pp. 1905-1916
Author(s):  
Yifeng Qi ◽  
Alejandro Reyes ◽  
Sarah E. Johnstone ◽  
Martin J. Aryee ◽  
Bradley E. Bernstein ◽  
...  
Keyword(s):  
Genome Organization ◽  
Data Driven ◽  
Polymer Model ◽  
Diploid Genome

scholarly journals Generation of dynamic three-dimensional genome structure through phase separation of chromatin

2021 ◽  
Author(s):  
Shin Fujishiro ◽  
Masaki Sasai
Keyword(s):  
Phase Separation ◽  
Genome Organization ◽  
Critical Role ◽  
Genome Structure ◽  
Three Dimensional ◽  
Human Cells ◽  
Polymer Model ◽  
Interphase Nuclei ◽  
Dynamic Genome ◽  
The Impact

Three-dimensional genome organization plays a critical role in DNA function. Flexible chromatin structure suggested that the genome is phase-separated to form A/B compartments in interphase nuclei. Here, we examined this hypothesis by developing a polymer model of the whole genome of human cells and assessing the impact of phase separation on genome structure. Upon entry to the G1 phase, the simulated genome expanded according to heterogeneous repulsion among chromatin chains, which moved chromatin heterogeneously, inducing phase separation. This repulsion-driven phase separation quantitatively reproduces the experimentally observed chromatin domains, A/B compartments, lamina-associated domains, and nucleolus-associated domains, consistently explaining nuclei of different human cells and predicting their dynamic fluctuations. We propose that phase separation induced by heterogeneous repulsive interactions among chromatin chains largely determines dynamic genome organization.

The Anti-Atherogenic Properties of Sesamin are Mediated via Improved Macrophage Cholesterol Efflux Through PPARγ1-LXRα and MAPK Signaling

2014 ◽  
Vol 84 (1-2) ◽  
pp. 79-91 ◽  
Author(s):  
Amin F. Majdalawieh ◽  
Hyo-Sung Ro
Keyword(s):  
Cholesterol Efflux ◽  
Transcriptional Activity ◽  
Molecular Mechanisms ◽  
Foam Cell ◽  
Mapk Signaling ◽  
Luciferase Reporter ◽  
Foam Cell Formation ◽  
Dependent Manner ◽  
Concentration Dependent Manner ◽  
Macrophage Cholesterol Efflux

Background: Foam cell formation resulting from disrupted macrophage cholesterol efflux, which is triggered by PPARγ1 and LXRα, is a hallmark of atherosclerosis. Sesamin and sesame oil exert anti-atherogenic effects in vivo. However, the exact molecular mechanisms underlying such effects are not fully understood. Aim: This study examines the potential effects of sesamin (0, 25, 50, 75, 100 μM) on PPARγ1 and LXRα expression and transcriptional activity as well as macrophage cholesterol efflux. Methods: PPARγ1 and LXRα expression and transcriptional activity are assessed by luciferase reporter assays. Macrophage cholesterol efflux is evaluated by ApoAI-specific cholesterol efflux assays. Results: The 50 μM, 75 μM, and 100 μM concentrations of sesamin up-regulated the expression of PPARγ1 (p< 0.001, p < 0.001, p < 0.001, respectively) and LXRα (p = 0.002, p < 0.001, p < 0.001, respectively) in a concentration-dependent manner. Moreover, 75 μM and 100 μM concentrations of sesamin led to 5.2-fold (p < 0.001) and 6.0-fold (p<0.001) increases in PPAR transcriptional activity and 3.9-fold (p< 0.001) and 4.2-fold (p < 0.001) increases in LXR transcriptional activity, respectively, in a concentration- and time-dependent manner via MAPK signaling. Consistently, 50 μM, 75 μM, and 100 μM concentrations of sesamin improved macrophage cholesterol efflux by 2.7-fold (p < 0.001), 4.2-fold (p < 0.001), and 4.2-fold (p < 0.001), respectively, via MAPK signaling. Conclusion: Our findings shed light on the molecular mechanism(s) underlying sesamin’s anti-atherogenic effects, which seem to be due, at least in part, to its ability to up-regulate PPARγ1 and LXRα expression and transcriptional activity, improving macrophage cholesterol efflux. We anticipate that sesamin may be used as a therapeutic agent for treating atherosclerosis.

scholarly journals TEAD4 modulated LncRNA MNX1-AS1 contributes to gastric cancer progression partly through suppressing BTG2 and activating BCL2

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
You Shuai ◽  
Zhonghua Ma ◽  
Weitao Liu ◽  
Tao Yu ◽  
Changsheng Yan ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Progression ◽  
Molecular Mechanisms ◽  
Mechanistic Model ◽  
Ectopic Expression ◽  
Luciferase Reporter ◽  
Migration And Invasion ◽  
Tissue Samples ◽  
Reporter Assays

Abstract Background Gastric cancer (GC) is the third leading cause of cancer-related mortality globally. Long noncoding RNAs (lncRNAs) are dysregulated in obvious malignancies including GC and exploring the regulatory mechanisms underlying their expression is an attractive research area. However, these molecular mechanisms require further clarification, especially upstream mechanisms. Methods LncRNA MNX1-AS1 expression in GC tissue samples was investigated via microarray analysis and further determined in a cohort of GC tissues via quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays. Cell proliferation and flow cytometry assays were performed to confirm the roles of MNX1-AS1 in GC proliferation, cell cycle regulation, and apoptosis. The influence of MNX1-AS1 on GC cell migration and invasion was explored with Transwell assays. A xenograft tumour model was established to verify the effects of MNX1-AS1 on in vivo tumourigenesis. The TEAD4-involved upstream regulatory mechanism of MNX1-AS1 was explored through ChIP and luciferase reporter assays. The mechanistic model of MNX1-AS1 in regulating gene expression was further detected by subcellular fractionation, FISH, RIP, ChIP and luciferase reporter assays. Results It was found that MNX1-AS1 displayed obvious upregulation in GC tissue samples and cell lines, and ectopic expression of MNX1-AS1 predicted poor clinical outcomes for patients with GC. Overexpressed MNX1-AS1 expression promoted proliferation, migration and invasion of GC cells markedly, whereas decreased MNX1-AS1 expression elicited the opposite effects. Consistent with the in vitro results, MNX1-AS1 depletion effectively inhibited the growth of xenograft tumour in vivo. Mechanistically, TEAD4 directly bound the promoter region of MNX1-AS1 and stimulated the transcription of MNX1-AS1. Furthermore, MNX1-AS1 can sponge miR-6785-5p to upregulate the expression of BCL2 in GC cells. Meanwhile, MNX1-AS1 suppressed the transcription of BTG2 by recruiting polycomb repressive complex 2 to BTG2 promoter regions. Conclusions Our findings demonstrate that MNX1-AS1 may be able to serve as a prognostic indicator in GC patients and that TEAD4-activatd MNX1-AS1 can promote GC progression through EZH2/BTG2 and miR-6785-5p/BCL2 axes, implicating it as a novel and potent target for the treatment of GC.

scholarly journals HP1 drives de novo 3D genome reorganization in early Drosophila embryos

Nature ◽  
2021 ◽  
Author(s):  
Fides Zenk ◽  
Yinxiu Zhan ◽  
Pavel Kos ◽  
Eva Löser ◽  
Nazerke Atinbayeva ◽  
...  
Keyword(s):  
Genome Organization ◽  
Molecular Mechanisms ◽  
High Throughput Sequencing ◽  
De Novo ◽  
Early Embryo ◽  
Heterochromatin Protein ◽  
Chromosome Conformation ◽  
3D Genome ◽  
Genome Reorganization

AbstractFundamental features of 3D genome organization are established de novo in the early embryo, including clustering of pericentromeric regions, the folding of chromosome arms and the segregation of chromosomes into active (A-) and inactive (B-) compartments. However, the molecular mechanisms that drive de novo organization remain unknown1,2. Here, by combining chromosome conformation capture (Hi-C), chromatin immunoprecipitation with high-throughput sequencing (ChIP–seq), 3D DNA fluorescence in situ hybridization (3D DNA FISH) and polymer simulations, we show that heterochromatin protein 1a (HP1a) is essential for de novo 3D genome organization during Drosophila early development. The binding of HP1a at pericentromeric heterochromatin is required to establish clustering of pericentromeric regions. Moreover, HP1a binding within chromosome arms is responsible for overall chromosome folding and has an important role in the formation of B-compartment regions. However, depletion of HP1a does not affect the A-compartment, which suggests that a different molecular mechanism segregates active chromosome regions. Our work identifies HP1a as an epigenetic regulator that is involved in establishing the global structure of the genome in the early embryo.

scholarly journals EGCG binds intrinsically disordered N-terminal domain of p53 and disrupts p53-MDM2 interaction

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jing Zhao ◽  
Alan Blayney ◽  
Xiaorong Liu ◽  
Lauren Gandy ◽  
Weihua Jin ◽  
...  
Keyword(s):  
Large Scale ◽  
Molecular Mechanisms ◽  
Epigallocatechin Gallate ◽  
Cancer Drug ◽  
Dynamic Interactions ◽  
Cancer Drug Discovery ◽  
Intrinsically Disordered ◽  
Terminal Domain ◽  
Cancerous Cells

AbstractEpigallocatechin gallate (EGCG) from green tea can induce apoptosis in cancerous cells, but the underlying molecular mechanisms remain poorly understood. Using SPR and NMR, here we report a direct, μM interaction between EGCG and the tumor suppressor p53 (KD = 1.6 ± 1.4 μM), with the disordered N-terminal domain (NTD) identified as the major binding site (KD = 4 ± 2 μM). Large scale atomistic simulations (>100 μs), SAXS and AUC demonstrate that EGCG-NTD interaction is dynamic and EGCG causes the emergence of a subpopulation of compact bound conformations. The EGCG-p53 interaction disrupts p53 interaction with its regulatory E3 ligase MDM2 and inhibits ubiquitination of p53 by MDM2 in an in vitro ubiquitination assay, likely stabilizing p53 for anti-tumor activity. Our work provides insights into the mechanisms for EGCG’s anticancer activity and identifies p53 NTD as a target for cancer drug discovery through dynamic interactions with small molecules.

scholarly journals Erythrocytes 3D genome organization in vertebrates

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Anastasia Ryzhkova ◽  
Alena Taskina ◽  
Anna Khabarova ◽  
Veniamin Fishman ◽  
Nariman Battulin
Keyword(s):  
Blood Cells ◽  
Genome Organization ◽  
Large Scale ◽  
Chromatin Condensation ◽  
Erythroid Differentiation ◽  
Interaction Patterns ◽  
3D Interaction ◽  
Interphase Chromosome ◽  
3D Genome ◽  
Contact Maps

AbstractGeneration of mature red blood cells, consisting mainly of hemoglobin, is a remarkable example of coordinated action of various signaling networks. Chromatin condensation is an essential step for terminal erythroid differentiation and subsequent nuclear expulsion in mammals. Here, we profiled 3D genome organization in the blood cells from ten species belonging to different vertebrate classes. Our analysis of contact maps revealed a striking absence of such 3D interaction patterns as loops or TADs in blood cells of all analyzed representatives. We also detect large-scale chromatin rearrangements in blood cells from mammals, birds, reptiles and amphibians: their contact maps display strong second diagonal pattern, representing an increased frequency of long-range contacts, unrelated to TADs or compartments. This pattern is completely atypical for interphase chromosome structure. We confirm that these principles of genome organization are conservative in vertebrate erythroid cells.

scholarly journals Accelerating In-Transit Co-Processing for Scientific Simulations Using Region-Based Data-Driven Analysis

Algorithms ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 154
Author(s):  
Marcus Walldén ◽  
Masao Okita ◽  
Fumihiko Ino ◽  
Dimitris Drikakis ◽  
Ioannis Kokkinakis
Keyword(s):  
Large Scale ◽  
Data Driven ◽  
Data Sets ◽  
Output Constraints ◽  
Data Driven Approach ◽  
Scientific Simulations ◽  
Multiple Metrics ◽  
In Transit ◽  
Multiple Compression ◽  
Large Scale Simulations

Increasing processing capabilities and input/output constraints of supercomputers have increased the use of co-processing approaches, i.e., visualizing and analyzing data sets of simulations on the fly. We present a method that evaluates the importance of different regions of simulation data and a data-driven approach that uses the proposed method to accelerate in-transit co-processing of large-scale simulations. We use the importance metrics to simultaneously employ multiple compression methods on different data regions to accelerate the in-transit co-processing. Our approach strives to adaptively compress data on the fly and uses load balancing to counteract memory imbalances. We demonstrate the method’s efficiency through a fluid mechanics application, a Richtmyer–Meshkov instability simulation, showing how to accelerate the in-transit co-processing of simulations. The results show that the proposed method expeditiously can identify regions of interest, even when using multiple metrics. Our approach achieved a speedup of 1.29× in a lossless scenario. The data decompression time was sped up by 2× compared to using a single compression method uniformly.

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