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Tolokh IS, Kinney NA, Sharakhov IV, Onufriev AV. Strong interactions between highly dynamic lamina-associated domains and the nuclear envelope stabilize the 3D architecture of Drosophila interphase chromatin. Epigenetics Chromatin 2023; 16:21. [PMID: 37254161 PMCID: PMC10228000 DOI: 10.1186/s13072-023-00492-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 05/04/2023] [Indexed: 06/01/2023] Open
Abstract
BACKGROUND Interactions among topologically associating domains (TADs), and between the nuclear envelope (NE) and lamina-associated domains (LADs) are expected to shape various aspects of three-dimensional (3D) chromatin structure and dynamics; however, relevant genome-wide experiments that may provide statistically significant conclusions remain difficult. RESULTS We have developed a coarse-grained dynamical model of D. melanogaster nuclei at TAD resolution that explicitly accounts for four distinct epigenetic classes of TADs and LAD-NE interactions. The model is parameterized to reproduce the experimental Hi-C map of the wild type (WT) nuclei; it describes time evolution of the chromatin over the G1 phase of the interphase. The simulations include an ensemble of nuclei, corresponding to the experimentally observed set of several possible mutual arrangements of chromosomal arms. The model is validated against multiple structural features of chromatin from several different experiments not used in model development. Predicted positioning of all LADs at the NE is highly dynamic-the same LAD can attach, detach and move far away from the NE multiple times during interphase. The probabilities of LADs to be in contact with the NE vary by an order of magnitude, despite all having the same affinity to the NE in the model. These probabilities are mostly determined by a highly variable local linear density of LADs along the genome, which also has the same strong effect on the predicted positioning of individual TADs -- higher probability of a TAD to be near NE is largely determined by a higher linear density of LADs surrounding this TAD. The distribution of LADs along the chromosome chains plays a notable role in maintaining a non-random average global structure of chromatin. Relatively high affinity of LADs to the NE in the WT nuclei substantially reduces sensitivity of the global radial chromatin distribution to variations in the strength of TAD-TAD interactions compared to the lamin depleted nuclei, where a small (0.5 kT) increase of cross-type TAD-TAD interactions doubles the chromatin density in the central nucleus region. CONCLUSIONS A dynamical model of the entire fruit fly genome makes multiple genome-wide predictions of biological interest. The distribution of LADs along the chromatin chains affects their probabilities to be in contact with the NE and radial positioning of highly mobile TADs, playing a notable role in creating a non-random average global structure of the chromatin. We conjecture that an important role of attractive LAD-NE interactions is to stabilize global chromatin structure against inevitable cell-to-cell variations in TAD-TAD interactions.
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Affiliation(s)
- Igor S. Tolokh
- Department of Computer Science, Virginia Tech, Blacksburg, VA 24061 USA
| | - Nicholas Allen Kinney
- Department of Computer Science, Virginia Tech, Blacksburg, VA 24061 USA
- Department of Entomology, Virginia Tech, Blacksburg, VA 24061 USA
- Edward Via College of Osteopathic Medicine, 2265 Kraft Drive, Blacksburg, VA 24060 USA
| | | | - Alexey V. Onufriev
- Department of Computer Science, Virginia Tech, Blacksburg, VA 24061 USA
- Department of Physics, Virginia Tech, Blacksburg, VA 24061 USA
- Center for Soft Matter and Biological Physics, Virginia Tech, Blacksburg, VA 24061 USA
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2
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Kamat K, Lao Z, Qi Y, Wang Y, Ma J, Zhang B. Compartmentalization with nuclear landmarks yields random, yet precise, genome organization. Biophys J 2023; 122:1376-1389. [PMID: 36871158 PMCID: PMC10111368 DOI: 10.1016/j.bpj.2023.03.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 02/19/2023] [Accepted: 03/01/2023] [Indexed: 03/06/2023] Open
Abstract
The 3D organization of eukaryotic genomes plays an important role in genome function. While significant progress has been made in deciphering the folding mechanisms of individual chromosomes, the principles of the dynamic large-scale spatial arrangement of all chromosomes inside the nucleus are poorly understood. We use polymer simulations to model the diploid human genome compartmentalization relative to nuclear bodies such as nuclear lamina, nucleoli, and speckles. We show that a self-organization process based on a cophase separation between chromosomes and nuclear bodies can capture various features of genome organization, including the formation of chromosome territories, phase separation of A/B compartments, and the liquid property of nuclear bodies. The simulated 3D structures quantitatively reproduce both sequencing-based genomic mapping and imaging assays that probe chromatin interaction with nuclear bodies. Importantly, our model captures the heterogeneous distribution of chromosome positioning across cells while simultaneously producing well-defined distances between active chromatin and nuclear speckles. Such heterogeneity and preciseness of genome organization can coexist due to the nonspecificity of phase separation and the slow chromosome dynamics. Together, our work reveals that the cophase separation provides a robust mechanism for us to produce functionally important 3D contacts without requiring thermodynamic equilibration that can be difficult to achieve.
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Affiliation(s)
- Kartik Kamat
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Zhuohan Lao
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Yifeng Qi
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Yuchuan Wang
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania
| | - Jian Ma
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts.
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3
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Abstract
Three-dimensional protein structural data at the molecular level are pivotal for successful precision medicine. Such data are crucial not only for discovering drugs that act to block the active site of the target mutant protein but also for clarifying to the patient and the clinician how the mutations harbored by the patient work. The relative paucity of structural data reflects their cost, challenges in their interpretation, and lack of clinical guidelines for their utilization. Rapid technological advancements in experimental high-resolution structural determination increasingly generate structures. Computationally, modeling algorithms, including molecular dynamics simulations, are becoming more powerful, as are compute-intensive hardware, particularly graphics processing units, overlapping with the inception of the exascale era. Accessible, freely available, and detailed structural and dynamical data can be merged with big data to powerfully transform personalized pharmacology. Here we review protein and emerging genome high-resolution data, along with means, applications, and examples underscoring their usefulness in precision medicine. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA; .,Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA;
| | - Guy Nir
- Department of Biochemistry and Molecular Biology, Department of Neuroscience, Cell Biology and Anatomy, and Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, Texas, USA
| | - Chung-Jung Tsai
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA;
| | - Feixiong Cheng
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA.,Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, Ohio, USA.,Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
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4
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Chu W, Chu X, Wang J. Uncovering the Quantitative Relationships Among Chromosome Fluctuations, Epigenetics, and Gene Expressions of Transdifferentiation on Waddington Landscape. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2103617. [PMID: 35104056 PMCID: PMC8981899 DOI: 10.1002/advs.202103617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 12/21/2021] [Indexed: 06/14/2023]
Abstract
The 3D spatial organization of the chromosomes appears to be linked to the gene function, which is cell type-specific. The chromosome structural ensemble switching model (CSESM) is developed by employing a heteropolymer model on different cell types and the important quantitative relationships among the chromosome ensemble, the epigenetic marks, and the gene expressions are uncovered, that both chromosome fluctuation and epigenetic marks have strong linear correlations with the gene expressions. The results support that the two compartments have different behaviors, corresponding to the relatively sparse and fluctuating phase (compartment A) and the relatively dense and stable phase (compartment B). Importantly, through the investigation of the transdifferentiation processes between the peripheral blood mononuclear cell (PBMC) and the bipolar neuron (BN), a quantitative description for the transdifferentiation is provided, which can be linked to the Waddington landscape. In addition, compared to the direct transdifferentiation between PBMC and BN, the transdifferentiation via the intermediate state neural progenitor cell (NPC) follows a different path (an "uphill" followed by a "downhill"). These theoretical studies bridge the gap among the chromosome fluctuations/ensembles, the epigenetics, and gene expressions in determining the cell fate.
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Affiliation(s)
- Wen‐Ting Chu
- State Key Laboratory of Electroanalytical ChemistryChangchun Institute of Applied ChemistryChinese Academy of SciencesChangchunJilin130022China
| | - Xiakun Chu
- Department of Chemistry & PhysicsState University of New York at Stony BrookStony BrookNY11794USA
| | - Jin Wang
- Department of Chemistry & PhysicsState University of New York at Stony BrookStony BrookNY11794USA
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5
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Cheng Q, Delafrouz P, Liang J, Liu C, Shen J. Modeling and simulation of cell nuclear architecture reorganization process. JOURNAL OF COMPUTATIONAL PHYSICS 2022; 449:110808. [PMID: 36185393 PMCID: PMC9524197 DOI: 10.1016/j.jcp.2021.110808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
We develop a special phase field/diffusive interface method to model the nuclear architecture reorganization process. In particular, we use a Lagrange multiplier approach in the phase field model to preserve the specific physical and geometrical constraints for the biological events. We develop several efficient and robust linear and weakly nonlinear schemes for this new model. To validate the model and numerical methods, we present ample numerical simulations which in particular reproduce several processes of nuclear architecture reorganization from the experiment literature.
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Affiliation(s)
- Qing Cheng
- Department of Mathematics,Purdue University, West Lafayette, IN 47907, USA
| | - Pourya Delafrouz
- Department of Bioengineering, University of Illinois at Chicago, SEO, MC-063, Chicago, IL, 60607-7052, USA
| | - Jie Liang
- Department of Bioengineering, University of Illinois at Chicago, SEO, MC-063, Chicago, IL, 60607-7052, USA
| | - Chun Liu
- Department of Applied Mathematics, Illinois Institute of Technology, Chicago, IL 60616, USA
| | - Jie Shen
- Department of Mathematics,Purdue University, West Lafayette, IN 47907, USA
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6
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Liu L, Zhang B, Hyeon C. Extracting multi-way chromatin contacts from Hi-C data. PLoS Comput Biol 2021; 17:e1009669. [PMID: 34871311 PMCID: PMC8675768 DOI: 10.1371/journal.pcbi.1009669] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 12/16/2021] [Accepted: 11/19/2021] [Indexed: 11/29/2022] Open
Abstract
There is a growing realization that multi-way chromatin contacts formed in chromosome structures are fundamental units of gene regulation. However, due to the paucity and complexity of such contacts, it is challenging to detect and identify them using experiments. Based on an assumption that chromosome structures can be mapped onto a network of Gaussian polymer, here we derive analytic expressions for n-body contact probabilities (n > 2) among chromatin loci based on pairwise genomic contact frequencies available in Hi-C, and show that multi-way contact probability maps can in principle be extracted from Hi-C. The three-body (triplet) contact probabilities, calculated from our theory, are in good correlation with those from measurements including Tri-C, MC-4C and SPRITE. Maps of multi-way chromatin contacts calculated from our analytic expressions can not only complement experimental measurements, but also can offer better understanding of the related issues, such as cell-line dependent assemblies of multiple genes and enhancers to chromatin hubs, competition between long-range and short-range multi-way contacts, and condensates of multiple CTCF anchors.
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Affiliation(s)
- Lei Liu
- Key Laboratory of Optical Field Manipulation of Zhejiang Province, Department of Physics, Zhejiang Sci-Tech University, Hangzhou, China
| | - Bokai Zhang
- Key Laboratory of Optical Field Manipulation of Zhejiang Province, Department of Physics, Zhejiang Sci-Tech University, Hangzhou, China
| | - Changbong Hyeon
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Korea
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7
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Liang J, Perez-Rathke A. Minimalistic 3D chromatin models: Sparse interactions in single cells drive the chromatin fold and form many-body units. Curr Opin Struct Biol 2021; 71:200-214. [PMID: 34399301 DOI: 10.1016/j.sbi.2021.06.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 06/27/2021] [Accepted: 06/29/2021] [Indexed: 11/26/2022]
Abstract
Computational three-dimensional chromatin modeling has helped uncover principles of genome organization. Here, we discuss methods for modeling three-dimensional chromatin structures, with focus on a minimalistic polymer model which inverts population Hi-C into single-cell conformations. Utilizing only basic physical properties, this model reveals that a few specific Hi-C interactions can fold chromatin into conformations consistent with single-cell imaging, Dip-C, and FISH measurements. Aggregated single-cell chromatin conformations also reproduce Hi-C frequencies. This approach allows quantification of structural heterogeneity and discovery of many-body interaction units and has revealed additional insights, including (1) topologically associating domains as a byproduct of folding driven by specific interactions, (2) cell subpopulations with different structural scaffolds are developmental stage dependent, and (3) the functional landscape of many-body units within enhancer-rich regions. We also discuss these findings in relation to the genome structure-function relationship.
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Affiliation(s)
- Jie Liang
- Center for Bioinformatics and Quantitative Biology & Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, 60612, USA.
| | - Alan Perez-Rathke
- Center for Bioinformatics and Quantitative Biology & Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, 60612, USA
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8
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Sun Q, Perez-Rathke A, Czajkowsky DM, Shao Z, Liang J. High-resolution single-cell 3D-models of chromatin ensembles during Drosophila embryogenesis. Nat Commun 2021; 12:205. [PMID: 33420075 PMCID: PMC7794469 DOI: 10.1038/s41467-020-20490-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 12/02/2020] [Indexed: 01/29/2023] Open
Abstract
Single-cell chromatin studies provide insights into how chromatin structure relates to functions of individual cells. However, balancing high-resolution and genome wide-coverage remains challenging. We describe a computational method for the reconstruction of large 3D-ensembles of single-cell (sc) chromatin conformations from population Hi-C that we apply to study embryogenesis in Drosophila. With minimal assumptions of physical properties and without adjustable parameters, our method generates large ensembles of chromatin conformations via deep-sampling. Our method identifies specific interactions, which constitute 5-6% of Hi-C frequencies, but surprisingly are sufficient to drive chromatin folding, giving rise to the observed Hi-C patterns. Modeled sc-chromatins quantify chromatin heterogeneity, revealing significant changes during embryogenesis. Furthermore, >50% of modeled sc-chromatin maintain topologically associating domains (TADs) in early embryos, when no population TADs are perceptible. Domain boundaries become fixated during development, with strong preference at binding-sites of insulator-complexes upon the midblastula transition. Overall, high-resolution 3D-ensembles of sc-chromatin conformations enable further in-depth interpretation of population Hi-C, improving understanding of the structure-function relationship of genome organization.
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Affiliation(s)
- Qiu Sun
- Shanghai Center for System Biomedicine, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Alan Perez-Rathke
- Department of Bioengineering, University of Illinois at Chicago, SEO, MC-063, Chicago, IL, 60607-7052, USA
| | - Daniel M Czajkowsky
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Zhifeng Shao
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Jie Liang
- Department of Bioengineering, University of Illinois at Chicago, SEO, MC-063, Chicago, IL, 60607-7052, USA.
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9
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Nussinov R, Jang H, Nir G, Tsai CJ, Cheng F. A new precision medicine initiative at the dawn of exascale computing. Signal Transduct Target Ther 2021; 6:3. [PMID: 33402669 PMCID: PMC7785737 DOI: 10.1038/s41392-020-00420-3] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 10/27/2020] [Accepted: 10/30/2020] [Indexed: 12/14/2022] Open
Abstract
Which signaling pathway and protein to select to mitigate the patient's expected drug resistance? The number of possibilities facing the physician is massive, and the drug combination should fit the patient status. Here, we briefly review current approaches and data and map an innovative patient-specific strategy to forecast drug resistance targets that centers on parallel (or redundant) proliferation pathways in specialized cells. It considers the availability of each protein in each pathway in the specific cell, its activating mutations, and the chromatin accessibility of its encoding gene. The construction of the resulting Proliferation Pathway Network Atlas will harness the emerging exascale computing and advanced artificial intelligence (AI) methods for therapeutic development. Merging the resulting set of targets, pathways, and proteins, with current strategies will augment the choice for the attending physicians to thwart resistance.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD, 21702, USA.
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, 69978, Israel.
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD, 21702, USA
| | - Guy Nir
- Department of Genetics, Harvard Medical School, Boston, MA, 02115, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, 02115, USA
- Department of Biochemistry & Molecular Biology, Department of Neuroscience, Cell Biology and Anatomy, Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, TX, 77555, USA
| | - Chung-Jung Tsai
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD, 21702, USA
| | - Feixiong Cheng
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44106, USA
- Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, 44195, USA
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10
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Meluzzi D, Arya G. Computational approaches for inferring 3D conformations of chromatin from chromosome conformation capture data. Methods 2020; 181-182:24-34. [PMID: 31470090 PMCID: PMC7044057 DOI: 10.1016/j.ymeth.2019.08.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 06/24/2019] [Accepted: 08/23/2019] [Indexed: 02/08/2023] Open
Abstract
Chromosome conformation capture (3C) and its variants are powerful experimental techniques for probing intra- and inter-chromosomal interactions within cell nuclei at high resolution and in a high-throughput, quantitative manner. The contact maps derived from such experiments provide an avenue for inferring the 3D spatial organization of the genome. This review provides an overview of the various computational methods developed in the past decade for addressing the very important but challenging problem of deducing the detailed 3D structure or structure population of chromosomal domains, chromosomes, and even entire genomes from 3C contact maps.
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Affiliation(s)
- Dario Meluzzi
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, United States
| | - Gaurav Arya
- Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708, United States.
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11
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Kumari K, Duenweg B, Padinhateeri R, Prakash JR. Computing 3D Chromatin Configurations from Contact Probability Maps by Inverse Brownian Dynamics. Biophys J 2020; 118:2193-2208. [PMID: 32389215 PMCID: PMC7203009 DOI: 10.1016/j.bpj.2020.02.017] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Revised: 02/04/2020] [Accepted: 02/11/2020] [Indexed: 01/20/2023] Open
Abstract
The three-dimensional (3D) organization of chromatin, on the length scale of a few genes, is crucial in determining the functional state-accessibility and amount of gene expression-of the chromatin. Recent advances in chromosome conformation capture experiments provide partial information on the chromatin organization in a cell population, namely the contact count between any segment pairs, but not on the interaction strength that leads to these contact counts. However, given the contact matrix, determining the complete 3D organization of the whole chromatin polymer is an inverse problem. In this work, a novel inverse Brownian dynamics method based on a coarse-grained bead-spring chain model has been proposed to compute the optimal interaction strengths between different segments of chromatin such that the experimentally measured contact count probability constraints are satisfied. Applying this method to the α-globin gene locus in two different cell types, we predict the 3D organizations corresponding to active and repressed states of chromatin at the locus. We show that the average distance between any two segments of the region has a broad distribution and cannot be computed as a simple inverse relation based on the contact probability alone. The results presented for multiple normalization methods suggest that all measurable quantities may crucially depend on the nature of normalization. We argue that by experimentally measuring predicted quantities, one may infer the appropriate form of normalization.
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Affiliation(s)
- Kiran Kumari
- Department of Chemical Engineering, Monash University, Melbourne, Victoria, Australia; Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India; IITB-Monash Research Academy, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India
| | - Burkhard Duenweg
- Department of Chemical Engineering, Monash University, Melbourne, Victoria, Australia; Max Planck Institute for Polymer Research, Mainz, Germany
| | - Ranjith Padinhateeri
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India.
| | - J Ravi Prakash
- Department of Chemical Engineering, Monash University, Melbourne, Victoria, Australia.
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12
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Are Parallel Proliferation Pathways Redundant? Trends Biochem Sci 2020; 45:554-563. [PMID: 32345469 DOI: 10.1016/j.tibs.2020.03.013] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 03/16/2020] [Accepted: 03/30/2020] [Indexed: 12/14/2022]
Abstract
Are the receptor tyrosine kinase (RTK) and JAK-STAT-driven proliferation pathways 'parallel' or 'redundant'? And what about those of K-Ras4B versus N-Ras? 'Parallel' proliferation pathways accomplish a similar drug resistance outcome. Thus, are they 'redundant'? In this paper, it is argued that there is a fundamental distinction between 'parallel' and 'redundant'. Cellular proliferation pathways are influenced by the genome sequence, 3D organization and chromatin accessibility, and determined by protein availability prior to cancer emergence. In the opinion presented, if they operate the same downstream protein families, they are redundant; if evolutionary-independent, they are parallel. Thus, RTK and JAK-STAT-driven proliferation pathways are parallel; those of Ras isoforms are redundant. Our Precision Medicine Call to map cancer proliferation pathways is vastly important since it can expedite effective therapeutics.
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13
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Bayesian inference of chromatin structure ensembles from population-averaged contact data. Proc Natl Acad Sci U S A 2020; 117:7824-7830. [PMID: 32193349 DOI: 10.1073/pnas.1910364117] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Mounting experimental evidence suggests a role for the spatial organization of chromatin in crucial processes of the cell nucleus such as transcription regulation. Chromosome conformation capture techniques allow us to characterize chromatin structure by mapping contacts between chromosomal loci on a genome-wide scale. The most widespread modality is to measure contact frequencies averaged over a population of cells. Single-cell variants exist, but suffer from low contact numbers and have not yet gained the same resolution as population methods. While intriguing biological insights have already been garnered from ensemble-averaged data, information about three-dimensional (3D) genome organization in the underlying individual cells remains largely obscured because the contact maps show only an average over a huge population of cells. Moreover, computational methods for structure modeling of chromatin have mostly focused on fitting a single consensus structure, thereby ignoring any cell-to-cell variability in the model itself. Here, we propose a fully Bayesian method to infer ensembles of chromatin structures and to determine the optimal number of states in a principled, objective way. We illustrate our approach on simulated data and compute multistate models of chromatin from chromosome conformation capture carbon copy (5C) data. Comparison with independent data suggests that the inferred ensembles represent the underlying sample population faithfully. Harnessing the rich information contained in multistate models, we investigate cell-to-cell variability of chromatin organization into topologically associating domains, thus highlighting the ability of our approach to deliver insights into chromatin organization of great biological relevance.
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14
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Chiariello AM, Bianco S, Oudelaar AM, Esposito A, Annunziatella C, Fiorillo L, Conte M, Corrado A, Prisco A, Larke MS, Telenius JM, Sciarretta R, Musella F, Buckle VJ, Higgs DR, Hughes JR, Nicodemi M. A Dynamic Folded Hairpin Conformation Is Associated with α-Globin Activation in Erythroid Cells. Cell Rep 2020; 30:2125-2135.e5. [DOI: 10.1016/j.celrep.2020.01.044] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2019] [Revised: 08/13/2019] [Accepted: 01/14/2020] [Indexed: 01/07/2023] Open
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15
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Perez-Rathke A, Sun Q, Wang B, Boeva V, Shao Z, Liang J. CHROMATIX: computing the functional landscape of many-body chromatin interactions in transcriptionally active loci from deconvolved single cells. Genome Biol 2020; 21:13. [PMID: 31948478 PMCID: PMC6966897 DOI: 10.1186/s13059-019-1904-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Accepted: 11/27/2019] [Indexed: 02/06/2023] Open
Abstract
Chromatin interactions are important for gene regulation and cellular specialization. Emerging evidence suggests many-body spatial interactions play important roles in condensing super-enhancer regions into a cohesive transcriptional apparatus. Chromosome conformation studies using Hi-C are limited to pairwise, population-averaged interactions; therefore unsuitable for direct assessment of many-body interactions. We describe a computational model, CHROMATIX, which reconstructs ensembles of single-cell chromatin structures by deconvolving Hi-C data and identifies significant many-body interactions. For a diverse set of highly active transcriptional loci with at least 2 super-enhancers, we detail the many-body functional landscape and show DNase accessibility, POLR2A binding, and decreased H3K27me3 are predictive of interaction-enriched regions.
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Affiliation(s)
- Alan Perez-Rathke
- Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL USA
| | - Qiu Sun
- Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
| | - Boshen Wang
- Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL USA
| | - Valentina Boeva
- Institut Cochin, INSERM U1016, CNRS UMR 8104, Paris Descartes University UMR-S1016, Paris, 75014 France
- Department of Computer Science, ETH Zurich, Zürich, Switzerland
| | - Zhifeng Shao
- State Key Laboratory for Oncogenes and Bio-ID Center, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jie Liang
- Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL USA
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16
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Liu L, Kim MH, Hyeon C. Heterogeneous Loop Model to Infer 3D Chromosome Structures from Hi-C. Biophys J 2019; 117:613-625. [PMID: 31337548 DOI: 10.1016/j.bpj.2019.06.032] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 05/22/2019] [Accepted: 06/25/2019] [Indexed: 10/26/2022] Open
Abstract
Adapting a well-established formalism in polymer physics, we develop a minimalist approach to infer three-dimensional folding of chromatin from Hi-C data. The three-dimensional chromosome structures generated from our heterogeneous loop model (HLM) are used to visualize chromosome organizations that can substantiate the measurements from fluorescence in situ hybridization, chromatin interaction analysis by paired-end tag sequencing, and RNA-seq signals. We demonstrate the utility of the HLM with several case studies. Specifically, the HLM-generated chromosome structures, which reproduce the spatial distribution of topologically associated domains from fluorescence in situ hybridization measurement, show the phase segregation between two types of topologically associated domains explicitly. We discuss the origin of cell-type-dependent gene-expression level by modeling the chromatin globules of α-globin and SOX2 gene loci for two different cell lines. We also use the HLM to discuss how the chromatin folding and gene-expression level of Pax6 loci, associated with mouse neural development, are modulated by interactions with two enhancers. Finally, HLM-generated structures of chromosome 19 of mouse embryonic stem cells, based on single-cell Hi-C data collected over each cell-cycle phase, visualize changes in chromosome conformation along the cell-cycle. Given a contact frequency map between chromatic loci supplied from Hi-C, HLM is a computationally efficient and versatile modeling tool to generate chromosome structures that can complement interpreting other experimental data.
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Affiliation(s)
- Lei Liu
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Republic of Korea
| | - Min Hyeok Kim
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Republic of Korea
| | - Changbong Hyeon
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Republic of Korea.
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17
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Perez-Rathke A, Mali S, Du L, Liang J. Alterations in Chromatin Folding Patterns in Cancer Variant-Enriched Loci. ... IEEE-EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH INFORMATICS. IEEE-EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH INFORMATICS 2019; 2019. [PMID: 34085045 DOI: 10.1109/bhi.2019.8834565] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
In this study, we focus on the following question: do genomic regions enriched in cancer variant mutations have significantly different chromatin folding patterns? We utilize publicly available Hi-C data to characterize chromatin folding patterns in healthy (GM12878) and cancer (K562) cells based on status of A/B compartmentalization and random vs non-random chromatin physical interactions. We then perform statistical testing to assess if chromatin folding patterns in cancer variant-enriched loci are significantly different from non-enriched loci. Our results indicate that loci with cancer variant status have significantly altered (FDR < 0.05) chromatin folding patterns.
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Affiliation(s)
- Alan Perez-Rathke
- Bioinformatics Program, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Samira Mali
- Bioinformatics Program, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Lin Du
- Bioinformatics Program, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Jie Liang
- Bioinformatics Program, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA
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18
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Nussinov R, Tsai CJ, Shehu A, Jang H. Computational Structural Biology: Successes, Future Directions, and Challenges. Molecules 2019; 24:molecules24030637. [PMID: 30759724 PMCID: PMC6384756 DOI: 10.3390/molecules24030637] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 02/05/2019] [Accepted: 02/10/2019] [Indexed: 02/06/2023] Open
Abstract
Computational biology has made powerful advances. Among these, trends in human health have been uncovered through heterogeneous 'big data' integration, and disease-associated genes were identified and classified. Along a different front, the dynamic organization of chromatin is being elucidated to gain insight into the fundamental question of genome regulation. Powerful conformational sampling methods have also been developed to yield a detailed molecular view of cellular processes. when combining these methods with the advancements in the modeling of supramolecular assemblies, including those at the membrane, we are finally able to get a glimpse into how cells' actions are regulated. Perhaps most intriguingly, a major thrust is on to decipher the mystery of how the brain is coded. Here, we aim to provide a broad, yet concise, sketch of modern aspects of computational biology, with a special focus on computational structural biology. We attempt to forecast the areas that computational structural biology will embrace in the future and the challenges that it may face. We skirt details, highlight successes, note failures, and map directions.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.
- Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel.
| | - Chung-Jung Tsai
- Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.
| | - Amarda Shehu
- Departments of Computer Science, Department of Bioengineering, and School of Systems Biology, George Mason University, Fairfax, VA 22030, USA.
| | - Hyunbum Jang
- Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.
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19
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The 10-nm chromatin fiber and its relationship to interphase chromosome organization. Biochem Soc Trans 2017; 46:67-76. [PMID: 29263138 PMCID: PMC5818668 DOI: 10.1042/bst20170101] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Revised: 10/25/2017] [Accepted: 10/27/2017] [Indexed: 01/09/2023]
Abstract
A chromosome is a single long DNA molecule assembled along its length with nucleosomes and proteins. During interphase, a mammalian chromosome exists as a highly organized supramolecular globule in the nucleus. Here, we discuss new insights into how genomic DNA is packaged and organized within interphase chromosomes. Our emphasis is on the structural principles that underlie chromosome organization, with a particular focus on the intrinsic contributions of the 10-nm chromatin fiber, but not the regular 30-nm fiber. We hypothesize that the hierarchical globular organization of an interphase chromosome is fundamentally established by the self-interacting properties of a 10-nm zig-zag array of nucleosomes, while histone post-translational modifications, histone variants, and chromatin-associated proteins serve to mold generic chromatin domains into specific structural and functional entities.
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