1
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Shi C, Liu L, Hyeon C. Hi-C-guided many-polymer model to decipher 3D genome organization. Biophys J 2024:S0006-3495(24)00420-X. [PMID: 38932457 DOI: 10.1016/j.bpj.2024.06.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/27/2024] [Accepted: 06/21/2024] [Indexed: 06/28/2024] Open
Abstract
We propose a high-throughput chromosome conformation capture data-based many-polymer model that allows us to generate an ensemble of multi-scale genome structures. We demonstrate the efficacy of our model by validating the generated structures against experimental measurements and employ them to address key questions regarding genome organization. Our model first confirms a significant correlation between chromosome size and nuclear positioning. Specifically, smaller chromosomes are distributed at the core region, whereas larger chromosomes are at the periphery, interacting with the nuclear envelope. The spatial distribution of A- and B-type compartments, which is nontrivial to infer from the corresponding high-throughput chromosome conformation capture maps alone, can also be elucidated using our model, accounting for an issue such as the effect of chromatin-lamina interaction on the compartmentalization of conventional and inverted nuclei. In accordance with imaging data, the overall shape of the 3D genome structures generated from our model displays significant variation. As a case study, we apply our method to the yellow fever mosquito genome, finding that the predicted morphology displays, on average, a more globular shape than the previously suggested spindle-like organization and that our prediction better aligns with the fluorescence in situ hybridization data. Our model has great potential to be extended to investigate many outstanding issues concerning 3D genome organization.
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Affiliation(s)
- Chen Shi
- Key Laboratory of Optical Field Manipulation of Zhejiang Province, Department of Physics, Zhejiang Sci-Tech University, Hangzhou, China
| | - Lei Liu
- 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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2
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Zhao Y, Yang X, Yang L, Xing F, Liu C, Di Y, Cao G, Wei S, Yang X, Zhang X, Liu Y, Gan Z. Advanced Optical Information Encryption Enabled by Polychromatic and Stimuli-Responsive Luminescence of Sb-Doped Double Perovskites. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2308390. [PMID: 38626374 PMCID: PMC11200084 DOI: 10.1002/advs.202308390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 03/08/2024] [Indexed: 04/18/2024]
Abstract
The smart materials with multi-color and stimuli-responsive luminescence are very promising for next generation of optical information encryption and anti-counterfeiting, but these materials are still scarce. Herein, a multi-level information encryption strategy is developed based on the polychromatic emission of Sb-doped double perovskite powders (SDPPs). Cs2NaInCl6:Sb, Cs2KInCl6:Sb, and Cs2AgInCl6:Sb synthesized through coprecipitation methods exhibit broadband emissions with bright blue, cyan, and orange colors, respectively. The information transmitted by specific SDPP is encrypted when different SDPPs are mixed. The confidential information can be decrypted by selecting the corresponding narrowband filter. Then, an encrypted quick response (QR) code with improved security is demonstrated based on this multi-channel selection strategy. Moreover, the three types of SDPPs exhibit three different water-triggered luminescence switching behaviors. The confidential information represented by Cs2NaInCl6:Sb can be erased/recovered through a simple water spray/drying. Whereas, the information collected from the green channel is permanently erased by moisture, which fundamentally avoids information leakage. Therefore, different encryption schemes can be designed to meet a variety of encryption requirements. The multicolor and stimuli-responsive luminescence greatly enrich the flexibility of optical information encryption, which leaps the level of security and confidentiality.
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Affiliation(s)
- Yijun Zhao
- Center for Future Optoelectronic Functional MaterialsSchool of Computer and Electronic Information/School of Artificial IntelligenceNanjing Normal UniversityNanjing210023China
| | - Xingru Yang
- Center for Future Optoelectronic Functional MaterialsSchool of Computer and Electronic Information/School of Artificial IntelligenceNanjing Normal UniversityNanjing210023China
| | - Lun Yang
- Institute for Advanced MaterialsHubei Key Laboratory of Pollutant Analysis & Reuse TechnologyHubei Normal UniversityHuangshi435002China
| | - Fangjian Xing
- Center for Future Optoelectronic Functional MaterialsSchool of Computer and Electronic Information/School of Artificial IntelligenceNanjing Normal UniversityNanjing210023China
| | - Cihui Liu
- Center for Future Optoelectronic Functional MaterialsSchool of Computer and Electronic Information/School of Artificial IntelligenceNanjing Normal UniversityNanjing210023China
| | - Yunsong Di
- Center for Future Optoelectronic Functional MaterialsSchool of Computer and Electronic Information/School of Artificial IntelligenceNanjing Normal UniversityNanjing210023China
| | - Guiyuan Cao
- Nanophotonics Research CenterShenzhen Key Laboratory of Micro‐Scale Optical Information TechnologyShenzhen UniversityShenzhen518060China
| | - Shibiao Wei
- Nanophotonics Research CenterShenzhen Key Laboratory of Micro‐Scale Optical Information TechnologyShenzhen UniversityShenzhen518060China
| | - Xifeng Yang
- College of Electronic and Information EngineeringChangshu Institute of TechnologySuzhou215500China
| | - Xiaowei Zhang
- Department of Electrical Engineering and Computer ScienceNingbo UniversityNingbo315211China
| | - Yushen Liu
- College of Electronic and Information EngineeringChangshu Institute of TechnologySuzhou215500China
| | - Zhixing Gan
- Center for Future Optoelectronic Functional MaterialsSchool of Computer and Electronic Information/School of Artificial IntelligenceNanjing Normal UniversityNanjing210023China
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3
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Kadlof M, Banecki K, Chiliński M, Plewczynski D. Chromatin image-driven modelling. Methods 2024; 226:54-60. [PMID: 38636797 DOI: 10.1016/j.ymeth.2024.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 03/13/2024] [Accepted: 04/05/2024] [Indexed: 04/20/2024] Open
Abstract
The challenge of modelling the spatial conformation of chromatin remains an open problem. While multiple data-driven approaches have been proposed, each has limitations. This work introduces two image-driven modelling methods based on the Molecular Dynamics Flexible Fitting (MDFF) approach: the force method and the correlational method. Both methods have already been used successfully in protein modelling. We propose a novel way to employ them for building chromatin models directly from 3D images. This approach is termed image-driven modelling. Additionally, we introduce the initial structure generator, a tool designed to generate optimal starting structures for the proposed algorithms. The methods are versatile and can be applied to various data types, with minor modifications to accommodate new generation imaging techniques.
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Affiliation(s)
- Michał Kadlof
- Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland.
| | - Krzysztof Banecki
- Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland; Centre of New Technologies, University of Warsaw, Warsaw, Poland
| | - Mateusz Chiliński
- Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland; Centre of New Technologies, University of Warsaw, Warsaw, Poland; Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Dariusz Plewczynski
- Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland; Centre of New Technologies, University of Warsaw, Warsaw, Poland
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4
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Brückner DB, Broedersz CP. Learning dynamical models of single and collective cell migration: a review. REPORTS ON PROGRESS IN PHYSICS. PHYSICAL SOCIETY (GREAT BRITAIN) 2024; 87:056601. [PMID: 38518358 DOI: 10.1088/1361-6633/ad36d2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 03/22/2024] [Indexed: 03/24/2024]
Abstract
Single and collective cell migration are fundamental processes critical for physiological phenomena ranging from embryonic development and immune response to wound healing and cancer metastasis. To understand cell migration from a physical perspective, a broad variety of models for the underlying physical mechanisms that govern cell motility have been developed. A key challenge in the development of such models is how to connect them to experimental observations, which often exhibit complex stochastic behaviours. In this review, we discuss recent advances in data-driven theoretical approaches that directly connect with experimental data to infer dynamical models of stochastic cell migration. Leveraging advances in nanofabrication, image analysis, and tracking technology, experimental studies now provide unprecedented large datasets on cellular dynamics. In parallel, theoretical efforts have been directed towards integrating such datasets into physical models from the single cell to the tissue scale with the aim of conceptualising the emergent behaviour of cells. We first review how this inference problem has been addressed in both freely migrating and confined cells. Next, we discuss why these dynamics typically take the form of underdamped stochastic equations of motion, and how such equations can be inferred from data. We then review applications of data-driven inference and machine learning approaches to heterogeneity in cell behaviour, subcellular degrees of freedom, and to the collective dynamics of multicellular systems. Across these applications, we emphasise how data-driven methods can be integrated with physical active matter models of migrating cells, and help reveal how underlying molecular mechanisms control cell behaviour. Together, these data-driven approaches are a promising avenue for building physical models of cell migration directly from experimental data, and for providing conceptual links between different length-scales of description.
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Affiliation(s)
- David B Brückner
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - Chase P Broedersz
- Department of Physics and Astronomy, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
- Arnold Sommerfeld Center for Theoretical Physics and Center for NanoScience, Department of Physics, Ludwig-Maximilian-University Munich, Theresienstr. 37, D-80333 Munich, Germany
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5
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Zhang Y, Boninsegna L, Yang M, Misteli T, Alber F, Ma J. Computational methods for analysing multiscale 3D genome organization. Nat Rev Genet 2024; 25:123-141. [PMID: 37673975 PMCID: PMC11127719 DOI: 10.1038/s41576-023-00638-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/12/2023] [Indexed: 09/08/2023]
Abstract
Recent progress in whole-genome mapping and imaging technologies has enabled the characterization of the spatial organization and folding of the genome in the nucleus. In parallel, advanced computational methods have been developed to leverage these mapping data to reveal multiscale three-dimensional (3D) genome features and to provide a more complete view of genome structure and its connections to genome functions such as transcription. Here, we discuss how recently developed computational tools, including machine-learning-based methods and integrative structure-modelling frameworks, have led to a systematic, multiscale delineation of the connections among different scales of 3D genome organization, genomic and epigenomic features, functional nuclear components and genome function. However, approaches that more comprehensively integrate a wide variety of genomic and imaging datasets are still needed to uncover the functional role of 3D genome structure in defining cellular phenotypes in health and disease.
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Affiliation(s)
- Yang Zhang
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Lorenzo Boninsegna
- Department of Microbiology, Immunology and Molecular Genetics and Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Muyu Yang
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Tom Misteli
- Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
| | - Frank Alber
- Department of Microbiology, Immunology and Molecular Genetics and Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, USA.
| | - Jian Ma
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
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6
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Kocanova S, Raynal F, Goiffon I, Oksuz BA, Baú D, Kamgoué A, Cantaloube S, Zhan Y, Lajoie B, Marti-Renom MA, Dekker J, Bystricky K. Enhancer-driven 3D chromatin domain folding modulates transcription in human mammary tumor cells. Life Sci Alliance 2024; 7:e202302154. [PMID: 37989525 PMCID: PMC10663337 DOI: 10.26508/lsa.202302154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 11/03/2023] [Accepted: 11/06/2023] [Indexed: 11/23/2023] Open
Abstract
The genome is organized in functional compartments and structural domains at the sub-megabase scale. How within these domains interactions between numerous cis-acting enhancers and promoters regulate transcription remains an open question. Here, we determined chromatin folding and composition over several hundred kb around estrogen-responsive genes in human breast cancer cell lines after hormone stimulation. Modeling of 5C data at 1.8 kb resolution was combined with quantitative 3D analysis of multicolor FISH measurements at 100 nm resolution and integrated with ChIP-seq data on transcription factor binding and histone modifications. We found that rapid estradiol induction of the progesterone gene expression occurs in the context of preexisting, cell type-specific chromosomal architectures encompassing the 90 kb progesterone gene coding region and an enhancer-spiked 5' 300 kb upstream genomic region. In response to estradiol, interactions between estrogen receptor α (ERα) bound regulatory elements are reinforced. Whereas initial enhancer-gene contacts coincide with RNA Pol 2 binding and transcription initiation, sustained hormone stimulation promotes ERα accumulation creating a regulatory hub stimulating transcript synthesis. In addition to implications for estrogen receptor signaling, we uncover that preestablished chromatin architectures efficiently regulate gene expression upon stimulation without the need for de novo extensive rewiring of long-range chromatin interactions.
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Affiliation(s)
- Silvia Kocanova
- Molecular, Cellular and Developmental Biology Unit (MCD), Centre de Biologie Integrative (CBI), University of Toulouse, UPS, CNRS, Toulouse, France
| | - Flavien Raynal
- Molecular, Cellular and Developmental Biology Unit (MCD), Centre de Biologie Integrative (CBI), University of Toulouse, UPS, CNRS, Toulouse, France
| | - Isabelle Goiffon
- Molecular, Cellular and Developmental Biology Unit (MCD), Centre de Biologie Integrative (CBI), University of Toulouse, UPS, CNRS, Toulouse, France
| | - Betul Akgol Oksuz
- https://ror.org/0464eyp60 Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Davide Baú
- Centre Nacional d'Anàlisi Genòmica (CNAG), Barcelona, Spain
| | - Alain Kamgoué
- Molecular, Cellular and Developmental Biology Unit (MCD), Centre de Biologie Integrative (CBI), University of Toulouse, UPS, CNRS, Toulouse, France
| | - Sylvain Cantaloube
- Molecular, Cellular and Developmental Biology Unit (MCD), Centre de Biologie Integrative (CBI), University of Toulouse, UPS, CNRS, Toulouse, France
| | - Ye Zhan
- https://ror.org/0464eyp60 Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Bryan Lajoie
- https://ror.org/0464eyp60 Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Marc A Marti-Renom
- Centre Nacional d'Anàlisi Genòmica (CNAG), Barcelona, Spain
- Genome Biology Program, Centre de Regulació Genòmica (CRG), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Job Dekker
- https://ror.org/0464eyp60 Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Kerstin Bystricky
- Molecular, Cellular and Developmental Biology Unit (MCD), Centre de Biologie Integrative (CBI), University of Toulouse, UPS, CNRS, Toulouse, France
- Institut Universitaire de France (IUF), Paris, France
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7
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Li Z, Schlick T. Hi-BDiSCO: folding 3D mesoscale genome structures from Hi-C data using brownian dynamics. Nucleic Acids Res 2024; 52:583-599. [PMID: 38015443 PMCID: PMC10810283 DOI: 10.1093/nar/gkad1121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 10/12/2023] [Accepted: 11/22/2023] [Indexed: 11/29/2023] Open
Abstract
The structure and dynamics of the eukaryotic genome are intimately linked to gene regulation and transcriptional activity. Many chromosome conformation capture experiments like Hi-C have been developed to detect genome-wide contact frequencies and quantify loop/compartment structures for different cellular contexts and time-dependent processes. However, a full understanding of these events requires explicit descriptions of representative chromatin and chromosome configurations. With the exponentially growing amount of data from Hi-C experiments, many methods for deriving 3D structures from contact frequency data have been developed. Yet, most reconstruction methods use polymer models with low resolution to predict overall genome structure. Here we present a Brownian Dynamics (BD) approach termed Hi-BDiSCO for producing 3D genome structures from Hi-C and Micro-C data using our mesoscale-resolution chromatin model based on the Discrete Surface Charge Optimization (DiSCO) model. Our approach integrates reconstruction with chromatin simulations at nucleosome resolution with appropriate biophysical parameters. Following a description of our protocol, we present applications to the NXN, HOXC, HOXA and Fbn2 mouse genes ranging in size from 50 to 100 kb. Such nucleosome-resolution genome structures pave the way for pursuing many biomedical applications related to the epigenomic regulation of chromatin and control of human disease.
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Affiliation(s)
- Zilong Li
- Department of Chemistry, 100 Washington Square East, Silver Building, New York University, New York, NY 10003, USA
- Simons Center for Computational Physical Chemistry, 24 Waverly Place, Silver Building, New York University, New York, NY 10003, USA
| | - Tamar Schlick
- Department of Chemistry, 100 Washington Square East, Silver Building, New York University, New York, NY 10003, USA
- Courant Institute of Mathematical Sciences, New York University, 251 Mercer St., New York, NY 10012, USA
- New York University-East China Normal University Center for Computational Chemistry, New York University Shanghai, Shanghai 200122, China
- Simons Center for Computational Physical Chemistry, 24 Waverly Place, Silver Building, New York University, New York, NY 10003, USA
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8
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Caudai C, Salerno E. Complementing Hi-C information for 3D chromatin reconstruction by ChromStruct. FRONTIERS IN BIOINFORMATICS 2024; 3:1287168. [PMID: 38318534 PMCID: PMC10840501 DOI: 10.3389/fbinf.2023.1287168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 12/20/2023] [Indexed: 02/07/2024] Open
Abstract
A multiscale method proposed elsewhere for reconstructing plausible 3D configurations of the chromatin in cell nuclei is recalled, based on the integration of contact data from Hi-C experiments and additional information coming from ChIP-seq, RNA-seq and ChIA-PET experiments. Provided that the additional data come from independent experiments, this kind of approach is supposed to leverage them to complement possibly noisy, biased or missing Hi-C records. When the different data sources are mutually concurrent, the resulting solutions are corroborated; otherwise, their validity would be weakened. Here, a problem of reliability arises, entailing an appropriate choice of the relative weights to be assigned to the different informational contributions. A series of experiments is presented that help to quantify the advantages and the limitations offered by this strategy. Whereas the advantages in accuracy are not always significant, the case of missing Hi-C data demonstrates the effectiveness of additional information in reconstructing the highly packed segments of the structure.
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Affiliation(s)
- Claudia Caudai
- Institute of Information Science and Technologies, National Research Council of Italy, Pisa, Italy
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9
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Liu T, Qiu QT, Hua KJ, Ma BG. Chromosome structure modeling tools and their evaluation in bacteria. Brief Bioinform 2024; 25:bbae044. [PMID: 38385874 PMCID: PMC10883143 DOI: 10.1093/bib/bbae044] [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: 10/30/2023] [Revised: 12/31/2023] [Accepted: 01/22/2024] [Indexed: 02/23/2024] Open
Abstract
The three-dimensional (3D) structure of bacterial chromosomes is crucial for understanding chromosome function. With the growing availability of high-throughput chromosome conformation capture (3C/Hi-C) data, the 3D structure reconstruction algorithms have become powerful tools to study bacterial chromosome structure and function. It is highly desired to have a recommendation on the chromosome structure reconstruction tools to facilitate the prokaryotic 3D genomics. In this work, we review existing chromosome 3D structure reconstruction algorithms and classify them based on their underlying computational models into two categories: constraint-based modeling and thermodynamics-based modeling. We briefly compare these algorithms utilizing 3C/Hi-C datasets and fluorescence microscopy data obtained from Escherichia coli and Caulobacter crescentus, as well as simulated datasets. We discuss current challenges in the 3D reconstruction algorithms for bacterial chromosomes, primarily focusing on software usability. Finally, we briefly prospect future research directions for bacterial chromosome structure reconstruction algorithms.
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Affiliation(s)
- Tong Liu
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Qin-Tian Qiu
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Kang-Jian Hua
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Bin-Guang Ma
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
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10
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Gilbert BR, Luthey-Schulten Z. Replicating Chromosomes in Whole-Cell Models of Bacteria. Methods Mol Biol 2024; 2819:625-653. [PMID: 39028527 DOI: 10.1007/978-1-0716-3930-6_29] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Computational models of cells cannot be considered complete unless they include the most fundamental process of life, the replication of genetic material. In a recent study, we presented a computational framework to model systems of replicating bacterial chromosomes as polymers at 10 bp resolution with Brownian dynamics. This approach was used to investigate changes in chromosome organization during replication and extend the applicability of an existing whole-cell model (WCM) for a genetically minimal bacterium, JCVI-syn3A, to the entire cell cycle. To achieve cell-scale chromosome structures that are realistic, we modeled the chromosome as a self-avoiding homopolymer with bending and torsional stiffnesses that capture the essential mechanical properties of dsDNA in Syn3A. Additionally, the polymer interacts with ribosomes distributed according to cryo-electron tomograms of Syn3A. The polymer model was further augmented by computational models of loop extrusion by structural maintenance of chromosomes (SMC) protein complexes and topoisomerase action, and the modeling and analysis of multi-fork replication states.
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Affiliation(s)
- Benjamin R Gilbert
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Zaida Luthey-Schulten
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
- NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
- NSF Science and Technology Center for Quantitative Cell Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
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11
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Feng C, Wang J, Chu X. Large-scale data-driven and physics-based models offer insights into the relationships among the structures, dynamics, and functions of chromosomes. J Mol Cell Biol 2023; 15:mjad042. [PMID: 37365687 PMCID: PMC10782906 DOI: 10.1093/jmcb/mjad042] [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: 01/06/2023] [Revised: 03/22/2023] [Accepted: 06/25/2023] [Indexed: 06/28/2023] Open
Abstract
The organized three-dimensional chromosome architecture in the cell nucleus provides scaffolding for precise regulation of gene expression. When the cell changes its identity in the cell-fate decision-making process, extensive rearrangements of chromosome structures occur accompanied by large-scale adaptations of gene expression, underscoring the importance of chromosome dynamics in shaping genome function. Over the last two decades, rapid development of experimental methods has provided unprecedented data to characterize the hierarchical structures and dynamic properties of chromosomes. In parallel, these enormous data offer valuable opportunities for developing quantitative computational models. Here, we review a variety of large-scale polymer models developed to investigate the structures and dynamics of chromosomes. Different from the underlying modeling strategies, these approaches can be classified into data-driven ('top-down') and physics-based ('bottom-up') categories. We discuss their contributions to offering valuable insights into the relationships among the structures, dynamics, and functions of chromosomes and propose the perspective of developing data integration approaches from different experimental technologies and multidisciplinary theoretical/simulation methods combined with different modeling strategies.
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Affiliation(s)
- Cibo Feng
- Advanced Materials Thrust, Function Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China
- Green e Materials Laboratory, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China
- College of Physics, Jilin University, Changchun 130012, China
| | - Jin Wang
- Department of Chemistry and Physics, The State University of New York at Stony Brook, Stony Brook, NY 11794, USA
| | - Xiakun Chu
- Advanced Materials Thrust, Function Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China
- Green e Materials Laboratory, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China
- Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong SAR 999077, China
- Guangzhou Municipal Key Laboratory of Materials Informatics, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China
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12
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Wang X, Gu WC, Li J, Ma BG. EVRC: reconstruction of chromosome 3D structure models using error-vector resultant algorithm with clustering coefficient. BIOINFORMATICS (OXFORD, ENGLAND) 2023; 39:btad638. [PMID: 37847746 DOI: 10.1093/bioinformatics/btad638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 09/28/2023] [Accepted: 10/16/2023] [Indexed: 10/19/2023]
Abstract
MOTIVATION Reconstruction of 3D structure models is of great importance for the study of chromosome function. Software tools for this task are highly needed. RESULTS We present a novel reconstruction algorithm, called EVRC, which utilizes co-clustering coefficients and error-vector resultant for chromosome 3D structure reconstruction. As an update of our previous EVR algorithm, EVRC now can deal with both single and multiple chromosomes in structure modeling. To evaluate the effectiveness and accuracy of the EVRC algorithm, we applied it to simulation datasets and real Hi-C datasets. The results show that the reconstructed structures have high similarity to the original/real structures, indicating the effectiveness and robustness of the EVRC algorithm. Furthermore, we applied the algorithm to the 3D conformation reconstruction of the wild-type and mutant Arabidopsis thaliana chromosomes and demonstrated the differences in structural characteristics between different chromosomes. We also accurately showed the conformational change in the centromere region of the mutant compared with the wild-type of Arabidopsis chromosome 1. Our EVRC algorithm is a valuable software tool for the field of chromatin structure reconstruction, and holds great promise for advancing our understanding on the chromosome functions. AVAILABILITY AND IMPLEMENTATION The software is available at https://github.com/mbglab/EVRC.
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Affiliation(s)
- Xiao Wang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Wei-Cheng Gu
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Jie Li
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Bin-Guang Ma
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
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13
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Li Z, Portillo-Ledesma S, Schlick T. Techniques for and challenges in reconstructing 3D genome structures from 2D chromosome conformation capture data. Curr Opin Cell Biol 2023; 83:102209. [PMID: 37506571 PMCID: PMC10529954 DOI: 10.1016/j.ceb.2023.102209] [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: 05/15/2023] [Revised: 06/07/2023] [Accepted: 06/26/2023] [Indexed: 07/30/2023]
Abstract
Chromosome conformation capture technologies that provide frequency information for contacts between genomic regions have been crucial for increasing our understanding of genome folding and regulation. However, such data do not provide direct evidence of the spatial 3D organization of chromatin. In this opinion article, we discuss the development and application of computational methods to reconstruct chromatin 3D structures from experimental 2D contact data, highlighting how such modeling provides biological insights and can suggest mechanisms anchored to experimental data. By applying different reconstruction methods to the same contact data, we illustrate some state-of-the-art of these techniques and discuss our gene resolution approach based on Brownian dynamics and Monte Carlo sampling.
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Affiliation(s)
- Zilong Li
- Department of Chemistry, New York University, 100 Washington Square East, Silver Building, New York, 10003, NY, USA; Simons Center for Computational Physical Chemistry, New York University, 24 Waverly Place, Silver Building, New York, NY, 10003, USA
| | - Stephanie Portillo-Ledesma
- Department of Chemistry, New York University, 100 Washington Square East, Silver Building, New York, 10003, NY, USA; Simons Center for Computational Physical Chemistry, New York University, 24 Waverly Place, Silver Building, New York, NY, 10003, USA
| | - Tamar Schlick
- Department of Chemistry, New York University, 100 Washington Square East, Silver Building, New York, 10003, NY, USA; Courant Institute of Mathematical Sciences, New York University, 251 Mercer St., New York, 10012, NY, USA; New York University-East China Normal University Center for Computational Chemistry, New York University Shanghai, Room 340, Geography Building, 3663 North Zhongshan Road, Shanghai, 200122, China; Simons Center for Computational Physical Chemistry, New York University, 24 Waverly Place, Silver Building, New York, NY, 10003, USA.
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14
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Cosma MP, Neguembor MV. The magic of unraveling genome architecture and function. Cell Rep 2023; 42:112361. [PMID: 37059093 DOI: 10.1016/j.celrep.2023.112361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 02/20/2023] [Accepted: 03/22/2023] [Indexed: 04/16/2023] Open
Abstract
Over the last decades, technological breakthroughs in super-resolution microscopy have allowed us to reach molecular resolution and design experiments of unprecedented complexity. Investigating how chromatin is folded in 3D, from the nucleosome level up to the entire genome, is becoming possible by "magic" (imaging genomic), i.e., the combination of imaging and genomic approaches. This offers endless opportunities to delve into the relationship between genome structure and function. Here, we review recently achieved objectives and the conceptual and technical challenges the field of genome architecture is currently undertaking. We discuss what we have learned so far and where we are heading. We elucidate how the different super-resolution microscopy approaches and, more specifically, live-cell imaging have contributed to the understanding of genome folding. Moreover, we discuss how future technical developments could address remaining open questions.
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Affiliation(s)
- Maria Pia Cosma
- Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 106 Zhongshan Er Road, Yuexiu District, 510080 Guangzhou, China; Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Spain; ICREA, Pg. Lluís Companys 23, 08010 Barcelona, Spain.
| | - Maria Victoria Neguembor
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, 08003 Barcelona, Spain.
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15
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Yang L, Yan Y, Li J, Zhou C, Jin J, Zhang T, Wu H, Li X, Wang W, Yuan L, Zhang X, Gao J. (Tn5-)FISH-based imaging in the era of 3D/spatial genomics. BIOPHYSICS REPORTS 2023; 9:15-25. [PMID: 37426200 PMCID: PMC10323772 DOI: 10.52601/bpr.2023.220025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 02/20/2023] [Indexed: 07/11/2023] Open
Abstract
3D genomics mainly focuses on the 3D position of single genes at the cell level, while spatial genomics focuses more on the tissue level. In this exciting new era of 3D/spatial genomics, half-century old FISH and its derivative methods, including Tn5-FISH, play important roles. In this review, we introduce the Tn5-FISH we developed recently, and present six different applications published by our collaborators and us, based on (Tn5-)FISH, which can be either general BAC clone-based FISH or Tn5-FISH. In these interesting cases, (Tn5-)FISH demonstrated its vigorous ability of targeting sub-chromosomal structures across different diseases and cell lines (leukemia, mESCs (mouse embryonic stem cells), and differentiation cell lines). Serving as an effective tool to image genomic structures at the kilobase level, Tn5-FISH holds great potential to detect chromosomal structures in a high-throughput manner, thus bringing the dawn for new discoveries in the great era of 3D/spatial genomics.
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Affiliation(s)
- Liheng Yang
- Seaver College, Pepperdine University, CA 90263, USA
| | - Yan Yan
- Center for Synthetic & Systems Biology, Tsinghua University, Beijing 100084, China
- Bioinformatics Division, BNRist, Department of Automation, Beijing 100084, China
- MOE Key Laboratory of Bioinformatics, Beijing 100084, China
| | - JunLin Li
- Savaid Medical School, University of Chinese Academy of Sciences, Beijing 100084, China
| | - Cheng Zhou
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Jinlan Jin
- Department of Critical Care Medicine, Shenzhen Hospital (Futian) of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong 518034, China
| | - Tongmei Zhang
- Medical Oncology, Beijing Chest Hospital, Capital Medical University & Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, China
| | - Haokaifeng Wu
- Centre for Regenerative Medicine and Health, HongKong Institute of Science & Innovation, Chinese Academy of Sciences, HongKong SAR, China
- Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou 510000, China
| | - Xingang Li
- Centre for Precision Health, Edith Cowan University, Perth, WA 6027, Australia
| | - Wei Wang
- Centre for Precision Health, Edith Cowan University, Perth, WA 6027, Australia
| | - Li Yuan
- Savaid Medical School, University of Chinese Academy of Sciences, Beijing 100084, China
| | - Xu Zhang
- Beijing Institute of Collaborative Innovation, Beijing 100094, China
| | - Juntao Gao
- Center for Synthetic & Systems Biology, Tsinghua University, Beijing 100084, China
- Bioinformatics Division, BNRist, Department of Automation, Beijing 100084, China
- MOE Key Laboratory of Bioinformatics, Beijing 100084, China
- Institute for TCM-X, Beijing 100084, China
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16
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Golloshi R, Playter C, Freeman TF, Das P, Raines TI, Garretson JH, Thurston D, McCord RP. Constricted migration is associated with stable 3D genome structure differences in cancer cells. EMBO Rep 2022; 23:e52149. [PMID: 35969179 PMCID: PMC9535800 DOI: 10.15252/embr.202052149] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 07/01/2022] [Accepted: 07/12/2022] [Indexed: 01/14/2023] Open
Abstract
To spread from a localized tumor, metastatic cancer cells must squeeze through constrictions that cause major nuclear deformations. Since chromosome structure affects nucleus stiffness, gene regulation, and DNA repair, here, we investigate the relationship between 3D genome structure and constricted migration in cancer cells. Using melanoma (A375) cells, we identify phenotypic differences in cells that have undergone multiple rounds of constricted migration. These cells display a stably higher migration efficiency, elongated morphology, and differences in the distribution of Lamin A/C and heterochromatin. Hi-C experiments reveal differences in chromosome spatial compartmentalization specific to cells that have passed through constrictions and related alterations in expression of genes associated with migration and metastasis. Certain features of the 3D genome structure changes, such as a loss of B compartment interaction strength, are consistently observed after constricted migration in clonal populations of A375 cells and in MDA-MB-231 breast cancer cells. Our observations suggest that consistent types of chromosome structure changes are induced or selected by passage through constrictions and that these may epigenetically encode stable differences in gene expression and cellular migration phenotype.
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Affiliation(s)
- Rosela Golloshi
- Biochemistry & Cellular and Molecular Biology DepartmentUniversity of TennesseeKnoxvilleTNUSA
| | - Christopher Playter
- Biochemistry & Cellular and Molecular Biology DepartmentUniversity of TennesseeKnoxvilleTNUSA
| | - Trevor F Freeman
- Biochemistry & Cellular and Molecular Biology DepartmentUniversity of TennesseeKnoxvilleTNUSA
| | - Priyojit Das
- UT‐ORNL Graduate School of Genome Science and TechnologyUniversity of TennesseeKnoxvilleTNUSA
| | - Thomas Isaac Raines
- Biochemistry & Cellular and Molecular Biology DepartmentUniversity of TennesseeKnoxvilleTNUSA
| | - Joshua H Garretson
- Biochemistry & Cellular and Molecular Biology DepartmentUniversity of TennesseeKnoxvilleTNUSA
| | - Delaney Thurston
- Biochemistry & Cellular and Molecular Biology DepartmentUniversity of TennesseeKnoxvilleTNUSA
| | - Rachel Patton McCord
- Biochemistry & Cellular and Molecular Biology DepartmentUniversity of TennesseeKnoxvilleTNUSA
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17
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Neguembor MV, Arcon JP, Buitrago D, Lema R, Walther J, Garate X, Martin L, Romero P, AlHaj Abed J, Gut M, Blanc J, Lakadamyali M, Wu CT, Brun Heath I, Orozco M, Dans PD, Cosma MP. MiOS, an integrated imaging and computational strategy to model gene folding with nucleosome resolution. Nat Struct Mol Biol 2022; 29:1011-1023. [PMID: 36220894 PMCID: PMC9627188 DOI: 10.1038/s41594-022-00839-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 08/23/2022] [Indexed: 11/06/2022]
Abstract
The linear sequence of DNA provides invaluable information about genes and their regulatory elements along chromosomes. However, to fully understand gene function and regulation, we need to dissect how genes physically fold in the three-dimensional nuclear space. Here we describe immuno-OligoSTORM, an imaging strategy that reveals the distribution of nucleosomes within specific genes in super-resolution, through the simultaneous visualization of DNA and histones. We combine immuno-OligoSTORM with restraint-based and coarse-grained modeling approaches to integrate super-resolution imaging data with Hi-C contact frequencies and deconvoluted micrococcal nuclease-sequencing information. The resulting method, called Modeling immuno-OligoSTORM, allows quantitative modeling of genes with nucleosome resolution and provides information about chromatin accessibility for regulatory factors, such as RNA polymerase II. With Modeling immuno-OligoSTORM, we explore intercellular variability, transcriptional-dependent gene conformation, and folding of housekeeping and pluripotency-related genes in human pluripotent and differentiated cells, thereby obtaining the highest degree of data integration achieved so far to our knowledge.
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Affiliation(s)
- Maria Victoria Neguembor
- Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Spain.
| | - Juan Pablo Arcon
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Diana Buitrago
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona, Spain
- Departamento de Física y Matemáticas, Universidad Autónoma de Manizales, Manizales, Colombia
| | - Rafael Lema
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Jürgen Walther
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Ximena Garate
- Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Laura Martin
- Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Pablo Romero
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona, Spain
| | | | - Marta Gut
- CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Julie Blanc
- CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Melike Lakadamyali
- Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Chao-Ting Wu
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Isabelle Brun Heath
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Modesto Orozco
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona, Spain.
- Faculty of Biology, University of Barcelona, Barcelona, Spain.
- ICREA, Barcelona, Spain.
| | - Pablo D Dans
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona, Spain.
- Department of Biological Sciences, CENUR Litoral Norte, Universidad de la República (UdelaR), Salto, Uruguay.
- Bioinformatics Unit, Institut Pasteur de Montevideo, Montevideo, Uruguay.
| | - Maria Pia Cosma
- Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Spain.
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.
- ICREA, Barcelona, Spain.
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.
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18
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Integrative genome modeling platform reveals essentiality of rare contact events in 3D genome organizations. Nat Methods 2022; 19:938-949. [PMID: 35817938 PMCID: PMC9349046 DOI: 10.1038/s41592-022-01527-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 05/18/2022] [Indexed: 02/07/2023]
Abstract
A multitude of sequencing-based and microscopy technologies provide the means to unravel the relationship between the three-dimensional organization of genomes and key regulatory processes of genome function. Here, we develop a multimodal data integration approach to produce populations of single-cell genome structures that are highly predictive for nuclear locations of genes and nuclear bodies, local chromatin compaction and spatial segregation of functionally related chromatin. We demonstrate that multimodal data integration can compensate for systematic errors in some of the data and can greatly increase accuracy and coverage of genome structure models. We also show that alternative combinations of different orthogonal data sources can converge to models with similar predictive power. Moreover, our study reveals the key contributions of low-frequency (‘rare’) interchromosomal contacts to accurately predicting the global nuclear architecture, including the positioning of genes and chromosomes. Overall, our results highlight the benefits of multimodal data integration for genome structure analysis, available through the Integrative Genome Modeling software package. The Integrative Genome Modeling platform is a tool for population-based three-dimensional genome structure modeling and analysis by integrating various experimental data sources.
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19
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Yildirim A, Boninsegna L, Zhan Y, Alber F. Uncovering the Principles of Genome Folding by 3D Chromatin Modeling. Cold Spring Harb Perspect Biol 2022; 14:a039693. [PMID: 34400556 PMCID: PMC9248826 DOI: 10.1101/cshperspect.a039693] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Our understanding of how genomic DNA is tightly packed inside the nucleus, yet is still accessible for vital cellular processes, has grown dramatically over recent years with advances in microscopy and genomics technologies. Computational methods have played a pivotal role in the structural interpretation of experimental data, which helped unravel some organizational principles of genome folding. Here, we give an overview of current computational efforts in mechanistic and data-driven 3D chromatin structure modeling. We discuss strengths and limitations of different methods and evaluate the added value and benefits of computational approaches to infer the 3D structural and dynamic properties of the genome and its underlying mechanisms at different scales and resolution, ranging from the dynamic formation of chromatin loops and topological associated domains to nuclear compartmentalization of chromatin and nuclear bodies.
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Affiliation(s)
- Asli Yildirim
- Institute for Quantitative and Computational Biosciences, Department of Microbiology, Immunology and Molecular Genetics, University of California Los Angeles, Los Angeles, California 90095, USA
| | - Lorenzo Boninsegna
- Institute for Quantitative and Computational Biosciences, Department of Microbiology, Immunology and Molecular Genetics, University of California Los Angeles, Los Angeles, California 90095, USA
| | - Yuxiang Zhan
- Institute for Quantitative and Computational Biosciences, Department of Microbiology, Immunology and Molecular Genetics, University of California Los Angeles, Los Angeles, California 90095, USA
- Quantitative and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, California 90089, USA
| | - Frank Alber
- Institute for Quantitative and Computational Biosciences, Department of Microbiology, Immunology and Molecular Genetics, University of California Los Angeles, Los Angeles, California 90095, USA
- Quantitative and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, California 90089, USA
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20
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Mulero Hernández J, Fernández-Breis JT. Analysis of the landscape of human enhancer sequences in biological databases. Comput Struct Biotechnol J 2022; 20:2728-2744. [PMID: 35685360 PMCID: PMC9168495 DOI: 10.1016/j.csbj.2022.05.045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 05/20/2022] [Accepted: 05/21/2022] [Indexed: 12/01/2022] Open
Abstract
The process of gene regulation extends as a network in which both genetic sequences and proteins are involved. The levels of regulation and the mechanisms involved are multiple. Transcription is the main control mechanism for most genes, being the downstream steps responsible for refining the transcription patterns. In turn, gene transcription is mainly controlled by regulatory events that occur at promoters and enhancers. Several studies are focused on analyzing the contribution of enhancers in the development of diseases and their possible use as therapeutic targets. The study of regulatory elements has advanced rapidly in recent years with the development and use of next generation sequencing techniques. All this information has generated a large volume of information that has been transferred to a growing number of public repositories that store this information. In this article, we analyze the content of those public repositories that contain information about human enhancers with the aim of detecting whether the knowledge generated by scientific research is contained in those databases in a way that could be computationally exploited. The analysis will be based on three main aspects identified in the literature: types of enhancers, type of evidence about the enhancers, and methods for detecting enhancer-promoter interactions. Our results show that no single database facilitates the optimal exploitation of enhancer data, most types of enhancers are not represented in the databases and there is need for a standardized model for enhancers. We have identified major gaps and challenges for the computational exploitation of enhancer data.
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Affiliation(s)
- Juan Mulero Hernández
- Dept. Informática y Sistemas, Universidad de Murcia, CEIR Campus Mare Nostrum, IMIB-Arrixaca, Spain
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21
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Segal MR. Can 3D diploid genome reconstruction from unphased Hi-C data be salvaged? NAR Genom Bioinform 2022; 4:lqac038. [PMID: 35571676 PMCID: PMC9097817 DOI: 10.1093/nargab/lqac038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 03/31/2022] [Accepted: 04/29/2022] [Indexed: 11/13/2022] Open
Abstract
The three-dimensional (3D) configuration of chromatin impacts numerous cellular processes. However, directly observing chromatin architecture at high resolution is challenging. Accordingly, inferring 3D structure utilizing chromatin conformation capture assays, notably Hi-C, has received considerable attention, with a multitude of reconstruction algorithms advanced. While these have enhanced appreciation of chromatin organization, most suffer from a serious shortcoming when faced with diploid genomes: inability to disambiguate contacts between corresponding loci on homologous chromosomes, making attendant reconstructions potentially meaningless. Three recent proposals offer a computational way forward at the expense of strong assumptions. Here, we show that making plausible assumptions about the components of homologous chromosome contacts provides a basis for rescuing conventional consensus-based, unphased reconstruction. This would be consequential since not only are assumptions needed for diploid reconstruction considerable, but the sophistication of select unphased algorithms affords substantive advantages with regard resolution and folding complexity. Rather than presuming that the requisite salvaging assumptions are met, we exploit a recent imaging technology, in situ genome sequencing (IGS), to comprehensively evaluate their reasonableness. We analogously use IGS to assess assumptions underpinning diploid reconstruction algorithms. Results convincingly demonstrate that, in all instances, assumptions are not met, making further algorithm development, potentially informed by IGS data, essential.
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Affiliation(s)
- Mark R Segal
- Department of Epidemiology and Biostatistics, University of California, 550 16th Street, San Francisco, CA 94143-0560, USA
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22
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Wang H, Yang J, Zhang Y, Qian J, Wang J. Reconstruct high-resolution 3D genome structures for diverse cell-types using FLAMINGO. Nat Commun 2022; 13:2645. [PMID: 35551182 PMCID: PMC9098643 DOI: 10.1038/s41467-022-30270-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 04/22/2022] [Indexed: 11/30/2022] Open
Abstract
High-resolution reconstruction of spatial chromosome organizations from chromatin contact maps is highly demanded, but is hindered by extensive pairwise constraints, substantial missing data, and limited resolution and cell-type availabilities. Here, we present FLAMINGO, a computational method that addresses these challenges by compressing inter-dependent Hi-C interactions to delineate the underlying low-rank structures in 3D space, based on the low-rank matrix completion technique. FLAMINGO successfully generates 5 kb- and 1 kb-resolution spatial conformations for all chromosomes in the human genome across multiple cell-types, the largest resources to date. Compared to other methods using various experimental metrics, FLAMINGO consistently demonstrates superior accuracy in recapitulating observed structures with raises in scalability by orders of magnitude. The reconstructed 3D structures efficiently facilitate discoveries of higher-order multi-way interactions, imply biological interpretations of long-range QTLs, reveal geometrical properties of chromatin, and provide high-resolution references to understand structural variabilities. Importantly, FLAMINGO achieves robust predictions against high rates of missing data and significantly boosts 3D structure resolutions. Moreover, FLAMINGO shows vigorous cross cell-type structure predictions that capture cell-type specific spatial configurations via integration of 1D epigenomic signals. FLAMINGO can be widely applied to large-scale chromatin contact maps and expand high-resolution spatial genome conformations for diverse cell-types. High-resolution reconstruction of spatial chromosome organisation is in demand. Here the authors report FLAMINGO, for reconstructing high-resolution 3D Genome Organisation from HiC data which they use to generate both 5 kb and 1 kb-resolution 3D chromosomal structures for the human genome.
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Affiliation(s)
- Hao Wang
- Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, MI, 48824, USA
| | - Jiaxin Yang
- Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, MI, 48824, USA
| | - Yu Zhang
- Center for Immunobiology, Department of Investigative Medicine, Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, MI, 49007, USA
| | - Jianliang Qian
- Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, MI, 48824, USA. .,Department of Mathematics, Michigan State University, East Lansing, MI, 48824, USA.
| | - Jianrong Wang
- Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, MI, 48824, USA.
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23
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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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24
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Bell RAV, Al-Khalaf MH, Brunette S, Alsowaida D, Chu A, Bandukwala H, Dechant G, Apostolova G, Dilworth FJ, Megeney LA. Chromatin Reorganization during Myoblast Differentiation Involves the Caspase-Dependent Removal of SATB2. Cells 2022; 11:cells11060966. [PMID: 35326417 PMCID: PMC8946544 DOI: 10.3390/cells11060966] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 02/27/2022] [Accepted: 03/09/2022] [Indexed: 11/17/2022] Open
Abstract
The induction of lineage-specific gene programs are strongly influenced by alterations in local chromatin architecture. However, key players that impact this genome reorganization remain largely unknown. Here, we report that the removal of the special AT-rich binding protein 2 (SATB2), a nuclear protein known to bind matrix attachment regions, is a key event in initiating myogenic differentiation. The deletion of myoblast SATB2 in vitro initiates chromatin remodeling and accelerates differentiation, which is dependent on the caspase 7-mediated cleavage of SATB2. A genome-wide analysis indicates that SATB2 binding within chromatin loops and near anchor points influences both loop and sub-TAD domain formation. Consequently, the chromatin changes that occur with the removal of SATB2 lead to the derepression of differentiation-inducing factors while also limiting the expression of genes that inhibit this cell fate change. Taken together, this study demonstrates that the temporal control of the SATB2 protein is critical in shaping the chromatin environment and coordinating the myogenic differentiation program.
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Affiliation(s)
- Ryan A. V. Bell
- Regenerative Medicine Program, Sprott Center for Stem Cell Research, Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON K1H 8L6, Canada; (R.A.V.B.); (M.H.A.-K.); (S.B.); (D.A.); (A.C.); (H.B.); (F.J.D.)
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Mohammad H. Al-Khalaf
- Regenerative Medicine Program, Sprott Center for Stem Cell Research, Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON K1H 8L6, Canada; (R.A.V.B.); (M.H.A.-K.); (S.B.); (D.A.); (A.C.); (H.B.); (F.J.D.)
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
- University of Ottawa Heart Institute, Ottawa, ON K1Y 4W7, Canada
| | - Steve Brunette
- Regenerative Medicine Program, Sprott Center for Stem Cell Research, Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON K1H 8L6, Canada; (R.A.V.B.); (M.H.A.-K.); (S.B.); (D.A.); (A.C.); (H.B.); (F.J.D.)
| | - Dalal Alsowaida
- Regenerative Medicine Program, Sprott Center for Stem Cell Research, Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON K1H 8L6, Canada; (R.A.V.B.); (M.H.A.-K.); (S.B.); (D.A.); (A.C.); (H.B.); (F.J.D.)
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Alphonse Chu
- Regenerative Medicine Program, Sprott Center for Stem Cell Research, Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON K1H 8L6, Canada; (R.A.V.B.); (M.H.A.-K.); (S.B.); (D.A.); (A.C.); (H.B.); (F.J.D.)
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Hina Bandukwala
- Regenerative Medicine Program, Sprott Center for Stem Cell Research, Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON K1H 8L6, Canada; (R.A.V.B.); (M.H.A.-K.); (S.B.); (D.A.); (A.C.); (H.B.); (F.J.D.)
| | - Georg Dechant
- Institute of Neuroscience, Medical University of Innsbruck, A-6020 Innsbruck, Austria; (G.D.); (G.A.)
| | - Galina Apostolova
- Institute of Neuroscience, Medical University of Innsbruck, A-6020 Innsbruck, Austria; (G.D.); (G.A.)
| | - F. Jeffrey Dilworth
- Regenerative Medicine Program, Sprott Center for Stem Cell Research, Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON K1H 8L6, Canada; (R.A.V.B.); (M.H.A.-K.); (S.B.); (D.A.); (A.C.); (H.B.); (F.J.D.)
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Lynn A. Megeney
- Regenerative Medicine Program, Sprott Center for Stem Cell Research, Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON K1H 8L6, Canada; (R.A.V.B.); (M.H.A.-K.); (S.B.); (D.A.); (A.C.); (H.B.); (F.J.D.)
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
- Correspondence:
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25
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Collins B, Oluwadare O, Brown P. ChromeBat: A Bio-Inspired Approach to 3D Genome Reconstruction. Genes (Basel) 2021; 12:1757. [PMID: 34828363 PMCID: PMC8617892 DOI: 10.3390/genes12111757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 10/28/2021] [Accepted: 11/01/2021] [Indexed: 11/20/2022] Open
Abstract
With the advent of Next Generation Sequencing and the Hi-C experiment, high quality genome-wide contact data are becoming increasingly available. These data represents an empirical measure of how a genome interacts inside the nucleus. Genome conformation is of particular interest as it has been experimentally shown to be a driving force for many genomic functions from regulation to transcription. Thus, the Three Dimensional-Genome Reconstruction Problem (3D-GRP) seeks to take Hi-C data and produces a complete physical genome structure as it appears in the nucleus for genomic analysis. We propose and develop a novel method to solve the Chromosome and Genome Reconstruction problem based on the Bat Algorithm (BA) which we called ChromeBat. We demonstrate on real Hi-C data that ChromeBat is capable of state-of-the-art performance. Additionally, the domain of Genome Reconstruction has been criticized for lacking algorithmic diversity, and the bio-inspired nature of ChromeBat contributes algorithmic diversity to the problem domain. ChromeBat is an effective approach for solving the Genome Reconstruction Problem.
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Affiliation(s)
| | - Oluwatosin Oluwadare
- Department of Computer Science, University of Colorado, Colorado Springs, CO 80918, USA; (B.C.); (P.B.)
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26
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Maslova A, Krasikova A. FISH Going Meso-Scale: A Microscopic Search for Chromatin Domains. Front Cell Dev Biol 2021; 9:753097. [PMID: 34805161 PMCID: PMC8597843 DOI: 10.3389/fcell.2021.753097] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 10/08/2021] [Indexed: 12/14/2022] Open
Abstract
The intimate relationships between genome structure and function direct efforts toward deciphering three-dimensional chromatin organization within the interphase nuclei at different genomic length scales. For decades, major insights into chromatin structure at the level of large-scale euchromatin and heterochromatin compartments, chromosome territories, and subchromosomal regions resulted from the evolution of light microscopy and fluorescence in situ hybridization. Studies of nanoscale nucleosomal chromatin organization benefited from a variety of electron microscopy techniques. Recent breakthroughs in the investigation of mesoscale chromatin structures have emerged from chromatin conformation capture methods (C-methods). Chromatin has been found to form hierarchical domains with high frequency of local interactions from loop domains to topologically associating domains and compartments. During the last decade, advances in super-resolution light microscopy made these levels of chromatin folding amenable for microscopic examination. Here we are reviewing recent developments in FISH-based approaches for detection, quantitative measurements, and validation of contact chromatin domains deduced from C-based data. We specifically focus on the design and application of Oligopaint probes, which marked the latest progress in the imaging of chromatin domains. Vivid examples of chromatin domain FISH-visualization by means of conventional, super-resolution light and electron microscopy in different model organisms are provided.
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Affiliation(s)
| | - Alla Krasikova
- Laboratory of Nuclear Structure and Dynamics, Cytology and Histology Department, Saint Petersburg State University, Saint Petersburg, Russia
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27
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Four-dimensional chromosome reconstruction elucidates the spatiotemporal reorganization of the mammalian X chromosome. Proc Natl Acad Sci U S A 2021; 118:2107092118. [PMID: 34645712 DOI: 10.1073/pnas.2107092118] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/27/2021] [Indexed: 12/14/2022] Open
Abstract
Chromosomes are segmented into domains and compartments, but how these structures are spatially related in three dimensions (3D) is unclear. Here, we developed tools that directly extract 3D information from Hi-C experiments and integrate the data across time. With our "4DHiC" method, we use X chromosome inactivation (XCI) as a model to examine the time evolution of 3D chromosome architecture during large-scale changes in gene expression. Our modeling resulted in several insights. Both A/B and S1/S2 compartments divide the X chromosome into hemisphere-like structures suggestive of a spatial phase-separation. During the XCI, the X chromosome transits through A/B, S1/S2, and megadomain structures by undergoing only partial mixing to assume new structures. Interestingly, when an active X chromosome (Xa) is reorganized into an inactive X chromosome (Xi), original underlying compartment structures are not fully eliminated within the Xi superstructure. Our study affirms slow mixing dynamics in the inner chromosome core and faster dynamics near the surface where escapees reside. Once established, the Xa and Xi resemble glassy polymers where mixing no longer occurs. Finally, Xist RNA molecules initially reside within the A compartment but transition to the interface between the A and B hemispheres and then spread between hemispheres via both surface and core to establish the Xi.
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28
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Zha M, Wang N, Zhang C, Wang Z. Inferring Single-Cell 3D Chromosomal Structures Based on the Lennard-Jones Potential. Int J Mol Sci 2021; 22:ijms22115914. [PMID: 34072879 PMCID: PMC8199262 DOI: 10.3390/ijms22115914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 05/23/2021] [Accepted: 05/28/2021] [Indexed: 11/16/2022] Open
Abstract
Reconstructing three-dimensional (3D) chromosomal structures based on single-cell Hi-C data is a challenging scientific problem due to the extreme sparseness of the single-cell Hi-C data. In this research, we used the Lennard-Jones potential to reconstruct both 500 kb and high-resolution 50 kb chromosomal structures based on single-cell Hi-C data. A chromosome was represented by a string of 500 kb or 50 kb DNA beads and put into a 3D cubic lattice for simulations. A 2D Gaussian function was used to impute the sparse single-cell Hi-C contact matrices. We designed a novel loss function based on the Lennard-Jones potential, in which the ε value, i.e., the well depth, was used to indicate how stable the binding of every pair of beads is. For the bead pairs that have single-cell Hi-C contacts and their neighboring bead pairs, the loss function assigns them stronger binding stability. The Metropolis-Hastings algorithm was used to try different locations for the DNA beads, and simulated annealing was used to optimize the loss function. We proved the correctness and validness of the reconstructed 3D structures by evaluating the models according to multiple criteria and comparing the models with 3D-FISH data.
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Affiliation(s)
- Mengsheng Zha
- School of Computing Sciences and Computer Engineering, University of Southern Mississippi, 118 College Dr, Hattiesburg, MS 39406, USA; (M.Z.); (C.Z.)
| | - Nan Wang
- Department of Computer Science, New Jersey City University, 2039 Kennedy Blvd, Jersey City, NJ 07305, USA;
| | - Chaoyang Zhang
- School of Computing Sciences and Computer Engineering, University of Southern Mississippi, 118 College Dr, Hattiesburg, MS 39406, USA; (M.Z.); (C.Z.)
| | - Zheng Wang
- Department of Computer Science, University of Miami, 1364 Memorial Drive, Coral Gables, FL 33124, USA
- Correspondence:
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Wasim A, Gupta A, Mondal J. A Hi-C data-integrated model elucidates E. coli chromosome's multiscale organization at various replication stages. Nucleic Acids Res 2021; 49:3077-3091. [PMID: 33660781 PMCID: PMC8034658 DOI: 10.1093/nar/gkab094] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Revised: 01/31/2021] [Accepted: 02/17/2021] [Indexed: 11/13/2022] Open
Abstract
The chromosome of Escherichia coli is riddled with multi-faceted complexity. The emergence of chromosome conformation capture techniques are providing newer ways to explore chromosome organization. Here we combine a beads-on-a-spring polymer-based framework with recently reported Hi-C data for E. coli chromosome, in rich growth condition, to develop a comprehensive model of its chromosome at 5 kb resolution. The investigation focuses on a range of diverse chromosome architectures of E. coli at various replication states corresponding to a collection of cells, individually present in different stages of cell cycle. The Hi-C data-integrated model captures the self-organization of E. coli chromosome into multiple macrodomains within a ring-like architecture. The model demonstrates that the position of oriC is dependent on architecture and replication state of chromosomes. The distance profiles extracted from the model reconcile fluorescence microscopy and DNA-recombination assay experiments. Investigations into writhe of the chromosome model reveal that it adopts helix-like conformation with no net chirality, earlier hypothesized in experiments. A genome-wide radius of gyration map captures multiple chromosomal interaction domains and identifies the precise locations of rrn operons in the chromosome. We show that a model devoid of Hi-C encoded information would fail to recapitulate most genomic features unique to E. coli.
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Affiliation(s)
- Abdul Wasim
- Tata Institute of Fundamental Research, Centre for Interdisciplinary Sciences, Hyderabad 500046, India
| | - Ankit Gupta
- Tata Institute of Fundamental Research, Centre for Interdisciplinary Sciences, Hyderabad 500046, India
| | - Jagannath Mondal
- Tata Institute of Fundamental Research, Centre for Interdisciplinary Sciences, Hyderabad 500046, India
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Integration of Multiple Resolution Data in 3D Chromatin Reconstruction Using ChromStruct. BIOLOGY 2021; 10:biology10040338. [PMID: 33923796 PMCID: PMC8072831 DOI: 10.3390/biology10040338] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 03/30/2021] [Accepted: 04/15/2021] [Indexed: 11/29/2022]
Abstract
The three-dimensional structure of chromatin in the cellular nucleus carries important information that is connected to physiological and pathological correlates and dysfunctional cell behaviour. As direct observation is not feasible at present, on one side, several experimental techniques have been developed to provide information on the spatial organization of the DNA in the cell; on the other side, several computational methods have been developed to elaborate experimental data and infer 3D chromatin conformations. The most relevant experimental methods are Chromosome Conformation Capture and its derivatives, chromatin immunoprecipitation and sequencing techniques (CHIP-seq), RNA-seq, fluorescence in situ hybridization (FISH) and other genetic and biochemical techniques. All of them provide important and complementary information that relate to the three-dimensional organization of chromatin. However, these techniques employ very different experimental protocols and provide information that is not easily integrated, due to different contexts and different resolutions. Here, we present an open-source tool, which is an expansion of the previously reported code ChromStruct, for inferring the 3D structure of chromatin that, by exploiting a multilevel approach, allows an easy integration of information derived from different experimental protocols and referred to different resolution levels of the structure, from a few kilobases up to Megabases. Our results show that the introduction of chromatin modelling features related to CTCF CHIA-PET data, histone modification CHIP-seq, and RNA-seq data produce appreciable improvements in ChromStruct’s 3D reconstructions, compared to the use of HI-C data alone, at a local level and at a very high resolution.
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31
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Gong H, Yang Y, Zhang S, Li M, Zhang X. Application of Hi-C and other omics data analysis in human cancer and cell differentiation research. Comput Struct Biotechnol J 2021; 19:2070-2083. [PMID: 33995903 PMCID: PMC8086027 DOI: 10.1016/j.csbj.2021.04.016] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 04/04/2021] [Accepted: 04/04/2021] [Indexed: 02/07/2023] Open
Abstract
With the development of 3C (chromosome conformation capture) and its derivative technology Hi-C (High-throughput chromosome conformation capture) research, the study of the spatial structure of the genomic sequence in the nucleus helps researchers understand the functions of biological processes such as gene transcription, replication, repair, and regulation. In this paper, we first introduce the research background and purpose of Hi-C data visualization analysis. After that, we discuss the Hi-C data analysis methods from genome 3D structure, A/B compartment, TADs (topologically associated domain), and loop detection. We also discuss how to apply genome visualization technologies to the identification of chromosome feature structures. We continue with a review of correlation analysis differences among multi-omics data, and how to apply Hi-C and other omics data analysis into cancer and cell differentiation research. Finally, we summarize the various problems in joint analyses based on Hi-C and other multi-omics data. We believe this review can help researchers better understand the progress and applications of 3D genome technology.
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Affiliation(s)
- Haiyan Gong
- Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing 100083, China
- Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, Beijing 100083, China
- Beijing Key Laboratory of Knowledge Engineering for Materials Science, Beijing 100083, China
- Shunde Graduate School of University of Science and Technology Beijing, Foshan 528000, China
| | - Yi Yang
- Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing 100083, China
| | - Sichen Zhang
- Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing 100083, China
| | - Minghong Li
- Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing 100083, China
| | - Xiaotong Zhang
- Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing 100083, China
- Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, Beijing 100083, China
- Beijing Key Laboratory of Knowledge Engineering for Materials Science, Beijing 100083, China
- Shunde Graduate School of University of Science and Technology Beijing, Foshan 528000, China
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32
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Messelink JJB, van Teeseling MCF, Janssen J, Thanbichler M, Broedersz CP. Learning the distribution of single-cell chromosome conformations in bacteria reveals emergent order across genomic scales. Nat Commun 2021; 12:1963. [PMID: 33785756 PMCID: PMC8010069 DOI: 10.1038/s41467-021-22189-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 02/15/2021] [Indexed: 02/01/2023] Open
Abstract
The order and variability of bacterial chromosome organization, contained within the distribution of chromosome conformations, are unclear. Here, we develop a fully data-driven maximum entropy approach to extract single-cell 3D chromosome conformations from Hi-C experiments on the model organism Caulobacter crescentus. The predictive power of our model is validated by independent experiments. We find that on large genomic scales, organizational features are predominantly present along the long cell axis: chromosomal loci exhibit striking long-ranged two-point axial correlations, indicating emergent order. This organization is associated with large genomic clusters we term Super Domains (SuDs), whose existence we support with super-resolution microscopy. On smaller genomic scales, our model reveals chromosome extensions that correlate with transcriptional and loop extrusion activity. Finally, we quantify the information contained in chromosome organization that may guide cellular processes. Our approach can be extended to other species, providing a general strategy to resolve variability in single-cell chromosomal organization.
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Affiliation(s)
- Joris J B Messelink
- Arnold Sommerfeld Center for Theoretical Physics and Center for NanoScience, Department of Physics, Ludwig Maximilian University Munich, Munich, Germany
| | - Muriel C F van Teeseling
- Department of Biology, University of Marburg, Marburg, Germany
- Prokaryotic Cell Biology Group, Department of Microbial Interactions, Institute for Microbiology, Friedrich Schiller University Jena, Jena, Germany
| | - Jacqueline Janssen
- Arnold Sommerfeld Center for Theoretical Physics and Center for NanoScience, Department of Physics, Ludwig Maximilian University Munich, Munich, Germany
| | - Martin Thanbichler
- Department of Biology, University of Marburg, Marburg, Germany
- Max Planck Institute for Terrestrial Microbiology, Marburg, Germany
- Center for Synthetic Microbiology (SYNMIKRO), Marburg, Germany
| | - Chase P Broedersz
- Arnold Sommerfeld Center for Theoretical Physics and Center for NanoScience, Department of Physics, Ludwig Maximilian University Munich, Munich, Germany.
- Department of Physics and Astronomy, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
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33
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Liu L, Hyeon C. Revisiting the organization of Polycomb-repressed domains: 3D chromatin models from Hi-C compared with super-resolution imaging. Nucleic Acids Res 2021; 48:11486-11494. [PMID: 33095877 PMCID: PMC7672452 DOI: 10.1093/nar/gkaa932] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 09/22/2020] [Accepted: 10/06/2020] [Indexed: 01/07/2023] Open
Abstract
The accessibility of target gene, a factor critical for gene regulation, is controlled by epigenetic fine-tuning of chromatin organization. While there are multiple experimental techniques to study change of chromatin architecture with its epigenetic state, measurements from them are not always complementary. A qualitative discrepancy is noted between recent super-resolution imaging studies, particularly on Polycomb-group protein repressed domains in Drosophila cell. One of the studies shows that Polycomb-repressed domains are more compact than inactive domains and are segregated from neighboring active domains, whereas Hi-C and chromatin accessibility assay as well as the other super-resolution imaging studies paint a different picture. To examine this issue in detail, we analyzed Hi-C libraries of Drosophila chromosomes as well as distance constraints from one of the imaging studies, and modeled different epigenetic domains by employing a polymer-based approach. According to our chromosome models, both Polycomb-repressed and inactive domains are featured with a similar degree of intra-domain packaging and significant intermixing with adjacent active domains. The epigenetic domains explicitly visualized by our polymer model call for extra attention to the discrepancy of the super-resolution imaging with other measurements, although its precise physicochemical origin still remains to be elucidated.
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Affiliation(s)
- Lei Liu
- Department of Physics, Zhejiang Sci-Tech University, Hangzhou 310018, People's Republic of China
| | - Changbong Hyeon
- Korea Institute for Advanced Study, Seoul 02455, Republic of Korea
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34
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Tao H, Li H, Xu K, Hong H, Jiang S, Du G, Wang J, Sun Y, Huang X, Ding Y, Li F, Zheng X, Chen H, Bo X. Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles. Brief Bioinform 2021; 22:6102668. [PMID: 33454752 PMCID: PMC8424394 DOI: 10.1093/bib/bbaa405] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 11/26/2020] [Accepted: 12/10/2020] [Indexed: 12/14/2022] Open
Abstract
The exploration of three-dimensional chromatin interaction and organization provides insight into mechanisms underlying gene regulation, cell differentiation and disease development. Advances in chromosome conformation capture technologies, such as high-throughput chromosome conformation capture (Hi-C) and chromatin interaction analysis by paired-end tag (ChIA-PET), have enabled the exploration of chromatin interaction and organization. However, high-resolution Hi-C and ChIA-PET data are only available for a limited number of cell lines, and their acquisition is costly, time consuming, laborious and affected by theoretical limitations. Increasing evidence shows that DNA sequence and epigenomic features are informative predictors of regulatory interaction and chromatin architecture. Based on these features, numerous computational methods have been developed for the prediction of chromatin interaction and organization, whereas they are not extensively applied in biomedical study. A systematical study to summarize and evaluate such methods is still needed to facilitate their application. Here, we summarize 48 computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles, categorize them and compare their performance. Besides, we provide a comprehensive guideline for the selection of suitable methods to predict chromatin interaction and organization based on available data and biological question of interest.
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Affiliation(s)
- Huan Tao
- Beijing Institute of Radiation Medicine
| | - Hao Li
- Beijing Institute of Radiation Medicine
| | - Kang Xu
- Beijing Institute of Radiation Medicine
| | - Hao Hong
- Beijing Institute of Radiation Medicine, Department of Biotechnology
| | - Shuai Jiang
- Beijing Institute of Radiation Medicine, Department of Biotechnology
| | - Guifang Du
- Beijing Institute of Radiation Medicine, Department of Biotechnology
| | | | - Yu Sun
- Beijing Institute of Radiation Medicine, Department of Biotechnology
| | - Xin Huang
- Beijing Institute of Radiation Medicine, Department of Biotechnology
| | - Yang Ding
- Beijing Institute of Radiation Medicine
| | - Fei Li
- Chinese Academy of Sciences, Department of Computer Network Information Center
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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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36
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Ingram SP, Henthorn NT, Warmenhoven JW, Kirkby NF, Mackay RI, Kirkby KJ, Merchant MJ. Hi-C implementation of genome structure for in silico models of radiation-induced DNA damage. PLoS Comput Biol 2020; 16:e1008476. [PMID: 33326415 PMCID: PMC7773326 DOI: 10.1371/journal.pcbi.1008476] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 12/30/2020] [Accepted: 10/28/2020] [Indexed: 02/06/2023] Open
Abstract
Developments in the genome organisation field has resulted in the recent methodology to infer spatial conformations of the genome directly from experimentally measured genome contacts (Hi-C data). This provides a detailed description of both intra- and inter-chromosomal arrangements. Chromosomal intermingling is an important driver for radiation-induced DNA mis-repair. Which is a key biological endpoint of relevance to the fields of cancer therapy (radiotherapy), public health (biodosimetry) and space travel. For the first time, we leverage these methods of inferring genome organisation and couple them to nano-dosimetric radiation track structure modelling to predict quantities and distribution of DNA damage within cell-type specific geometries. These nano-dosimetric simulations are highly dependent on geometry and are benefited from the inclusion of experimentally driven chromosome conformations. We show how the changes in Hi-C contract maps impact the inferred geometries resulting in significant differences in chromosomal intermingling. We demonstrate how these differences propagate through to significant changes in the distribution of DNA damage throughout the cell nucleus, suggesting implications for DNA repair fidelity and subsequent cell fate. We suggest that differences in the geometric clustering for the chromosomes between the cell-types are a plausible factor leading to changes in cellular radiosensitivity. Furthermore, we investigate changes in cell shape, such as flattening, and show that this greatly impacts the distribution of DNA damage. This should be considered when comparing in vitro results to in vivo systems. The effect may be especially important when attempting to translate radiosensitivity measurements at the experimental in vitro level to the patient or human level.
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Affiliation(s)
- Samuel P. Ingram
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, United Kingdom
| | - Nicholas T. Henthorn
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
- The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - John W. Warmenhoven
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
- The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Norman F. Kirkby
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
- The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Ranald I. Mackay
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, United Kingdom
| | - Karen J. Kirkby
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
- The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Michael J. Merchant
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
- The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
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Johnstone CP, Wang NB, Sevier SA, Galloway KE. Understanding and Engineering Chromatin as a Dynamical System across Length and Timescales. Cell Syst 2020; 11:424-448. [PMID: 33212016 DOI: 10.1016/j.cels.2020.09.011] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 09/22/2020] [Accepted: 09/29/2020] [Indexed: 12/20/2022]
Abstract
Connecting the molecular structure and function of chromatin across length and timescales remains a grand challenge to understanding and engineering cellular behaviors. Across five orders of magnitude, dynamic processes constantly reshape chromatin structures, driving spaciotemporal patterns of gene expression and cell fate. Through the interplay of structure and function, the genome operates as a highly dynamic feedback control system. Recent experimental techniques have provided increasingly detailed data that revise and augment the relatively static, hierarchical view of genomic architecture with an understanding of how dynamic processes drive organization. Here, we review how novel technologies from sequencing, imaging, and synthetic biology refine our understanding of chromatin structure and function and enable chromatin engineering. Finally, we discuss opportunities to use these tools to enhance understanding of the dynamic interrelationship of chromatin structure and function.
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Affiliation(s)
| | - Nathan B Wang
- Department of Chemical Engineering, MIT, 25 Ames St., Cambridge, MA 02139, USA
| | - Stuart A Sevier
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA; Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA.
| | - Kate E Galloway
- Department of Chemical Engineering, MIT, 25 Ames St., Cambridge, MA 02139, USA.
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38
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Advances in technologies for 3D genomics research. SCIENCE CHINA-LIFE SCIENCES 2020; 63:811-824. [PMID: 32394244 DOI: 10.1007/s11427-019-1704-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 04/21/2020] [Indexed: 01/08/2023]
Abstract
The spatial structure of the orderly organized chromatin in the nucleus has important roles in maintaining normal cell function and in regulation of gene expression, and the high-throughput Hi-C and ChIA-PET methods have been widely used in various biological studies for determining potential spatial genome structures and their functions. However, there are still great difficulties and challenges in three-dimensional (3D) genomics research. More efficient, economical, and unbiased approaches to studying 3D genomics need to be developed for more widespread and easier applications. Here, we review the most recent studies on new 3D genomics research technologies, such as improvements of the traditional Hi-C and ChIA-PET methods, new approaches based on non-proximal-ligation strategies, and imaging-based methods improved in recent years. Especially, we review the CRISPR-based methods for functional validations in 3D genomics, which could be the forthcoming directions. We hope this review can show some insights into the potential improvements for future 3D genomics.
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39
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Ma W, Gu C, Ma L, Fan C, Zhang C, Sun Y, Li C, Yang G. Mixed secondary chromatin structure revealed by modeling radiation-induced DNA fragment length distribution. SCIENCE CHINA-LIFE SCIENCES 2020; 63:825-834. [PMID: 32279284 DOI: 10.1007/s11427-019-1638-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 01/20/2020] [Indexed: 10/24/2022]
Abstract
Spatial chromatin structure plays fundamental roles in many vital biological processes including DNA replication, transcription, damage and repair. However, the current understanding of the secondary structure of chromatin formed by local nucleosome-nucleosome interactions remains controversial, especially for the existence and conformation of 30 nm structure. Since chromatin structure influences the fragment length distribution (FLD) of ionizing radiation-induced DNA strand breaks, a 3D chromatin model fitting FLD patterns can help to distinguish different models of chromatin structure. Here, we developed a novel "30-C" model combining 30 nm chromatin structure models with Hi-C data, which measured the spatial contact frequency between different loci in the genome. We first reconstructed the 3D coordinates of the 25 kb bins from Hi-C heatmaps. Within the 25 kb bins, lower level chromatin structures supported by recent studies were filled. Simulated FLD patterns based on the 30-C model were compared to published FLD patterns induced by heavy ion radiation to validate the models. Importantly, the 30-C model predicted that the most probable chromatin fiber structure for human interphase fibroblasts in vivo was 45% zig-zag 30 nm fibers and 55% 10 nm fibers.
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Affiliation(s)
- Wenzong Ma
- State Key Laboratory of Nuclear Physics and Technology, School of Physics, Peking University, Beijing, 100871, China
| | - Chenyang Gu
- State Key Laboratory of Nuclear Physics and Technology, School of Physics, Peking University, Beijing, 100871, China.,Radiation Biology Center, Graduate School of Biostudies, Kyoto University, Kyoto, 606-8501, Japan
| | - Lin Ma
- State Key Laboratory of Nuclear Physics and Technology, School of Physics, Peking University, Beijing, 100871, China.,Medical Artificial Intelligence and Automation, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Caoqi Fan
- Center for Bioinformatics, School of Life Sciences and Center for Statistical Science, Peking University, Beijing, 100871, China
| | - Chao Zhang
- Center for Bioinformatics, School of Life Sciences and Center for Statistical Science, Peking University, Beijing, 100871, China
| | - Yujie Sun
- State Key Laboratory of Membrane Biology, School of Life Sciences, and Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, 100871, China
| | - Cheng Li
- Center for Bioinformatics, School of Life Sciences and Center for Statistical Science, Peking University, Beijing, 100871, China.
| | - Gen Yang
- State Key Laboratory of Nuclear Physics and Technology, School of Physics, Peking University, Beijing, 100871, China.
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40
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McCord RP, Kaplan N, Giorgetti L. Chromosome Conformation Capture and Beyond: Toward an Integrative View of Chromosome Structure and Function. Mol Cell 2020; 77:688-708. [PMID: 32001106 PMCID: PMC7134573 DOI: 10.1016/j.molcel.2019.12.021] [Citation(s) in RCA: 110] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Rapidly developing technologies have recently fueled an exciting era of discovery in the field of chromosome structure and nuclear organization. In addition to chromosome conformation capture (3C) methods, new alternative techniques have emerged to study genome architecture and biological processes in the nucleus, often in single or living cells. This sets an unprecedented stage for exploring the mechanisms that link chromosome structure and biological function. Here we review popular as well as emerging approaches to study chromosome organization, focusing on the contribution of complementary methodologies to our understanding of structures revealed by 3C methods and their biological implications, and discuss the next technical and conceptual frontiers.
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Affiliation(s)
- Rachel Patton McCord
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA
| | - Noam Kaplan
- Department of Physiology, Biophysics and Systems Biology, Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel
| | - Luca Giorgetti
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
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