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Wang W, Ye Y, Gao L. Statistical modeling and significance estimation of multi-way chromatin contacts with HyperloopFinder. Brief Bioinform 2024; 25:bbae341. [PMID: 39003726 PMCID: PMC11246602 DOI: 10.1093/bib/bbae341] [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: 03/27/2024] [Revised: 06/12/2024] [Accepted: 07/03/2024] [Indexed: 07/16/2024] Open
Abstract
Recent advances in chromatin conformation capture technologies, such as SPRITE and Pore-C, have enabled the detection of simultaneous contacts among multiple chromatin loci. This has made it possible to investigate the cooperative transcriptional regulation involving multiple genes and regulatory elements at the resolution of a single molecule. However, these technologies are unavoidably subject to the random polymer looping effect and technical biases, making it challenging to distinguish genuine regulatory relationships directly from random polymer interactions. Here, we present HyperloopFinder, a method for identifying regulatory multi-way chromatin contacts (hyperloops) by jointly modeling the random polymer looping effect and technical biases to estimate the statistical significance of multi-way contacts. The results show that our model can accurately estimate the expected interaction frequency of multi-way contacts based on the distance distribution of pairwise contacts, revealing that most multi-way contacts can be formed by randomly linking the pairwise contacts adjacent to each other. Moreover, we observed the spatial colocalization of the interaction sites of hyperloops from image-based data. Our results also revealed that hyperloops can function as scaffolds for the cooperation among multiple genes and regulatory elements. In summary, our work contributes novel insights into higher-order chromatin structures and functions and has the potential to enhance our understanding of transcriptional regulation and other cellular processes.
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Affiliation(s)
- Weibing Wang
- Department of Computer Science, School of Computer Science and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Yusen Ye
- Department of Computer Science, School of Computer Science and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Lin Gao
- Department of Computer Science, School of Computer Science and Technology, Xidian University, Xi'an, Shaanxi, China
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2
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Kim M, Wang P, Clow PA, Chien I(E, Wang X, Peng J, Chai H, Liu X, Lee B, Ngan CY, Yue F, Milenkovic O, Chuang JH, Wei CL, Casellas R, Cheng AW, Ruan Y. Multifaceted roles of cohesin in regulating transcriptional loops. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.25.586715. [PMID: 38585764 PMCID: PMC10996690 DOI: 10.1101/2024.03.25.586715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Cohesin is required for chromatin loop formation. However, its precise role in regulating gene transcription remains largely unknown. We investigated the relationship between cohesin and RNA Polymerase II (RNAPII) using single-molecule mapping and live-cell imaging methods in human cells. Cohesin-mediated transcriptional loops were highly correlated with those of RNAPII and followed the direction of gene transcription. Depleting RAD21, a subunit of cohesin, resulted in the loss of long-range (>100 kb) loops between distal (super-)enhancers and promoters of cell-type-specific genes. By contrast, the short-range (<50 kb) loops were insensitive to RAD21 depletion and connected genes that are mostly housekeeping. This result explains why only a small fraction of genes are affected by the loss of long-range chromatin interactions due to cohesin depletion. Remarkably, RAD21 depletion appeared to up-regulate genes located in early initiation zones (EIZ) of DNA replication, and the EIZ signals were amplified drastically without RAD21. Our results revealed new mechanistic insights of cohesin's multifaceted roles in establishing transcriptional loops, preserving long-range chromatin interactions for cell-specific genes, and maintaining timely order of DNA replication.
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Affiliation(s)
- Minji Kim
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Present address: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
- Equal contributions
| | - Ping Wang
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Evanston, IL, 60201, USA
- Equal contributions
| | - Patricia A. Clow
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Equal contributions
| | - I (Eli) Chien
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61820, USA
| | - Xiaotao Wang
- Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Reproduction and Development, Shanghai, China
| | - Jianhao Peng
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61820, USA
| | - Haoxi Chai
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Xiyuan Liu
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- State Key Laboratory of Ophthalmology, Optometry and Vision Science, Eye hospital and School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, 325027, P.R. China
| | - Byoungkoo Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Chew Yee Ngan
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Feng Yue
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Evanston, IL, 60201, USA
- Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Olgica Milenkovic
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61820, USA
| | - Jeffrey H. Chuang
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, 06030, USA
| | - Chia-Lin Wei
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Rafael Casellas
- Hematopoietic Biology and Malignancy, MD Anderson Cancer Center, Houston, TX, 77054, USA
| | - Albert W. Cheng
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, 85281, USA
| | - Yijun Ruan
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang Province, 310058, P.R. China
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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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4
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Mora A, Huang X, Jauhari S, Jiang Q, Li X. Chromatin Hubs: A biological and computational outlook. Comput Struct Biotechnol J 2022; 20:3796-3813. [PMID: 35891791 PMCID: PMC9304431 DOI: 10.1016/j.csbj.2022.07.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 07/02/2022] [Accepted: 07/02/2022] [Indexed: 11/20/2022] Open
Abstract
This review discusses our current understanding of chromatin biology and bioinformatics under the unifying concept of “chromatin hubs.” The first part reviews the biology of chromatin hubs, including chromatin–chromatin interaction hubs, chromatin hubs at the nuclear periphery, hubs around macromolecules such as RNA polymerase or lncRNAs, and hubs around nuclear bodies such as the nucleolus or nuclear speckles. The second part reviews existing computational methods, including enhancer–promoter interaction prediction, network analysis, chromatin domain callers, transcription factory predictors, and multi-way interaction analysis. We introduce an integrated model that makes sense of the existing evidence. Understanding chromatin hubs may allow us (i) to explain long-unsolved biological questions such as interaction specificity and redundancy of mechanisms, (ii) to develop more realistic kinetic and functional predictions, and (iii) to explain the etiology of genomic disease.
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Affiliation(s)
- Antonio Mora
- Joint School of Life Sciences, Guangzhou Medical University and Guangzhou Institutes of Biomedicine and Health (Chinese Academy of Sciences), Guangzhou 511436, PR China
- Corresponding authors.
| | - Xiaowei Huang
- Joint School of Life Sciences, Guangzhou Medical University and Guangzhou Institutes of Biomedicine and Health (Chinese Academy of Sciences), Guangzhou 511436, PR China
| | - Shaurya Jauhari
- Joint School of Life Sciences, Guangzhou Medical University and Guangzhou Institutes of Biomedicine and Health (Chinese Academy of Sciences), Guangzhou 511436, PR China
| | - Qin Jiang
- Affiliated Eye Hospital of Nanjing Medical University, Nanjing 210000, PR China
| | - Xuri Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, and Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, PR China
- Corresponding authors.
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5
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Deng S, Feng Y, Pauklin S. 3D chromatin architecture and transcription regulation in cancer. J Hematol Oncol 2022; 15:49. [PMID: 35509102 PMCID: PMC9069733 DOI: 10.1186/s13045-022-01271-x] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 04/21/2022] [Indexed: 12/18/2022] Open
Abstract
Chromatin has distinct three-dimensional (3D) architectures important in key biological processes, such as cell cycle, replication, differentiation, and transcription regulation. In turn, aberrant 3D structures play a vital role in developing abnormalities and diseases such as cancer. This review discusses key 3D chromatin structures (topologically associating domain, lamina-associated domain, and enhancer-promoter interactions) and corresponding structural protein elements mediating 3D chromatin interactions [CCCTC-binding factor, polycomb group protein, cohesin, and Brother of the Regulator of Imprinted Sites (BORIS) protein] with a highlight of their associations with cancer. We also summarise the recent development of technologies and bioinformatics approaches to study the 3D chromatin interactions in gene expression regulation, including crosslinking and proximity ligation methods in the bulk cell population (ChIA-PET and HiChIP) or single-molecule resolution (ChIA-drop), and methods other than proximity ligation, such as GAM, SPRITE, and super-resolution microscopy techniques.
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Affiliation(s)
- Siwei Deng
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Botnar Research Centre, University of Oxford, Old Road, Headington, Oxford, OX3 7LD, UK
| | - Yuliang Feng
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Botnar Research Centre, University of Oxford, Old Road, Headington, Oxford, OX3 7LD, UK
| | - Siim Pauklin
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Botnar Research Centre, University of Oxford, Old Road, Headington, Oxford, OX3 7LD, UK.
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6
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Abstract
The spatial organization of the genome in the cell nucleus is pivotal to cell function. However, how the 3D genome organization and its dynamics influence cellular phenotypes remains poorly understood. The very recent development of single-cell technologies for probing the 3D genome, especially single-cell Hi-C (scHi-C), has ushered in a new era of unveiling cell-to-cell variability of 3D genome features at an unprecedented resolution. Here, we review recent developments in computational approaches to the analysis of scHi-C, including data processing, dimensionality reduction, imputation for enhancing data quality, and the revealing of 3D genome features at single-cell resolution. While much progress has been made in computational method development to analyze single-cell 3D genomes, substantial future work is needed to improve data interpretation and multimodal data integration, which are critical to reveal fundamental connections between genome structure and function among heterogeneous cell populations in various biological contexts.
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Affiliation(s)
- Tianming Zhou
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA;
| | - Ruochi Zhang
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA;
| | - Jian Ma
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA;
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7
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Zhang R, Ma J. MATCHA: Probing multi-way chromatin interaction with hypergraph representation learning. Cell Syst 2020; 10:397-407.e5. [PMID: 32550271 PMCID: PMC7299183 DOI: 10.1016/j.cels.2020.04.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Recent advances in ligation-free, genome-wide chromatin interaction mapping such as SPRITE and ChIA-Drop have enabled the identification of simultaneous interactions involving multiple genomic loci within the same nuclei, which are informative to delineate higher-order genome organization and gene regulation mechanisms at single-nucleus resolution. Unfortunately, computational methods for analyzing multi-way chromatin interaction data are significantly underexplored. Here we develop an algorithm, called MATCHA, based on hypergraph representation learning where multi-way chromatin interactions are represented as hyperedges. Applications to SPRITE and ChIA-Drop data suggest that MATCHA is effective to denoise the data and make de novo predictions, which greatly enhances the data quality for analyzing the properties of multi-way chromatin interactions. MATCHA provides a promising framework to significantly improve the analysis of multi-way chromatin interaction data and has the potential to offer unique insights into higher-order chromosome organization and function. MATCHA is freely available for download here: https://github.com/ma-compbio/MATCHA.
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Affiliation(s)
- Ruochi Zhang
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Jian Ma
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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8
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Xu H, Zhang S, Yi X, Plewczynski D, Li MJ. Exploring 3D chromatin contacts in gene regulation: The evolution of approaches for the identification of functional enhancer-promoter interaction. Comput Struct Biotechnol J 2020; 18:558-570. [PMID: 32226593 PMCID: PMC7090358 DOI: 10.1016/j.csbj.2020.02.013] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Revised: 02/21/2020] [Accepted: 02/22/2020] [Indexed: 12/12/2022] Open
Abstract
Mechanisms underlying gene regulation are key to understand how multicellular organisms with various cell types develop from the same genetic blueprint. Dynamic interactions between enhancers and genes are revealed to play central roles in controlling gene transcription, but the determinants to link functional enhancer-promoter pairs remain elusive. A major challenge is the lack of reliable approach to detect and verify functional enhancer-promoter interactions (EPIs). In this review, we summarized the current methods for detecting EPIs and described how developing techniques facilitate the identification of EPI through assessing the merits and drawbacks of these methods. We also reviewed recent state-of-art EPI prediction methods in terms of their rationale, data usage and characterization. Furthermore, we briefly discussed the evolved strategies for validating functional EPIs.
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Affiliation(s)
- Hang Xu
- 2011 Collaborative Innovation Center of Tianjin for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, Tianjin Medical University, Tianjin, China
| | - Shijie Zhang
- 2011 Collaborative Innovation Center of Tianjin for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, Tianjin Medical University, Tianjin, China
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Xianfu Yi
- School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
| | - Dariusz Plewczynski
- Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097 Warsaw, Poland
- Faculty of Mathematics and Information Science, Warsaw University of Technology, Koszykowa 75, 00-662 Warsaw, Poland
| | - Mulin Jun Li
- 2011 Collaborative Innovation Center of Tianjin for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, Tianjin Medical University, Tianjin, China
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
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