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Xu Y, Das P, McCord RP, Shen T. Node features of chromosome structure networks and their connections to genome annotation. Comput Struct Biotechnol J 2024; 23:2240-2250. [PMID: 38827231 PMCID: PMC11140560 DOI: 10.1016/j.csbj.2024.05.026] [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: 12/13/2023] [Revised: 05/14/2024] [Accepted: 05/15/2024] [Indexed: 06/04/2024] Open
Abstract
The 3D conformations of chromosomes can encode biological significance, and the implications of such structures have been increasingly appreciated recently. Certain chromosome structural features, such as A/B compartmentalization, are frequently extracted from Hi-C pairwise genome contact information (physical association between different regions of the genome) and compared with linear annotations of the genome, such as histone modifications and lamina association. We investigate how additional properties of chromosome structure can be deduced using an abstract graph representation of the contact heatmap, and describe specific network properties that can have a strong connection with some of these biological annotations. We constructed chromosome structure networks (CSNs) from bulk Hi-C data and calculated a set of site-resolved (node-based) network properties. These properties are useful for characterizing certain aspects of chromosomal structure. We examined the ability of network properties to differentiate several scenarios, such as haploid vs diploid cells, partially inverted nuclei vs conventional architecture, depletion of chromosome architectural proteins, and structural changes during cell development. We also examined the connection between network properties and a series of other linear annotations, such as histone modifications and chromatin states including poised promoter and enhancer labels. We found that semi-local network properties exhibit greater capability in characterizing genome annotations compared to diffusive or ultra-local node features. For example, the local square clustering coefficient can be a strong classifier of lamina-associated domains. We demonstrated that network properties can be useful for highlighting large-scale chromosome structure differences that emerge in different biological situations.
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Affiliation(s)
- Yingjie Xu
- Graduate School of Genome Science & Technology, University of Tennessee, Knoxville, TN 37996, USA
| | - Priyojit Das
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Department of Molecular Biology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Rachel Patton McCord
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
| | - Tongye Shen
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
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2
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Jin X, Zhang R, Fu Y, Zhu Q, Hong L, Wu A, Wang H. Unveiling aging dynamics in the hematopoietic system insights from single-cell technologies. Brief Funct Genomics 2024; 23:639-650. [PMID: 38688725 DOI: 10.1093/bfgp/elae019] [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: 02/10/2024] [Revised: 04/10/2024] [Accepted: 04/15/2024] [Indexed: 05/02/2024] Open
Abstract
As the demographic structure shifts towards an aging society, strategies aimed at slowing down or reversing the aging process become increasingly essential. Aging is a major predisposing factor for many chronic diseases in humans. The hematopoietic system, comprising blood cells and their associated bone marrow microenvironment, intricately participates in hematopoiesis, coagulation, immune regulation and other physiological phenomena. The aging process triggers various alterations within the hematopoietic system, serving as a spectrum of risk factors for hematopoietic disorders, including clonal hematopoiesis, immune senescence, myeloproliferative neoplasms and leukemia. The emerging single-cell technologies provide novel insights into age-related changes in the hematopoietic system. In this review, we summarize recent studies dissecting hematopoietic system aging using single-cell technologies. We discuss cellular changes occurring during aging in the hematopoietic system at the levels of the genomics, transcriptomics, epigenomics, proteomics, metabolomics and spatial multi-omics. Finally, we contemplate the future prospects of single-cell technologies, emphasizing the impact they may bring to the field of hematopoietic system aging research.
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Affiliation(s)
- Xinrong Jin
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Ruohan Zhang
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Yunqi Fu
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Qiunan Zhu
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Liquan Hong
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Aiwei Wu
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Hu Wang
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
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3
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Zhang Q, Falqués‐Costa T, Pilheden M, Sturesson H, Ovlund T, Rissler V, Castor A, Marquart HVH, Lausen B, Fioretos T, Hyrenius‐Wittsten A, Hagström‐Andersson AK. Activating mutations remodel the chromatin accessibility landscape to drive distinct regulatory networks in KMT2A-rearranged acute leukemia. Hemasphere 2024; 8:e70006. [PMID: 39329074 PMCID: PMC11426354 DOI: 10.1002/hem3.70006] [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: 02/22/2024] [Revised: 08/02/2024] [Accepted: 08/07/2024] [Indexed: 09/28/2024] Open
Abstract
Activating FLT3 and RAS mutations commonly occur in leukemia with KMT2A-gene rearrangements (KMT2A-r). However, how these mutations cooperate with the KMT2A-r to remodel the epigenetic landscape is unknown. Using a retroviral acute myeloid leukemia (AML) mouse model driven by KMT2A::MLLT3, we show that FLT3 ITD , FLT3 N676K , and NRAS G12D remodeled the chromatin accessibility landscape and associated transcriptional networks. Although the activating mutations shared a common core of chromatin changes, each mutation exhibits unique profiles with most opened peaks associating with enhancers in intronic or intergenic regions. Specifically, FLT3 N676K and NRAS G12D rewired similar chromatin and transcriptional networks, distinct from those mediated by FLT3 ITD . Motif analysis uncovered a role for the AP-1 family of transcription factors in KMT2A::MLLT3 leukemia with FLT3 N676K and NRAS G12D , whereas Runx1 and Stat5a/Stat5b were active in the presence of FLT3 ITD . Furthermore, transcriptional programs linked to immune cell regulation were activated in KMT2A-r AML expressing NRAS G12D or FLT3 N676K , and the expression of NKG2D-ligands on KMT2A-r cells rendered them sensitive to CAR T cell-mediated killing. Human KMT2A-r AML cells could be pharmacologically sensitized to NKG2D-CAR T cells by treatment with the histone deacetylase inhibitor LBH589 (panobinostat) which caused upregulation of NKG2D-ligand levels. Co-treatment with LBH589 and NKG2D-CAR T cells enabled robust AML cell killing, and the strongest effect was observed for cells expressing NRAS G12D . Finally, the results were validated and extended to acute leukemia in infancy. Combined, activating mutations induced mutation-specific changes in the epigenetic landscape, leading to changes in transcriptional programs orchestrated by specific transcription factor networks.
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Affiliation(s)
- Qirui Zhang
- Department of Laboratory Medicine, Division of Clinical GeneticsLund UniversityLundSweden
| | - Ton Falqués‐Costa
- Department of Laboratory Medicine, Division of Clinical GeneticsLund UniversityLundSweden
| | - Mattias Pilheden
- Department of Laboratory Medicine, Division of Clinical GeneticsLund UniversityLundSweden
| | - Helena Sturesson
- Department of Laboratory Medicine, Division of Clinical GeneticsLund UniversityLundSweden
| | - Tina Ovlund
- Department of Laboratory Medicine, Division of Clinical GeneticsLund UniversityLundSweden
| | - Vendela Rissler
- Department of Laboratory Medicine, Division of Clinical GeneticsLund UniversityLundSweden
| | - Anders Castor
- Childhood Cancer CenterSkåne University HospitalLundSweden
| | - Hanne V. H. Marquart
- Department of Clinical ImmunologyNational University HospitalRigshospitalet, CopenhagenDenmark
- Department of Clinical Medicine, Faculty of Health and Medical SciencesUniversity of CopenhagenCopenhagenDenmark
| | - Birgitte Lausen
- Department of Paediatrics and Adolescent Medicine, RigshospitaletUniversity of CopenhagenCopenhagenDenmark
| | - Thoas Fioretos
- Department of Laboratory Medicine, Division of Clinical GeneticsLund UniversityLundSweden
| | - Axel Hyrenius‐Wittsten
- Department of Laboratory Medicine, Division of Clinical GeneticsLund UniversityLundSweden
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4
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He M, Li X, Xu B, Lu Y, Lai J, Ling Y, Liu H, An Z, Zhang W, Li F. Reprogramming of 3D genome structure underlying HSPC development in zebrafish. Stem Cell Res Ther 2024; 15:172. [PMID: 38886858 PMCID: PMC11184745 DOI: 10.1186/s13287-024-03798-x] [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: 01/24/2024] [Accepted: 06/10/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Development of hematopoietic stem and progenitor cells (HSPC) is a multi-staged complex process that conserved between zebrafish and mammals. Understanding the mechanism underlying HSPC development is a holy grail of hematopoietic biology, which is helpful for HSPC clinical application. Chromatin conformation plays important roles in transcriptional regulation and cell fate decision; however, its dynamic and role in HSPC development is poorly investigated. METHODS We performed chromatin structure and multi-omics dissection across different stages of HSPC developmental trajectory in zebrafish for the first time, including Hi-C, RNA-seq, ATAC-seq, H3K4me3 and H3K27ac ChIP-seq. RESULTS The chromatin organization of zebrafish HSPC resemble mammalian cells with similar hierarchical structure. We revealed the multi-scale reorganization of chromatin structure and its influence on transcriptional regulation and transition of cell fate during HSPC development. Nascent HSPC is featured by loose conformation with obscure structure at all layers. Notably, PU.1 was identified as a potential factor mediating formation of promoter-involved loops and regulating gene expression of HSPC. CONCLUSIONS Our results provided a global view of chromatin structure dynamics associated with development of zebrafish HSPC and discovered key transcription factors involved in HSPC chromatin interactions, which will provide new insights into the epigenetic regulatory mechanisms underlying vertebrate HSPC fate decision.
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Affiliation(s)
- Min He
- Division of Cell, Developmental and Integrative Biology, School of Medicine, South China University of Technology, Guangzhou, 510006, China
| | - Xiaoli Li
- Division of Cell, Developmental and Integrative Biology, School of Medicine, South China University of Technology, Guangzhou, 510006, China
- Laboratory of Developmental Biology, Department of Cell Biology and Genetics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, 400016, China
| | - Bingxiang Xu
- Key Laboratory of Hebei Province for Molecular Biophysics, Institute of Biophysics, School of Health Science & Biomedical Engineering, Hebei University of Technology, Tianjin, 300130, China
| | - Yinbo Lu
- Division of Cell, Developmental and Integrative Biology, School of Medicine, South China University of Technology, Guangzhou, 510006, China
| | - Jingyi Lai
- Division of Cell, Developmental and Integrative Biology, School of Medicine, South China University of Technology, Guangzhou, 510006, China
| | - Yiming Ling
- Division of Cell, Developmental and Integrative Biology, School of Medicine, South China University of Technology, Guangzhou, 510006, China
| | - Huakai Liu
- Vehicle Engineering, School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, 510000, China
| | - Ziyang An
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Wenqing Zhang
- Division of Cell, Developmental and Integrative Biology, School of Medicine, South China University of Technology, Guangzhou, 510006, China.
| | - Feifei Li
- Division of Cell, Developmental and Integrative Biology, School of Medicine, South China University of Technology, Guangzhou, 510006, China.
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5
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Tang B, Wang X, He H, Chen R, Qiao G, Yang Y, Xu Z, Wang L, Dong Q, Yu J, Zhang MQ, Shi M, Wang J. Aging-disturbed FUS phase transition impairs hematopoietic stem cells by altering chromatin structure. Blood 2024; 143:124-138. [PMID: 37748139 DOI: 10.1182/blood.2023020539] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 09/08/2023] [Accepted: 09/09/2023] [Indexed: 09/27/2023] Open
Abstract
ABSTRACT Aged hematopoietic stem cells (HSCs) exhibit compromised reconstitution capacity. The molecular mechanisms behind this phenomenon are not fully understood. Here, we observed that the expression of FUS is increased in aged HSCs, and enforced FUS recapitulates the phenotype of aged HSCs through arginine-glycine-glycine-mediated aberrant FUS phase transition. By using Fus-gfp mice, we observed that FUShigh HSCs exhibit compromised FUS mobility and resemble aged HSCs both functionally and transcriptionally. The percentage of FUShigh HSCs is increased upon physiological aging and replication stress, and FUSlow HSCs of aged mice exhibit youthful function. Mechanistically, FUShigh HSCs exhibit a different global chromatin organization compared with FUSlow HSCs, which is observed in aged HSCs. Many topologically associating domains (TADs) are merged in aged HSCs because of the compromised binding of CCCTC-binding factor with chromatin, which is invoked by aberrant FUS condensates. It is notable that the transcriptional alteration between FUShigh and FUSlow HSCs originates from the merged TADs and is enriched in HSC aging-related genes. Collectively, this study reveals for the first time that aberrant FUS mobility promotes HSC aging by altering chromatin structure.
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Affiliation(s)
- Baixue Tang
- Department of Biology, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
| | - Xinming Wang
- Tsinghua-Peking Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing, China
| | - Hanqing He
- Department of Biology, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
| | - Ruiqing Chen
- Department of Biology, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
| | - Guofeng Qiao
- Department of Biology, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
| | - Yang Yang
- Department of Biology, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
| | - Zihan Xu
- School of Life Sciences, Joint Graduate Program of Peking-Tsinghua-National Institute of Biological Sciences, Peking University, Beijing, China
| | - Longteng Wang
- School of Life Sciences, Joint Graduate Program of Peking-Tsinghua-National Institute of Biological Sciences, Peking University, Beijing, China
| | - Qiongye Dong
- Institute of Precision of Medicine, Peking University Shenzhen Hospital, Shenzhen, China
| | - Jia Yu
- State Key Laboratory of Medical Molecular Biology, Department of Biochemistry and Molecular Biology, Haihe Laboratory of Cell Ecosystem, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, China
| | - Michael Q Zhang
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, Beijing National Research Center for Information Science and Technology, School of Medicine, Tsinghua University, Beijing, China
- Department of Biological Sciences, Center for Systems Biology, The University of Texas, Richardson, TX
| | - Minglei Shi
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, Beijing National Research Center for Information Science and Technology, School of Medicine, Tsinghua University, Beijing, China
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
| | - Jianwei Wang
- Department of Biology, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
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6
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Zhang Y, Liu F. The evolving views of hematopoiesis: from embryo to adulthood and from in vivo to in vitro. J Genet Genomics 2024; 51:3-15. [PMID: 37734711 DOI: 10.1016/j.jgg.2023.09.005] [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: 08/23/2023] [Revised: 09/13/2023] [Accepted: 09/13/2023] [Indexed: 09/23/2023]
Abstract
The hematopoietic system composed of hematopoietic stem and progenitor cells (HSPCs) and their differentiated lineages serves as an ideal model to uncover generic principles of cell fate transitions. From gastrulation onwards, there successively emerge primitive hematopoiesis (that produces specialized hematopoietic cells), pro-definitive hematopoiesis (that produces lineage-restricted progenitor cells), and definitive hematopoiesis (that produces multipotent HSPCs). These nascent lineages develop in several transient hematopoietic sites and finally colonize into lifelong hematopoietic sites. The development and maintenance of hematopoietic lineages are orchestrated by cell-intrinsic gene regulatory networks and cell-extrinsic microenvironmental cues. Owing to the progressive methodology (e.g., high-throughput lineage tracing and single-cell functional and omics analyses), our understanding of the developmental origin of hematopoietic lineages and functional properties of certain hematopoietic organs has been updated; meanwhile, new paradigms to characterize rare cell types, cell heterogeneity and its causes, and comprehensive regulatory landscapes have been provided. Here, we review the evolving views of HSPC biology during developmental and postnatal hematopoiesis. Moreover, we discuss recent advances in the in vitro induction and expansion of HSPCs, with a focus on the implications for clinical applications.
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Affiliation(s)
- Yifan Zhang
- Shandong Provincial Key Laboratory of Animal Cell and Developmental Biology, School of Life Sciences, Shandong University, Qingdao, Shandong 266237, China
| | - Feng Liu
- Shandong Provincial Key Laboratory of Animal Cell and Developmental Biology, School of Life Sciences, Shandong University, Qingdao, Shandong 266237, China; State Key Laboratory of Membrane Biology, Institute of Zoology, Institute for Stem Cell and Regeneration, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100101, China.
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7
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Poinsignon T, Gallopin M, Grognet P, Malagnac F, Lelandais G, Poulain P. 3D models of fungal chromosomes to enhance visual integration of omics data. NAR Genom Bioinform 2023; 5:lqad104. [PMID: 38058589 PMCID: PMC10696920 DOI: 10.1093/nargab/lqad104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 10/11/2023] [Accepted: 11/17/2023] [Indexed: 12/08/2023] Open
Abstract
The functions of eukaryotic chromosomes and their spatial architecture in the nucleus are reciprocally dependent. Hi-C experiments are routinely used to study chromosome 3D organization by probing chromatin interactions. Standard representation of the data has relied on contact maps that show the frequency of interactions between parts of the genome. In parallel, it has become easier to build 3D models of the entire genome based on the same Hi-C data, and thus benefit from the methodology and visualization tools developed for structural biology. 3D modeling of entire genomes leverages the understanding of their spatial organization. However, this opportunity for original and insightful modeling is underexploited. In this paper, we show how seeing the spatial organization of chromosomes can bring new perspectives to omics data integration. We assembled state-of-the-art tools into a workflow that goes from Hi-C raw data to fully annotated 3D models and we re-analysed public omics datasets available for three fungal species. Besides the well-described properties of the spatial organization of their chromosomes (Rabl conformation, hypercoiling and chromosome territories), our results highlighted (i) in Saccharomyces cerevisiae, the backbones of the cohesin anchor regions, which were aligned all along the chromosomes, (ii) in Schizosaccharomyces pombe, the oscillations of the coiling of chromosome arms throughout the cell cycle and (iii) in Neurospora crassa, the massive relocalization of histone marks in mutants of heterochromatin regulators. 3D modeling of the chromosomes brings new opportunities for visual integration of omics data. This holistic perspective supports intuition and lays the foundation for building new concepts.
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Affiliation(s)
- Thibault Poinsignon
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université Paris-Saclay, 91198 Gif-sur-Yvette, France
- Université Paris Cité, CNRS, Institut Jacques Monod, F-75013 Paris, France
| | - Mélina Gallopin
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université Paris-Saclay, 91198 Gif-sur-Yvette, France
| | - Pierre Grognet
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université Paris-Saclay, 91198 Gif-sur-Yvette, France
| | - Fabienne Malagnac
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université Paris-Saclay, 91198 Gif-sur-Yvette, France
| | - Gaëlle Lelandais
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université Paris-Saclay, 91198 Gif-sur-Yvette, France
| | - Pierre Poulain
- Université Paris Cité, CNRS, Institut Jacques Monod, F-75013 Paris, France
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8
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Salafranca J, Ko JK, Mukherjee AK, Fritzsche M, van Grinsven E, Udalova IA. Neutrophil nucleus: shaping the past and the future. J Leukoc Biol 2023; 114:585-594. [PMID: 37480361 PMCID: PMC10673716 DOI: 10.1093/jleuko/qiad084] [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: 03/21/2023] [Revised: 07/10/2023] [Accepted: 07/12/2023] [Indexed: 07/24/2023] Open
Abstract
Neutrophils are innate immune cells that are key to protecting the host against infection and maintaining body homeostasis. However, if dysregulated, they can contribute to disease, such as in cancer or chronic autoinflammatory disorders. Recent studies have highlighted the heterogeneity in the neutrophil compartment and identified the presence of immature neutrophils and their precursors in these pathologies. Therefore, understanding neutrophil maturity and the mechanisms through which they contribute to disease is critical. Neutrophils were first characterized morphologically by Ehrlich in 1879 using microscopy, and since then, different technologies have been used to assess neutrophil maturity. The advances in the imaging field, including state-of-the-art microscopy and machine learning algorithms for image analysis, reinforce the use of neutrophil nuclear morphology as a fundamental marker of maturity, applicable for objective classification in clinical diagnostics. New emerging approaches, such as the capture of changes in chromatin topology, will provide mechanistic links between the nuclear shape, chromatin organization, and transcriptional regulation during neutrophil maturation.
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Affiliation(s)
- Julia Salafranca
- The Kennedy Institute of Rheumatology, University of Oxford, Old Road Campus Research Build, Roosevelt Dr, Headington, Oxford OX3 7DQ, United Kingdom
| | - Jacky Ka Ko
- The Kennedy Institute of Rheumatology, University of Oxford, Old Road Campus Research Build, Roosevelt Dr, Headington, Oxford OX3 7DQ, United Kingdom
| | - Ananda K Mukherjee
- The Kennedy Institute of Rheumatology, University of Oxford, Old Road Campus Research Build, Roosevelt Dr, Headington, Oxford OX3 7DQ, United Kingdom
| | - Marco Fritzsche
- The Kennedy Institute of Rheumatology, University of Oxford, Old Road Campus Research Build, Roosevelt Dr, Headington, Oxford OX3 7DQ, United Kingdom
| | - Erinke van Grinsven
- The Kennedy Institute of Rheumatology, University of Oxford, Old Road Campus Research Build, Roosevelt Dr, Headington, Oxford OX3 7DQ, United Kingdom
| | - Irina A Udalova
- The Kennedy Institute of Rheumatology, University of Oxford, Old Road Campus Research Build, Roosevelt Dr, Headington, Oxford OX3 7DQ, United Kingdom
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9
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Lin D, Zou Y, Li X, Wang J, Xiao Q, Gao X, Lin F, Zhang N, Jiao M, Guo Y, Teng Z, Li S, Wei Y, Zhou F, Yin R, Zhang S, Xing L, Xu W, Wu X, Yang B, Xiao K, Wu C, Tao Y, Yang X, Zhang J, Hu S, Dong S, Li X, Ye S, Hong Z, Pan Y, Yang Y, Sun H, Cao G. MGA-seq: robust identification of extrachromosomal DNA and genetic variants using multiple genetic abnormality sequencing. Genome Biol 2023; 24:247. [PMID: 37904244 PMCID: PMC10614391 DOI: 10.1186/s13059-023-03081-x] [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: 02/05/2023] [Accepted: 10/04/2023] [Indexed: 11/01/2023] Open
Abstract
Genomic abnormalities are strongly associated with cancer and infertility. In this study, we develop a simple and efficient method - multiple genetic abnormality sequencing (MGA-Seq) - to simultaneously detect structural variation, copy number variation, single-nucleotide polymorphism, homogeneously staining regions, and extrachromosomal DNA (ecDNA) from a single tube. MGA-Seq directly sequences proximity-ligated genomic fragments, yielding a dataset with concurrent genome three-dimensional and whole-genome sequencing information, enabling approximate localization of genomic structural variations and facilitating breakpoint identification. Additionally, by utilizing MGA-Seq, we map focal amplification and oncogene coamplification, thus facilitating the exploration of ecDNA's transcriptional regulatory function.
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Affiliation(s)
- Da Lin
- Precision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Yanyan Zou
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Informatics, Huazhong Agricultural University, Wuhan, China
| | - Xinyu Li
- Precision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jinyue Wang
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Bio-Medicine and Health, Huazhong Agricultural University, Wuhan, China
- College of Life Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Qin Xiao
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Bio-Medicine and Health, Huazhong Agricultural University, Wuhan, China
- College of Life Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Xiaochen Gao
- Precision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Fei Lin
- Reproductive Medical Center, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Ningyuan Zhang
- Reproductive Medical Center, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Ming Jiao
- Department of Laboratory Animal Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Guo
- Department of Laboratory Animal Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhaowei Teng
- The First People's Hospital of Yunnan Province, Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
| | - Shiyi Li
- Baylor College of Medicine, Houston, TX, USA
- Department of Radiation & Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yongchang Wei
- Department of Radiation & Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Tumor Biological Behaviors, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Fuling Zhou
- Department of Hematology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Rong Yin
- Department of Hematology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Siheng Zhang
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Lingyu Xing
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Weize Xu
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Xiaofeng Wu
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Bing Yang
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Ke Xiao
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Chengchao Wu
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Yingfeng Tao
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Xiaoqing Yang
- Hospital of Huazhong Agricultural University, Wuhan, China
| | - Jing Zhang
- Department of Medical Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Sheng Hu
- Department of Medical Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shuang Dong
- Department of Medical Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoyu Li
- Department of Medical Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shengwei Ye
- Department of Gastrointestinal Surgery, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhidan Hong
- Dapartment of Reproductive Medicine Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yihang Pan
- Precision Medicine Center, Scientific Research Center, School of Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China
| | - Yuqin Yang
- Department of Laboratory Animal Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Haixiang Sun
- Reproductive Medical Center, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
| | - Gang Cao
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China.
- College of Bio-Medicine and Health, Huazhong Agricultural University, Wuhan, China.
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China.
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
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10
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Gao GF, Li P, Leonard WJ. Co-localization of clusters of TCR-regulated genes with TAD rearrangements. BMC Genomics 2023; 24:650. [PMID: 37898735 PMCID: PMC10613383 DOI: 10.1186/s12864-023-09693-8] [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: 05/18/2023] [Accepted: 09/21/2023] [Indexed: 10/30/2023] Open
Abstract
BACKGROUND Gene expression has long been known to be influenced by the relative proximity of DNA regulatory elements. Topologically associating domains (TADs) are self-interacting genomic regions involved in regulating gene expression by controlling the proximity of these elements. Prior studies of TADs and their biological roles have revealed correlations between TAD changes and cellular differentiation. Here, we used Hi-C and RNA-seq data to correlate TCR-induced changes in TAD structure and gene expression in human CD4+ T cells. RESULTS We developed a pipeline, Differentially Expressed Gene Enrichment Finder (DEGEF), that identifies regions of differentially expressed gene enrichment. Using DEGEF, we found that TCR-regulated genes cluster non-uniformly across the genome and that these clusters preferentially localized in regions of TAD rearrangement. Interestingly, clusters of upregulated genes preferentially formed new Hi-C contacts compared to downregulated clusters, suggesting that TCR-activated CD4+ T cells may regulate genes by changing stimulatory contacts rather than inhibitory contacts. CONCLUSIONS Our observations support a significant relationship between TAD rearrangements and changes in local gene expression. These findings indicate potentially important roles for TAD rearrangements in shaping their local regulatory environments and thus driving differential expression of nearby genes during CD4+ T cell activation. Moreover, they provide new insights into global mechanisms that regulate gene expression.
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Affiliation(s)
- Galen F Gao
- Laboratory of Molecular Immunology and the Immunology Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892-1674, USA
| | - Peng Li
- Laboratory of Molecular Immunology and the Immunology Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892-1674, USA
| | - Warren J Leonard
- Laboratory of Molecular Immunology and the Immunology Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892-1674, USA.
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11
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Ng M, Verboon L, Issa H, Bhayadia R, Vermunt MW, Winkler R, Schüler L, Alejo O, Schuschel K, Regenyi E, Borchert D, Heuser M, Reinhardt D, Yaspo ML, Heckl D, Klusmann JH. Myeloid leukemia vulnerabilities embedded in long noncoding RNA locus MYNRL15. iScience 2023; 26:107844. [PMID: 37766974 PMCID: PMC10520325 DOI: 10.1016/j.isci.2023.107844] [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: 10/19/2022] [Revised: 05/02/2023] [Accepted: 09/04/2023] [Indexed: 09/29/2023] Open
Abstract
The noncoding genome presents a largely untapped source of new biological insights, including thousands of long noncoding RNA (lncRNA) loci. While lncRNA dysregulation has been reported in myeloid malignancies, their functional relevance remains to be systematically interrogated. We performed CRISPRi screens of lncRNA signatures from normal and malignant hematopoietic cells and identified MYNRL15 as a myeloid leukemia dependency. Functional dissection suggests an RNA-independent mechanism mediated by two regulatory elements embedded in the locus. Genetic perturbation of these elements triggered a long-range chromatin interaction and downregulation of leukemia dependency genes near the gained interaction sites, as well as overall suppression of cancer dependency pathways. Thus, this study describes a new noncoding myeloid leukemia vulnerability and mechanistic concept for myeloid leukemia. Importantly, MYNRL15 perturbation caused strong and selective impairment of leukemia cells of various genetic backgrounds over normal hematopoietic stem and progenitor cells in vitro, and depletion of patient-derived xenografts in vivo.
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Affiliation(s)
- Michelle Ng
- Department of Pediatric Hematology and Oncology, Martin Luther University Halle-Wittenberg, 06120 Halle (Saale), Germany
| | - Lonneke Verboon
- Department of Pediatrics, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- Frankfurt Cancer Institute, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hasan Issa
- Department of Pediatrics, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- Frankfurt Cancer Institute, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Raj Bhayadia
- Department of Pediatrics, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- Frankfurt Cancer Institute, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Marit Willemijn Vermunt
- Department of Pediatrics, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Robert Winkler
- Department of Pediatrics, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- Frankfurt Cancer Institute, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Leah Schüler
- Department of Pediatrics, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- Frankfurt Cancer Institute, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Oriol Alejo
- Department of Pediatric Hematology and Oncology, Martin Luther University Halle-Wittenberg, 06120 Halle (Saale), Germany
| | - Konstantin Schuschel
- Department of Pediatrics, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- Frankfurt Cancer Institute, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Eniko Regenyi
- Department of Pediatric Hematology and Oncology, Martin Luther University Halle-Wittenberg, 06120 Halle (Saale), Germany
- Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Dorit Borchert
- Department of Pediatric Hematology and Oncology, Hannover Medical School, 30625 Hannover, Germany
| | - Michael Heuser
- Department of Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School, 30625 Hannover, Germany
| | - Dirk Reinhardt
- Clinic for Pediatrics III, University Hospital Essen, 45147 Essen, Germany
| | - Marie-Laure Yaspo
- Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Dirk Heckl
- Institute for Experimental Pediatric Hematology and Oncology, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
| | - Jan-Henning Klusmann
- Department of Pediatrics, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- Frankfurt Cancer Institute, Goethe University Frankfurt, 60323 Frankfurt (Main), Germany
- German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz and German Cancer Research Center (DKFZ), Heidelberg, Germany
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12
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Yue H, Li A, Tang Y, Chen R. TapHi-C for profiling genome-wide chromosome conformation capture. TRENDS IN PLANT SCIENCE 2023; 28:1192-1193. [PMID: 37460330 DOI: 10.1016/j.tplants.2023.06.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 05/20/2023] [Accepted: 06/19/2023] [Indexed: 09/16/2023]
Affiliation(s)
- Haiyan Yue
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China; College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Aixuan Li
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China; College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Yiheng Tang
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China; College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Runsheng Chen
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China; College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China.
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13
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Christou-Kent M, Cuartero S, Garcia-Cabau C, Ruehle J, Naderi J, Erber J, Neguembor MV, Plana-Carmona M, Alcoverro-Bertran M, De Andres-Aguayo L, Klonizakis A, Julià-Vilella E, Lynch C, Serrano M, Hnisz D, Salvatella X, Graf T, Stik G. CEBPA phase separation links transcriptional activity and 3D chromatin hubs. Cell Rep 2023; 42:112897. [PMID: 37516962 DOI: 10.1016/j.celrep.2023.112897] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 06/02/2023] [Accepted: 07/14/2023] [Indexed: 08/01/2023] Open
Abstract
Cell identity is orchestrated through an interplay between transcription factor (TF) action and genome architecture. The mechanisms used by TFs to shape three-dimensional (3D) genome organization remain incompletely understood. Here we present evidence that the lineage-instructive TF CEBPA drives extensive chromatin compartment switching and promotes the formation of long-range chromatin hubs during induced B cell-to-macrophage transdifferentiation. Mechanistically, we find that the intrinsically disordered region (IDR) of CEBPA undergoes in vitro phase separation (PS) dependent on aromatic residues. Both overexpressing B cells and native CEBPA-expressing cell types such as primary granulocyte-macrophage progenitors, liver cells, and trophectoderm cells reveal nuclear CEBPA foci and long-range 3D chromatin hubs at CEBPA-bound regions. In short, we show that CEBPA can undergo PS through its IDR, which may underlie in vivo foci formation and suggest a potential role of PS in regulating CEBPA function.
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Affiliation(s)
- Marie Christou-Kent
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Sergi Cuartero
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, Spain; Germans Trias I Pujol Research Institute (IGTP), Badalona, Spain
| | - Carla Garcia-Cabau
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac 10, 08028 Barcelona, Spain
| | - Julia Ruehle
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Julian Naderi
- Department of Genome Regulation, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany
| | - Julia Erber
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Maria Victoria Neguembor
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Marcos Plana-Carmona
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain
| | | | - Luisa De Andres-Aguayo
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Antonios Klonizakis
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain
| | | | - Cian Lynch
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac 10, 08028 Barcelona, Spain; Altos Labs, Cambridge Institute of Science, Cambridge CB21 6GP, UK
| | - Manuel Serrano
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac 10, 08028 Barcelona, Spain; Altos Labs, Cambridge Institute of Science, Cambridge CB21 6GP, UK
| | - Denes Hnisz
- Department of Genome Regulation, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany
| | - Xavier Salvatella
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac 10, 08028 Barcelona, Spain; ICREA, Passeig Lluís Companys 23, 08010 Barcelona, Spain
| | - Thomas Graf
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain.
| | - Grégoire Stik
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, Spain.
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14
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Tomás-Daza L, Rovirosa L, López-Martí P, Nieto-Aliseda A, Serra F, Planas-Riverola A, Molina O, McDonald R, Ghevaert C, Cuatrecasas E, Costa D, Camós M, Bueno C, Menéndez P, Valencia A, Javierre BM. Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution. Nat Commun 2023; 14:268. [PMID: 36650138 PMCID: PMC9845235 DOI: 10.1038/s41467-023-35911-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 01/06/2023] [Indexed: 01/18/2023] Open
Abstract
Long-range interactions between regulatory elements and promoters are key in gene transcriptional control; however, their study requires large amounts of starting material, which is not compatible with clinical scenarios nor the study of rare cell populations. Here we introduce low input capture Hi-C (liCHi-C) as a cost-effective, flexible method to map and robustly compare promoter interactomes at high resolution. As proof of its broad applicability, we implement liCHi-C to study normal and malignant human hematopoietic hierarchy in clinical samples. We demonstrate that the dynamic promoter architecture identifies developmental trajectories and orchestrates transcriptional transitions during cell-state commitment. Moreover, liCHi-C enables the identification of disease-relevant cell types, genes and pathways potentially deregulated by non-coding alterations at distal regulatory elements. Finally, we show that liCHi-C can be harnessed to uncover genome-wide structural variants, resolve their breakpoints and infer their pathogenic effects. Collectively, our optimized liCHi-C method expands the study of 3D chromatin organization to unique, low-abundance cell populations, and offers an opportunity to uncover factors and regulatory networks involved in disease pathogenesis.
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Affiliation(s)
- Laureano Tomás-Daza
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain
- Barcelona Supercomputing Center, Barcelona, Barcelona, Spain
| | - Llorenç Rovirosa
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain
| | - Paula López-Martí
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain
- Barcelona Supercomputing Center, Barcelona, Barcelona, Spain
| | | | - François Serra
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain
| | | | - Oscar Molina
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain
| | | | - Cedric Ghevaert
- Wellcome-MRC Cambridge Stem Cell Institute, Cambridge, UK
- NHS Blood and Transplant, Cambridge, UK
| | - Esther Cuatrecasas
- Pediatric Institute of Rare Diseases, Sant Joan de Déu Hospital, Esplugues de Llobregat, Barcelona, Spain
| | - Dolors Costa
- Hospital Clinic, Barcelona, Spain
- Institute of Biomedical Research August Pi i Sunyer, Barcelona, Spain
- Cancer Network Biomedical Research Center, Barcelona, Spain
| | - Mireia Camós
- Sant Joan de Déu Research Institute, Esplugues de Llobregat, Barcelona, Spain
- Sant Joan de Déu Hospital, Esplugues de Llobregat, Barcelona, Spain
- Center for Biomedical Research in the Rare Diseases Network (CIBERER), Carlos III Health Institute, Madrid, Spain
| | - Clara Bueno
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain
| | - Pablo Menéndez
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Alfonso Valencia
- Barcelona Supercomputing Center, Barcelona, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Biola M Javierre
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain.
- Institute for Health Science Research Germans Trias i Pujol, Badalona, Barcelona, Spain.
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15
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Wang X, Liu S, Yu J. Multi-lineage Differentiation from Hematopoietic Stem Cells. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1442:159-175. [PMID: 38228964 DOI: 10.1007/978-981-99-7471-9_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
The hematopoietic stem cells (HSCs) have the ability to differentiate and give rise to all mature blood cells. Commitment to differentiation progressively limits the self-renewal potential of the original HSCs by regulating the level of lineage-specific gene expression. In this review, we will summarize the current understanding of the molecular mechanisms underlying HSC differentiation toward erythroid, myeloid, and lymphocyte lineages. Moreover, we will decipher how the single-cell technologies advance the lineage-biased HSC subpopulations and their differentiation potential.
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Affiliation(s)
- Xiaoshuang Wang
- The State Key Laboratory for Complex, Severe, and Rare Diseases, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences / Peking Union Medical College, Beijing, China.
- The Institute of Blood Transfusion, Chinese Academy of Medical Sciences / Peking Union Medical College, Chengdu, China.
| | - Siqi Liu
- State Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences / Peking Union Medical College, Beijing, China
| | - Jia Yu
- State Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences / Peking Union Medical College, Beijing, China.
- The Institute of Blood Transfusion, Chinese Academy of Medical Sciences / Peking Union Medical College, Chengdu, China.
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16
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Ling X, Liu X, Jiang S, Fan L, Ding J. The dynamics of three-dimensional chromatin organization and phase separation in cell fate transitions and diseases. CELL REGENERATION (LONDON, ENGLAND) 2022; 11:42. [PMID: 36539553 PMCID: PMC9768101 DOI: 10.1186/s13619-022-00145-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2022] [Accepted: 10/18/2022] [Indexed: 12/24/2022]
Abstract
Cell fate transition is a fascinating process involving complex dynamics of three-dimensional (3D) chromatin organization and phase separation, which play an essential role in cell fate decision by regulating gene expression. Phase separation is increasingly being considered a driving force of chromatin folding. In this review, we have summarized the dynamic features of 3D chromatin and phase separation during physiological and pathological cell fate transitions and systematically analyzed recent evidence of phase separation facilitating the chromatin structure. In addition, we discuss current advances in understanding how phase separation contributes to physical and functional enhancer-promoter contacts. We highlight the functional roles of 3D chromatin organization and phase separation in cell fate transitions, and more explorations are required to study the regulatory relationship between 3D chromatin organization and phase separation. 3D chromatin organization (shown by Hi-C contact map) and phase separation are highly dynamic and play functional roles during early embryonic development, cell differentiation, somatic reprogramming, cell transdifferentiation and pathogenetic process. Phase separation can regulate 3D chromatin organization directly, but whether 3D chromatin organization regulates phase separation remains unclear.
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Affiliation(s)
- Xiaoru Ling
- grid.12981.330000 0001 2360 039XAdvanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong China ,grid.12981.330000 0001 2360 039XRNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong China ,grid.12981.330000 0001 2360 039XCenter for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong China
| | - Xinyi Liu
- grid.12981.330000 0001 2360 039XAdvanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong China ,grid.12981.330000 0001 2360 039XRNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong China ,grid.12981.330000 0001 2360 039XCenter for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong China
| | - Shaoshuai Jiang
- grid.12981.330000 0001 2360 039XAdvanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong China ,grid.12981.330000 0001 2360 039XRNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong China ,grid.12981.330000 0001 2360 039XCenter for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong China
| | - Lili Fan
- grid.258164.c0000 0004 1790 3548Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, Guangdong China
| | - Junjun Ding
- grid.12981.330000 0001 2360 039XAdvanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong China ,grid.12981.330000 0001 2360 039XRNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong China ,grid.12981.330000 0001 2360 039XCenter for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong China ,grid.410737.60000 0000 8653 1072Department of Histology and Embryology, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, 511436 China ,grid.13291.380000 0001 0807 1581West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610041 China
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17
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Liang W, Wang S, Wang H, Li X, Meng Q, Zhao Y, Zheng C. When 3D genome technology meets viral infection, including SARS-CoV-2. J Med Virol 2022; 94:5627-5639. [PMID: 35916043 PMCID: PMC9538846 DOI: 10.1002/jmv.28040] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 07/09/2022] [Accepted: 07/30/2022] [Indexed: 01/06/2023]
Abstract
Mammalian chromosomes undergo varying degrees of compression to form three-dimensional genome structures. These three-dimensional structures undergo dynamic and precise chromatin interactions to achieve precise spatial and temporal regulation of gene expression. Most eukaryotic DNA viruses can invade their genomes into the nucleus. However, it is still poorly understood how the viral genome is precisely positioned after entering the host cell nucleus to find the most suitable location and whether it can specifically interact with the host genome to hijack the host transcriptional factories or even integrate into the host genome to complete its transcription and replication rapidly. Chromosome conformation capture technology can reveal long-range chromatin interactions between different chromosomal sites in the nucleus, potentially providing a reference for viral DNA-host chromatin interactions. This review summarized the research progress on the three-dimensional interaction between virus and host genome and the impact of virus integration into the host genome on gene transcription regulation, aiming to provide new insights into chromatin interaction and viral gene transcription regulation, laying the foundation for the treatment of infectious diseases.
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Affiliation(s)
- Weizheng Liang
- Central LaboratoryThe First Affiliated Hospital of Hebei North UniversityZhangjiakouChina
- Department of Immunology, School of Basic Medical SciencesFujian Medical UniversityFuzhouChina
| | - Shuangqing Wang
- Department of NeurologyShenzhen University General Hospital, Shenzhen UniversityShenzhen, Guangdong ProvinceChina
| | - Hao Wang
- Department of Obstetrics and GynecologyShenzhen University General HospitalShenzhen, GuangdongChina
| | - Xiushen Li
- Department of Obstetrics and GynecologyShenzhen University General HospitalShenzhen, GuangdongChina
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical EngineeringShenzhen University Health Science CenterShenzhen, GuangdongChina
- Shenzhen Key LaboratoryShenzhen University General HospitalShenzhen, GuangdongChina
| | - Qingxue Meng
- Central LaboratoryThe First Affiliated Hospital of Hebei North UniversityZhangjiakouChina
| | - Yan Zhao
- Department of Mathematics and Computer ScienceFree University BerlinBerlinGermany
| | - Chunfu Zheng
- Department of Immunology, School of Basic Medical SciencesFujian Medical UniversityFuzhouChina
- Department of Microbiology, Immunology and Infectious DiseasesUniversity of CalgaryCalgaryAlbertaCanada
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life SciencesInner Mongolia UniversityHohhotChina
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18
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Chakraborty A, Wang JG, Ay F. dcHiC detects differential compartments across multiple Hi-C datasets. Nat Commun 2022; 13:6827. [PMID: 36369226 PMCID: PMC9652325 DOI: 10.1038/s41467-022-34626-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 11/01/2022] [Indexed: 11/13/2022] Open
Abstract
The compartmental organization of mammalian genomes and its changes play important roles in distinct biological processes. Here, we introduce dcHiC, which utilizes a multivariate distance measure to identify significant changes in compartmentalization among multiple contact maps. Evaluating dcHiC on four collections of bulk and single-cell contact maps from in vitro mouse neural differentiation (n = 3), mouse hematopoiesis (n = 10), human LCLs (n = 20) and post-natal mouse brain development (n = 3 stages), we show its effectiveness and sensitivity in detecting biologically relevant changes, including those orthogonally validated. dcHiC reported regions with dynamically regulated genes associated with cell identity, along with correlated changes in chromatin states, subcompartments, replication timing and lamin association. With its efficient implementation, dcHiC enables high-resolution compartment analysis as well as standalone browser visualization, differential interaction identification and time-series clustering. dcHiC is an essential addition to the Hi-C analysis toolbox for the ever-growing number of bulk and single-cell contact maps. Available at: https://github.com/ay-lab/dcHiC .
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Affiliation(s)
- Abhijit Chakraborty
- Centers for Autoimmunity, Inflammation and Cancer Immunotherapy, La Jolla Institute for Immunology, La Jolla, CA, 92037, USA.
| | - Jeffrey G Wang
- Centers for Autoimmunity, Inflammation and Cancer Immunotherapy, La Jolla Institute for Immunology, La Jolla, CA, 92037, USA
- The Bishop's School, La Jolla, CA, 92037, USA
- Harvard College, Cambridge, MA, 02138, USA
| | - Ferhat Ay
- Centers for Autoimmunity, Inflammation and Cancer Immunotherapy, La Jolla Institute for Immunology, La Jolla, CA, 92037, USA.
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, 92093, USA.
- Department of Pediatrics, University of California San Diego, La Jolla, CA, 92093, USA.
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19
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Zheng Y, Shen S, Keleş S. Normalization and de-noising of single-cell Hi-C data with BandNorm and scVI-3D. Genome Biol 2022; 23:222. [PMID: 36253828 PMCID: PMC9575231 DOI: 10.1186/s13059-022-02774-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 09/19/2022] [Indexed: 11/10/2022] Open
Abstract
Single-cell high-throughput chromatin conformation capture methodologies (scHi-C) enable profiling of long-range genomic interactions. However, data from these technologies are prone to technical noise and biases that hinder downstream analysis. We develop a normalization approach, BandNorm, and a deep generative modeling framework, scVI-3D, to account for scHi-C specific biases. In benchmarking experiments, BandNorm yields leading performances in a time and memory efficient manner for cell-type separation, identification of interacting loci, and recovery of cell-type relationships, while scVI-3D exhibits advantages for rare cell types and under high sparsity scenarios. Application of BandNorm coupled with gene-associating domain analysis reveals scRNA-seq validated sub-cell type identification.
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Affiliation(s)
- Ye Zheng
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, USA
| | - Siqi Shen
- Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison, Madison, USA
| | - Sündüz Keleş
- Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison, Madison, USA
- Department of Statistics, University of Wisconsin - Madison, Madison, USA
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20
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Cuartero S, Stik G, Stadhouders R. Three-dimensional genome organization in immune cell fate and function. Nat Rev Immunol 2022; 23:206-221. [PMID: 36127477 DOI: 10.1038/s41577-022-00774-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/04/2022] [Indexed: 11/09/2022]
Abstract
Immune cell development and activation demand the precise and coordinated control of transcriptional programmes. Three-dimensional (3D) organization of the genome has emerged as an important regulator of chromatin state, transcriptional activity and cell identity by facilitating or impeding long-range genomic interactions among regulatory elements and genes. Chromatin folding thus enables cell type-specific and stimulus-specific transcriptional responses to extracellular signals, which are essential for the control of immune cell fate, for inflammatory responses and for generating a diverse repertoire of antigen receptor specificities. Here, we review recent findings connecting 3D genome organization to the control of immune cell differentiation and function, and discuss how alterations in genome folding may lead to immune dysfunction and malignancy.
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Affiliation(s)
- Sergi Cuartero
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, Spain. .,Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain.
| | - Grégoire Stik
- Centre for Genomic Regulation (CRG), Institute of Science and Technology (BIST), Barcelona, Spain. .,Universitat Pompeu Fabra (UPF), Barcelona, Spain.
| | - Ralph Stadhouders
- Department of Pulmonary Medicine, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. .,Department of Cell Biology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
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21
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Shen S, Zheng Y, Keleş S. scGAD: single-cell gene associating domain scores for exploratory analysis of scHi-C data. Bioinformatics 2022; 38:3642-3644. [PMID: 35652733 PMCID: PMC9272792 DOI: 10.1093/bioinformatics/btac372] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 03/30/2022] [Accepted: 05/26/2022] [Indexed: 11/12/2022] Open
Abstract
SUMMARY Quantitative tools are needed to leverage the unprecedented resolution of single-cell high-throughput chromatin conformation (scHi-C) data and integrate it with other single-cell data modalities. We present single-cell gene associating domain (scGAD) scores as a dimension reduction and exploratory analysis tool for scHi-C data. scGAD enables summarization at the gene unit while accounting for inherent gene-level genomic biases. Low-dimensional projections with scGAD capture clustering of cells based on their 3D structures. Significant chromatin interactions within and between cell types can be identified with scGAD. We further show that scGAD facilitates the integration of scHi-C data with other single-cell data modalities by enabling its projection onto reference low-dimensional embeddings. This multi-modal data integration provides an automated and refined cell-type annotation for scHi-C data. AVAILABILITY AND IMPLEMENTATION scGAD is part of the BandNorm R package at https://sshen82.github.io/BandNorm/articles/scGAD-tutorial.html. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Siqi Shen
- Department of Biostatistics and Medical Informatics, University of Wisconsin—Madison, Madison, WI 53706, USA
| | - Ye Zheng
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Sündüz Keleş
- Department of Biostatistics and Medical Informatics, University of Wisconsin—Madison, Madison, WI 53706, USA
- Department of Statistics, University of Wisconsin—Madison, Madison, WI 53706, USA
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22
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Kong S, Lu Y, Tan S, Li R, Gao Y, Li K, Zhang Y. Nucleosome-Omics: A Perspective on the Epigenetic Code and 3D Genome Landscape. Genes (Basel) 2022; 13:1114. [PMID: 35885897 PMCID: PMC9323251 DOI: 10.3390/genes13071114] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 06/14/2022] [Accepted: 06/17/2022] [Indexed: 12/04/2022] Open
Abstract
Genetic information is loaded on chromatin, which involves DNA sequence arrangement and the epigenetic landscape. The epigenetic information including DNA methylation, nucleosome positioning, histone modification, 3D chromatin conformation, and so on, has a crucial impact on gene transcriptional regulation. Out of them, nucleosomes, as basal chromatin structural units, play an important central role in epigenetic code. With the discovery of nucleosomes, various nucleosome-level technologies have been developed and applied, pushing epigenetics to a new climax. As the underlying methodology, next-generation sequencing technology has emerged and allowed scientists to understand the epigenetic landscape at a genome-wide level. Combining with NGS, nucleosome-omics (or nucleosomics) provides a fresh perspective on the epigenetic code and 3D genome landscape. Here, we summarized and discussed research progress in technology development and application of nucleosome-omics. We foresee the future directions of epigenetic development at the nucleosome level.
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Affiliation(s)
| | | | | | | | | | | | - Yubo Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Animal Functional Genomics Group, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; (S.K.); (Y.L.); (S.T.); (R.L.); (Y.G.); (K.L.)
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23
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Chen L, Li J, Yuan R, Wang Y, Zhang J, Lin Y, Wang L, Zhu X, Zhu W, Bai J, Kong F, Zeng B, Lu L, Ma J, Long K, Jin L, Huang Z, Huo J, Gu Y, Wang D, Mo D, Li D, Tang Q, Li X, Wu J, Chen Y, Li M. Dynamic 3D genome reorganization during development and metabolic stress of the porcine liver. Cell Discov 2022; 8:56. [PMID: 35701393 PMCID: PMC9197842 DOI: 10.1038/s41421-022-00416-z] [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: 12/07/2021] [Accepted: 04/28/2022] [Indexed: 11/28/2022] Open
Abstract
Liver development is a complex process that is regulated by a series of signaling pathways. Three-dimensional (3D) chromatin architecture plays an important role in transcriptional regulation; nonetheless, its dynamics and role in the rapid transition of core liver functions during development and obesity-induced metabolic stress remain largely unexplored. To investigate the dynamic chromatin architecture during liver development and under metabolic stress, we generated high-resolution maps of chromatin architecture for porcine livers across six major developmental stages (from embryonic day 38 to the adult stage) and under a high-fat diet-induced obesity. The characteristically loose chromatin architecture supports a highly plastic genome organization during early liver development, which fundamentally contributes to the rapid functional transitions in the liver after birth. We reveal the multi-scale reorganization of chromatin architecture and its influence on transcriptional regulation of critical signaling processes during liver development, and show its close association with transition in hepatic functions (i.e., from hematopoiesis in the fetus to metabolism and immunity after birth). The limited changes in chromatin structure help explain the observed metabolic adaptation to excessive energy intake in pigs. These results provide a global overview of chromatin architecture dynamics associated with the transition of physiological liver functions between prenatal development and postnatal maturation, and a foundational resource that allows for future in-depth functional characterization.
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Affiliation(s)
- Luxi Chen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Jing Li
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Renqiang Yuan
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yujie Wang
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Jiaman Zhang
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Yu Lin
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Lina Wang
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China.,Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Xingxing Zhu
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Wei Zhu
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Jingyi Bai
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Fanli Kong
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Bo Zeng
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Lu Lu
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Jideng Ma
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Keren Long
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Long Jin
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Zhiqing Huang
- Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Jinlong Huo
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Yiren Gu
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu, Sichuan, China
| | - Danyang Wang
- Beijing Institute of Genomics, Chinese Academy of Sciences, and China National Center for Bioinformation, Beijing, China
| | - Delin Mo
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Diyan Li
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Qianzi Tang
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Xuewei Li
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Jiangwei Wu
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China.
| | - Yaosheng Chen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China.
| | - Mingzhou Li
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China.
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24
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Exogenous artificial DNA forms chromatin structure with active transcription in yeast. SCIENCE CHINA. LIFE SCIENCES 2022; 65:851-860. [PMID: 34970711 DOI: 10.1007/s11427-021-2044-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Accepted: 12/10/2021] [Indexed: 12/25/2022]
Abstract
Yeast artificial chromosomes (YACs) are important tools for sequencing, gene cloning, and transferring large quantities of genetic information. However, the structure and activity of YAC chromatin, as well as the unintended impacts of introducing foreign DNA sequences on DNA-associated biochemical events, have not been widely explored. Here, we showed that abundant genetic elements like TATA box and transcription factor-binding motifs occurred unintentionally in a previously reported data-carrying chromosome (dChr). In addition, we used state-of-the-art sequencing technologies to comprehensively profile the genetic, epigenetic, transcriptional, and proteomic characteristics of the exogenous dChr. We found that the data-carrying DNA formed active chromatin with high chromatin accessibility and H3K4 tri-methylation levels. The dChr also displayed highly pervasive transcriptional ability and transcribed hundreds of noncoding RNAs. The results demonstrated that exogenous artificial chromosomes formed chromatin structures and did not remain as naked or loose plasmids. A better understanding of the YAC chromatin nature will improve our ability to design better data-storage chromosomes.
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25
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Sati S, Jones P, Kim HS, Zhou LA, Rapp-Reyes E, Leung TH. HiCuT: An efficient and low input method to identify protein-directed chromatin interactions. PLoS Genet 2022; 18:e1010121. [PMID: 35320278 PMCID: PMC8979432 DOI: 10.1371/journal.pgen.1010121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 04/04/2022] [Accepted: 02/25/2022] [Indexed: 12/21/2022] Open
Abstract
3D genome organization regulates gene expression, and disruption of these long-range (>20kB) DNA-protein interactions results in pathogenic phenotypes. Chromosome conformation methods in conjunction with chromatin immunoprecipitation were used to decipher protein-directed chromatin interactions. However, these methods required abundant starting material (>500,000 cells), sizable number of sequencing reads (>100 million reads), and elaborate data processing methods to reduce background noise, which limited their use in primary cells. Hi-C Coupled chromatin cleavage and Tagmentation (HiCuT) is a new transposase-assisted tagmentation method that generates high-resolution protein directed long-range chromatin interactions as efficiently as existing methods, HiChIP and ChIA-PET, despite using 100,000 cells (5-fold less) and 12 million sequencing reads (8-fold fewer). Moreover, HiCuT generates high resolution fragment libraries with low background signal that are easily interpreted with minimal computational processing. We used HiCuT in human primary skin cells to link previously identified single nucleotide polymorphisms (SNPs) in skin disease to candidate genes and to identify functionally relevant transcription factors in an unbiased manner. HiCuT broadens the capacity for genomic profiling in systems previously unmeasurable, including primary cells, human tissue samples, and rare cell populations, and may be a useful tool for all investigators studying human genetics and personalized epigenomics. DNA is precisely packaged and organized within a nucleus to regulate gene expression. Altering this structure results in disease and developmental abnormalities. Current methods to probe 3D genome organization require a minimum of 500,000 cells, 100 million sequencing reads, and elaborate computational genomics skills. This limits general adoption and prevents use in small populations of cells, including primary tissues. We report a new method called Hi-C Coupled chromatin cleavage and Tagmentation (HiCuT). This method couples current 3D genome methods in conjunction with target specific tagmentation, an enzyme-assisted approach to cut and tag DNA. We benchmarked HiCuT against existing methods and found similar efficiency and specificity in assessing target specific 3D genome organization despite reducing assay requirements to 100,000 cells (5-fold less) and 12 million sequencing reads (8-fold fewer). Strikingly, HiCuT data exhibited reduced background noise and required minimal computational processing. Taken together, HiCuT broadens the capacity for 3D genome profiling in cell populations previously unmeasurable, including primary cells and human tissues, reduces sequencing costs, and lowers the need for computational expertise. HiCuT will benefit all investigators studying gene regulation and disease pathophysiology.
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Affiliation(s)
- Satish Sati
- Department of Dermatology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Parker Jones
- Department of Dermatology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Hali S. Kim
- Department of Dermatology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Linda A. Zhou
- Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Emmanuel Rapp-Reyes
- Department of Dermatology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Thomas H. Leung
- Department of Dermatology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Corporal Michael J. Crescenz Department of Veterans Affairs Medical Center, Philadelphia, Pennsylvania, United States of America
- * E-mail:
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26
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Owens DDG, Anselmi G, Oudelaar AM, Downes DJ, Cavallo A, Harman JR, Schwessinger R, Bucakci A, Greder L, de Ornellas S, Jeziorska D, Telenius J, Hughes JR, de Bruijn MFTR. Dynamic Runx1 chromatin boundaries affect gene expression in hematopoietic development. Nat Commun 2022; 13:773. [PMID: 35140205 PMCID: PMC8828719 DOI: 10.1038/s41467-022-28376-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 01/12/2022] [Indexed: 01/22/2023] Open
Abstract
The transcription factor RUNX1 is a critical regulator of developmental hematopoiesis and is frequently disrupted in leukemia. Runx1 is a large, complex gene that is expressed from two alternative promoters under the spatiotemporal control of multiple hematopoietic enhancers. To dissect the dynamic regulation of Runx1 in hematopoietic development, we analyzed its three-dimensional chromatin conformation in mouse embryonic stem cell (ESC) differentiation cultures. Runx1 resides in a 1.1 Mb topologically associating domain (TAD) demarcated by convergent CTCF motifs. As ESCs differentiate to mesoderm, chromatin accessibility, Runx1 enhancer-promoter (E-P) interactions, and CTCF-CTCF interactions increase in the TAD, along with initiation of Runx1 expression from the P2 promoter. Differentiation to hematopoietic progenitor cells is associated with the formation of tissue-specific sub-TADs over Runx1, a shift in E-P interactions, P1 promoter demethylation, and robust expression from both Runx1 promoters. Deletion of promoter-proximal CTCF sites at the sub-TAD boundaries has no obvious effects on E-P interactions but leads to partial loss of domain structure, mildly affects gene expression, and delays hematopoietic development. Together, our analysis of gene regulation at a large multi-promoter developmental gene reveals that dynamic sub-TAD chromatin boundaries play a role in establishing TAD structure and coordinated gene expression.
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Affiliation(s)
- Dominic D G Owens
- MRC Molecular Hematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Structural Genomics Consortium, University of Toronto, Toronto, Ontario, Canada
| | - Giorgio Anselmi
- MRC Molecular Hematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - A Marieke Oudelaar
- MRC Molecular Hematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
| | - Damien J Downes
- MRC Molecular Hematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Alessandro Cavallo
- MRC Molecular Hematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Joe R Harman
- MRC Molecular Hematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Ron Schwessinger
- MRC Molecular Hematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Akin Bucakci
- MRC Molecular Hematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Lucas Greder
- MRC Molecular Hematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Sara de Ornellas
- MRC Molecular Hematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Physical and Theoretical Chemistry Building, Department of Chemistry, University of Oxford, Oxford, UK
| | - Danuta Jeziorska
- MRC Molecular Hematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Jelena Telenius
- MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Jim R Hughes
- MRC Molecular Hematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
- MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
| | - Marella F T R de Bruijn
- MRC Molecular Hematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
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27
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Chen Z, Mo B, Lei A, Wang J. Microbial Single-Cell Analysis: What Can We Learn From Mammalian? Front Cell Dev Biol 2022; 9:829990. [PMID: 35111764 PMCID: PMC8801874 DOI: 10.3389/fcell.2021.829990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 12/31/2021] [Indexed: 11/23/2022] Open
Affiliation(s)
- Zixi Chen
- Shenzhen Key Laboratory of Marine Bioresource and Eco-Environmental Science, Shenzhen Engineering Laboratory for Marine Algal Biotechnology, Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China
- Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, China
| | - Beixin Mo
- Shenzhen Key Laboratory of Marine Bioresource and Eco-Environmental Science, Shenzhen Engineering Laboratory for Marine Algal Biotechnology, Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China
| | - Anping Lei
- Shenzhen Key Laboratory of Marine Bioresource and Eco-Environmental Science, Shenzhen Engineering Laboratory for Marine Algal Biotechnology, Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China
| | - Jiangxin Wang
- Shenzhen Key Laboratory of Marine Bioresource and Eco-Environmental Science, Shenzhen Engineering Laboratory for Marine Algal Biotechnology, Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China
- *Correspondence: Jiangxin Wang,
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28
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Yi X, Zheng Z, Xu H, Zhou Y, Huang D, Wang J, Feng X, Zhao K, Fan X, Zhang S, Dong X, Wang Z, Shen Y, Cheng H, Shi L, Li MJ. Interrogating cell type-specific cooperation of transcriptional regulators in 3D chromatin. iScience 2021; 24:103468. [PMID: 34888502 PMCID: PMC8634045 DOI: 10.1016/j.isci.2021.103468] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 09/23/2021] [Accepted: 11/12/2021] [Indexed: 12/14/2022] Open
Abstract
Context-specific activities of transcription regulators (TRs) in the nucleus modulate spatiotemporal gene expression precisely. Using the largest ChIP-seq data and chromatin loops in the human K562 cell line, we initially interrogated TR cooperation in 3D chromatin via a graphical model and revealed many known and novel TRs manipulating context-specific pathways. To explore TR cooperation across broad tissue/cell types, we systematically leveraged large-scale open chromatin profiles, computational footprinting, and high-resolution chromatin interactions to investigate tissue/cell type-specific TR cooperation. We first delineated a landscape of TR cooperation across 40 human tissue/cell types. Network modularity analyses uncovered the commonality and specificity of TR cooperation in different conditions. We also demonstrated that TR cooperation information can better interpret the disease-causal variants identified by genome-wide association studies and recapitulate cell states during neural development. Our study characterizes shared and unique patterns of TR cooperation associated with the cell type specificity of gene regulation in 3D chromatin. Computational inference of transcriptional regulator (TR) cooperation in 3D chromatin A landscape of 3D TR cooperation across 40 human tissue/cell types TR cooperation can better interpret the disease-causal variants identified by GWAS Cooperation of certain TRs shapes context-specific gene regulation in cell development
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Affiliation(s)
- Xianfu Yi
- School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, China.,Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China
| | - Zhanye Zheng
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Hang Xu
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China
| | - Yao Zhou
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Dandan Huang
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Jianhua Wang
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xiangling Feng
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Ke Zhao
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xutong Fan
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Shijie Zhang
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xiaobao Dong
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Genetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Zhao Wang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Yujun Shen
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Hui Cheng
- State Key Laboratory of Experimental Hematology, Chinese Academy of Medical Sciences, Tianjin 300070, China
| | - Lei Shi
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Mulin Jun Li
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.,Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
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29
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CoolBox: a flexible toolkit for visual analysis of genomics data. BMC Bioinformatics 2021; 22:489. [PMID: 34629071 PMCID: PMC8504052 DOI: 10.1186/s12859-021-04408-w] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 09/27/2021] [Indexed: 01/20/2023] Open
Abstract
Background Data visualization, especially the genome track plots, is crucial for genomics researchers to discover patterns in large-scale sequencing dataset. Although existing tools works well for producing a normal view of the input data, they are not convenient when users want to create customized data representations. Such gap between the visualization and data processing, prevents the users to uncover more hidden structure of the dataset. Results We developed CoolBox—an open-source toolkit for visual analysis of genomics data. This user-friendly toolkit is highly compatible with the Python ecosystem and customizable with a well-designed user interface. It can be used in various visualization situations like a Swiss army knife. For example, to produce high-quality genome track plots or fetch commonly used genomic data files with a Python script or command line, to explore genomic data interactively within Jupyter environment or web browser. Moreover, owing to the highly extensible Application Programming Interface design, users can customize their own tracks without difficulty, which greatly facilitate analytical, comparative genomic data visualization tasks. Conclusions CoolBox allows users to produce high-quality visualization plots and explore their data in a flexible, programmable and user-friendly way.
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30
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MacPhillamy C, Pitchford WS, Alinejad-Rokny H, Low WY. Opportunity to improve livestock traits using 3D genomics. Anim Genet 2021; 52:785-798. [PMID: 34494283 DOI: 10.1111/age.13135] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/24/2021] [Indexed: 11/30/2022]
Abstract
The advent of high-throughput chromosome conformation capture and sequencing (Hi-C) has enabled researchers to probe the 3D architecture of the mammalian genome in a genome-wide manner. Simultaneously, advances in epigenomic assays, such as chromatin immunoprecipitation and sequencing (ChIP-seq) and DNase-seq, have enabled researchers to study cis-regulatory interactions and chromatin accessibility across the same genome-wide scale. The use of these data has revealed many unique insights into gene regulation and disease pathomechanisms in several model organisms. With the advent of these high-throughput sequencing technologies, there has been an ever-increasing number of datasets available for study; however, this is often limited to model organisms. Livestock species play critical roles in the economies of developing and developed nations alike. Despite this, they are greatly underrepresented in the 3D genomics space; Hi-C and related technologies have the potential to revolutionise livestock breeding by enabling a more comprehensive understanding of how production traits are controlled. The growth in human and model organism Hi-C data has seen a surge in the availability of computational tools for use in 3D genomics, with some tools using machine learning techniques to predict features and improve dataset quality. In this review, we provide an overview of the 3D genome and discuss the status of 3D genomics in livestock before delving into advancing the field by drawing inspiration from research in human and mouse. We end by offering future directions for livestock research in the field of 3D genomics.
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Affiliation(s)
- C MacPhillamy
- Davies Livestock Research Centre, The University of Adelaide, Roseworthy Campus, Mudla Wirra Rd, Roseworthy, SA, 5371, Australia
| | - W S Pitchford
- Davies Livestock Research Centre, The University of Adelaide, Roseworthy Campus, Mudla Wirra Rd, Roseworthy, SA, 5371, Australia
| | - H Alinejad-Rokny
- Biological & Medical Machine Learning Lab, The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW, 2052, Australia.,School of Computer Science and Engineering, The University of New South Wales (UNSW Sydney), Sydney, NSW, 2052, Australia
| | - W Y Low
- Davies Livestock Research Centre, The University of Adelaide, Roseworthy Campus, Mudla Wirra Rd, Roseworthy, SA, 5371, Australia
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31
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Liu N, Low WY, Alinejad-Rokny H, Pederson S, Sadlon T, Barry S, Breen J. Seeing the forest through the trees: prioritising potentially functional interactions from Hi-C. Epigenetics Chromatin 2021; 14:41. [PMID: 34454581 PMCID: PMC8399707 DOI: 10.1186/s13072-021-00417-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 08/19/2021] [Indexed: 11/30/2022] Open
Abstract
Eukaryotic genomes are highly organised within the nucleus of a cell, allowing widely dispersed regulatory elements such as enhancers to interact with gene promoters through physical contacts in three-dimensional space. Recent chromosome conformation capture methodologies such as Hi-C have enabled the analysis of interacting regions of the genome providing a valuable insight into the three-dimensional organisation of the chromatin in the nucleus, including chromosome compartmentalisation and gene expression. Complicating the analysis of Hi-C data, however, is the massive amount of identified interactions, many of which do not directly drive gene function, thus hindering the identification of potentially biologically functional 3D interactions. In this review, we collate and examine the downstream analysis of Hi-C data with particular focus on methods that prioritise potentially functional interactions. We classify three groups of approaches: structural-based discovery methods, e.g. A/B compartments and topologically associated domains, detection of statistically significant chromatin interactions, and the use of epigenomic data integration to narrow down useful interaction information. Careful use of these three approaches is crucial to successfully identifying potentially functional interactions within the genome.
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Affiliation(s)
- Ning Liu
- Computational & Systems Biology, Precision Medicine Theme, South Australian Health & Medical Research Institute, SA, 5000, Adelaide, Australia
- Robinson Research Institute, University of Adelaide, SA, 5005, Adelaide, Australia
- Adelaide Medical School, University of Adelaide, SA, 5005, Adelaide, Australia
| | - Wai Yee Low
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, 5371, Australia
| | - Hamid Alinejad-Rokny
- BioMedical Machine Learning Lab, The Graduate School of Biomedical Engineering, The University of New South Wales, NSW, 2052, Sydney, Australia
- Core Member of UNSW Data Science Hub, The University of New South Wales, 2052, Sydney, Australia
| | - Stephen Pederson
- Adelaide Medical School, University of Adelaide, SA, 5005, Adelaide, Australia
- Dame Roma Mitchell Cancer Research Laboratories (DRMCRL), Adelaide Medical School, University of Adelaide, SA, 5005, Adelaide, Australia
| | - Timothy Sadlon
- Robinson Research Institute, University of Adelaide, SA, 5005, Adelaide, Australia
- Women's & Children's Health Network, SA, 5006, North Adelaide, Australia
| | - Simon Barry
- Robinson Research Institute, University of Adelaide, SA, 5005, Adelaide, Australia
- Core Member of UNSW Data Science Hub, The University of New South Wales, 2052, Sydney, Australia
- Women's & Children's Health Network, SA, 5006, North Adelaide, Australia
| | - James Breen
- Computational & Systems Biology, Precision Medicine Theme, South Australian Health & Medical Research Institute, SA, 5000, Adelaide, Australia.
- Robinson Research Institute, University of Adelaide, SA, 5005, Adelaide, Australia.
- Adelaide Medical School, University of Adelaide, SA, 5005, Adelaide, Australia.
- South Australian Genomics Centre (SAGC), South Australian Health & Medical Research Institute (SAHMRI), SA, 5000, Adelaide, Australia.
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32
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Ryzhkova A, Battulin N. Genome Reorganization during Erythroid Differentiation. Genes (Basel) 2021; 12:genes12071012. [PMID: 34208866 PMCID: PMC8306769 DOI: 10.3390/genes12071012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 06/28/2021] [Accepted: 06/29/2021] [Indexed: 01/02/2023] Open
Abstract
Hematopoiesis is a convenient model to study how chromatin dynamics plays a decisive role in regulation of cell fate. During erythropoiesis a population of stem and progenitor cells becomes increasingly lineage restricted, giving rise to terminally differentiated progeny. The concerted action of transcription factors and epigenetic modifiers leads to a silencing of the multipotent transcriptome and activation of the transcriptional program that controls terminal differentiation. This article reviews some aspects of the biology of red blood cells production with the focus on the extensive chromatin reorganization during differentiation.
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Affiliation(s)
- Anastasia Ryzhkova
- Institute of Cytology and Genetics SB RAS, Laboratory of Developmental Genetics, 630090 Novosibirsk, Russia;
| | - Nariman Battulin
- Institute of Cytology and Genetics SB RAS, Laboratory of Developmental Genetics, 630090 Novosibirsk, Russia;
- Department of Natural Sciences, Novosibirsk State University, 630090 Novosibirsk, Russia
- Correspondence:
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33
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Scourzic L, Salataj E, Apostolou E. Deciphering the Complexity of 3D Chromatin Organization Driving Lymphopoiesis and Lymphoid Malignancies. Front Immunol 2021; 12:669881. [PMID: 34054841 PMCID: PMC8160312 DOI: 10.3389/fimmu.2021.669881] [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: 02/19/2021] [Accepted: 04/26/2021] [Indexed: 12/18/2022] Open
Abstract
Proper lymphopoiesis and immune responses depend on the spatiotemporal control of multiple processes, including gene expression, DNA recombination and cell fate decisions. High-order 3D chromatin organization is increasingly appreciated as an important regulator of these processes and dysregulation of genomic architecture has been linked to various immune disorders, including lymphoid malignancies. In this review, we present the general principles of the 3D chromatin topology and its dynamic reorganization during various steps of B and T lymphocyte development and activation. We also discuss functional interconnections between architectural, epigenetic and transcriptional changes and introduce major key players of genomic organization in B/T lymphocytes. Finally, we present how alterations in architectural factors and/or 3D genome organization are linked to dysregulation of the lymphopoietic transcriptional program and ultimately to hematological malignancies.
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Affiliation(s)
| | | | - Effie Apostolou
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
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34
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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: 9] [Impact Index Per Article: 3.0] [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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35
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Tottone L, Lancho O, Loh JW, Singh A, Kimura S, Roels J, Kuchmiy A, Strubbe S, Lawlor MA, da Silva-Diz V, Luo S, Gachet S, García-Prieto CA, Hagelaar R, Esteller M, Meijerink JPP, Soulier J, Taghon T, Van Vlierberghe P, Mullighan CG, Khiabanian H, Rocha PP, Herranz D. A Tumor Suppressor Enhancer of PTEN in T-cell development and leukemia. Blood Cancer Discov 2020; 2:92-109. [PMID: 33458694 DOI: 10.1158/2643-3230.bcd-20-0201] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Long-range oncogenic enhancers play an important role in cancer. Yet, whether similar regulation of tumor suppressor genes is relevant remains unclear. Loss of expression of PTEN is associated with the pathogenesis of various cancers, including T-cell leukemia (T-ALL). Here, we identify a highly conserved distal enhancer (PE) that interacts with the PTEN promoter in multiple hematopoietic populations, including T-cells, and acts as a hub of relevant transcription factors in T-ALL. Consistently, loss of PE leads to reduced PTEN levels in T-ALL cells. Moreover, PE-null mice show reduced Pten levels in thymocytes and accelerated development of NOTCH1-induced T-ALL. Furthermore, secondary loss of PE in established leukemias leads to accelerated progression and a gene expression signature driven by Pten loss. Finally, we uncovered recurrent deletions encompassing PE in T-ALL, which are associated with decreased PTEN levels. Altogether, our results identify PE as the first long-range tumor suppressor enhancer directly implicated in cancer.
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Affiliation(s)
- Luca Tottone
- Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, New Jersey
| | - Olga Lancho
- Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, New Jersey
| | - Jui-Wan Loh
- Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, New Jersey
- Center for Systems and Computational Biology, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, New Jersey
| | - Amartya Singh
- Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, New Jersey
- Center for Systems and Computational Biology, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, New Jersey
| | - Shunsuke Kimura
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Juliette Roels
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Anna Kuchmiy
- Cancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Steven Strubbe
- Cancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Matthew A Lawlor
- Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, New Jersey
| | - Victoria da Silva-Diz
- Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, New Jersey
| | - Shirley Luo
- Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, New Jersey
| | - Stéphanie Gachet
- INSERM U944 and University de Paris, Hopital Saint-Louis, Paris, France
| | - Carlos A García-Prieto
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, Barcelona, Catalonia, Spain
- Barcelona Supercomputing Center (BSC), Barcelona, Catalonia, Spain
| | - Rico Hagelaar
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | - Manel Esteller
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, Barcelona, Catalonia, Spain
- Centro de Investigación Biomédica en Red de Cancer (CIBERONC), Madrid, Spain
- Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona (UB), Barcelona, Catalonia, Spain
- Institucio Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain
| | | | - Jean Soulier
- INSERM U944 and University de Paris, Hopital Saint-Louis, Paris, France
| | - Tom Taghon
- Cancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Pieter Van Vlierberghe
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium
| | - Charles G Mullighan
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Hossein Khiabanian
- Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, New Jersey
- Center for Systems and Computational Biology, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, New Jersey
- Department of Pathology and Laboratory Medicine, Rutgers Robert Wood Johnson Medical School, Rutgers University, New Brunswick, New Jersey
| | - Pedro P Rocha
- Unit on Genome Structure and Regulation, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
- National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Daniel Herranz
- Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, New Jersey.
- Department of Pharmacology, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey
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