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Zhao H, Lin Y, Lin E, Liu F, Shu L, Jing D, Wang B, Wang M, Shan F, Zhang L, Lam JC, Midla SC, Giardine BM, Keller CA, Hardison RC, Blobel GA, Zhang H. Genome folding principles uncovered in condensin-depleted mitotic chromosomes. Nat Genet 2024:10.1038/s41588-024-01759-x. [PMID: 38802567 DOI: 10.1038/s41588-024-01759-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 04/18/2024] [Indexed: 05/29/2024]
Abstract
During mitosis, condensin activity is thought to interfere with interphase chromatin structures. To investigate genome folding principles in the absence of chromatin loop extrusion, we codepleted condensin I and condensin II, which triggered mitotic chromosome compartmentalization in ways similar to that in interphase. However, two distinct euchromatic compartments, indistinguishable in interphase, emerged upon condensin loss with different interaction preferences and dependencies on H3K27ac. Constitutive heterochromatin gradually self-aggregated and cocompartmentalized with facultative heterochromatin, contrasting with their separation during interphase. Notably, some cis-regulatory element contacts became apparent even in the absence of CTCF/cohesin-mediated structures. Heterochromatin protein 1 (HP1) proteins, which are thought to partition constitutive heterochromatin, were absent from mitotic chromosomes, suggesting, surprisingly, that constitutive heterochromatin can self-aggregate without HP1. Indeed, in cells traversing from M to G1 phase in the combined absence of HP1α, HP1β and HP1γ, constitutive heterochromatin compartments are normally re-established. In sum, condensin-deficient mitotic chromosomes illuminate forces of genome compartmentalization not identified in interphase cells.
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Affiliation(s)
- Han Zhao
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, China
| | - Yinzhi Lin
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, China
| | - En Lin
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, China
| | - Fuhai Liu
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, China
| | - Lirong Shu
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, China
| | - Dannan Jing
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, China
- Department of Biology, College of Science, Shantou University, Shantou, China
| | - Baiyue Wang
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, China
| | - Manzhu Wang
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, China
- School of Basic Medicine, Capital Medical University, Beijing, China
| | - Fengnian Shan
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, China
- School of Pharmacology, South China University of Technology, Guangzhou, China
| | - Lin Zhang
- School of Biological Science, Hongkong University, Hongkong, China
| | - Jessica C Lam
- Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Susannah C Midla
- Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Belinda M Giardine
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, USA
| | - Cheryl A Keller
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, USA
| | - Ross C Hardison
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, USA
| | - Gerd A Blobel
- Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Haoyue Zhang
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, China.
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2
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Keenan CR, Coughlan HD, Iannarella N, Tapia Del Fierro A, Keniry A, Johanson TM, Chan WF, Garnham AL, Whitehead LW, Blewitt ME, Smyth GK, Allan RS. Suv39h-catalyzed H3K9me3 is critical for euchromatic genome organization and the maintenance of gene transcription. Genome Res 2024; 34:556-571. [PMID: 38719473 PMCID: PMC11146594 DOI: 10.1101/gr.279119.124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 04/03/2024] [Indexed: 06/05/2024]
Abstract
H3K9me3-dependent heterochromatin is critical for the silencing of repeat-rich pericentromeric regions and also has key roles in repressing lineage-inappropriate protein-coding genes in differentiation and development. Here, we investigate the molecular consequences of heterochromatin loss in cells deficient in both SUV39H1 and SUV39H2 (Suv39DKO), the major mammalian histone methyltransferase enzymes that catalyze heterochromatic H3K9me3 deposition. We reveal a paradoxical repression of protein-coding genes in Suv39DKO cells, with these differentially expressed genes principally in euchromatic (Tn5-accessible, H3K4me3- and H3K27ac-marked) rather than heterochromatic (H3K9me3-marked) or polycomb (H3K27me3-marked) regions. Examination of the three-dimensional (3D) nucleome reveals that transcriptomic dysregulation occurs in euchromatic regions close to the nuclear periphery in 3D space. Moreover, this transcriptomic dysregulation is highly correlated with altered 3D genome organization in Suv39DKO cells. Together, our results suggest that the nuclear lamina-tethering of Suv39-dependent H3K9me3 domains provides an essential scaffold to support euchromatic genome organization and the maintenance of gene transcription for healthy cellular function.
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Affiliation(s)
- Christine R Keenan
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia;
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Hannah D Coughlan
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Nadia Iannarella
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
| | - Andres Tapia Del Fierro
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Andrew Keniry
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Timothy M Johanson
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Wing Fuk Chan
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Alexandra L Garnham
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Lachlan W Whitehead
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Marnie E Blewitt
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Gordon K Smyth
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- School of Mathematics and Statistics, The University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Rhys S Allan
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia;
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia
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3
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Hu S, Liu Y, Zhang Q, Bai J, Xu C. A continuum of zinc finger transcription factor retention on native chromatin underlies dynamic genome organization. Mol Syst Biol 2024:10.1038/s44320-024-00038-5. [PMID: 38745107 DOI: 10.1038/s44320-024-00038-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 04/10/2024] [Accepted: 04/15/2024] [Indexed: 05/16/2024] Open
Abstract
Transcription factor (TF) residence on chromatin translates into quantitative transcriptional or structural outcomes on genome. Commonly used formaldehyde crosslinking fixes TF-DNA interactions cumulatively and compromises the measured occupancy level. Here we mapped the occupancy level of global or individual zinc finger TFs like CTCF and MAZ, in the form of highly resolved footprints, on native chromatin. By incorporating reinforcing perturbation conditions, we established S-score, a quantitative metric to proxy the continuum of CTCF or MAZ retention across different motifs on native chromatin. The native chromatin-retained CTCF sites harbor sequence features within CTCF motifs better explained by S-score than the metrics obtained from other crosslinking or native assays. CTCF retention on native chromatin correlates with local SUMOylation level, and anti-correlates with transcriptional activity. The S-score successfully delineates the otherwise-masked differential stability of chromatin structures mediated by CTCF, or by MAZ independent of CTCF. Overall, our study established a paradigm continuum of TF retention across binding sites on native chromatin, explaining the dynamic genome organization.
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Affiliation(s)
- Siling Hu
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
- China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yangying Liu
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
- China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Qifan Zhang
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
- China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Juan Bai
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
- China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Chenhuan Xu
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.
- China National Center for Bioinformation, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
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4
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Xie T, Danieli-Mackay A, Buccarelli M, Barbieri M, Papadionysiou I, D'Alessandris QG, Robens C, Übelmesser N, Vinchure OS, Lauretti L, Fotia G, Schwarz RF, Wang X, Ricci-Vitiani L, Gopalakrishnan J, Pallini R, Papantonis A. Pervasive structural heterogeneity rewires glioblastoma chromosomes to sustain patient-specific transcriptional programs. Nat Commun 2024; 15:3905. [PMID: 38724522 PMCID: PMC11082206 DOI: 10.1038/s41467-024-48053-2] [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: 11/24/2023] [Accepted: 04/18/2024] [Indexed: 05/12/2024] Open
Abstract
Glioblastoma multiforme (GBM) encompasses brain malignancies marked by phenotypic and transcriptional heterogeneity thought to render these tumors aggressive, resistant to therapy, and inevitably recurrent. However, little is known about how the spatial organization of GBM genomes underlies this heterogeneity and its effects. Here, we compile a cohort of 28 patient-derived glioblastoma stem cell-like lines (GSCs) known to reflect the properties of their tumor-of-origin; six of these were primary-relapse tumor pairs from the same patient. We generate and analyze 5 kbp-resolution chromosome conformation capture (Hi-C) data from all GSCs to systematically map thousands of standalone and complex structural variants (SVs) and the multitude of neoloops arising as a result. By combining Hi-C, histone modification, and gene expression data with chromatin folding simulations, we explain how the pervasive, uneven, and idiosyncratic occurrence of neoloops sustains tumor-specific transcriptional programs via the formation of new enhancer-promoter contacts. We also show how even moderately recurrent neoloops can relate to patient-specific vulnerabilities. Together, our data provide a resource for dissecting GBM biology and heterogeneity, as well as for informing therapeutic approaches.
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Affiliation(s)
- Ting Xie
- Institute of Pathology, University Medical Center Göttingen, Göttingen, Germany
| | - Adi Danieli-Mackay
- Institute of Pathology, University Medical Center Göttingen, Göttingen, Germany
| | - Mariachiara Buccarelli
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy
| | - Mariano Barbieri
- Institute of Pathology, University Medical Center Göttingen, Göttingen, Germany
| | | | - Q Giorgio D'Alessandris
- Department of Neuroscience, Catholic University School of Medicine, Rome, Italy
- Department of Neuroscience, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma, Italy
| | - Claudia Robens
- Institute for Computational Cancer Biology (ICCB), Center for Integrated Oncology (CIO), Cancer Research Center Cologne Essen (CCCE), University of Cologne, Cologne, Germany
| | - Nadine Übelmesser
- Institute of Pathology, University Medical Center Göttingen, Göttingen, Germany
| | - Omkar Suhas Vinchure
- Institute of Human Genetics, University Hospital and Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Liverana Lauretti
- Department of Neuroscience, Catholic University School of Medicine, Rome, Italy
| | - Giorgio Fotia
- Centre for Advanced Studies, Research and Development in Sardinia (CRS4), Pula, Italy
| | - Roland F Schwarz
- Institute for Computational Cancer Biology (ICCB), Center for Integrated Oncology (CIO), Cancer Research Center Cologne Essen (CCCE), University of Cologne, Cologne, Germany
- Berlin Institute for the Foundations of Learning and Data (BIFOLD), Berlin, Germany
| | - Xiaotao Wang
- Institute of Reproduction and Development, Fudan University, Shanghai, China
- Research Units of Embryo Original Diseases, Chinese Academy of Medical Sciences, Shanghai, China
| | - Lucia Ricci-Vitiani
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy
| | - Jay Gopalakrishnan
- Institute of Human Genetics, University Hospital and Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
- Institute of Human Genetics, Jena University Hospital and Friedrich Schiller University of Jena, Jena, Germany
| | - Roberto Pallini
- Department of Neuroscience, Catholic University School of Medicine, Rome, Italy.
| | - Argyris Papantonis
- Institute of Pathology, University Medical Center Göttingen, Göttingen, Germany.
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5
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Gao G, Liu R, Hu S, He M, Zhang J, Gao D, Li J, Hu J, Wang J, Wang Q, Li M, Jin L. Exploring the dynamic three-dimensional chromatin architecture and transcriptional landscape in goose liver tissues underlying metabolic adaptations induced by a high-fat diet. J Anim Sci Biotechnol 2024; 15:60. [PMID: 38693536 PMCID: PMC11064361 DOI: 10.1186/s40104-024-01016-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 02/29/2024] [Indexed: 05/03/2024] Open
Abstract
BACKGROUND Goose, descendants of migratory ancestors, have undergone extensive selective breeding, resulting in their remarkable ability to accumulate fat in the liver and exhibit a high tolerance for significant energy intake. As a result, goose offers an excellent model for studying obesity, metabolic disorders, and liver diseases in mammals. Although the impact of the three-dimensional arrangement of chromatin within the cell nucleus on gene expression and transcriptional regulation is widely acknowledged, the precise functions of chromatin architecture reorganization during fat deposition in goose liver tissues still need to be fully comprehended. RESULTS In this study, geese exhibited more pronounced changes in the liver index and triglyceride (TG) content following the consumption of the high-fat diet (HFD) than mice without significant signs of inflammation. Additionally, we performed comprehensive analyses on 10 goose liver tissues (5 HFD, 5 normal), including generating high-resolution maps of chromatin architecture, conducting whole-genome gene expression profiling, and identifying H3K27ac peaks in the livers of geese and mice subjected to the HFD. Our results unveiled a multiscale restructuring of chromatin architecture, encompassing Compartment A/B, topologically associated domains, and interactions between promoters and enhancers. The dynamism of the three-dimensional genome architecture, prompted by the HFD, assumed a pivotal role in the transcriptional regulation of crucial genes. Furthermore, we identified genes that regulate chromatin conformation changes, contributing to the metabolic adaptation process of lipid deposition and hepatic fat changes in geese in response to excessive energy intake. Moreover, we conducted a cross-species analysis comparing geese and mice exposed to the HFD, revealing unique characteristics specific to the goose liver compared to a mouse. These chromatin conformation changes help elucidate the observed characteristics of fat deposition and hepatic fat regulation in geese under conditions of excessive energy intake. CONCLUSIONS We examined the dynamic modifications in three-dimensional chromatin architecture and gene expression induced by an HFD in goose liver tissues. We conducted a cross-species analysis comparing that of mice. Our results contribute significant insights into the chromatin architecture of goose liver tissues, offering a novel perspective for investigating mammal liver diseases.
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Affiliation(s)
- Guangliang Gao
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Sciences, Rongchang District, Chongqing, 402460, China
| | - Rui Liu
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Silu Hu
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Mengnan He
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jiaman Zhang
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Dengfeng Gao
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jing Li
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jiwei Hu
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jiwen Wang
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Qigui Wang
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Sciences, Rongchang District, Chongqing, 402460, China
| | - Mingzhou Li
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China.
| | - Long Jin
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China.
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Duan N, Hua Y, Yan X, He Y, Zeng T, Gong J, Fu Z, Li W, Yin Y. Unveiling Alterations of Epigenetic Modifications and Chromatin Architecture Leading to Lipid Metabolic Reprogramming during the Evolutionary Trastuzumab Adaptation of HER2-Positive Breast Cancer. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2309424. [PMID: 38460162 PMCID: PMC11095153 DOI: 10.1002/advs.202309424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 02/08/2024] [Indexed: 03/11/2024]
Abstract
Secondary trastuzumab resistance represents an evolutionary adaptation of HER2-positive breast cancer during anti-HER2 treatment. Most current studies have tended to prioritize HER2 and its associated signaling pathways, often overlooking broader but seemingly less relevant cellular processes, along with their associated genetic and epigenetic mechanisms. Here, transcriptome data is not only characterized but also examined epigenomic and 3D genome architecture information in both trastuzumab-sensitive and secondary-resistant breast cancer cells. The findings reveal that the global metabolic reprogramming associated with trastuzumab resistance may stem from genome-wide alterations in both histone modifications and chromatin structure. Specifically, the transcriptional activities of key genes involved in lipid metabolism appear to be regulated by variant promoter H3K27me3 and H3K4me3 modifications, as well as promoter-enhancer interactions. These discoveries offer valuable insights into how cancer cells adapt to anti-tumor drugs and have the potential to impact future diagnostic and treatment strategies.
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Affiliation(s)
- Ningjun Duan
- Department of oncologyFirst affiliation hospital of Nanjing medical universityNanjing210029China
| | - Yijia Hua
- Department of oncologyFirst affiliation hospital of Nanjing medical universityNanjing210029China
| | - Xueqi Yan
- Department of oncologyFirst affiliation hospital of Nanjing medical universityNanjing210029China
| | - Yaozhou He
- Department of oncologyFirst affiliation hospital of Nanjing medical universityNanjing210029China
| | - Tianyu Zeng
- Department of oncologyFirst affiliation hospital of Nanjing medical universityNanjing210029China
| | - Jue Gong
- Department of oncologyFirst affiliation hospital of Nanjing medical universityNanjing210029China
| | - Ziyi Fu
- Department of oncologyFirst affiliation hospital of Nanjing medical universityNanjing210029China
| | - Wei Li
- Department of oncologyFirst affiliation hospital of Nanjing medical universityNanjing210029China
| | - Yongmei Yin
- Department of oncologyFirst affiliation hospital of Nanjing medical universityNanjing210029China
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7
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Shi Z, Wu H. CTPredictor: A comprehensive and robust framework for predicting cell types by integrating multi-scale features from single-cell Hi-C data. Comput Biol Med 2024; 173:108336. [PMID: 38513390 DOI: 10.1016/j.compbiomed.2024.108336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 03/01/2024] [Accepted: 03/17/2024] [Indexed: 03/23/2024]
Abstract
Single-cell Hi-C (scHi-C) has emerged as a powerful technology for deciphering cell-to-cell variability in three-dimensional (3D) chromatin organization, providing insights into genome-wide chromatin interactions and their correlation with cellular functions. Nevertheless, the accurate identification of cell types across different datasets remains a formidable challenge, hindering comprehensive investigations into genome structure. In response, we introduce CTPredictor, an innovative computational method that integrates multi-scale features to accurately predict cell types in various datasets. CTPredictor strategically incorporates three distinct feature sets, namely, small intra-domain contact probability (SICP), smoothed small intra-domain contact probability (SSICP), and smoothed bin contact probability (SBCP). The resulting fusion classification model significantly enhances the accuracy of cell type prediction based on single-cell Hi-C data (scHi-C). Rigorous benchmarking against established methods and three conventional machine learning approaches demonstrates the robust performance of CTPredictor, positioning it as an advanced tool for cell type prediction within scHi-C data. Beyond its prediction capabilities, CTPredictor holds promise in illuminating 3D genome structures and their functional significance across a wide array of biological processes.
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Affiliation(s)
- Zhenqi Shi
- School of Software, Shandong University, 250100, Jinan, China
| | - Hao Wu
- School of Software, Shandong University, 250100, Jinan, China.
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8
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Guo J, Chen Y, Zhu H, Tong X, Cao L, Zhang Y, Xie W, Li C. Three-dimensional chromatin landscapes in somatotroph tumour. Clin Transl Med 2024; 14:e1682. [PMID: 38769659 PMCID: PMC11106515 DOI: 10.1002/ctm2.1682] [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: 11/17/2023] [Revised: 04/01/2024] [Accepted: 04/19/2024] [Indexed: 05/22/2024] Open
Abstract
BACKGROUND The three-dimensional (3D) genome architecture plays a critical role inregulating gene expression. However, the specific alterations in thisarchitecture within somatotroph tumors and their implications for gene expression remain largely unexplored. METHODS We employed Hi-C and RNA-seq analyses to compare the 3D genomic structures of somatotroph tumors with normal pituitary tissue. This comprehensive approachenabled the characterization of A/B compartments, topologically associateddomains (TADs), and chromatin loops, integrating these with gene expression patterns. RESULTS We observed a decrease in both the frequency of chromosomal interactions andthe size of TADs in tumor tissue compared to normal tissue. Conversely, the number of TADs and chromatin loops was found to be increased in tumors. Integrated analysis of Hi-C and RNA-seq data demonstrated that changes inhigher-order chromat in structure were associated with alterations in gene expression. Specifically, genes in A compartments showed higher density and increased expression relative to those in B compartments. Moreover, the weakand enhanced insulation boundaries were identified, and the associated genes were enriched in the Wnt/β-Catenin signaling pathway. We identified the gainedand lost loops in tumor and integrated these differences with transcriptional changes to examine the functional relevance of the identified loops. Notably, we observed an enhanced insulation boundary and a greater number of loops in the TCF7L2 gene region within tumors, which was accompanied by an upregulation of TCF7L2 expression. Subsequently, TCF7L2 expression was confirmed through qRT-PCR, and upregulated TCF7L2 prompted cell proliferation and growth hormone (GH) secretion in vitro. CONCLUSION Our results provide comprehensive 3D chromatin architecture maps of somatotroph tumors and offer a valuable resource for furthering the understanding of the underlying biology and mechanisms of gene expression regulation.
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Affiliation(s)
- Jing Guo
- Department of NeurosurgeryBeijing Tiantan Hospital affiliated to Capital Medical UniversityBeijingChina
- Beijing Neurosurgical InstituteCapital Medical UniversityBeijingChina
| | - Yiyuan Chen
- Department of NeurosurgeryBeijing Tiantan Hospital affiliated to Capital Medical UniversityBeijingChina
- Beijing Neurosurgical InstituteCapital Medical UniversityBeijingChina
| | - Haibo Zhu
- Department of NeurosurgeryBeijing Tiantan Hospital affiliated to Capital Medical UniversityBeijingChina
| | - Xinyu Tong
- Annoroad Gene Technology Co., LtdBeijingChina
| | - Lei Cao
- Department of NeurosurgeryBeijing Tiantan Hospital affiliated to Capital Medical UniversityBeijingChina
| | - Yazhuo Zhang
- Beijing Neurosurgical InstituteCapital Medical UniversityBeijingChina
- Beijing Institute for Brain Disorders Brain Tumor CenterBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Weiyan Xie
- Beijing Neurosurgical InstituteCapital Medical UniversityBeijingChina
| | - Chuzhong Li
- Department of NeurosurgeryBeijing Tiantan Hospital affiliated to Capital Medical UniversityBeijingChina
- Beijing Neurosurgical InstituteCapital Medical UniversityBeijingChina
- Beijing Institute for Brain Disorders Brain Tumor CenterBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
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9
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Guo R, Dong X, Chen F, Ji T, He Q, Zhang J, Sheng Y, Liu Y, Yang S, Liang W, Song Y, Fang K, Zhang L, Hu G, Yao H. TEAD2 initiates ground-state pluripotency by mediating chromatin looping. EMBO J 2024; 43:1965-1989. [PMID: 38605224 PMCID: PMC11099042 DOI: 10.1038/s44318-024-00086-5] [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: 06/25/2023] [Revised: 02/26/2024] [Accepted: 03/03/2024] [Indexed: 04/13/2024] Open
Abstract
The transition of mouse embryonic stem cells (ESCs) between serum/LIF and 2i(MEK and GSK3 kinase inhibitor)/LIF culture conditions serves as a valuable model for exploring the mechanisms underlying ground and confused pluripotent states. Regulatory networks comprising core and ancillary pluripotency factors drive the gene expression programs defining stable naïve pluripotency. In our study, we systematically screened factors essential for ESC pluripotency, identifying TEAD2 as an ancillary factor maintaining ground-state pluripotency in 2i/LIF ESCs and facilitating the transition from serum/LIF to 2i/LIF ESCs. TEAD2 exhibits increased binding to chromatin in 2i/LIF ESCs, targeting active chromatin regions to regulate the expression of 2i-specific genes. In addition, TEAD2 facilitates the expression of 2i-specific genes by mediating enhancer-promoter interactions during the serum/LIF to 2i/LIF transition. Notably, deletion of Tead2 results in reduction of a specific set of enhancer-promoter interactions without significantly affecting binding of chromatin architecture proteins, CCCTC-binding factor (CTCF), and Yin Yang 1 (YY1). In summary, our findings highlight a novel prominent role of TEAD2 in orchestrating higher-order chromatin structures of 2i-specific genes to sustain ground-state pluripotency.
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Affiliation(s)
- Rong Guo
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
- Center for Health Research, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Xiaotao Dong
- Center for Health Research, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
- School of Basic Medical Science, Henan University, Kaifeng, China
| | - Feng Chen
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
| | - Tianrong Ji
- Center for Health Research, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Qiannan He
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
- Center for Health Research, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Jie Zhang
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
- Center for Health Research, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Yingliang Sheng
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
- Center for Health Research, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Yanjiang Liu
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
- Center for Health Research, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Shengxiong Yang
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
- Center for Health Research, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Weifang Liang
- College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong, China
| | - Yawei Song
- Center for Health Research, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Ke Fang
- Center for Health Research, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Lingling Zhang
- Institute of Clinical Pharmacology, Anhui Medical University, Hefei, China
| | - Gongcheng Hu
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
- Center for Health Research, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Hongjie Yao
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China.
- Center for Health Research, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.
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10
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Cao C, Xu Q, Zhu Z, Xu M, Wei Y, Lin S, Cheng S, Zhi W, Hong P, Huang X, Lin D, Cao G, Meng Y, Wu P, Peng T, Wei J, Ding W, Huang X, Sung W, Chen G, Ma D, Li G, Wu P. Three-dimensional chromatin analysis reveals Sp1 as a mediator to program and reprogram HPV-host epigenetic architecture in cervical cancer. Cancer Lett 2024; 588:216809. [PMID: 38471646 DOI: 10.1016/j.canlet.2024.216809] [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: 01/15/2024] [Revised: 02/29/2024] [Accepted: 03/07/2024] [Indexed: 03/14/2024]
Abstract
Human papillomavirus (HPV) is predominantly associated with HPV-related cancers, however, the precise mechanisms underlying the HPV-host epigenetic architectures in HPV carcinogenesis remain elusive. Here, we employed high-throughput chromosome conformation capture (Hi-C) to comprehensively map HPV16/18-host chromatin interactions. Our study identified the transcription factor Sp1 as a pivotal mediator in programming HPV-host interactions. By targeting Sp1, the active histone modifications (H3K27ac, H3K4me1, and H3K4me3) and the HPV-host chromatin interactions are reprogrammed, which leads to the downregulation of oncogenes located near the integration sites in both HPV (E6/E7) and the host genome (KLF5/MYC). Additionally, Sp1 inhibition led to the upregulation of immune checkpoint genes by reprogramming histone modifications in host cells. Notably, humanized patient-derived xenograft (PDX-HuHSC-NSG) models demonstrated that Sp1 inhibition promoted anti-PD-1 immunotherapy via remodeling the tumor immune microenvironment in cervical cancer. Moreover, single-cell transcriptomic analysis validated the enrichment of transcription factor Sp1 in epithelial cells of cervical cancer. In summary, our findings elucidate Sp1 as a key mediator involved in the programming and reprogramming of HPV-host epigenetic architecture. Inhibiting Sp1 with plicamycin may represent a promising therapeutic option for HPV-related carcinoma.
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Affiliation(s)
- Canhui Cao
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qian Xu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China; Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan, China
| | - Zhixian Zhu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China; Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan, China
| | - Miaochun Xu
- Department of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ye Wei
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shitong Lin
- Department of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Sheng Cheng
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China; Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan, China
| | - Wenhua Zhi
- Department of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ping Hong
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China; Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan, China
| | - Xingyu Huang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China; Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan, China
| | - Da Lin
- Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan, China; State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
| | - Gang Cao
- Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan, China; State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
| | - Yifan Meng
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ping Wu
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ting Peng
- Department of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Juncheng Wei
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wencheng Ding
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoyuan Huang
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - WingKin Sung
- Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan, China; School of Computing, National University of Singapore, 13 Computing Drive, 117417, Singapore
| | - Gang Chen
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ding Ma
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Guoliang Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China; Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan, China.
| | - Peng Wu
- Department of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; National Clinical Research Center for Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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11
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Li B, Xiong W, Zuo W, Shi Y, Wang T, Chang L, Wu Y, Ma H, Bian Q, Chang ACY. Proximal telomeric decompaction due to telomere shortening drives FOXC1-dependent myocardial senescence. Nucleic Acids Res 2024:gkae274. [PMID: 38634789 DOI: 10.1093/nar/gkae274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 02/29/2024] [Accepted: 04/03/2024] [Indexed: 04/19/2024] Open
Abstract
Telomeres, TTAGGGn DNA repeat sequences located at the ends of eukaryotic chromosomes, play a pivotal role in aging and are targets of DNA damage response. Although we and others have demonstrated presence of short telomeres in genetic cardiomyopathic and heart failure cardiomyocytes, little is known about the role of telomere lengths in cardiomyocyte. Here, we demonstrate that in heart failure patient cardiomyocytes, telomeres are shortened compared to healthy controls. We generated isogenic human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) with short telomeres (sTL-CMs) and normal telomeres (nTL-CMs) as model. Compared to nTL-CMs, short telomeres result in cardiac dysfunction and expression of senescent markers. Using Hi-C and RNASeq, we observe that short telomeres induced TAD insulation decrease near telomeric ends and this correlated with a transcription upregulation in sTL-CMs. FOXC1, a key transcription factor involved in early cardiogenesis, was upregulated in sTL-CMs and its protein levels were negatively correlated with telomere lengths in heart failure patients. Overexpression of FOXC1 induced hiPSC-CM aging, mitochondrial and contractile dysfunction; knockdown of FOXC1 rescued these phenotypes. Overall, the work presented demonstrate that increased chromatin accessibility due to telomere shortening resulted in the induction of FOXC1-dependent expression network responsible for contractile dysfunction and myocardial senescence.
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Affiliation(s)
- Bin Li
- Department of Cardiology and Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200125, China
| | - Weiyao Xiong
- Department of Cardiology and Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200125, China
| | - Wu Zuo
- Department of Cardiology and Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200125, China
| | - Yuanyuan Shi
- Department of Cardiology and Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200125, China
| | - Teng Wang
- Department of Cardiology and Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200125, China
| | - Lingling Chang
- Department of Cardiology and Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200125, China
| | - Yueheng Wu
- Department of Cardiovascular Medicine, Guangdong General Hospital, Guangzhou, Guangdong, China
| | - Heng Ma
- Department of Physiology and Pathophysiology, Fourth Military Medical University, No. 169 Changle West Rd, Xi'an 710032, China
| | - Qian Bian
- Department of Cardiology and Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200125, China
| | - Alex C Y Chang
- Department of Cardiology and Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200125, China
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12
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Li J, Lin Y, Li D, He M, Kui H, Bai J, Chen Z, Gou Y, Zhang J, Wang T, Tang Q, Kong F, Jin L, Li M. Building Haplotype-Resolved 3D Genome Maps of Chicken Skeletal Muscle. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2305706. [PMID: 38582509 DOI: 10.1002/advs.202305706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 03/07/2024] [Indexed: 04/08/2024]
Abstract
Haplotype-resolved 3D chromatin architecture related to allelic differences in avian skeletal muscle development has not been addressed so far, although chicken husbandry for meat consumption has been prevalent feature of cultures on every continent for more than thousands of years. Here, high-resolution Hi-C diploid maps (1.2-kb maximum resolution) are generated for skeletal muscle tissues in chicken across three developmental stages (embryonic day 15 to day 30 post-hatching). The sequence features governing spatial arrangement of chromosomes and characterize homolog pairing in the nucleus, are identified. Multi-scale characterization of chromatin reorganization between stages from myogenesis in the fetus to myofiber hypertrophy after hatching show concordant changes in transcriptional regulation by relevant signaling pathways. Further interrogation of parent-of-origin-specific chromatin conformation supported that genomic imprinting is absent in birds. This study also reveals promoter-enhancer interaction (PEI) differences between broiler and layer haplotypes in skeletal muscle development-related genes are related to genetic variation between breeds, however, only a minority of breed-specific variations likely contribute to phenotypic divergence in skeletal muscle potentially via allelic PEI rewiring. Beyond defining the haplotype-specific 3D chromatin architecture in chicken, this study provides a rich resource for investigating allelic regulatory divergence among chicken breeds.
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Affiliation(s)
- Jing Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yu Lin
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Diyan Li
- School of Pharmacy, Chengdu University, Chengdu, 610106, China
| | - Mengnan He
- Wildlife Conservation Research Department, Chengdu Research Base of Giant Panda Breeding, Chengdu, 610057, China
| | - Hua Kui
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jingyi Bai
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Ziyu Chen
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yuwei Gou
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jiaman Zhang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Tao Wang
- School of Pharmacy, Chengdu University, Chengdu, 610106, China
| | - Qianzi Tang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Fanli Kong
- College of Life Science, Sichuan Agricultural University, Ya'an, 625014, China
| | - Long Jin
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Mingzhou Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
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13
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Tang X, Zeng P, Liu K, Qing L, Sun Y, Liu X, Lu L, Wei C, Wang J, Jiang S, Sun J, Chang W, Yu H, Chen H, Zhou J, Xu C, Fan L, Miao YL, Ding J. The PTM profiling of CTCF reveals the regulation of 3D chromatin structure by O-GlcNAcylation. Nat Commun 2024; 15:2813. [PMID: 38561336 PMCID: PMC10985093 DOI: 10.1038/s41467-024-47048-3] [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: 11/28/2023] [Accepted: 03/18/2024] [Indexed: 04/04/2024] Open
Abstract
CCCTC-binding factor (CTCF), a ubiquitously expressed and highly conserved protein, is known to play a critical role in chromatin structure. Post-translational modifications (PTMs) diversify the functions of protein to regulate numerous cellular processes. However, the effects of PTMs on the genome-wide binding of CTCF and the organization of three-dimensional (3D) chromatin structure have not been fully understood. In this study, we uncovered the PTM profiling of CTCF and demonstrated that CTCF can be O-GlcNAcylated and arginine methylated. Functionally, we demonstrated that O-GlcNAcylation inhibits CTCF binding to chromatin. Meanwhile, deficiency of CTCF O-GlcNAcylation results in the disruption of loop domains and the alteration of chromatin loops associated with cellular development. Furthermore, the deficiency of CTCF O-GlcNAcylation increases the expression of developmental genes and negatively regulates maintenance and establishment of stem cell pluripotency. In conclusion, these results provide key insights into the role of PTMs for the 3D chromatin structure.
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Affiliation(s)
- Xiuxiao Tang
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Pharmacology and Cardiac & Cerebral Vascular Research Center, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Pengguihang Zeng
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Kezhi Liu
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Li Qing
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Yifei Sun
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Xinyi Liu
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Lizi Lu
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Chao Wei
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Jia Wang
- GMU-GIBH Joint School of Life Sciences, Guangzhou Medical University, Guangzhou, 511436, China
| | - Shaoshuai Jiang
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Jun Sun
- West China Biomedical Big Data Center, West China Hospital/West China School of Medicine, Sichuan University, Chengdu, 610041, China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610041, China
| | - Wakam Chang
- Department of Biomedical Sciences, Faculty of Health Sciences, University of Macau, Taipa, Macau, China
| | - Haopeng Yu
- West China Biomedical Big Data Center, West China Hospital/West China School of Medicine, Sichuan University, Chengdu, 610041, China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610041, China
| | - Hebing Chen
- Institute of Health Service and Transfusion Medicine, Beijing, 100850, China
| | - Jiaguo Zhou
- Department of Pharmacology and Cardiac & Cerebral Vascular Research Center, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Chengfang Xu
- The obstetric and gynecology Department of The third affiliated hospital of Sun Yat-Sen University, Guangzhou, China.
| | - Lili Fan
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, Guangdong, China.
| | - Yi-Liang Miao
- Institute of Stem Cell and Regenerative Biology, College of Animal Science and Veterinary Medicine, Huazhong Agricultural University, Wuhan, Hubei, China.
| | - Junjun Ding
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China.
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China.
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China.
- West China Biomedical Big Data Center, West China Hospital/West China School of Medicine, Sichuan University, Chengdu, 610041, China.
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14
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Serra F, Nieto-Aliseda A, Fanlo-Escudero L, Rovirosa L, Cabrera-Pasadas M, Lazarenkov A, Urmeneta B, Alcalde-Merino A, Nola EM, Okorokov AL, Fraser P, Graupera M, Castillo SD, Sardina JL, Valencia A, Javierre BM. p53 rapidly restructures 3D chromatin organization to trigger a transcriptional response. Nat Commun 2024; 15:2821. [PMID: 38561401 PMCID: PMC10984980 DOI: 10.1038/s41467-024-46666-1] [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: 06/15/2023] [Accepted: 03/04/2024] [Indexed: 04/04/2024] Open
Abstract
Activation of the p53 tumor suppressor triggers a transcriptional program to control cellular response to stress. However, the molecular mechanisms by which p53 controls gene transcription are not completely understood. Here, we uncover the critical role of spatio-temporal genome architecture in this process. We demonstrate that p53 drives direct and indirect changes in genome compartments, topologically associating domains, and DNA loops prior to one hour of its activation, which escort the p53 transcriptional program. Focusing on p53-bound enhancers, we report 340 genes directly regulated by p53 over a median distance of 116 kb, with 74% of these genes not previously identified. Finally, we showcase that p53 controls transcription of distal genes through newly formed and pre-existing enhancer-promoter loops in a cohesin dependent manner. Collectively, our findings demonstrate a previously unappreciated architectural role of p53 as regulator at distinct topological layers and provide a reliable set of new p53 direct target genes that may help designs of cancer therapies.
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Affiliation(s)
- François Serra
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
| | | | | | | | - Mónica Cabrera-Pasadas
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
- Barcelona Supercomputing Center, Barcelona, Spain
| | | | - Blanca Urmeneta
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
| | | | - Emanuele M Nola
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
| | - Andrei L Okorokov
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Peter Fraser
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Mariona Graupera
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
- CIBERONC, Instituto de Salud Carlos III, Madrid, Spain
| | | | - Jose L Sardina
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
| | - Alfonso Valencia
- Barcelona Supercomputing Center, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Biola M Javierre
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain.
- Institute for Health Science Research Germans Trias i Pujol, Barcelona, Spain.
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15
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Fletez-Brant K, Qiu Y, Gorkin DU, Hu M, Hansen KD. Removing unwanted variation between samples in Hi-C experiments. Brief Bioinform 2024; 25:bbae217. [PMID: 38711367 DOI: 10.1093/bib/bbae217] [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: 05/25/2023] [Revised: 01/26/2024] [Accepted: 04/24/2024] [Indexed: 05/08/2024] Open
Abstract
Hi-C data are commonly normalized using single sample processing methods, with focus on comparisons between regions within a given contact map. Here, we aim to compare contact maps across different samples. We demonstrate that unwanted variation, of likely technical origin, is present in Hi-C data with replicates from different individuals, and that properties of this unwanted variation change across the contact map. We present band-wise normalization and batch correction, a method for normalization and batch correction of Hi-C data and show that it substantially improves comparisons across samples, including in a quantitative trait loci analysis as well as differential enrichment across cell types.
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Affiliation(s)
- Kipper Fletez-Brant
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltmore, MD 21205, USA
| | - Yunjiang Qiu
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
- Ludwig Institute for Cancer Research, New York, NY 10016, USA
| | - David U Gorkin
- Ludwig Institute for Cancer Research, New York, NY 10016, USA
- Department of Cellular and Molecular Medicine, University of California at San Diego, La Jolla, CA 92093, USA
- Currently: Department of Biology. Emory University. Atlanta, GA 30322, USA
| | - Ming Hu
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH 44196, USA
| | - Kasper D Hansen
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltmore, MD 21205, USA
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16
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Kim M, Wang P, Clow PA, Chien I(E, Wang X, Peng J, Chai H, Liu X, Lee B, Ngan CY, Yue F, Milenkovic O, Chuang JH, Wei CL, Casellas R, Cheng AW, Ruan Y. Multifaceted roles of cohesin in regulating transcriptional loops. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.25.586715. [PMID: 38585764 PMCID: PMC10996690 DOI: 10.1101/2024.03.25.586715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Cohesin is required for chromatin loop formation. However, its precise role in regulating gene transcription remains largely unknown. We investigated the relationship between cohesin and RNA Polymerase II (RNAPII) using single-molecule mapping and live-cell imaging methods in human cells. Cohesin-mediated transcriptional loops were highly correlated with those of RNAPII and followed the direction of gene transcription. Depleting RAD21, a subunit of cohesin, resulted in the loss of long-range (>100 kb) loops between distal (super-)enhancers and promoters of cell-type-specific genes. By contrast, the short-range (<50 kb) loops were insensitive to RAD21 depletion and connected genes that are mostly housekeeping. This result explains why only a small fraction of genes are affected by the loss of long-range chromatin interactions due to cohesin depletion. Remarkably, RAD21 depletion appeared to up-regulate genes located in early initiation zones (EIZ) of DNA replication, and the EIZ signals were amplified drastically without RAD21. Our results revealed new mechanistic insights of cohesin's multifaceted roles in establishing transcriptional loops, preserving long-range chromatin interactions for cell-specific genes, and maintaining timely order of DNA replication.
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Affiliation(s)
- Minji Kim
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Present address: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
- Equal contributions
| | - Ping Wang
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Evanston, IL, 60201, USA
- Equal contributions
| | - Patricia A. Clow
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Equal contributions
| | - I (Eli) Chien
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61820, USA
| | - Xiaotao Wang
- Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Reproduction and Development, Shanghai, China
| | - Jianhao Peng
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61820, USA
| | - Haoxi Chai
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Xiyuan Liu
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- State Key Laboratory of Ophthalmology, Optometry and Vision Science, Eye hospital and School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, 325027, P.R. China
| | - Byoungkoo Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Chew Yee Ngan
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Feng Yue
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Evanston, IL, 60201, USA
- Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Olgica Milenkovic
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61820, USA
| | - Jeffrey H. Chuang
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, 06030, USA
| | - Chia-Lin Wei
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Rafael Casellas
- Hematopoietic Biology and Malignancy, MD Anderson Cancer Center, Houston, TX, 77054, USA
| | - Albert W. Cheng
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, 85281, USA
| | - Yijun Ruan
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang Province, 310058, P.R. China
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17
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Patta I, Zand M, Lee L, Mishra S, Bortnick A, Lu H, Prusty A, McArdle S, Mikulski Z, Wang HY, Cheng CS, Fisch KM, Hu M, Murre C. Nuclear morphology is shaped by loop-extrusion programs. Nature 2024; 627:196-203. [PMID: 38355805 PMCID: PMC11052650 DOI: 10.1038/s41586-024-07086-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 01/17/2024] [Indexed: 02/16/2024]
Abstract
It is well established that neutrophils adopt malleable polymorphonuclear shapes to migrate through narrow interstitial tissue spaces1-3. However, how polymorphonuclear structures are assembled remains unknown4. Here we show that in neutrophil progenitors, halting loop extrusion-a motor-powered process that generates DNA loops by pulling in chromatin5-leads to the assembly of polymorphonuclear genomes. Specifically, we found that in mononuclear neutrophil progenitors, acute depletion of the loop-extrusion loading factor nipped-B-like protein (NIPBL) induced the assembly of horseshoe, banded, ringed and hypersegmented nuclear structures and led to a reduction in nuclear volume, mirroring what is observed during the differentiation of neutrophils. Depletion of NIPBL also induced cell-cycle arrest, activated a neutrophil-specific gene program and conditioned a loss of interactions across topologically associating domains to generate a chromatin architecture that resembled that of differentiated neutrophils. Removing NIPBL resulted in enrichment for mega-loops and interchromosomal hubs that contain genes associated with neutrophil-specific enhancer repertoires and an inflammatory gene program. On the basis of these observations, we propose that in neutrophil progenitors, loop-extrusion programs produce lineage-specific chromatin architectures that permit the packing of chromosomes into geometrically confined lobular structures. Our data also provide a blueprint for the assembly of polymorphonuclear structures, and point to the possibility of engineering de novo nuclear shapes to facilitate the migration of effector cells in densely populated tumorigenic environments.
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Affiliation(s)
- Indumathi Patta
- Department of Molecular Biology, University of California, San Diego, La Jolla, CA, USA
| | - Maryam Zand
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Lindsay Lee
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Shreya Mishra
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Alexandra Bortnick
- Department of Molecular Biology, University of California, San Diego, La Jolla, CA, USA
| | - Hanbin Lu
- Department of Molecular Biology, University of California, San Diego, La Jolla, CA, USA
| | - Arpita Prusty
- Department of Molecular Biology, University of California, San Diego, La Jolla, CA, USA
| | - Sara McArdle
- Microscopy and Histology Core Facility, La Jolla Institute for Immunology, La Jolla, CA, USA
| | - Zbigniew Mikulski
- Microscopy and Histology Core Facility, La Jolla Institute for Immunology, La Jolla, CA, USA
| | - Huan-You Wang
- Department of Pathology, University of California, San Diego, La Jolla, CA, USA
| | - Christine S Cheng
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Kathleen M Fisch
- Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Diego, La Jolla, CA, USA.
| | - Ming Hu
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA.
| | - Cornelis Murre
- Department of Molecular Biology, University of California, San Diego, La Jolla, CA, USA.
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18
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Kim YY, Gryder BE, Sinniah R, Peach ML, Shern JF, Abdelmaksoud A, Pomella S, Woldemichael GM, Stanton BZ, Milewski D, Barchi JJ, Schneekloth JS, Chari R, Kowalczyk JT, Shenoy SR, Evans JR, Song YK, Wang C, Wen X, Chou HC, Gangalapudi V, Esposito D, Jones J, Procter L, O'Neill M, Jenkins LM, Tarasova NI, Wei JS, McMahon JB, O'Keefe BR, Hawley RG, Khan J. KDM3B inhibitors disrupt the oncogenic activity of PAX3-FOXO1 in fusion-positive rhabdomyosarcoma. Nat Commun 2024; 15:1703. [PMID: 38402212 PMCID: PMC10894237 DOI: 10.1038/s41467-024-45902-y] [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: 11/21/2022] [Accepted: 02/07/2024] [Indexed: 02/26/2024] Open
Abstract
Fusion-positive rhabdomyosarcoma (FP-RMS) is an aggressive pediatric sarcoma driven primarily by the PAX3-FOXO1 fusion oncogene, for which therapies targeting PAX3-FOXO1 are lacking. Here, we screen 62,643 compounds using an engineered cell line that monitors PAX3-FOXO1 transcriptional activity identifying a hitherto uncharacterized compound, P3FI-63. RNA-seq, ATAC-seq, and docking analyses implicate histone lysine demethylases (KDMs) as its targets. Enzymatic assays confirm the inhibition of multiple KDMs with the highest selectivity for KDM3B. Structural similarity search of P3FI-63 identifies P3FI-90 with improved solubility and potency. Biophysical binding of P3FI-90 to KDM3B is demonstrated using NMR and SPR. P3FI-90 suppresses the growth of FP-RMS in vitro and in vivo through downregulating PAX3-FOXO1 activity, and combined knockdown of KDM3B and KDM1A phenocopies P3FI-90 effects. Thus, we report KDM inhibitors P3FI-63 and P3FI-90 with the highest specificity for KDM3B. Their potent suppression of PAX3-FOXO1 activity indicates a possible therapeutic approach for FP-RMS and other transcriptionally addicted cancers.
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Affiliation(s)
| | - Berkley E Gryder
- Genetics Branch, NCI, NIH, Bethesda, MD, USA
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, USA
| | | | - Megan L Peach
- Basic Science Program, Frederick National Laboratory for Cancer Research (FNLCR), Frederick, MD, USA
| | - Jack F Shern
- Pediatric Oncology Branch, NCI, NIH, Bethesda, MD, USA
| | | | - Silvia Pomella
- Genetics Branch, NCI, NIH, Bethesda, MD, USA
- Department of Hematology and Oncology, Cell and Gene Therapy, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Girma M Woldemichael
- Leidos Biomed Res Inc, FNLCR, Basic Sci Program, Frederick, MD, USA
- Molecular Targets Program, NCI, NIH, Frederick, MD, USA
| | - Benjamin Z Stanton
- Genetics Branch, NCI, NIH, Bethesda, MD, USA
- Nationwide Children's Hospital, Center for Childhood Cancer Research, Columbus, OH, USA
- Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, USA
- Department of Biological Chemistry & Pharmacology, The Ohio State University College of Medicine, Columbus, OH, USA
| | | | | | | | - Raj Chari
- Genome Modification Core, Laboratory Animal Sciences Program, FNLCR, Frederick, MD, USA
| | | | - Shilpa R Shenoy
- Leidos Biomed Res Inc, FNLCR, Basic Sci Program, Frederick, MD, USA
- Molecular Targets Program, NCI, NIH, Frederick, MD, USA
| | - Jason R Evans
- Natural Products Branch, NCI, NIH, Frederick, MD, USA
| | | | - Chaoyu Wang
- Genetics Branch, NCI, NIH, Bethesda, MD, USA
| | - Xinyu Wen
- Genetics Branch, NCI, NIH, Bethesda, MD, USA
| | | | | | | | - Jane Jones
- Protein Expression Laboratory, FNLCR, NIH, Frederick, MD, USA
| | - Lauren Procter
- Protein Expression Laboratory, FNLCR, NIH, Frederick, MD, USA
| | - Maura O'Neill
- Protein Characterization Laboratory, FNLCR, NIH, Frederick, MD, USA
| | | | | | - Jun S Wei
- Genetics Branch, NCI, NIH, Bethesda, MD, USA
| | | | - Barry R O'Keefe
- Molecular Targets Program, NCI, NIH, Frederick, MD, USA
- Natural Products Branch, NCI, NIH, Frederick, MD, USA
| | - Robert G Hawley
- Genetics Branch, NCI, NIH, Bethesda, MD, USA
- Department of Anatomy and Cell Biology, George Washington University, Washington, DC, USA
| | - Javed Khan
- Genetics Branch, NCI, NIH, Bethesda, MD, USA.
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19
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Zhang Y, Cameron CJF, Blanchette M. Posterior inference of Hi-C contact frequency through sampling. FRONTIERS IN BIOINFORMATICS 2024; 3:1285828. [PMID: 38455089 PMCID: PMC10919286 DOI: 10.3389/fbinf.2023.1285828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 12/20/2023] [Indexed: 03/09/2024] Open
Abstract
Hi-C is one of the most widely used approaches to study three-dimensional genome conformations. Contacts captured by a Hi-C experiment are represented in a contact frequency matrix. Due to the limited sequencing depth and other factors, Hi-C contact frequency matrices are only approximations of the true interaction frequencies and are further reported without any quantification of uncertainty. Hence, downstream analyses based on Hi-C contact maps (e.g., TAD and loop annotation) are themselves point estimations. Here, we present the Hi-C interaction frequency sampler (HiCSampler) that reliably infers the posterior distribution of the interaction frequency for a given Hi-C contact map by exploiting dependencies between neighboring loci. Posterior predictive checks demonstrate that HiCSampler can infer highly predictive chromosomal interaction frequency. Summary statistics calculated by HiCSampler provide a measurement of the uncertainty for Hi-C experiments, and samples inferred by HiCSampler are ready for use by most downstream analysis tools off the shelf and permit uncertainty measurements in these analyses without modifications.
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Affiliation(s)
- Yanlin Zhang
- School of Computer Science, McGill University, Montréal, QC, Canada
| | - Christopher J. F. Cameron
- School of Computer Science, McGill University, Montréal, QC, Canada
- Department of Biochemistry and Goodman Cancer Research Center, McGill University, Montreal, QC, Canada
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20
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Wahl N, Espeso-Gil S, Chietera P, Nagel A, Laighneach A, Morris DW, Rajarajan P, Akbarian S, Dechant G, Apostolova G. SATB2 organizes the 3D genome architecture of cognition in cortical neurons. Mol Cell 2024; 84:621-639.e9. [PMID: 38244545 PMCID: PMC10923151 DOI: 10.1016/j.molcel.2023.12.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 10/02/2023] [Accepted: 12/15/2023] [Indexed: 01/22/2024]
Abstract
The DNA-binding protein SATB2 is genetically linked to human intelligence. We studied its influence on the three-dimensional (3D) epigenome by mapping chromatin interactions and accessibility in control versus SATB2-deficient cortical neurons. We find that SATB2 affects the chromatin looping between enhancers and promoters of neuronal-activity-regulated genes, thus influencing their expression. It also alters A/B compartments, topologically associating domains, and frequently interacting regions. Genes linked to SATB2-dependent 3D genome changes are implicated in highly specialized neuronal functions and contribute to cognitive ability and risk for neuropsychiatric and neurodevelopmental disorders. Non-coding DNA regions with a SATB2-dependent structure are enriched for common variants associated with educational attainment, intelligence, and schizophrenia. Our data establish SATB2 as a cell-type-specific 3D genome modulator, which operates both independently and in cooperation with CCCTC-binding factor (CTCF) to set up the chromatin landscape of pyramidal neurons for cognitive processes.
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Affiliation(s)
- Nico Wahl
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria.
| | - Sergio Espeso-Gil
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria; Department of Psychiatry, Friedman Brain Institute, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Paola Chietera
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria
| | - Amelie Nagel
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria
| | - Aodán Laighneach
- Centre for Neuroimaging, Cognition and Genomics (NICOG), School of Biological and Chemical Sciences, University of Galway, Galway, H91 TK33, Ireland
| | - Derek W Morris
- Centre for Neuroimaging, Cognition and Genomics (NICOG), School of Biological and Chemical Sciences, University of Galway, Galway, H91 TK33, Ireland
| | - Prashanth Rajarajan
- Department of Psychiatry, Friedman Brain Institute, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Schahram Akbarian
- Department of Psychiatry, Friedman Brain Institute, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Georg Dechant
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria.
| | - Galina Apostolova
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria.
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21
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Serizay J, Matthey-Doret C, Bignaud A, Baudry L, Koszul R. Orchestrating chromosome conformation capture analysis with Bioconductor. Nat Commun 2024; 15:1072. [PMID: 38316789 PMCID: PMC10844600 DOI: 10.1038/s41467-024-44761-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: 09/02/2023] [Accepted: 12/28/2023] [Indexed: 02/07/2024] Open
Abstract
Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data structures, computational methods and visualization tools available in Bioconductor to investigate Hi-C, micro-C and other 3C-related data, in R. An online book ( https://bioconductor.org/books/OHCA/ ) further provides prospective end users with a number of workflows to process, import, analyze and visualize any type of chromosome conformation capture data.
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Affiliation(s)
- Jacques Serizay
- Institut Pasteur, CNRS UMR3525, Université Paris Cité, Unité Régulation Spatiale des Génomes, Paris, France.
| | - Cyril Matthey-Doret
- Institut Pasteur, CNRS UMR3525, Université Paris Cité, Unité Régulation Spatiale des Génomes, Paris, France
- Sorbonne Université, Collège Doctoral, Paris, France
- Swiss Data Science Center, École Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland
| | - Amaury Bignaud
- Institut Pasteur, CNRS UMR3525, Université Paris Cité, Unité Régulation Spatiale des Génomes, Paris, France
- Sorbonne Université, Collège Doctoral, Paris, France
| | - Lyam Baudry
- Institut Pasteur, CNRS UMR3525, Université Paris Cité, Unité Régulation Spatiale des Génomes, Paris, France
- Sorbonne Université, Collège Doctoral, Paris, France
- Université de Lausanne, Center for Integrative Genomics, Quartier Sorge, 1015, Lausanne, Switzerland
| | - Romain Koszul
- Institut Pasteur, CNRS UMR3525, Université Paris Cité, Unité Régulation Spatiale des Génomes, Paris, France
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22
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Zhang ACY, Rosa A, Sanguinetti G. Bottom-up data integration in polymer models of chromatin organization. Biophys J 2024; 123:184-194. [PMID: 38087781 PMCID: PMC10808044 DOI: 10.1016/j.bpj.2023.12.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 11/20/2023] [Accepted: 12/07/2023] [Indexed: 12/24/2023] Open
Abstract
Cellular functions crucially depend on the precise execution of complex biochemical reactions taking place on the chromatin fiber in the tightly packed environment of the cell nucleus. Despite the availability of large datasets probing this process from multiple angles, bottom-up frameworks that allow the incorporation of the sequence-specific nature of biochemistry in a unified model of 3D chromatin structure remain scarce. Here, we propose Sequence-Enhanced Magnetic Polymer (SEMPER), a novel stochastic polymer model that naturally incorporates observational data about sequence-driven biochemical processes, such as binding of transcription factor proteins, in a 3D model of chromatin structure. We introduce a novel approximate Bayesian algorithm to quantify a posteriori the relative importance of various factors, including the polymeric nature of DNA, in determining chromatin epigenetic state, thus providing a transparent way to generate biological hypotheses. Although accurate prediction of contact frequencies (a problem already extensively studied in the literature) is not our main aim, as a by-product of the inference procedure and without additional input from the genome 3D structure, our model can predict with reasonable accuracy some notable and nontrivial conformational features of chromatin folding within the nucleus. Our work highlights the importance of introducing physically realistic statistical models for predicting chromatin states from epigenetic data and opens the way to a new class of more systematic approaches to interpreting epigenomic data.
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Affiliation(s)
- Alex Chen Yi Zhang
- Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy.
| | - Angelo Rosa
- Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy.
| | - Guido Sanguinetti
- Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy.
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23
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Yu H, Wu D, Shen G, Hu M, Li Y. SnapFISH-IMPUTE: an imputation method for multiplexed DNA FISH data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.12.575427. [PMID: 38293083 PMCID: PMC10827092 DOI: 10.1101/2024.01.12.575427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Chromatin spatial organization plays a crucial role in gene regulation. Recently developed and prospering multiplexed DNA FISH technologies enable direct visualization of chromatin conformation in nucleus. However, incomplete data caused by limited detection efficiency can substantially complicate and impair downstream analysis. Here, we present SnapFISH-IMPUTE that imputes missing values in multiplexed DNA FISH data. Analysis on multiple published datasets shows that the proposed method preserves the distribution of pairwise distances between imaging loci, and the imputed chromatin conformations are indistinguishable from the observed conformations. Additionally, imputation greatly improves downstream analyses such as identifying enhancer-promoter loops and clustering cells into distinct cell types. SnapFISH-IMPUTE is freely available at https://github.com/hyuyu104/SnapFISH-IMPUTE.
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Affiliation(s)
- Hongyu Yu
- Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Daiqing Wu
- Department of Mathematics, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Guning Shen
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
- Department of Biology, University of North Carolina, Chapel Hill, NC, USA
| | - Ming Hu
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Yun Li
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
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24
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Hua D, Gu M, Zhang X, Du Y, Xie H, Qi L, Du X, Bai Z, Zhu X, Tian D. DiffDomain enables identification of structurally reorganized topologically associating domains. Nat Commun 2024; 15:502. [PMID: 38218905 PMCID: PMC10787792 DOI: 10.1038/s41467-024-44782-6] [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: 12/16/2022] [Accepted: 01/02/2024] [Indexed: 01/15/2024] Open
Abstract
Topologically associating domains (TADs) are critical structural units in three-dimensional genome organization of mammalian genome. Dynamic reorganizations of TADs between health and disease states are associated with essential genome functions. However, computational methods for identifying reorganized TADs are still in the early stages of development. Here, we present DiffDomain, an algorithm leveraging high-dimensional random matrix theory to identify structurally reorganized TADs using high-throughput chromosome conformation capture (Hi-C) contact maps. Method comparison using multiple real Hi-C datasets reveals that DiffDomain outperforms alternative methods for false positive rates, true positive rates, and identifying a new subtype of reorganized TADs. Applying DiffDomain to Hi-C data from different cell types and disease states demonstrates its biological relevance. Identified reorganized TADs are associated with structural variations and epigenomic changes such as changes in CTCF binding sites. By applying to a single-cell Hi-C data from mouse neuronal development, DiffDomain can identify reorganized TADs between cell types with reasonable reproducibility using pseudo-bulk Hi-C data from as few as 100 cells per condition. Moreover, DiffDomain reveals differential cell-to-population variability and heterogeneous cell-to-cell variability in TADs. Therefore, DiffDomain is a statistically sound method for better comparative analysis of TADs using both Hi-C and single-cell Hi-C data.
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Affiliation(s)
- Dunming Hua
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 510275, China
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Ming Gu
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 510275, China
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Xiao Zhang
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 510275, China
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Yanyi Du
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 510275, China
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Hangcheng Xie
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 510275, China
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Li Qi
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Xiangjun Du
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 510275, China
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Zhidong Bai
- KLASMOE & School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, 130024, China
| | - Xiaopeng Zhu
- MyCellome LLC., Allison Park, PA, 15101, USA
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, 15213, USA
| | - Dechao Tian
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 510275, China.
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China.
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25
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Abbas A, Chandratre K, Gao Y, Yuan J, Zhang MQ, Mani RS. ChIPr: accurate prediction of cohesin-mediated 3D genome organization from 2D chromatin features. Genome Biol 2024; 25:15. [PMID: 38217027 PMCID: PMC10785520 DOI: 10.1186/s13059-023-03158-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 12/22/2023] [Indexed: 01/14/2024] Open
Abstract
The three-dimensional genome organization influences diverse nuclear processes. Here we present Chromatin Interaction Predictor (ChIPr), a suite of regression models based on deep neural networks, random forest, and gradient boosting to predict cohesin-mediated chromatin interaction strength between any two loci in the genome. The predictions of ChIPr correlate well with ChIA-PET data in four cell lines. The standard ChIPr model requires three experimental inputs: ChIP-Seq signals for RAD21, H3K27ac, and H3K27me3 but works well with just RAD21 signal. Integrative analysis reveals novel insights into the role of CTCF motif, its orientation, and CTCF binding on cohesin-mediated chromatin interactions.
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Affiliation(s)
- Ahmed Abbas
- Department of Pathology, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Khyati Chandratre
- Department of Biological Sciences, Center for Systems Biology, The University of Texas at Dallas, Richardson, TX, 75080, USA
| | - Yunpeng Gao
- Department of Pathology, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Jiapei Yuan
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, 300020, China
| | - Michael Q Zhang
- Department of Biological Sciences, Center for Systems Biology, The University of Texas at Dallas, Richardson, TX, 75080, USA.
| | - Ram S Mani
- Department of Pathology, UT Southwestern Medical Center, Dallas, TX, 75390, USA.
- Department of Urology, UT Southwestern Medical Center, Dallas, TX, 75390, USA.
- Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX, 75390, USA.
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26
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Qu Z, Batz Z, Singh N, Marchal C, Swaroop A. Stage-specific dynamic reorganization of genome topology shapes transcriptional neighborhoods in developing human retinal organoids. Cell Rep 2023; 42:113543. [PMID: 38048222 PMCID: PMC10790351 DOI: 10.1016/j.celrep.2023.113543] [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: 05/12/2023] [Revised: 09/21/2023] [Accepted: 11/17/2023] [Indexed: 12/06/2023] Open
Abstract
We have generated a high-resolution Hi-C map of developing human retinal organoids to elucidate spatiotemporal dynamics of genomic architecture and its relationship with gene expression patterns. We demonstrate progressive stage-specific alterations in DNA topology and correlate these changes with transcription of cell-type-restricted gene markers during retinal differentiation. Temporal Hi-C reveals a shift toward A compartment for protein-coding genes and B compartment for non-coding RNAs, displaying high and low expression, respectively. Notably, retina-enriched genes are clustered near lost boundaries of topologically associated domains (TADs), and higher-order assemblages (i.e., TAD cliques) localize in active chromatin regions with binding sites for eye-field transcription factors. These genes gain chromatin contacts at their transcription start site as organoid differentiation proceeds. Our study provides a global view of chromatin architecture dynamics associated with diversification of cell types during retinal development and serves as a foundational resource for in-depth functional investigations of retinal developmental traits.
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Affiliation(s)
- Zepeng Qu
- Neurobiology, Neurodegeneration, and Repair Laboratory, National Eye Institute, National Institutes of Health, MSC0610, 6 Center Drive, Bethesda, MD 20892, USA
| | - Zachary Batz
- Neurobiology, Neurodegeneration, and Repair Laboratory, National Eye Institute, National Institutes of Health, MSC0610, 6 Center Drive, Bethesda, MD 20892, USA
| | - Nivedita Singh
- Neurobiology, Neurodegeneration, and Repair Laboratory, National Eye Institute, National Institutes of Health, MSC0610, 6 Center Drive, Bethesda, MD 20892, USA
| | - Claire Marchal
- Neurobiology, Neurodegeneration, and Repair Laboratory, National Eye Institute, National Institutes of Health, MSC0610, 6 Center Drive, Bethesda, MD 20892, USA; In silichrom Ltd, 15 Digby Road, Newbury RG14 1TS, UK
| | - Anand Swaroop
- Neurobiology, Neurodegeneration, and Repair Laboratory, National Eye Institute, National Institutes of Health, MSC0610, 6 Center Drive, Bethesda, MD 20892, USA.
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27
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He J, Yan A, Chen B, Huang J, Kee K. 3D genome remodeling and homologous pairing during meiotic prophase of mouse oogenesis and spermatogenesis. Dev Cell 2023; 58:3009-3027.e6. [PMID: 37963468 DOI: 10.1016/j.devcel.2023.10.009] [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: 04/02/2023] [Revised: 08/29/2023] [Accepted: 10/23/2023] [Indexed: 11/16/2023]
Abstract
During meiosis, the chromatin and transcriptome undergo prominent switches. Although recent studies have explored the genome reorganization during spermatogenesis, the chromatin remodeling in oogenesis and characteristics of homologous pairing remain largely elusive. We comprehensively compared chromatin structures and transcriptomes at successive substages of meiotic prophase in both female and male mice using low-input high-through chromosome conformation capture (Hi-C) and RNA sequencing (RNA-seq). Compartments and topologically associating domains (TADs) gradually disappeared and slowly recovered in both sexes. We found that homologs adopted different sex-conserved pairing strategies prior to and after the leptotene-to-zygotene transition, changing from long interspersed nuclear element (LINE)-enriched compartments B to short interspersed nuclear element (SINE)-enriched compartments A. We complemented marker genes and predicted the sex-specific meiotic sterile genes for each substage. This study provides valuable insights into the similarities and distinctions between sexes in chromosome architecture, homologous pairing, and transcriptome during meiotic prophase of both oogenesis and spermatogenesis.
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Affiliation(s)
- Jing He
- The State Key Laboratory for Complex, Severe, and Rare Diseases, Center for Stem Cell Biology and Regenerative Medicine, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing, China; SXMU-Tsinghua Collaborative Innovation Center for Frontier Medicine, School of Medicine, Tsinghua University, Beijing, China
| | - An Yan
- The State Key Laboratory for Complex, Severe, and Rare Diseases, Center for Stem Cell Biology and Regenerative Medicine, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing, China; SXMU-Tsinghua Collaborative Innovation Center for Frontier Medicine, School of Medicine, Tsinghua University, Beijing, China
| | - Bo Chen
- The State Key Laboratory for Complex, Severe, and Rare Diseases, Center for Stem Cell Biology and Regenerative Medicine, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing, China; SXMU-Tsinghua Collaborative Innovation Center for Frontier Medicine, School of Medicine, Tsinghua University, Beijing, China
| | - Jiahui Huang
- The State Key Laboratory for Complex, Severe, and Rare Diseases, Center for Stem Cell Biology and Regenerative Medicine, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing, China; SXMU-Tsinghua Collaborative Innovation Center for Frontier Medicine, School of Medicine, Tsinghua University, Beijing, China
| | - Kehkooi Kee
- The State Key Laboratory for Complex, Severe, and Rare Diseases, Center for Stem Cell Biology and Regenerative Medicine, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing, China; SXMU-Tsinghua Collaborative Innovation Center for Frontier Medicine, School of Medicine, Tsinghua University, Beijing, China.
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28
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Noack F, Vangelisti S, Ditzer N, Chong F, Albert M, Bonev B. Joint epigenome profiling reveals cell-type-specific gene regulatory programmes in human cortical organoids. Nat Cell Biol 2023; 25:1873-1883. [PMID: 37996647 PMCID: PMC10709149 DOI: 10.1038/s41556-023-01296-5] [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: 09/20/2022] [Accepted: 10/17/2023] [Indexed: 11/25/2023]
Abstract
Gene expression is regulated by multiple epigenetic mechanisms, which are coordinated in development and disease. However, current multiomics methods are frequently limited to one or two modalities at a time, making it challenging to obtain a comprehensive gene regulatory signature. Here, we describe a method-3D genome, RNA, accessibility and methylation sequencing (3DRAM-seq)-that simultaneously interrogates spatial genome organization, chromatin accessibility and DNA methylation genome-wide and at high resolution. We combine 3DRAM-seq with immunoFACS and RNA sequencing in cortical organoids to map the cell-type-specific regulatory landscape of human neural development across multiple epigenetic layers. Finally, we apply a massively parallel reporter assay to profile cell-type-specific enhancer activity in organoids and to functionally assess the role of key transcription factors for human enhancer activation and function. More broadly, 3DRAM-seq can be used to profile the multimodal epigenetic landscape in rare cell types and different tissues.
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Affiliation(s)
- Florian Noack
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany
| | - Silvia Vangelisti
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany
| | - Nora Ditzer
- Center for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany
| | - Faye Chong
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany
| | - Mareike Albert
- Center for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany
| | - Boyan Bonev
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany.
- Physiological Genomics, Biomedical Center, Ludwig-Maximilians-Universität München, Munich, Germany.
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29
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Rossini R, Oshaghi M, Nekrasov M, Bellanger A, Domaschenz R, Dijkwel Y, Abdelhalim M, Collas P, Tremethick D, Paulsen J. Multi-level 3D genome organization deteriorates during breast cancer progression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.26.568711. [PMID: 38076897 PMCID: PMC10705249 DOI: 10.1101/2023.11.26.568711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Breast cancer entails intricate alterations in genome organization and expression. However, how three-dimensional (3D) chromatin structure changes in the progression from a normal to a breast cancer malignant state remains unknown. To address this, we conducted an analysis combining Hi-C data with lamina-associated domains (LADs), epigenomic marks, and gene expression in an in vitro model of breast cancer progression. Our results reveal that while the fundamental properties of topologically associating domains (TADs) remain largely stable, significant changes occur in the organization of compartments and subcompartments. These changes are closely correlated with alterations in the expression of oncogenic genes. We also observe a restructuring of TAD-TAD interactions, coinciding with a loss of spatial compartmentalization and radial positioning of the 3D genome. Notably, we identify a previously unrecognized interchromosomal insertion event, wherein a locus on chromosome 8 housing the MYC oncogene is inserted into a highly active subcompartment on chromosome 10. This insertion leads to the formation of de novo enhancer contacts and activation of the oncogene, illustrating how structural variants can interact with the 3D genome to drive oncogenic states. In summary, our findings provide evidence for the degradation of genome organization at multiple scales during breast cancer progression revealing novel relationships between genome 3D structure and oncogenic processes.
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Affiliation(s)
- Roberto Rossini
- Department of Biosciences, Faculty of Mathematics and Natural Sciences, University of Oslo, 0316 Oslo, Norway
| | - Mohammadsaleh Oshaghi
- Department of Biosciences, Faculty of Mathematics and Natural Sciences, University of Oslo, 0316 Oslo, Norway
| | - Maxim Nekrasov
- Department of Genome Sciences, The John Curtin School of Medical Research, The Australian National University, Canberra, Australian Capital Territory, Australia
| | - Aurélie Bellanger
- Department of Molecular Medicine, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, 0317 Oslo, Norway
| | - Renae Domaschenz
- Department of Genome Sciences, The John Curtin School of Medical Research, The Australian National University, Canberra, Australian Capital Territory, Australia
| | - Yasmin Dijkwel
- Department of Genome Sciences, The John Curtin School of Medical Research, The Australian National University, Canberra, Australian Capital Territory, Australia
| | - Mohamed Abdelhalim
- Department of Molecular Medicine, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, 0317 Oslo, Norway
| | - Philippe Collas
- Department of Molecular Medicine, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, 0317 Oslo, Norway
- Department of Immunology and Transfusion Medicine, Oslo University Hospital, 0424 Oslo, Norway
| | - David Tremethick
- Department of Genome Sciences, The John Curtin School of Medical Research, The Australian National University, Canberra, Australian Capital Territory, Australia
| | - Jonas Paulsen
- Department of Biosciences, Faculty of Mathematics and Natural Sciences, University of Oslo, 0316 Oslo, Norway
- Centre for Bioinformatics, Department of Informatics, University of Oslo, 0316 Oslo, Norway
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30
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Roth C, Venu V, Job V, Lubbers N, Sanbonmatsu KY, Steadman CR, Starkenburg SR. Improved quality metrics for association and reproducibility in chromatin accessibility data using mutual information. BMC Bioinformatics 2023; 24:441. [PMID: 37990143 PMCID: PMC10664258 DOI: 10.1186/s12859-023-05553-0] [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: 06/13/2023] [Accepted: 10/30/2023] [Indexed: 11/23/2023] Open
Abstract
BACKGROUND Correlation metrics are widely utilized in genomics analysis and often implemented with little regard to assumptions of normality, homoscedasticity, and independence of values. This is especially true when comparing values between replicated sequencing experiments that probe chromatin accessibility, such as assays for transposase-accessible chromatin via sequencing (ATAC-seq). Such data can possess several regions across the human genome with little to no sequencing depth and are thus non-normal with a large portion of zero values. Despite distributed use in the epigenomics field, few studies have evaluated and benchmarked how correlation and association statistics behave across ATAC-seq experiments with known differences or the effects of removing specific outliers from the data. Here, we developed a computational simulation of ATAC-seq data to elucidate the behavior of correlation statistics and to compare their accuracy under set conditions of reproducibility. RESULTS Using these simulations, we monitored the behavior of several correlation statistics, including the Pearson's R and Spearman's [Formula: see text] coefficients as well as Kendall's [Formula: see text] and Top-Down correlation. We also test the behavior of association measures, including the coefficient of determination R[Formula: see text], Kendall's W, and normalized mutual information. Our experiments reveal an insensitivity of most statistics, including Spearman's [Formula: see text], Kendall's [Formula: see text], and Kendall's W, to increasing differences between simulated ATAC-seq replicates. The removal of co-zeros (regions lacking mapped sequenced reads) between simulated experiments greatly improves the estimates of correlation and association. After removing co-zeros, the R[Formula: see text] coefficient and normalized mutual information display the best performance, having a closer one-to-one relationship with the known portion of shared, enhanced loci between simulated replicates. When comparing values between experimental ATAC-seq data using a random forest model, mutual information best predicts ATAC-seq replicate relationships. CONCLUSIONS Collectively, this study demonstrates how measures of correlation and association can behave in epigenomics experiments. We provide improved strategies for quantifying relationships in these increasingly prevalent and important chromatin accessibility assays.
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Affiliation(s)
- Cullen Roth
- Los Alamos National Laboratory, Genomics and Bioanalytics, Los Alamos, NM, USA.
| | - Vrinda Venu
- Los Alamos National Laboratory, Climate, Ecosystems, and Environmental Science, Los Alamos, NM, USA
| | - Vanessa Job
- Los Alamos National Laboratory, High Performance Computing and Design, Los Alamos, NM, USA
| | - Nicholas Lubbers
- Los Alamos National Laboratory, Information Sciences, Los Alamos, NM, USA
| | - Karissa Y Sanbonmatsu
- Los Alamos National Laboratory, Theoretical Biology and Biophysics, Los Alamos, NM, USA
| | - Christina R Steadman
- Los Alamos National Laboratory, Climate, Ecosystems, and Environmental Science, Los Alamos, NM, USA
| | - Shawn R Starkenburg
- Los Alamos National Laboratory, Genomics and Bioanalytics, Los Alamos, NM, USA
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31
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Hu Y, Salgado Figueroa D, Zhang Z, Veselits M, Bhattacharyya S, Kashiwagi M, Clark MR, Morgan BA, Ay F, Georgopoulos K. Lineage-specific 3D genome organization is assembled at multiple scales by IKAROS. Cell 2023; 186:5269-5289.e22. [PMID: 37995656 PMCID: PMC10895928 DOI: 10.1016/j.cell.2023.10.023] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 07/28/2023] [Accepted: 10/25/2023] [Indexed: 11/25/2023]
Abstract
A generic level of chromatin organization generated by the interplay between cohesin and CTCF suffices to limit promiscuous interactions between regulatory elements, but a lineage-specific chromatin assembly that supersedes these constraints is required to configure the genome to guide gene expression changes that drive faithful lineage progression. Loss-of-function approaches in B cell precursors show that IKAROS assembles interactions across megabase distances in preparation for lymphoid development. Interactions emanating from IKAROS-bound enhancers override CTCF-imposed boundaries to assemble lineage-specific regulatory units built on a backbone of smaller invariant topological domains. Gain of function in epithelial cells confirms IKAROS' ability to reconfigure chromatin architecture at multiple scales. Although the compaction of the Igκ locus required for genome editing represents a function of IKAROS unique to lymphocytes, the more general function to preconfigure the genome to support lineage-specific gene expression and suppress activation of extra-lineage genes provides a paradigm for lineage restriction.
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Affiliation(s)
- Yeguang Hu
- Cutaneous Biology Research Center, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | - Daniela Salgado Figueroa
- Centers for Autoimmunity, Inflammation and Cancer Immunotherapy, La Jolla Institute for Immunology, La Jolla, CA 92037, USA; Bioinformatics and Systems Biology Program, La Jolla, CA, USA
| | - Zhihong Zhang
- Cutaneous Biology Research Center, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | - Margaret Veselits
- Gwen Knapp Center for Lupus and Immunology Research, Section of Rheumatology, Department of Medicine, The University of Chicago, Chicago, IL 60637, USA
| | - Sourya Bhattacharyya
- Centers for Autoimmunity, Inflammation and Cancer Immunotherapy, La Jolla Institute for Immunology, La Jolla, CA 92037, USA
| | - Mariko Kashiwagi
- Cutaneous Biology Research Center, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | - Marcus R Clark
- Gwen Knapp Center for Lupus and Immunology Research, Section of Rheumatology, Department of Medicine, The University of Chicago, Chicago, IL 60637, USA
| | - Bruce A Morgan
- Cutaneous Biology Research Center, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, 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, La Jolla, CA, USA; Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA.
| | - Katia Georgopoulos
- Cutaneous Biology Research Center, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA.
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32
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Wang M, He B, Hao Y, Srinivasan D, Shrinet J, Fraser P. Cellular reprogramming is driven by widespread rewiring of promoter-enhancer interactions. BMC Biol 2023; 21:264. [PMID: 37981682 PMCID: PMC10658794 DOI: 10.1186/s12915-023-01766-0] [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: 04/17/2023] [Accepted: 11/09/2023] [Indexed: 11/21/2023] Open
Abstract
BACKGROUND Long-range interactions between promoters and cis-regulatory elements, such as enhancers, play critical roles in gene regulation. However, the role of three-dimensional (3D) chromatin structure in orchestrating changes in transcriptional regulation during direct cell reprogramming is not fully understood. RESULTS Here, we performed integrated analyses of chromosomal architecture, epigenetics, and gene expression using Hi-C, promoter Capture Hi-C (PCHi-C), ChIP-seq, and RNA-seq during trans-differentiation of Pre-B cells into macrophages with a β-estradiol inducible C/EBPαER transgene. Within 1h of β-estradiol induction, C/EBPα translocated from the cytoplasm to the nucleus, binding to thousands of promoters and putative regulatory elements, resulting in the downregulation of Pre-B cell-specific genes and induction of macrophage-specific genes. Hi-C results were remarkably consistent throughout trans-differentiation, revealing only a small number of TAD boundary location changes, and A/B compartment switches despite significant changes in the expression of thousands of genes. PCHi-C revealed widespread changes in promoter-anchored loops with decreased interactions in parallel with decreased gene expression, and new and increased promoter-anchored interactions in parallel with increased expression of macrophage-specific genes. CONCLUSIONS Overall, our data demonstrate that C/EBPα-induced trans-differentiation involves few changes in genome architecture at the level of TADs and A/B compartments, in contrast with widespread reorganization of thousands of promoter-anchored loops in association with changes in gene expression and cell identity.
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Affiliation(s)
- Miao Wang
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Bing He
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Yueling Hao
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Divyaa Srinivasan
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Jatin Shrinet
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Peter Fraser
- Department of Biological Science, Florida State University, Tallahassee, FL, USA.
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Zhao H, Lin Y, Lin E, Liu F, Shu L, Jing D, Wang B, Wang M, Shan F, Zhang L, Lam JC, Midla SC, Giardine BM, Keller CA, Hardison RC, Blobel GA, Zhang H. Genome folding principles revealed in condensin-depleted mitotic chromosomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.09.566494. [PMID: 38014261 PMCID: PMC10680603 DOI: 10.1101/2023.11.09.566494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
During mitosis, condensin activity interferes with interphase chromatin structures. Here, we generated condensin-free mitotic chromosomes to investigate genome folding principles. Co- depletion of condensin I and II, but neither alone, triggered mitotic chromosome compartmentalization in ways that differ from interphase. Two distinct euchromatic compartments, indistinguishable in interphase, rapidly emerged upon condensin loss with different interaction preferences and dependence on H3K27ac. Constitutive heterochromatin gradually self-aggregated and co-compartmentalized with the facultative heterochromatin, contrasting with their separation during interphase. While topologically associating domains (TADs) and CTCF/cohesin mediated structural loops remained undetectable, cis-regulatory element contacts became apparent, providing an explanation for their quick re-establishment during mitotic exit. HP1 proteins, which are thought to partition constitutive heterochromatin, were absent from mitotic chromosomes, suggesting, surprisingly, that constitutive heterochromatin can self-aggregate without HP1. Indeed, in cells traversing from M- to G1-phase in the combined absence of HP1α, HP1Π and HP1γ, re-established constitutive heterochromatin compartments normally. In sum, "clean-slate" condensin-deficient mitotic chromosomes illuminate mechanisms of genome compartmentalization not revealed in interphase cells.
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Rahman S, Dong P, Apontes P, Fernando M, Kosoy R, Townsley KG, Girdhar K, Bendl J, Shao Z, Misir R, Tsankova N, Kleopoulos S, Brennand K, Fullard J, Roussos P. Lineage specific 3D genome structure in the adult human brain and neurodevelopmental changes in the chromatin interactome. Nucleic Acids Res 2023; 51:11142-11161. [PMID: 37811875 PMCID: PMC10639075 DOI: 10.1093/nar/gkad798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 08/18/2023] [Accepted: 09/19/2023] [Indexed: 10/10/2023] Open
Abstract
The human brain is a complex organ comprised of distinct cell types, and the contribution of the 3D genome to lineage specific gene expression remains poorly understood. To decipher cell type specific genome architecture, and characterize fine scale changes in the chromatin interactome across neural development, we compared the 3D genome of the human fetal cortical plate to that of neurons and glia isolated from the adult prefrontal cortex. We found that neurons have weaker genome compartmentalization compared to glia, but stronger TADs, which emerge during fetal development. Furthermore, relative to glia, the neuronal genome shifts more strongly towards repressive compartments. Neurons have differential TAD boundaries that are proximal to active promoters involved in neurodevelopmental processes. CRISPRi on CNTNAP2 in hIPSC-derived neurons reveals that transcriptional inactivation correlates with loss of insulation at the differential boundary. Finally, re-wiring of chromatin loops during neural development is associated with transcriptional and functional changes. Importantly, differential loops in the fetal cortex are associated with autism GWAS loci, suggesting a neuropsychiatric disease mechanism affecting the chromatin interactome. Furthermore, neural development involves gaining enhancer-promoter loops that upregulate genes that control synaptic activity. Altogether, our study provides multi-scale insights on the 3D genome in the human brain.
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Affiliation(s)
- Samir Rahman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Pengfei Dong
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Pasha Apontes
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Michael B Fernando
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Roman Kosoy
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kayla G Townsley
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kiran Girdhar
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Zhiping Shao
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ruth Misir
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Nadia Tsankova
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Pathology, Molecular, and Cell-based Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Steven P Kleopoulos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kristen J Brennand
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY 10468, USA
- Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
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35
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Milevskiy MJ, Coughlan HD, Kane SR, Johanson TM, Kordafshari S, Chan WF, Tsai M, Surgenor E, Wilcox S, Allan RS, Chen Y, Lindeman GJ, Smyth GK, Visvader JE. Three-dimensional genome architecture coordinates key regulators of lineage specification in mammary epithelial cells. CELL GENOMICS 2023; 3:100424. [PMID: 38020976 PMCID: PMC10667557 DOI: 10.1016/j.xgen.2023.100424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 06/20/2023] [Accepted: 09/20/2023] [Indexed: 12/01/2023]
Abstract
Although lineage-specific genes have been identified in the mammary gland, little is known about the contribution of the 3D genome organization to gene regulation in the epithelium. Here, we describe the chromatin landscape of the three major epithelial subsets through integration of long- and short-range chromatin interactions, accessibility, histone modifications, and gene expression. While basal genes display exquisite lineage specificity via distal enhancers, luminal-specific genes show widespread promoter priming in basal cells. Cell specificity in luminal progenitors is largely mediated through extensive chromatin interactions with super-enhancers in gene-body regions in addition to interactions with polycomb silencer elements. Moreover, lineage-specific transcription factors appear to be controlled through cell-specific chromatin interactivity. Finally, chromatin accessibility rather than interactivity emerged as a defining feature of the activation of quiescent basal stem cells. This work provides a comprehensive resource for understanding the role of higher-order chromatin interactions in cell-fate specification and differentiation in the adult mouse mammary gland.
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Affiliation(s)
- Michael J.G. Milevskiy
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Hannah D. Coughlan
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Serena R. Kane
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Timothy M. Johanson
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
- Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Somayeh Kordafshari
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Wing Fuk Chan
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
- Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Minhsuang Tsai
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Elliot Surgenor
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Stephen Wilcox
- Advanced Technology and Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Rhys S. Allan
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
- Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Yunshun Chen
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Geoffrey J. Lindeman
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC 3010, Australia
- Parkville Familial Cancer Centre and Department of Medical Oncology, The Royal Melbourne Hospital and Peter MacCallum Cancer Centre, Parkville, VIC 3050, Australia
| | - Gordon K. Smyth
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- School of Mathematics and Statistics, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Jane E. Visvader
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
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36
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Kuang S, Pollard KS. Exploring the Roles of RNAs in Chromatin Architecture Using Deep Learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.22.563498. [PMID: 37961712 PMCID: PMC10634726 DOI: 10.1101/2023.10.22.563498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Recent studies have highlighted the impact of both transcription and transcripts on 3D genome organization, particularly its dynamics. Here, we propose a deep learning framework, called AkitaR, that leverages both genome sequences and genome-wide RNA-DNA interactions to investigate the roles of chromatin-associated RNAs (caRNAs) on genome folding in HFFc6 cells. In order to disentangle the cis- and trans-regulatory roles of caRNAs, we compared models with nascent transcripts, trans-located caRNAs, open chromatin data, or DNA sequence alone. Both nascent transcripts and trans-located caRNAs improved the models' predictions, especially at cell-type-specific genomic regions. Analyses of feature importance scores revealed the contribution of caRNAs at TAD boundaries, chromatin loops and nuclear sub-structures such as nuclear speckles and nucleoli to the models' predictions. Furthermore, we identified non-coding RNAs (ncRNAs) known to regulate chromatin structures, such as MALAT1 and NEAT1, as well as several novel RNAs, RNY5, RPPH1, POLG-DT and THBS1-IT, that might modulate chromatin architecture through trans-interactions in HFFc6. Our modeling also suggests that transcripts from Alus and other repetitive elements may facilitate chromatin interactions through trans R-loop formation. Our findings provide new insights and generate testable hypotheses about the roles of caRNAs in shaping chromatin organization.
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Affiliation(s)
- Shuzhen Kuang
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA
| | - Katherine S. Pollard
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
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37
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Zhao S, Li Y, Chen G, Wang X, Chen N, Wu X. Genome-wide chromatin interaction profiling reveals a vital role of super-enhancers and rearrangements in host enhancer contacts during BmNPV infection. Genome Res 2023; 33:gr.277931.123. [PMID: 37871969 PMCID: PMC10760458 DOI: 10.1101/gr.277931.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 10/14/2023] [Indexed: 10/25/2023]
Abstract
As influential regulatory elements in the genome, enhancers control gene expression under specific cellular conditions, and such connections are dynamic under different conditions. However, because of the lack of a genome-wide enhancer-gene connection map, the roles and regulatory pattern of enhancers were poorly investigated in insects, and the dynamic changes of enhancer contacts and functions under different conditions remain elusive. Here, combining Hi-C, ATAC-seq, and H3K27ac ChIP-seq data, we generate the genome-wide enhancer-gene map of silkworm and identify super-enhancers with a role in regulating the expression of vital genes related to cell state maintenance through a sophisticated interaction network. Additionally, a radical attenuation of chromatin interactions is found after infection of Bombyx mori nucleopolyhedrovirus (BmNPV), the main pathogen of silkworm, which directly rearranges the enhancer contacts. Such a rearrangement disturbs the intrinsic enhancer-gene connections in several antiviral genes, resulting in reduced expression of these genes, which accelerates viral infection. Overall, our results reveal the regulatory role of super-enhancers and shed new light on the mechanisms and dynamic changes of the genome-wide enhancer regulatory network.
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Affiliation(s)
- Shudi Zhao
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Silkworm and Bee Resource Utilization and Innovation of Zhejiang Province, Hangzhou 310058, China
| | - Yuedong Li
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Silkworm and Bee Resource Utilization and Innovation of Zhejiang Province, Hangzhou 310058, China
| | - Guanping Chen
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Silkworm and Bee Resource Utilization and Innovation of Zhejiang Province, Hangzhou 310058, China
| | - Xingyang Wang
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Silkworm and Bee Resource Utilization and Innovation of Zhejiang Province, Hangzhou 310058, China
| | - Nan Chen
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Silkworm and Bee Resource Utilization and Innovation of Zhejiang Province, Hangzhou 310058, China
| | - Xiaofeng Wu
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China;
- Key Laboratory of Silkworm and Bee Resource Utilization and Innovation of Zhejiang Province, Hangzhou 310058, China
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Zhou Y, Li T, Choppavarapu L, Jin VX. Integration of scHi-C and scRNA-seq data defines distinct 3D-regulated and biological-context dependent cell subpopulations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.29.560193. [PMID: 37873257 PMCID: PMC10592853 DOI: 10.1101/2023.09.29.560193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
An integration of 3D chromatin structure and gene expression at single-cell resolution has yet been demonstrated. Here, we develop a computational method, a multiomic data integration (MUDI) algorithm, which integrates scHi-C and scRNA-seq data to precisely define the 3D-regulated and biological-context dependent cell subpopulations or topologically integrated subpopulations (TISPs). We demonstrate its algorithmic utility on the publicly available and newly generated scHi-C and scRNA-seq data. We then test and apply MUDI in a breast cancer cell model system to demonstrate its biological-context dependent utility. We found the newly defined topologically conserved associating domain (CAD) is the characteristic single-cell 3D chromatin structure and better characterizes chromatin domains in single-cell resolution. We further identify 20 TISPs uniquely characterizing 3D-regulated breast cancer cellular states. We reveal two of TISPs are remarkably resemble to high cycling breast cancer persister cells and chromatin modifying enzymes might be functional regulators to drive the alteration of the 3D chromatin structures. Our comprehensive integration of scHi-C and scRNA-seq data in cancer cells at single-cell resolution provides mechanistic insights into 3D-regulated heterogeneity of developing drug-tolerant cancer cells.
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Liu T, Wang Z. HiC4D: forecasting spatiotemporal Hi-C data with residual ConvLSTM. Brief Bioinform 2023; 24:bbad263. [PMID: 37478379 PMCID: PMC10516390 DOI: 10.1093/bib/bbad263] [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: 02/09/2023] [Revised: 06/12/2023] [Accepted: 06/28/2023] [Indexed: 07/23/2023] Open
Abstract
The Hi-C experiments have been extensively used for the studies of genomic structures. In the last few years, spatiotemporal Hi-C has largely contributed to the investigation of genome dynamic reorganization. However, computationally modeling and forecasting spatiotemporal Hi-C data still have not been seen in the literature. We present HiC4D for dealing with the problem of forecasting spatiotemporal Hi-C data. We designed and benchmarked a novel network and named it residual ConvLSTM (ResConvLSTM), which is a combination of residual network and convolutional long short-term memory (ConvLSTM). We evaluated our new ResConvLSTM networks and compared them with the other five methods, including a naïve network (NaiveNet) that we designed as a baseline method and four outstanding video-prediction methods from the literature: ConvLSTM, spatiotemporal LSTM (ST-LSTM), self-attention LSTM (SA-LSTM) and simple video prediction (SimVP). We used eight different spatiotemporal Hi-C datasets for the blind test, including two from mouse embryogenesis, one from somatic cell nuclear transfer (SCNT) embryos, three embryogenesis datasets from different species and two non-embryogenesis datasets. Our evaluation results indicate that our ResConvLSTM networks almost always outperform the other methods on the eight blind-test datasets in terms of accurately predicting the Hi-C contact matrices at future time-steps. Our benchmarks also indicate that all of the methods that we benchmarked can successfully recover the boundaries of topologically associating domains called on the experimental Hi-C contact matrices. Taken together, our benchmarks suggest that HiC4D is an effective tool for predicting spatiotemporal Hi-C data. HiC4D is publicly available at both http://dna.cs.miami.edu/HiC4D/ and https://github.com/zwang-bioinformatics/HiC4D/.
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Affiliation(s)
- Tong Liu
- Department of Computer Science, University of Miami, 1365 Memorial Drive, 33124, FL, USA
| | - Zheng Wang
- Department of Computer Science, University of Miami, 1365 Memorial Drive, 33124, FL, USA
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40
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Nakato R, Sakata T, Wang J, Nagai LAE, Nagaoka Y, Oba GM, Bando M, Shirahige K. Context-dependent perturbations in chromatin folding and the transcriptome by cohesin and related factors. Nat Commun 2023; 14:5647. [PMID: 37726281 PMCID: PMC10509244 DOI: 10.1038/s41467-023-41316-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 08/29/2023] [Indexed: 09/21/2023] Open
Abstract
Cohesin regulates gene expression through context-specific chromatin folding mechanisms such as enhancer-promoter looping and topologically associating domain (TAD) formation by cooperating with factors such as cohesin loaders and the insulation factor CTCF. We developed a computational workflow to explore how three-dimensional (3D) structure and gene expression are regulated collectively or individually by cohesin and related factors. The main component is CustardPy, by which multi-omics datasets are compared systematically. To validate our methodology, we generated 3D genome, transcriptome, and epigenome data before and after depletion of cohesin and related factors and compared the effects of depletion. We observed diverse effects on the 3D genome and transcriptome, and gene expression changes were correlated with the splitting of TADs caused by cohesin loss. We also observed variations in long-range interactions across TADs, which correlated with their epigenomic states. These computational tools and datasets will be valuable for 3D genome and epigenome studies.
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Affiliation(s)
- Ryuichiro Nakato
- Laboratory of Computational Genomics, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-0032, Japan.
| | - Toyonori Sakata
- Laboratory of Genome Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-0032, Japan
- Karolinska Institutet, Department of Biosciences and Nutrition, Biomedicum, Quarter A6, 171 77, Stockholm, Sweden
- Karolinska Institutet, Department of Cell and Molecular Biology, Biomedicum, Quarter A6, 171 77, Stockholm, Sweden
| | - Jiankang Wang
- School of Biomedical Sciences, Hunan University, Changsha, China
| | - Luis Augusto Eijy Nagai
- Laboratory of Computational Genomics, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-0032, Japan
| | - Yuya Nagaoka
- Laboratory of Computational Genomics, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-0032, Japan
| | - Gina Miku Oba
- Laboratory of Computational Genomics, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-0032, Japan
| | - Masashige Bando
- Laboratory of Genome Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-0032, Japan
| | - Katsuhiko Shirahige
- Laboratory of Genome Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-0032, Japan.
- Karolinska Institutet, Department of Biosciences and Nutrition, Biomedicum, Quarter A6, 171 77, Stockholm, Sweden.
- Karolinska Institutet, Department of Cell and Molecular Biology, Biomedicum, Quarter A6, 171 77, Stockholm, Sweden.
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Chahine Z, Gupta M, Lenz T, Hollin T, Abel S, Banks CAS, Saraf A, Prudhomme J, Florens L, Le Roch KG. PfMORC protein regulates chromatin accessibility and transcriptional repression in the human malaria parasite, P. falciparum. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.11.557253. [PMID: 37745554 PMCID: PMC10515874 DOI: 10.1101/2023.09.11.557253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
The environmental challenges the human malaria parasite, Plasmodium falciparum, faces during its progression into its various lifecycle stages warrant the use of effective and highly regulated access to chromatin for transcriptional regulation. Microrchidia (MORC) proteins have been implicated in DNA compaction and gene silencing across plant and animal kingdoms. Accumulating evidence has shed light into the role MORC protein plays as a transcriptional switch in apicomplexan parasites. In this study, using CRISPR/Cas9 genome editing tool along with complementary molecular and genomics approaches, we demonstrate that PfMORC not only modulates chromatin structure and heterochromatin formation throughout the parasite erythrocytic cycle, but is also essential to the parasite survival. Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) experiments suggest that PfMORC binds to not only sub-telomeric regions and genes involved in antigenic variation but is also most likely a key modulator of stage transition. Protein knockdown experiments followed by chromatin conformation capture (Hi-C) studies indicate that downregulation of PfMORC induces the collapse of the parasite heterochromatin structure leading to its death. All together these findings confirm that PfMORC plays a crucial role in chromatin structure and gene regulation, validating this factor as a strong candidate for novel antimalarial strategies.
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Affiliation(s)
- Z Chahine
- Department of Molecular, Cell and Systems Biology, University of California Riverside, CA, USA
| | - M Gupta
- Department of Molecular, Cell and Systems Biology, University of California Riverside, CA, USA
| | - T Lenz
- Department of Molecular, Cell and Systems Biology, University of California Riverside, CA, USA
| | - T Hollin
- Department of Molecular, Cell and Systems Biology, University of California Riverside, CA, USA
| | - S Abel
- Department of Molecular, Cell and Systems Biology, University of California Riverside, CA, USA
| | - CAS Banks
- Stowers Institute for Medical Research, 1000 E. 50th Street, Kansas City, MO 64110, USA
| | - A Saraf
- Stowers Institute for Medical Research, 1000 E. 50th Street, Kansas City, MO 64110, USA
| | - J Prudhomme
- Department of Molecular, Cell and Systems Biology, University of California Riverside, CA, USA
| | - L Florens
- Stowers Institute for Medical Research, 1000 E. 50th Street, Kansas City, MO 64110, USA
| | - KG Le Roch
- Department of Molecular, Cell and Systems Biology, University of California Riverside, CA, USA
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42
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Yang J, Zhu X, Wang R, Li M, Tang Q. Revisiting Assessment of Computational Methods for Hi-C Data Analysis. Int J Mol Sci 2023; 24:13814. [PMID: 37762117 PMCID: PMC10531246 DOI: 10.3390/ijms241813814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 08/30/2023] [Accepted: 09/03/2023] [Indexed: 09/29/2023] Open
Abstract
The performances of algorithms for Hi-C data preprocessing, the identification of topologically associating domains, and the detection of chromatin interactions and promoter-enhancer interactions have been mostly evaluated using semi-quantitative or synthetic data approaches, without utilizing the most recent methods, since 2017. In this study, we comprehensively evaluated 24 popular state-of-the-art methods for the complete end-to-end pipeline of Hi-C data analysis, using manually curated or experimentally validated benchmark datasets, including a CRISPR dataset for promoter-enhancer interaction validation. Our results indicate that, although no single method exhibited superior performance in all situations, HiC-Pro, DomainCaller, and Fit-Hi-C2 showed relatively balanced performances of most evaluation metrics for preprocessing, topologically associating domain identification, and chromatin interaction/promoter-enhancer interaction detection, respectively. The comprehensive comparison presented in this manuscript provides a reference for researchers to choose Hi-C analysis tools that best suit their needs.
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Affiliation(s)
- Jing Yang
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; (J.Y.); (X.Z.); (R.W.)
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu 610066, China
| | - Xingxing Zhu
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; (J.Y.); (X.Z.); (R.W.)
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu 610066, China
| | - Rui Wang
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; (J.Y.); (X.Z.); (R.W.)
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu 610066, China
| | - Mingzhou Li
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; (J.Y.); (X.Z.); (R.W.)
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu 610066, China
| | - Qianzi Tang
- Livestock and Poultry Multi-Omics Key Laboratory of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; (J.Y.); (X.Z.); (R.W.)
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu 610066, China
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43
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Qu J, Sun J, Zhao C, Liu X, Zhang X, Jiang S, Wei C, Yu H, Zeng X, Fan L, Ding J. Simultaneous profiling of chromatin architecture and transcription in single cells. Nat Struct Mol Biol 2023; 30:1393-1402. [PMID: 37580628 DOI: 10.1038/s41594-023-01066-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 07/12/2023] [Indexed: 08/16/2023]
Abstract
The three-dimensional structure of chromatin plays a crucial role in development and disease, both of which are associated with transcriptional changes. However, given the heterogeneity in single-cell chromatin architecture and transcription, the regulatory relationship between the three-dimensional chromatin structure and gene expression is difficult to explain based on bulk cell populations. Here we develop a single-cell, multimodal, omics method allowing the simultaneous detection of chromatin architecture and messenger RNA expression by sequencing (single-cell transcriptome sequencing (scCARE-seq)). Applying scCARE-seq to examine chromatin architecture and transcription from 2i to serum single mouse embryonic stem cells, we observe improved separation of cell clusters compared with single-cell chromatin conformation capture. In addition, after defining the cell-cycle phase of each cell through chromatin architecture extracted by scCARE-seq, we find that periodic changes in chromatin architecture occur in parallel with transcription during the cell cycle. These findings highlight the potential of scCARE-seq to facilitate comprehensive analyses that may boost our understanding of chromatin architecture and transcription in the same single cell.
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Affiliation(s)
- Jiale Qu
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center 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, China
| | - Jun Sun
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center 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, China
| | - Cai Zhao
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center 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, China
| | - Xinyi Liu
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center 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, China
| | - Xinyao Zhang
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center 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, China
| | - Shaoshuai Jiang
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center 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, China
| | - Chao Wei
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center 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, China
| | - Haopeng Yu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaoxi Zeng
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
| | - Lili Fan
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China.
| | - Junjun Ding
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
- Center 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, China.
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
- Department of Histology and Embryology, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China.
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44
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Yildirim A, Hua N, Boninsegna L, Zhan Y, Polles G, Gong K, Hao S, Li W, Zhou XJ, Alber F. Evaluating the role of the nuclear microenvironment in gene function by population-based modeling. Nat Struct Mol Biol 2023; 30:1193-1206. [PMID: 37580627 PMCID: PMC10442234 DOI: 10.1038/s41594-023-01036-1] [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: 11/03/2021] [Accepted: 06/16/2023] [Indexed: 08/16/2023]
Abstract
The nuclear folding of chromosomes relative to nuclear bodies is an integral part of gene function. Here, we demonstrate that population-based modeling-from ensemble Hi-C data-provides a detailed description of the nuclear microenvironment of genes and its role in gene function. We define the microenvironment by the subnuclear positions of genomic regions with respect to nuclear bodies, local chromatin compaction, and preferences in chromatin compartmentalization. These structural descriptors are determined in single-cell models, thereby revealing the structural variability between cells. We demonstrate that the microenvironment of a genomic region is linked to its functional potential in gene transcription, replication, and chromatin compartmentalization. Some chromatin regions feature a strong preference for a single microenvironment, due to association with specific nuclear bodies in most cells. Other chromatin shows high structural variability, which is a strong indicator of functional heterogeneity. Moreover, we identify specialized nuclear microenvironments, which distinguish chromatin in different functional states and reveal a key role of nuclear speckles in chromosome organization. We demonstrate that our method produces highly predictive three-dimensional genome structures, which accurately reproduce data from a variety of orthogonal experiments, thus considerably expanding the range of Hi-C data analysis.
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Affiliation(s)
- Asli Yildirim
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, USA
- Department of Microbiology, Immunology, and Molecular Genetics, University of California Los Angeles, Los Angeles, CA, USA
| | - Nan Hua
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, USA
- Department of Microbiology, Immunology, and Molecular Genetics, University of California Los Angeles, Los Angeles, CA, USA
| | - Lorenzo Boninsegna
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, USA
- Department of Microbiology, Immunology, and Molecular Genetics, University of California Los Angeles, Los Angeles, CA, USA
| | - Yuxiang Zhan
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, USA
- Department of Microbiology, Immunology, and Molecular Genetics, University of California Los Angeles, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Guido Polles
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, USA
- Department of Microbiology, Immunology, and Molecular Genetics, University of California Los Angeles, Los Angeles, CA, USA
| | - Ke Gong
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, USA
- Department of Microbiology, Immunology, and Molecular Genetics, University of California Los Angeles, Los Angeles, CA, USA
| | - Shengli Hao
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, USA
- Department of Microbiology, Immunology, and Molecular Genetics, University of California Los Angeles, Los Angeles, CA, USA
| | - Wenyuan Li
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Xianghong Jasmine Zhou
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Frank Alber
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, USA.
- Department of Microbiology, Immunology, and Molecular Genetics, University of California Los Angeles, Los Angeles, CA, USA.
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
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45
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Park DS, Nguyen SC, Isenhart R, Shah PP, Kim W, Barnett RJ, Chandra A, Luppino JM, Harke J, Wai M, Walsh PJ, Abdill RJ, Yang R, Lan Y, Yoon S, Yunker R, Kanemaki MT, Vahedi G, Phillips-Cremins JE, Jain R, Joyce EF. High-throughput Oligopaint screen identifies druggable 3D genome regulators. Nature 2023; 620:209-217. [PMID: 37438531 DOI: 10.1038/s41586-023-06340-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 06/19/2023] [Indexed: 07/14/2023]
Abstract
The human genome functions as a three-dimensional chromatin polymer, driven by a complex collection of chromosome interactions1-3. Although the molecular rules governing these interactions are being quickly elucidated, relatively few proteins regulating this process have been identified. Here, to address this gap, we developed high-throughput DNA or RNA labelling with optimized Oligopaints (HiDRO)-an automated imaging pipeline that enables the quantitative measurement of chromatin interactions in single cells across thousands of samples. By screening the human druggable genome, we identified more than 300 factors that influence genome folding during interphase. Among these, 43 genes were validated as either increasing or decreasing interactions between topologically associating domains. Our findings show that genetic or chemical inhibition of the ubiquitous kinase GSK3A leads to increased long-range chromatin looping interactions in a genome-wide and cohesin-dependent manner. These results demonstrate the importance of GSK3A signalling in nuclear architecture and the use of HiDRO for identifying mechanisms of spatial genome organization.
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Affiliation(s)
- Daniel S Park
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Son C Nguyen
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Randi Isenhart
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Parisha P Shah
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Wonho Kim
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - R Jordan Barnett
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Aditi Chandra
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jennifer M Luppino
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jailynn Harke
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - May Wai
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Patrick J Walsh
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Richard J Abdill
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Rachel Yang
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yemin Lan
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sora Yoon
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Rebecca Yunker
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Masato T Kanemaki
- Department of Chromosome Science, National Institute of Genetics, Research Organization of Information and Systems (ROIS), Shizuoka, Japan
- Department of Genetics, The Graduate University for Advanced Studies (SOKENDAI), Shizuoka, Japan
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, Japan
| | - Golnaz Vahedi
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jennifer E Phillips-Cremins
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Rajan Jain
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Eric F Joyce
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Wang Y, Guo Z, Cheng J. Single-cell Hi-C data enhancement with deep residual and generative adversarial networks. Bioinformatics 2023; 39:btad458. [PMID: 37498561 PMCID: PMC10403428 DOI: 10.1093/bioinformatics/btad458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 07/19/2023] [Accepted: 07/25/2023] [Indexed: 07/28/2023] Open
Abstract
MOTIVATION The spatial genome organization of a eukaryotic cell is important for its function. The development of single-cell technologies for probing the 3D genome conformation, especially single-cell chromosome conformation capture techniques, has enabled us to understand genome function better than before. However, due to extreme sparsity and high noise associated with single-cell Hi-C data, it is still difficult to study genome structure and function using the HiC-data of one single cell. RESULTS In this work, we developed a deep learning method ScHiCEDRN based on deep residual networks and generative adversarial networks for the imputation and enhancement of Hi-C data of a single cell. In terms of both image evaluation and Hi-C reproducibility metrics, ScHiCEDRN outperforms the four deep learning methods (DeepHiC, HiCPlus, HiCSR, and Loopenhance) on enhancing the raw single-cell Hi-C data of human and Drosophila. The experiments also show that it can generate single-cell Hi-C data more suitable for identifying topologically associating domain boundaries and reconstructing 3D chromosome structures than the existing methods. Moreover, ScHiCEDRN's performance generalizes well across different single cells and cell types, and it can be applied to improving population Hi-C data. AVAILABILITY AND IMPLEMENTATION The source code of ScHiCEDRN is available at the GitHub repository: https://github.com/BioinfoMachineLearning/ScHiCEDRN.
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Affiliation(s)
- Yanli Wang
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, United States
- NextGen Precision Health Institute, University of Missouri, Columbia, MO 65211, United States
| | - Zhiye Guo
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, United States
- NextGen Precision Health Institute, University of Missouri, Columbia, MO 65211, United States
| | - Jianlin Cheng
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, United States
- NextGen Precision Health Institute, University of Missouri, Columbia, MO 65211, United States
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47
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Zhang G, Li Y, Wei G. Multi-omic analysis reveals dynamic changes of three-dimensional chromatin architecture during T cell differentiation. Commun Biol 2023; 6:773. [PMID: 37488215 PMCID: PMC10366224 DOI: 10.1038/s42003-023-05141-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 07/13/2023] [Indexed: 07/26/2023] Open
Abstract
Cell differentiation results in widespread changes in transcriptional programs as well as multi-level remodeling of three-dimensional genome architecture. Nonetheless, few synthetically investigate the chromatin higher-order landscapes in different T helper (Th) cells. Using RNA-Seq, ATAC-Seq and Hi-C assays, we characterize dynamic changes in chromatin organization at different levels during Naive CD4+ T cells differentiation into T helper 17 (Th17) and T helper 1 (Th1) cells. Upon differentiation, we observe decreased short-range and increased extra-long-range chromatin interactions. Although there is no apparent global switch in the A/B compartments, Th cells display the weaker compartmentalization. A portion of topologically associated domains are rearranged. Furthermore, we identify cell-type specific enhancer-promoter loops, many of which are associated with functional genes in Th cells, such as Rorc facilitating Th17 differentiation and Hif1a responding to intracellular oxygen levels in Th1. Taken together, these results uncover the general patterns of chromatin reorganization and epigenetic landscapes of gene regulation during T helper cell differentiation.
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Affiliation(s)
- Ge Zhang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Ying Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Gang Wei
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
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48
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Li D, Zhao XY, Zhou S, Hu Q, Wu F, Lee HY. Multidimensional profiling reveals GATA1-modulated stage-specific chromatin states and functional associations during human erythropoiesis. Nucleic Acids Res 2023; 51:6634-6653. [PMID: 37254808 PMCID: PMC10359633 DOI: 10.1093/nar/gkad468] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Revised: 04/18/2023] [Accepted: 05/13/2023] [Indexed: 06/01/2023] Open
Abstract
Mammalian erythroid development can be divided into three stages: hematopoietic stem and progenitor cell (HSPC), erythroid progenitor (Ery-Pro), and erythroid precursor (Ery-Pre). However, the mechanisms by which the 3D genome changes to establish the stage-specific transcription programs that are critical for erythropoiesis remain unclear. Here, we analyze the chromatin landscape at multiple levels in defined populations from primary human erythroid culture. While compartments and topologically associating domains remain largely unchanged, ∼50% of H3K27Ac-marked enhancers are dynamic in HSPC versus Ery-Pre. The enhancer anchors of enhancer-promoter loops are enriched for occupancy of respective stage-specific transcription factors (TFs), indicating these TFs orchestrate the enhancer connectome rewiring. The master TF of erythropoiesis, GATA1, is found to occupy most erythroid gene promoters at the Ery-Pro stage, and mediate conspicuous local rewiring through acquiring binding at the distal regions in Ery-Pre, promoting productive erythroid transcription output. Knocking out GATA1 binding sites precisely abrogates local rewiring and corresponding gene expression. Interestingly, knocking down GATA1 can transiently revert the cell state to an earlier stage and prolong the window of progenitor state. This study reveals mechanistic insights underlying chromatin rearrangements during development by integrating multidimensional chromatin landscape analyses to associate with transcription output and cellular states.
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Affiliation(s)
- Dong Li
- Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Xin-Ying Zhao
- Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Shuo Zhou
- Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Qi Hu
- Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Fan Wu
- Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Hsiang-Ying Lee
- Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Peking University People's Hospital, Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, Beijing 100871, China
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49
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Li H, He X, Kurowski L, Zhang R, Zhao D, Zeng J. Improving comparative analyses of Hi-C data via contrastive self-supervised learning. Brief Bioinform 2023; 24:bbad193. [PMID: 37287135 DOI: 10.1093/bib/bbad193] [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: 02/06/2023] [Revised: 04/12/2023] [Accepted: 04/27/2023] [Indexed: 06/09/2023] Open
Abstract
Hi-C is a widely applied chromosome conformation capture (3C)-based technique, which has produced a large number of genomic contact maps with high sequencing depths for a wide range of cell types, enabling comprehensive analyses of the relationships between biological functionalities (e.g. gene regulation and expression) and the three-dimensional genome structure. Comparative analyses play significant roles in Hi-C data studies, which are designed to make comparisons between Hi-C contact maps, thus evaluating the consistency of replicate Hi-C experiments (i.e. reproducibility measurement) and detecting statistically differential interacting regions with biological significance (i.e. differential chromatin interaction detection). However, due to the complex and hierarchical nature of Hi-C contact maps, it remains challenging to conduct systematic and reliable comparative analyses of Hi-C data. Here, we proposed sslHiC, a contrastive self-supervised representation learning framework, for precisely modeling the multi-level features of chromosome conformation and automatically producing informative feature embeddings for genomic loci and their interactions to facilitate comparative analyses of Hi-C contact maps. Comprehensive computational experiments on both simulated and real datasets demonstrated that our method consistently outperformed the state-of-the-art baseline methods in providing reliable measurements of reproducibility and detecting differential interactions with biological meanings.
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Affiliation(s)
- Han Li
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
| | - Xuan He
- Machine Learning Department, Silexon AI Technology Co., Ltd., 210000 Nanjing, China
| | - Lawrence Kurowski
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
| | - Ruotian Zhang
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
| | - Dan Zhao
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
| | - Jianyang Zeng
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
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50
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Powell SK, Liao W, O’Shea C, Kammourh S, Ghorbani S, Rigat R, Elahi R, Deans PJM, Le DJ, Agarwal P, Seow WQ, Wang KC, Akbarian S, Brennand KJ. Schizophrenia Risk Mapping and Functional Engineering of the 3D Genome in Three Neuronal Subtypes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.17.549339. [PMID: 37502907 PMCID: PMC10370055 DOI: 10.1101/2023.07.17.549339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Common variants associated with schizophrenia are concentrated in non-coding regulatory sequences, but their precise target genes are context-dependent and impacted by cell-type-specific three-dimensional spatial chromatin organization. Here, we map long-range chromosomal conformations in isogenic human dopaminergic, GABAergic, and glutamatergic neurons to track developmentally programmed shifts in the regulatory activity of schizophrenia risk loci. Massive repressive compartmentalization, concomitant with the emergence of hundreds of neuron-specific multi-valent chromatin architectural stripes, occurs during neuronal differentiation, with genes interconnected to genetic risk loci through these long-range chromatin structures differing in their biological roles from genes more proximal to sequences conferring heritable risk. Chemically induced CRISPR-guided chromosomal loop-engineering for the proximal risk gene SNAP91 and distal risk gene BHLHE22 profoundly alters synaptic development and functional activity. Our findings highlight the large-scale cell-type-specific reorganization of chromosomal conformations at schizophrenia risk loci during neurodevelopment and establish a causal link between risk-associated gene-regulatory loop structures and neuronal function.
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Affiliation(s)
- Samuel K. Powell
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Graduate School of Biomedical Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Will Liao
- New York Genome Center, New York, NY, 10029
| | - Callan O’Shea
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Sarah Kammourh
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Sadaf Ghorbani
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Raymond Rigat
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Rahat Elahi
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - PJ Michael Deans
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Derek J. Le
- Department of Dermatology, Program in Epithelial Biology, Stanford University School of Medicine, Stanford, 94305, California, USA
- Cancer Biology Program, Stanford University School of Medicine, Stanford, California, 94305, USA
| | - Poonam Agarwal
- Department of Dermatology, Program in Epithelial Biology, Stanford University School of Medicine, Stanford, 94305, California, USA
| | - Wei Qiang Seow
- Department of Dermatology, Program in Epithelial Biology, Stanford University School of Medicine, Stanford, 94305, California, USA
| | - Kevin C. Wang
- Department of Dermatology, Program in Epithelial Biology, Stanford University School of Medicine, Stanford, 94305, California, USA
- Cancer Biology Program, Stanford University School of Medicine, Stanford, California, 94305, USA
- Veterans Affairs Palo Alto Healthcare System, Palo Alto, California, 94304, USA
| | - Schahram Akbarian
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Kristen J. Brennand
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
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