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Yao Z, Fang K, Liu G, Bjørås M, Jin VX, Wang J. Integrated analysis of differential intra-chromosomal community interactions: A study of breast cancer. Artif Intell Med 2025; 167:103180. [PMID: 40449144 DOI: 10.1016/j.artmed.2025.103180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2024] [Revised: 05/15/2025] [Accepted: 05/23/2025] [Indexed: 06/02/2025]
Abstract
It is challenging to analyze the dynamics of intra-chromosomal interactions when considering multiple high-dimensional epigenetic datasets. A computational approach, differential network analysis in intra-chromosomal community interaction (DNAICI), was proposed here to elucidate these dynamics by integrating Hi-C data with other epigenetic data. DNAICI utilized a novel hyperparameter tuning method, for optimizing the network clustering, to identify valid intra-chromosomal community interactions at different resolutions. The approach was first trained on Hi-C data and other epigenetic data in an untreated and one hour estrogen (E2)-treated breast cancer cell line, MCF7, and uncovered two major types of valid intra-chromosomal community interactions (active/repressive) that resembles the properties of A/B compartments (or open/closed chromatin domains). It was further tested on the breast cancer cell line MCF7 and its corresponding tamoxifen-resistant (TR) derivative, MCF7TR, and identified 515 differentially interacting and expressed genes (DIEGs) within intra-chromosomal community interactions. In silico analysis of these DIEGs revealed that endocrine resistance is among the top biological pathways, suggesting an interacting/looping-mediated mechanism in regulating breast cancer tamoxifen resistance. This novel integrated network analysis approach offers a broad application in diverse biological systems for identifying a biological-context-specific differential community interaction.
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Affiliation(s)
- Zhihao Yao
- Department of Clinical Molecular Biology (EpiGen), Akershus University Hospital and University of Oslo, Lørenskog, Norway; Department of Microbiology, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Kun Fang
- Division of Biostatistics, Data Science Institute, Medical College of Wisconsin, Milwaukee, WI 53226, USA; MCW Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA; Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Gege Liu
- Department of Pathology, Oslo University Hospital - Norwegian Radium Hospital, Oslo, Norway
| | - Magnar Bjørås
- Department of Microbiology, Oslo University Hospital and University of Oslo, Oslo, Norway; Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Victor X Jin
- Division of Biostatistics, Data Science Institute, Medical College of Wisconsin, Milwaukee, WI 53226, USA; MCW Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA; Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, WI 53226, USA.
| | - Junbai Wang
- Department of Clinical Molecular Biology (EpiGen), Akershus University Hospital and University of Oslo, Lørenskog, Norway.
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2
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Gregoricchio S, Kojic A, Hoogstraat M, Schuurman K, Stelloo S, Severson TM, O'Mara TA, Droog M, Singh AA, Glubb DM, Wessels LFA, Vermeulen M, van Leeuwen FE, Zwart W. Endometrial tumorigenesis involves epigenetic plasticity demarcating non-coding somatic mutations and 3D-genome alterations. Genome Biol 2025; 26:124. [PMID: 40346709 PMCID: PMC12063248 DOI: 10.1186/s13059-025-03596-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Accepted: 04/28/2025] [Indexed: 05/11/2025] Open
Abstract
BACKGROUND The incidence and mortality of endometrial cancer (EC) is on the rise. Eighty-five percent of ECs depend on estrogen receptor alpha (ERα) for proliferation, but little is known about its transcriptional regulation in these tumors. RESULTS We generate epigenomics, transcriptomics, and Hi-C datastreams in healthy and tumor endometrial tissues, identifying robust ERα reprogramming and profound alterations in 3D genome organization that lead to a gain of tumor-specific enhancer activity during EC development. Integration with endometrial cancer risk single-nucleotide polymorphisms and whole-genome sequencing data from primary tumors and metastatic samples reveals a striking enrichment of risk variants and non-coding somatic mutations at tumor-enriched ERα sites. Through machine learning-based predictions and interaction proteomics analyses, we identify an enhancer mutation which alters 3D genome conformation, impairing recruitment of the transcriptional repressor EHMT2/G9a/KMT1C, thereby alleviating transcriptional repression of ESR1 in EC. CONCLUSIONS In summary, we identify a complex genomic-epigenomic interplay in EC development and progression, altering 3D genome organization to enhance expression of the critical driver ERα.
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Affiliation(s)
- Sebastian Gregoricchio
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.
| | - Aleksandar Kojic
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Marlous Hoogstraat
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Karianne Schuurman
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Suzan Stelloo
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, Geert Grooteplein Zuid 28, 6525GA, Nijmegen, The Netherlands
| | - Tesa M Severson
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Tracy A O'Mara
- Cancer Research Program, QIMR Berghofer Medical Research Institute, Locked Bag 2000, Brisbane, QLD, 4029, Australia
| | - Marjolein Droog
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Abhishek A Singh
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Dylan M Glubb
- Cancer Research Program, QIMR Berghofer Medical Research Institute, Locked Bag 2000, Brisbane, QLD, 4029, Australia
| | - Lodewyk F A Wessels
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Michiel Vermeulen
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, Geert Grooteplein Zuid 28, 6525GA, Nijmegen, The Netherlands
- Division of Molecular Genetics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Flora E van Leeuwen
- Department of Epidemiology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Wilbert Zwart
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.
- Laboratory of Chemical Biology and Institute for Complex Molecular Systems, Department of Biomedical Engineering, Eindhoven University of Technology, P.O. Box 513, 5600 MB, Eindhoven, The Netherlands.
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3
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Lee DI, Roy S. Examining the dynamics of three-dimensional genome organization with multitask matrix factorization. Genome Res 2025; 35:1179-1193. [PMID: 40113262 PMCID: PMC12047540 DOI: 10.1101/gr.279930.124] [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: 08/15/2024] [Accepted: 02/20/2025] [Indexed: 03/22/2025]
Abstract
Three-dimensional (3D) genome organization, which determines how the DNA is packaged inside the nucleus, has emerged as a key component of the gene regulation machinery. High-throughput chromosome conformation data sets, such as Hi-C, have become available across multiple conditions and time points, offering a unique opportunity to examine changes in 3D genome organization and link them to phenotypic changes in normal and disease processes. However, systematic detection of higher-order structural changes across multiple Hi-C data sets remains a major challenge. Existing computational methods either do not model higher-order structural units or cannot model dynamics across more than two conditions of interest. We address these limitations with tree-guided integrated factorization (TGIF), a generalizable multitask nonnegative matrix factorization (NMF) approach that can be applied to time series or hierarchically related biological conditions. TGIF can identify large-scale changes at the compartment or subcompartment levels, as well as local changes at boundaries of topologically associated domains (TADs). Based on benchmarking in simulated and real Hi-C data, TGIF boundaries are more accurate and reproducible across differential levels of noise and sources of technical artifacts, and are more enriched in CTCF. Application to three multisample mammalian data sets shows that TGIF can detect differential regions at compartment, subcompartment, and boundary levels that are associated with significant changes in regulatory signals and gene expression enriched in tissue-specific processes. Finally, we leverage TGIF boundaries to prioritize sequence variants for multiple phenotypes from the NHGRI GWAS catalog. Taken together, TGIF is a flexible tool to examine 3D genome organization dynamics across disease and developmental processes.
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Affiliation(s)
- Da-Inn Lee
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin 53715, USA
| | - Sushmita Roy
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin 53715, USA;
- Wisconsin Institute for Discovery, Madison, Wisconsin 53715, USA
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4
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Lee J, Mo HL, Ha Y, Nam DY, Lim G, Park JW, Park S, Choi WY, Lee HJ, Rhee JK. Unraveling the three-dimensional genome structure using machine learning. BMB Rep 2025; 58:203-208. [PMID: 40058875 PMCID: PMC12123201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 03/07/2024] [Accepted: 09/06/2024] [Indexed: 05/29/2025] Open
Abstract
The study of chromatin interactions has advanced considerably with technologies such as high-throughput chromosome conformation capture (Hi-C) sequencing, providing a genome-wide view of physical interactions within the nucleus. These techniques have revealed the existence of hierarchical chromatin structures such as compartments, topologically associating domains (TADs), and chromatin loops, which are crucial in genome organization and regulation. However, identifying and analyzing these structural features require advanced computational methods. In recent years, machine learning approaches, particularly deep learning, have emerged as powerful tools for detecting and analyzing structural information. In this review, we present an overview of various machine learning-based techniques for determining chromosomal organization. Starting with the progress in predicting interactions from DNA sequences, we describe methods for identifying various hierarchical structures from Hi-C data. Additionally, we present advances in enhancing the chromosome contact frequency map resolution to overcome the limitations of Hi-C data. Finally, we identify the remaining challenges and propose potential solutions and future directions. [BMB Reports 2025; 58(5): 203-208].
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Affiliation(s)
- Jiho Lee
- School of Systems Biomedical Science, Soongsil University, Seoul 06978, Korea
| | - Hye-Lim Mo
- Department of Bioinformatics & Life Science, Soongsil University, Seoul 06978, Korea
| | - Yoon Ha
- Department of Bioinformatics & Life Science, Soongsil University, Seoul 06978, Korea
| | - Dong Yeon Nam
- Department of Bioinformatics & Life Science, Soongsil University, Seoul 06978, Korea
| | - Geumnim Lim
- Department of Bioinformatics & Life Science, Soongsil University, Seoul 06978, Korea
| | - Jeong-Woon Park
- Department of Bioinformatics & Life Science, Soongsil University, Seoul 06978, Korea
| | - Seoyoung Park
- Department of Bioinformatics & Life Science, Soongsil University, Seoul 06978, Korea
| | - Woo-Young Choi
- Department of Bioinformatics & Life Science, Soongsil University, Seoul 06978, Korea
| | - Hyun Ji Lee
- Department of Bioinformatics & Life Science, Soongsil University, Seoul 06978, Korea
| | - Je-Keun Rhee
- School of Systems Biomedical Science, Soongsil University, Seoul 06978, Korea
- Department of Bioinformatics & Life Science, Soongsil University, Seoul 06978, Korea
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5
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Choppavarapu L, Fang K, Liu T, Ohihoin AG, Jin VX. Hi-C profiling in tissues reveals 3D chromatin-regulated breast tumor heterogeneity informing a looping-mediated therapeutic avenue. Cell Rep 2025; 44:115450. [PMID: 40112000 PMCID: PMC12103084 DOI: 10.1016/j.celrep.2025.115450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Revised: 01/12/2025] [Accepted: 02/28/2025] [Indexed: 03/22/2025] Open
Abstract
The limitations of Hi-C (high-throughput chromosome conformation capture) profiling in in vitro cell culture include failing to recapitulate disease-specific physiological properties and lacking a clinically relevant disease microenvironment. In this study, we conduct Hi-C profiling in a pilot cohort of 12 breast tissues comprising two normal tissues, five ER+ breast primary tumors, and five tamoxifen-treated recurrent tumors. We demonstrate 3D chromatin-regulated breast tumor heterogeneity and identify a looping-mediated target gene, CA2, which might play a role in driving tamoxifen resistance. The inhibition of CA2 impedes tumor growth both in vitro and in vivo and reverses chromatin looping. The disruption of CA2 looping reduces tamoxifen-resistant cancer cell proliferation, decreases CA2 mRNA and protein expression, and weakens the looping interaction. Our study thus provides mechanistic and functional insights into the role of 3D chromatin architecture in regulating breast tumor heterogeneity and informs a new looping-mediated therapeutic avenue for treating breast cancer.
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Affiliation(s)
- Lavanya Choppavarapu
- Divison of Biostatistics, Data Science Institute, Medical College of Wisconsin, Milwaukee, WI 53226, USA; MCW Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA; Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Kun Fang
- Divison of Biostatistics, Data Science Institute, Medical College of Wisconsin, Milwaukee, WI 53226, USA; MCW Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA; Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Tianxiang Liu
- Divison of Biostatistics, Data Science Institute, Medical College of Wisconsin, Milwaukee, WI 53226, USA; MCW Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA; Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Aigbe G Ohihoin
- Cell and Developmental Biology PhD program, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Victor X Jin
- Divison of Biostatistics, Data Science Institute, Medical College of Wisconsin, Milwaukee, WI 53226, USA; MCW Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA; Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, WI 53226, USA.
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6
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Hildebrand EM, Cowell IG, Khazeem MM, Sambare S, Uyan O, Dekker J, Austin CA. TOP2B is required for compartment strength changes upon retinoic acid treatment in SH-SY5Y cells. Chromosome Res 2025; 33:5. [PMID: 40183884 PMCID: PMC11971153 DOI: 10.1007/s10577-025-09764-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2024] [Revised: 02/16/2025] [Accepted: 03/17/2025] [Indexed: 04/05/2025]
Abstract
DNA topoisomerase II beta (TOP2B) is required for correct execution of certain developmental transcriptional programs and for signal-induced transcriptional activation, including transcriptional activation by nuclear hormone ligands such as retinoic acid. In addition, TOP2B is enriched at genomic locations occupied by CCCTC-Binding factor (CTCF) and cohesin (RAD21). suggesting a role in chromosome looping and/or establishing or maintaining aspects of chromosome 3D structure. This led us to investigate the effect of TOP2B inactivation on patterns of intra- and inter- chromosomal interaction that reflect the 3D architecture of the genome. Using the retinoic acid responsive SH-SY5Y neuroblastoma cell line model, we had previously demonstrated many gene expression changes upon retinoic acid treatment and upon deletion of TOP2B. We report here that these expression changes in TOP2B null versus WT cells are accompanied by surprisingly subtle changes in local chromosome organization. However, we do observe quantitative changes in chromosome organization on a megabase scale. First, lack of TOP2B did affect compartment strength changes that occur upon ATRA treatment. Second, we observe an excess of very long-range interactions, reminiscent of interactions seen in mitotic cells, suggesting the possibility that in the absence of TOP2B some mitotic interactions are retained. Third, we see quantitative changes in centromere-telomere interactions, again indicating global changes at the megabase and chromosome level. These data support the surprising conclusion that TOP2B has only a minor role in chromosome dynamics and organization.
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Affiliation(s)
- Erica M Hildebrand
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Ian G Cowell
- Biosciences Institute, Newcastle University, Newcastle Upon Tyne, NE2 4HH, U.K
| | - Mushtaq M Khazeem
- National Center of Hematology, University of Mustansiriyah, Baghdad, Baghdad, IQ, Iraq
| | - Snehal Sambare
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Ozgun Uyan
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Job Dekker
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
| | - Caroline A Austin
- Biosciences Institute, Newcastle University, Newcastle Upon Tyne, NE2 4HH, U.K..
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7
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Li Y, Xiao P, Boadu F, Goldkamp AK, Nirgude S, Cheng J, Hagen DE, Kalish JM, Rivera RM. Beckwith-Wiedemann syndrome and large offspring syndrome involve alterations in methylome, transcriptome, and chromatin configuration. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2023.12.14.23299981. [PMID: 38168424 PMCID: PMC10760283 DOI: 10.1101/2023.12.14.23299981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Beckwith-Wiedemann Syndrome (BWS) is the most common epigenetic overgrowth syndrome, caused by epigenetic alterations on chromosome 11p15. In ∼50% of patients with BWS, the imprinted region KvDMR1 (IC2) is hypomethylated. Nearly all children with BWS develop organ overgrowth and up to 28% develop cancer during childhood. The global epigenetic alterations beyond the 11p15 region in BWS are not currently known. Uncovering these alterations at the methylome, transcriptome, and chromatin architecture levels are necessary steps to improve the diagnosis and understanding of patients with BWS. Here we characterized the complete epigenetic profiles of BWS IC2 individuals together with the animal model of BWS, bovine large offspring syndrome (LOS). A novel finding of this research is the identification of two molecular subgroups of BWS IC2 individuals. Genome-wide alternations were detected for DNA methylation, transcript abundance, alternative splicing events of RNA, chromosome compartments, and topologically associating domains (TADs) in BWS and LOS, with shared alterations identified between species. Altered chromosome compartments and TADs were correlated with differentially expressed genes in BWS and LOS. Together, we highlight genes and genomic regions that have the potential to serve as targets for biomarker development to improve current molecular diagnostic methodologies for BWS.
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8
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Jorge E, Foissac S, Neuvial P, Zytnicki M, Vialaneix N. A comprehensive review and benchmark of differential analysis tools for Hi-C data. Brief Bioinform 2025; 26:bbaf074. [PMID: 40037641 PMCID: PMC11879411 DOI: 10.1093/bib/bbaf074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2024] [Revised: 01/24/2025] [Accepted: 02/10/2025] [Indexed: 03/06/2025] Open
Abstract
MOTIVATION The 3D organization of the genome plays a crucial role in various biological processes. Hi-C technology is widely used to investigate chromosome structures by quantifying 3D proximity between genomic regions. While numerous computational tools exist for detecting differences in Hi-C data between conditions, a comprehensive review and benchmark comparing their effectiveness is lacking. RESULTS This study offers a comprehensive review and benchmark of 10 generic tools for differential analysis of Hi-C matrices at the interaction count level. The benchmark assesses the statistical methods, usability, and performance (in terms of precision and power) of these tools, using both real and simulated Hi-C data. Results reveal a striking variability in performance among the tools, highlighting the substantial impact of preprocessing filters and the difficulty all tools encounter in effectively controlling the false discovery rate across varying resolutions and chromosome sizes. AVAILABILITY The complete benchmark is available at https://forgemia.inra.fr/scales/replication-chrocodiff using processed data deposited at https://doi.org/10.57745/LR0W9R. CONTACT nathalie.vialaneix@inrae.fr.
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Affiliation(s)
- Elise Jorge
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31326 Castanet-Tolosan, France
| | - Sylvain Foissac
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31326 Castanet-Tolosan, France
| | - Pierre Neuvial
- Institut de Mathématiques de Toulouse, UMR 5219, Université de Toulouse, CNRS UPS, 31062 Toulouse, France
| | - Matthias Zytnicki
- Université Fédérale de Toulouse, INRAE, MIAT, 31326 Castanet-Tolosan, France
| | - Nathalie Vialaneix
- Université Fédérale de Toulouse, INRAE, MIAT, 31326 Castanet-Tolosan, France
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9
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Grant ZL, Kuang S, Zhang S, Horrillo AJ, Rao KS, Kameswaran V, Joubran C, Lau PK, Dong K, Yang B, Bartosik WM, Zemke NR, Ren B, Kathiriya IS, Pollard KS, Bruneau BG. Dose-dependent sensitivity of human 3D chromatin to a heart disease-linked transcription factor. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.01.09.632202. [PMID: 39829922 PMCID: PMC11741296 DOI: 10.1101/2025.01.09.632202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/22/2025]
Abstract
Dosage-sensitive transcription factors (TFs) underlie altered gene regulation in human developmental disorders, and cell-type specific gene regulation is linked to the reorganization of 3D chromatin during cellular differentiation. Here, we show dose-dependent regulation of chromatin organization by the congenital heart disease (CHD)-linked, lineage-restricted TF TBX5 in human cardiomyocyte differentiation. Genome organization, including compartments, topologically associated domains, and chromatin loops, are sensitive to reduced TBX5 dosage in a human model of CHD, with variations in response across individual cells. Regions normally bound by TBX5 are especially sensitive, while co-occupancy with CTCF partially protects TBX5-bound TAD boundaries and loop anchors. These results highlight the importance of lineage-restricted TF dosage in cell-type specific 3D chromatin dynamics, suggesting a new mechanism for TF-dependent disease.
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Affiliation(s)
| | | | - Shu Zhang
- Gladstone Institutes; San Francisco, CA, USA
- Bioinformatics Graduate Program, University of California, San Francisco; San Francisco, CA, USA
| | - Abraham J. Horrillo
- Gladstone Institutes; San Francisco, CA, USA
- TETRAD Graduate Program, University of California, San Francisco; San Francisco, CA, USA
| | | | | | | | - Pik Ki Lau
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Keyi Dong
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Bing Yang
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Weronika M. Bartosik
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Nathan R. Zemke
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Irfan S. Kathiriya
- Gladstone Institutes; San Francisco, CA, USA
- Department of Anesthesia and Perioperative Care, University of California, San Francisco; San Francisco, CA, USA
| | - Katherine S. Pollard
- Gladstone Institutes; San Francisco, CA, USA
- Department of Epidemiology & Biostatistics, University of California, San Francisco; San Francisco, CA, USA
- Chan Zuckerberg Biohub; San Francisco, CA, USA
| | - Benoit G. Bruneau
- Gladstone Institutes; San Francisco, CA, USA
- Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA
- Department of Pediatrics, Cardiovascular Research Institute, Institute for Human Genetics, and the Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco; San Francisco, CA, USA
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10
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Wall BPG, Nguyen M, Harrell JC, Dozmorov MG. Machine and Deep Learning Methods for Predicting 3D Genome Organization. Methods Mol Biol 2025; 2856:357-400. [PMID: 39283464 DOI: 10.1007/978-1-0716-4136-1_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
Three-dimensional (3D) chromatin interactions, such as enhancer-promoter interactions (EPIs), loops, topologically associating domains (TADs), and A/B compartments, play critical roles in a wide range of cellular processes by regulating gene expression. Recent development of chromatin conformation capture technologies has enabled genome-wide profiling of various 3D structures, even with single cells. However, current catalogs of 3D structures remain incomplete and unreliable due to differences in technology, tools, and low data resolution. Machine learning methods have emerged as an alternative to obtain missing 3D interactions and/or improve resolution. Such methods frequently use genome annotation data (ChIP-seq, DNAse-seq, etc.), DNA sequencing information (k-mers and transcription factor binding site (TFBS) motifs), and other genomic properties to learn the associations between genomic features and chromatin interactions. In this review, we discuss computational tools for predicting three types of 3D interactions (EPIs, chromatin interactions, and TAD boundaries) and analyze their pros and cons. We also point out obstacles to the computational prediction of 3D interactions and suggest future research directions.
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Affiliation(s)
- Brydon P G Wall
- Center for Biological Data Science, Virginia Commonwealth University, Richmond, VA, USA
| | - My Nguyen
- Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA
| | - J Chuck Harrell
- Department of Pathology, Virginia Commonwealth University, Richmond, VA, USA
- Massey Comprehensive Cancer Center, Virginia Commonwealth University, Richmond, VA, USA
- Center for Pharmaceutical Engineering, Virginia Commonwealth University, Richmond, VA, USA
| | - Mikhail G Dozmorov
- Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.
- Department of Pathology, Virginia Commonwealth University, Richmond, VA, USA.
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11
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Chen X, Li K, Wu X, Li Z, Jiang Q, Cui X, Gao Z, Wu Y, Jiang R. Descart: a method for detecting spatial chromatin accessibility patterns with inter-cellular correlations. Genome Biol 2024; 25:322. [PMID: 39736655 PMCID: PMC11686967 DOI: 10.1186/s13059-024-03458-6] [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: 03/25/2024] [Accepted: 12/09/2024] [Indexed: 01/01/2025] Open
Abstract
Spatial epigenomic technologies enable simultaneous capture of spatial location and chromatin accessibility of cells within tissue slices. Identifying peaks that display spatial variation and cellular heterogeneity is the key analytic task for characterizing the spatial chromatin accessibility landscape of complex tissues. Here, we propose an efficient and iterative model, Descart, for spatially variable peaks identification based on the graph of inter-cellular correlations. Through the comprehensive benchmarking, we demonstrate the superiority of Descart in revealing cellular heterogeneity and capturing tissue structure. Utilizing the graph of inter-cellular correlations, Descart shows its potential to denoise data, identify peak modules, and detect gene-peak interactions.
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Affiliation(s)
- Xiaoyang Chen
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Keyi Li
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Xiaoqing Wu
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Zhen Li
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Qun Jiang
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Xuejian Cui
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Zijing Gao
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Yanhong Wu
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Rui Jiang
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing, 100084, China.
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12
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Tavallaee G, Orouji E. Mapping the 3D genome architecture. Comput Struct Biotechnol J 2024; 27:89-101. [PMID: 39816913 PMCID: PMC11732852 DOI: 10.1016/j.csbj.2024.12.018] [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: 11/05/2024] [Revised: 12/17/2024] [Accepted: 12/20/2024] [Indexed: 01/18/2025] Open
Abstract
The spatial organization of the genome plays a critical role in regulating gene expression, cellular differentiation, and genome stability. This review provides an in-depth examination of the methodologies, computational tools, and frameworks developed to map the three-dimensional (3D) architecture of the genome, focusing on both ligation-based and ligation-free techniques. We also explore the limitations of these methods, including biases introduced by restriction enzyme digestion and ligation inefficiencies, and compare them to more recent ligation-free approaches such as Genome Architecture Mapping (GAM) and Split-Pool Recognition of Interactions by Tag Extension (SPRITE). These techniques offer unique insights into higher-order chromatin structures by bypassing ligation steps, thus enabling the capture of complex multi-way interactions that are often challenging to resolve with traditional methods. Furthermore, we discuss the integration of chromatin interaction data with other genomic layers through multimodal approaches, including recent advances in single-cell technologies like sci-HiC and scSPRITE, which help unravel the heterogeneity of chromatin architecture in development and disease.
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Affiliation(s)
- Ghazaleh Tavallaee
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Elias Orouji
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
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13
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Chen ZJ, Das SS, Kar A, Lee SHT, Abuhanna KD, Alvarez M, Sukhatme MG, Gelev KZ, Heffel MG, Zhang Y, Avram O, Rahmani E, Sankararaman S, Heinonen S, Peltoniemi H, Halperin E, Pietiläinen KH, Luo C, Pajukanta P. Single-cell DNA methylome and 3D genome atlas of the human subcutaneous adipose tissue. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.11.02.621694. [PMID: 39554055 PMCID: PMC11566006 DOI: 10.1101/2024.11.02.621694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/19/2024]
Abstract
Human subcutaneous adipose tissue (SAT) contains a diverse array of cell-types; however, the epigenomic landscape among the SAT cell-types has remained elusive. Our integrative analysis of single-cell resolution DNA methylation and chromatin conformation profiles (snm3C-seq), coupled with matching RNA expression (snRNA-seq), systematically cataloged the epigenomic, 3D topology, and transcriptomic dynamics across the SAT cell-types. We discovered that the SAT CG methylation (mCG) landscape is characterized by pronounced hyper-methylation in myeloid cells and hypo-methylation in adipocytes and adipose stem and progenitor cells (ASPCs), driving nearly half of the 705,063 detected differentially methylated regions (DMRs). In addition to the enriched cell-type-specific transcription factor binding motifs, we identified TET1 and DNMT3A as plausible candidates for regulating cell-type level mCG profiles. Furthermore, we observed that global mCG profiles closely correspond to SAT lineage, which is also reflected in cell-type-specific chromosome compartmentalization. Adipocytes, in particular, display significantly more short-range chromosomal interactions, facilitating the formation of complex local 3D genomic structures that regulate downstream transcriptomic activity, including those associated with adipogenesis. Finally, we discovered that variants in cell-type level DMRs and A compartments significantly predict and are enriched for variance explained in abdominal obesity. Together, our multimodal study characterizes human SAT epigenomic landscape at the cell-type resolution and links partitioned polygenic risk of abdominal obesity to SAT epigenome.
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14
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Heffel MG, Zhou J, Zhang Y, Lee DS, Hou K, Pastor-Alonso O, Abuhanna KD, Galasso J, Kern C, Tai CY, Garcia-Padilla C, Nafisi M, Zhou Y, Schmitt AD, Li T, Haeussler M, Wick B, Zhang MJ, Xie F, Ziffra RS, Mukamel EA, Eskin E, Nowakowski TJ, Dixon JR, Pasaniuc B, Ecker JR, Zhu Q, Bintu B, Paredes MF, Luo C. Temporally distinct 3D multi-omic dynamics in the developing human brain. Nature 2024; 635:481-489. [PMID: 39385032 PMCID: PMC11560841 DOI: 10.1038/s41586-024-08030-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 09/06/2024] [Indexed: 10/11/2024]
Abstract
The human hippocampus and prefrontal cortex play critical roles in learning and cognition1,2, yet the dynamic molecular characteristics of their development remain enigmatic. Here we investigated the epigenomic and three-dimensional chromatin conformational reorganization during the development of the hippocampus and prefrontal cortex, using more than 53,000 joint single-nucleus profiles of chromatin conformation and DNA methylation generated by single-nucleus methyl-3C sequencing (snm3C-seq3)3. The remodelling of DNA methylation is temporally separated from chromatin conformation dynamics. Using single-cell profiling and multimodal single-molecule imaging approaches, we have found that short-range chromatin interactions are enriched in neurons, whereas long-range interactions are enriched in glial cells and non-brain tissues. We reconstructed the regulatory programs of cell-type development and differentiation, finding putatively causal common variants for schizophrenia strongly overlapping with chromatin loop-connected, cell-type-specific regulatory regions. Our data provide multimodal resources for studying gene regulatory dynamics in brain development and demonstrate that single-cell three-dimensional multi-omics is a powerful approach for dissecting neuropsychiatric risk loci.
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Affiliation(s)
- Matthew G Heffel
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jingtian Zhou
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA
- Arc Institute, Palo Alto, CA, USA
| | - Yi Zhang
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Dong-Sung Lee
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Republic of Korea
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Kangcheng Hou
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Oier Pastor-Alonso
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Kevin D Abuhanna
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Joseph Galasso
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Colin Kern
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Chu-Yi Tai
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Carlos Garcia-Padilla
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Mahsa Nafisi
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Yi Zhou
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | | | - Terence Li
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Brittney Wick
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Martin Jinye Zhang
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Fangming Xie
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
| | - Ryan S Ziffra
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Department of Anatomy, University of California, San Francisco, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
| | - Eran A Mukamel
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
| | - Eleazar Eskin
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Tomasz J Nowakowski
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Department of Anatomy, University of California, San Francisco, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
| | - Jesse R Dixon
- Gene Expression Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Bogdan Pasaniuc
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Joseph R Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Quan Zhu
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Bogdan Bintu
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Mercedes F Paredes
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
- Neuroscience Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
- Developmental Stem Cell Biology, University of California, San Francisco, San Francisco, CA, USA.
| | - Chongyuan Luo
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA.
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15
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Chang L, Xie Y, Taylor B, Wang Z, Sun J, Armand EJ, Mishra S, Xu J, Tastemel M, Lie A, Gibbs ZA, Indralingam HS, Tan TM, Bejar R, Chen CC, Furnari FB, Hu M, Ren B. Droplet Hi-C enables scalable, single-cell profiling of chromatin architecture in heterogeneous tissues. Nat Biotechnol 2024:10.1038/s41587-024-02447-1. [PMID: 39424717 DOI: 10.1038/s41587-024-02447-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 09/24/2024] [Indexed: 10/21/2024]
Abstract
Current methods for analyzing chromatin architecture are not readily scalable to heterogeneous tissues. Here we introduce Droplet Hi-C, which uses a commercial microfluidic device for high-throughput, single-cell chromatin conformation profiling in droplets. Using Droplet Hi-C, we mapped the chromatin architecture of the mouse cortex and analyzed gene regulatory programs in major cortical cell types. In addition, we used this technique to detect copy number variations, structural variations and extrachromosomal DNA in human glioblastoma, colorectal and blood cancer cells, revealing clonal dynamics and other oncogenic events during treatment. We refined the technique to allow joint profiling of chromatin architecture and transcriptome in single cells, facilitating exploration of the links between chromatin architecture and gene expression in both normal tissues and tumors. Thus, Droplet Hi-C both addresses critical gaps in chromatin analysis of heterogeneous tissues and enhances understanding of gene regulation.
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Affiliation(s)
- Lei Chang
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Yang Xie
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA, USA
| | - Brett Taylor
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA, USA
- Medical Scientist Training Program, University of California, San Diego, La Jolla, CA, USA
| | - Zhaoning Wang
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Jiachen Sun
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
- Systems Biology and Bioinformatics PhD Program, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Ethan J Armand
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA
| | - Shreya Mishra
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Jie Xu
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Melodi Tastemel
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Audrey Lie
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Zane A Gibbs
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Hannah S Indralingam
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Tuyet M Tan
- Moores Cancer Center, UC San Diego, La Jolla, CA, USA
| | - Rafael Bejar
- Moores Cancer Center, UC San Diego, La Jolla, CA, USA
| | - Clark C Chen
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN, USA
| | - Frank B Furnari
- Department of Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Ming Hu
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA.
- Moores Cancer Center, UC San Diego, La Jolla, CA, USA.
- Center for Epigenomics, Institute for Genomic Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, USA.
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16
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Zemke NR, Lee S, Mamde S, Yang B, Berchtold N, Maximiliano Garduño B, Indralingam HS, Bartosik WM, Lau PK, Dong K, Yang A, Tani Y, Chen C, Zeng Q, Ajith V, Tong L, Seng C, Li D, Wang T, Xu X, Ren B. Epigenetic and 3D genome reprogramming during the aging of human hippocampus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.14.618338. [PMID: 39463924 PMCID: PMC11507755 DOI: 10.1101/2024.10.14.618338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/29/2024]
Abstract
Age-related cognitive decline is associated with altered physiology of the hippocampus. While changes in gene expression have been observed in aging brain, the regulatory mechanisms underlying these changes remain underexplored. We generated single-nucleus gene expression, chromatin accessibility, DNA methylation, and 3D genome data from 40 human hippocampal tissues spanning adult lifespan. We observed a striking loss of astrocytes, OPC, and endothelial cells during aging, including astrocytes that play a role in regulating synapses. Microglia undergo a dramatic switch from a homeostatic state to a primed inflammatory state through DNA methylome and 3D genome reprogramming. Aged cells experience erosion of their 3D genome architecture. Our study identifies age-associated changes in cell types/states and gene regulatory features that provide insight into cognitive decline during human aging.
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Affiliation(s)
- Nathan R. Zemke
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Seoyeon Lee
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Sainath Mamde
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Bing Yang
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Nicole Berchtold
- Department of Anatomy and Neurobiology, University of California, Irvine School of Medicine; Irvine, CA, USA
- Immunis Inc, 18301 Von Karman Ave; Irvine, CA, USA
| | - B. Maximiliano Garduño
- Department of Anatomy and Neurobiology, University of California, Irvine School of Medicine; Irvine, CA, USA
| | - Hannah S. Indralingam
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Weronika M. Bartosik
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Pik Ki Lau
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Keyi Dong
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Amanda Yang
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Yasmine Tani
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Chumo Chen
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Qiurui Zeng
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Varun Ajith
- Department of Anatomy and Neurobiology, University of California, Irvine School of Medicine; Irvine, CA, USA
| | - Liqi Tong
- Department of Anatomy and Neurobiology, University of California, Irvine School of Medicine; Irvine, CA, USA
| | - Chanrung Seng
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine; St. Louis, MO, USA
| | - Daofeng Li
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine; St. Louis, MO, USA
| | - Ting Wang
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine; St. Louis, MO, USA
- McDonnell Genome Institute, Washington University School of Medicine; St. Louis, MO, USA
| | - Xiangmin Xu
- Department of Anatomy and Neurobiology, University of California, Irvine School of Medicine; Irvine, CA, USA
- The Center for Neural Circuit Mapping, University of California; Irvine, CA, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
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17
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Banerjee A, Zhang S, Bahar I. Genome structural dynamics: insights from Gaussian network analysis of Hi-C data. Brief Funct Genomics 2024; 23:525-537. [PMID: 38654598 PMCID: PMC11428154 DOI: 10.1093/bfgp/elae014] [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: 11/02/2023] [Revised: 03/11/2024] [Accepted: 04/02/2024] [Indexed: 04/26/2024] Open
Abstract
Characterization of the spatiotemporal properties of the chromatin is essential to gaining insights into the physical bases of gene co-expression, transcriptional regulation and epigenetic modifications. The Gaussian network model (GNM) has proven in recent work to serve as a useful tool for modeling chromatin structural dynamics, using as input high-throughput chromosome conformation capture data. We focus here on the exploration of the collective dynamics of chromosomal structures at hierarchical levels of resolution, from single gene loci to topologically associating domains or entire chromosomes. The GNM permits us to identify long-range interactions between gene loci, shedding light on the role of cross-correlations between distal regions of the chromosomes in regulating gene expression. Notably, GNM analysis performed across diverse cell lines highlights the conservation of the global/cooperative movements of the chromatin across different types of cells. Variations driven by localized couplings between genomic loci, on the other hand, underlie cell differentiation, underscoring the significance of the four-dimensional properties of the genome in defining cellular identity. Finally, we demonstrate the close relation between the cell type-dependent mobility profiles of gene loci and their gene expression patterns, providing a clear demonstration of the role of chromosomal 4D features in defining cell-specific differential expression of genes.
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Affiliation(s)
- Anupam Banerjee
- Laufer Center for Physical & Quantitative Biology, Stony Brook University, NY 11794, USA
| | - She Zhang
- OpenEye, Cadence Molecular Sciences, Santa Fe, NM 87508, USA
| | - Ivet Bahar
- Laufer Center for Physical & Quantitative Biology, Stony Brook University, NY 11794, USA
- Department of Biochemistry and Cell Biology, Renaissance School of Medicine, Stony Brook University, NY 11794, USA
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18
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Xue Y, Liu L, Zhang Y, He Y, Wang J, Ma Z, Li TJ, Zhang J, Huang Y, Gao YQ. Unraveling the key role of chromatin structure in cancer development through epigenetic landscape characterization of oral cancer. Mol Cancer 2024; 23:190. [PMID: 39243015 PMCID: PMC11378415 DOI: 10.1186/s12943-024-02100-0] [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: 06/28/2024] [Accepted: 08/23/2024] [Indexed: 09/09/2024] Open
Abstract
Epigenetic alterations, such as those in chromatin structure and DNA methylation, have been extensively studied in a number of tumor types. But oral cancer, particularly oral adenocarcinoma, has received far less attention. Here, we combined laser-capture microdissection and muti-omics mini-bulk sequencing to systematically characterize the epigenetic landscape of oral cancer, including chromatin architecture, DNA methylation, H3K27me3 modification, and gene expression. In carcinogenesis, tumor cells exhibit reorganized chromatin spatial structures, including compromised compartment structures and altered gene-gene interaction networks. Notably, some structural alterations are observed in phenotypically non-malignant paracancerous but not in normal cells. We developed transformer models to identify the cancer propensity of individual genome loci, thereby determining the carcinogenic status of each sample. Insights into cancer epigenetic landscapes provide evidence that chromatin reorganization is an important hallmark of oral cancer progression, which is also linked with genomic alterations and DNA methylation reprogramming. In particular, regions of frequent copy number alternations in cancer cells are associated with strong spatial insulation in both cancer and normal samples. Aberrant methylation reprogramming in oral squamous cell carcinomas is closely related to chromatin structure and H3K27me3 signals, which are further influenced by intrinsic sequence properties. Our findings indicate that structural changes are both significant and conserved in two distinct types of oral cancer, closely linked to transcriptomic alterations and cancer development. Notably, the structural changes remain markedly evident in oral adenocarcinoma despite the considerably lower incidence of genomic copy number alterations and lesser extent of methylation alterations compared to squamous cell carcinoma. We expect that the comprehensive analysis of epigenetic reprogramming of different types and subtypes of primary oral tumors can provide additional guidance to the design of novel detection and therapy for oral cancer.
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Affiliation(s)
- Yue Xue
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Lu Liu
- Changping Laboratory, Beijing, 102206, China
| | - Ye Zhang
- Department of Stomatology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, China
- Department of Oral Pathology, National Center of Stomatology, National Clinical Research Center for Oral Diseases, Peking University School and Hospital of Stomatology, National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing, China
- Research Unit of Precision Pathologic Diagnosis in Tumors of the Oral and Maxillofacial Regions, Chinese Academy of Medical Sciences (2019RU034), Beijing, China
| | - Yueying He
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Jingyao Wang
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Zicheng Ma
- Changping Laboratory, Beijing, 102206, China
| | - Tie-Jun Li
- Department of Oral Pathology, National Center of Stomatology, National Clinical Research Center for Oral Diseases, Peking University School and Hospital of Stomatology, National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing, China
- Research Unit of Precision Pathologic Diagnosis in Tumors of the Oral and Maxillofacial Regions, Chinese Academy of Medical Sciences (2019RU034), Beijing, China
| | - Jianyun Zhang
- Department of Oral Pathology, National Center of Stomatology, National Clinical Research Center for Oral Diseases, Peking University School and Hospital of Stomatology, National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing, China.
- Research Unit of Precision Pathologic Diagnosis in Tumors of the Oral and Maxillofacial Regions, Chinese Academy of Medical Sciences (2019RU034), Beijing, China.
| | - Yanyi Huang
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China.
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China.
- Institute for Cell Analysis, Shenzhen Bay Laboratory, Shenzhen, 528107, China.
| | - Yi Qin Gao
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China.
- Changping Laboratory, Beijing, 102206, China.
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China.
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19
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Stephenson-Gussinye A, Rendón-Bautista LA, Ruiz-Medina BE, Blanco-Olais E, Pérez-Molina R, Marcial-Medina C, Chavarri-Guerra Y, Soto-Pérez-de-Celis E, Morales-Alfaro A, Esquivel-López A, Candanedo-González F, Gamboa-Domínguez A, Cortes-González R, Alfaro-Goldaracena A, Vázquez-Manjarrez SE, Grajales-Figueroa G, Astudillo-Romero B, Ruiz-Manriquez J, Poot-Hernández AC, Licona-Limón P, Furlan-Magaril M. Obtention of viable cell suspensions from breast cancer tumor biopsies for 3D chromatin conformation and single-cell transcriptome analysis. Front Mol Biosci 2024; 11:1420308. [PMID: 39239354 PMCID: PMC11375512 DOI: 10.3389/fmolb.2024.1420308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Accepted: 07/16/2024] [Indexed: 09/07/2024] Open
Abstract
Molecular and cellular characterization of tumors is essential due to the complex and heterogeneous nature of cancer. In recent decades, many bioinformatic tools and experimental techniques have been developed to achieve personalized characterization of tumors. However, sample handling continues to be a major challenge as limitations such as prior treatments before sample acquisition, the amount of tissue obtained, transportation, or the inability to process fresh samples pose a hurdle for experimental strategies that require viable cell suspensions. Here, we present an optimized protocol that allows the recovery of highly viable cell suspensions from breast cancer primary tumor biopsies. Using these cell suspensions we have successfully characterized genome architecture through Hi-C. Also, we have evaluated single-cell gene expression and the tumor cellular microenvironment through single-cell RNAseq. Both technologies are key in the detailed and personalized molecular characterization of tumor samples. The protocol described here is a cost-effective alternative to obtain viable cell suspensions from biopsies simply and efficiently.
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Affiliation(s)
- Aura Stephenson-Gussinye
- Molecular Genetics Department, Institute of Cellular Physiology, National Autonomous University of Mexico, Mexico City, Mexico
| | - Luis A Rendón-Bautista
- Department of Cellular and Developmental Biology, Institute of Cellular Physiology, National Autonomous University of Mexico, Mexico City, Mexico
| | - Blanca E Ruiz-Medina
- Department of Cellular and Developmental Biology, Institute of Cellular Physiology, National Autonomous University of Mexico, Mexico City, Mexico
| | - Eduardo Blanco-Olais
- Molecular Genetics Department, Institute of Cellular Physiology, National Autonomous University of Mexico, Mexico City, Mexico
| | - Rosario Pérez-Molina
- Molecular Genetics Department, Institute of Cellular Physiology, National Autonomous University of Mexico, Mexico City, Mexico
| | - Cleofas Marcial-Medina
- Department of Cellular and Developmental Biology, Institute of Cellular Physiology, National Autonomous University of Mexico, Mexico City, Mexico
| | - Yanin Chavarri-Guerra
- Department of Hemato-Oncology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Enrique Soto-Pérez-de-Celis
- Department of Geriatrics, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
- Department of Medicine, Division of Medical Oncology, University of Colorado Cancer Center, Denver, CO, United States
| | - Andrea Morales-Alfaro
- Department of Medicine, Division of Medical Oncology, University of Colorado Cancer Center, Denver, CO, United States
| | - Ayerim Esquivel-López
- Molecular Genetics Department, Institute of Cellular Physiology, National Autonomous University of Mexico, Mexico City, Mexico
| | - Fernando Candanedo-González
- Department of Pathology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Armando Gamboa-Domínguez
- Department of Pathology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Rubén Cortes-González
- Surgical Oncology Service, Department of Surgery, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Alejandro Alfaro-Goldaracena
- Surgical Oncology Service, Department of Surgery, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Sara E Vázquez-Manjarrez
- Department of Radiology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Guido Grajales-Figueroa
- Department of Gastrointestinal Endoscopy, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Beatriz Astudillo-Romero
- Department of Gastrointestinal Endoscopy, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Jesús Ruiz-Manriquez
- Department of Gastrointestinal Endoscopy, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - A César Poot-Hernández
- Unidad de Bioinformática y Manejo de Información, Institute of Cellular Physiology, National Autonomous University of Mexico, Mexico City, Mexico
| | - Paula Licona-Limón
- Department of Cellular and Developmental Biology, Institute of Cellular Physiology, National Autonomous University of Mexico, Mexico City, Mexico
| | - Mayra Furlan-Magaril
- Molecular Genetics Department, Institute of Cellular Physiology, National Autonomous University of Mexico, Mexico City, Mexico
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20
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Rossini R, Oshaghi M, Nekrasov M, Bellanger A, Domaschenz R, Dijkwel Y, Abdelhalim M, Collas P, Tremethick D, Paulsen J. Loss of multi-level 3D genome organization during breast cancer progression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.26.568711. [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) are overall maintained, 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 is accompanied by the formation of de novo enhancer contacts and activation of MYC, illustrating how structural genomic variants can alter the 3D genome to drive oncogenic states. In summary, our findings provide evidence for the loss 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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21
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Fang T, Liu Y, Woicik A, Lu M, Jha A, Wang X, Li G, Hristov B, Liu Z, Xu H, Noble WS, Wang S. Enhancing Hi-C contact matrices for loop detection with Capricorn: a multiview diffusion model. Bioinformatics 2024; 40:i471-i480. [PMID: 38940142 PMCID: PMC11211821 DOI: 10.1093/bioinformatics/btae211] [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] [Indexed: 06/29/2024] Open
Abstract
MOTIVATION High-resolution Hi-C contact matrices reveal the detailed three-dimensional architecture of the genome, but high-coverage experimental Hi-C data are expensive to generate. Simultaneously, chromatin structure analyses struggle with extremely sparse contact matrices. To address this problem, computational methods to enhance low-coverage contact matrices have been developed, but existing methods are largely based on resolution enhancement methods for natural images and hence often employ models that do not distinguish between biologically meaningful contacts, such as loops and other stochastic contacts. RESULTS We present Capricorn, a machine learning model for Hi-C resolution enhancement that incorporates small-scale chromatin features as additional views of the input Hi-C contact matrix and leverages a diffusion probability model backbone to generate a high-coverage matrix. We show that Capricorn outperforms the state of the art in a cross-cell-line setting, improving on existing methods by 17% in mean squared error and 26% in F1 score for chromatin loop identification from the generated high-coverage data. We also demonstrate that Capricorn performs well in the cross-chromosome setting and cross-chromosome, cross-cell-line setting, improving the downstream loop F1 score by 14% relative to existing methods. We further show that our multiview idea can also be used to improve several existing methods, HiCARN and HiCNN, indicating the wide applicability of this approach. Finally, we use DNA sequence to validate discovered loops and find that the fraction of CTCF-supported loops from Capricorn is similar to those identified from the high-coverage data. Capricorn is a powerful Hi-C resolution enhancement method that enables scientists to find chromatin features that cannot be identified in the low-coverage contact matrix. AVAILABILITY AND IMPLEMENTATION Implementation of Capricorn and source code for reproducing all figures in this paper are available at https://github.com/CHNFTQ/Capricorn.
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Affiliation(s)
- Tangqi Fang
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, United States
| | - Yifeng Liu
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, United States
| | - Addie Woicik
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, United States
| | - Minsi Lu
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, United States
| | - Anupama Jha
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, United States
| | - Xiao Wang
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, United States
| | - Gang Li
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, United States
- eScience Institute, University of Washington, Seattle, WA 98195, United States
| | - Borislav Hristov
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, United States
| | - Zixuan Liu
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, United States
| | - Hanwen Xu
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, United States
| | - William S Noble
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, United States
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, United States
| | - Sheng Wang
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, United States
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22
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Ma F, Cao Y, Du H, Braikia FZ, Zong L, Ollikainen N, Bayer M, Qiu X, Park B, Roy R, Nandi S, Sarantopoulou D, Ziman A, Bianchi AH, Beerman I, Zhao K, Grosschedl R, Sen R. Three-dimensional chromatin reorganization regulates B cell development during ageing. Nat Cell Biol 2024; 26:991-1002. [PMID: 38866970 PMCID: PMC11178499 DOI: 10.1038/s41556-024-01424-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 04/16/2024] [Indexed: 06/14/2024]
Abstract
The contribution of three-dimensional genome organization to physiological ageing is not well known. Here we show that large-scale chromatin reorganization distinguishes young and old bone marrow progenitor (pro-) B cells. These changes result in increased interactions at the compartment level and reduced interactions within topologically associated domains (TADs). The gene encoding Ebf1, a key B cell regulator, switches from compartment A to B with age. Genetically reducing Ebf1 recapitulates some features of old pro-B cells. TADs that are most reduced with age contain genes important for B cell development, including the immunoglobulin heavy chain (Igh) locus. Weaker intra-TAD interactions at Igh correlate with altered variable (V), diversity (D) and joining (J) gene recombination. Our observations implicate three-dimensional chromatin reorganization as a major driver of pro-B cell phenotypes that impair B lymphopoiesis with age.
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Affiliation(s)
- Fei Ma
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, Baltimore, MD, USA
| | - Yaqiang Cao
- Laboratory of Epigenome Biology, Systems Biology Center, National Heart, Lung and Blood Institute, Bethesda, MD, USA
| | - Hansen Du
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, Baltimore, MD, USA
| | - Fatima Zohra Braikia
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, Baltimore, MD, USA
| | - Le Zong
- Epigenetics and Stem Cell Init, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Noah Ollikainen
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, Baltimore, MD, USA
| | - Marc Bayer
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | - Xiang Qiu
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, Baltimore, MD, USA
| | - Bongsoo Park
- Epigenetics and Stem Cell Init, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Roshni Roy
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, Baltimore, MD, USA
| | - Satabdi Nandi
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, Baltimore, MD, USA
| | - Dimitra Sarantopoulou
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, Baltimore, MD, USA
| | | | - Aisha Haley Bianchi
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, Baltimore, MD, USA
| | - Isabel Beerman
- Epigenetics and Stem Cell Init, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Keji Zhao
- Laboratory of Epigenome Biology, Systems Biology Center, National Heart, Lung and Blood Institute, Bethesda, MD, USA
| | - Rudolf Grosschedl
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | - Ranjan Sen
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, Baltimore, MD, USA.
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23
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Chang L, Xie Y, Taylor B, Wang Z, Sun J, Tan TR, Bejar R, Chen CC, Furnari FB, Hu M, Ren B. Droplet Hi-C for Fast and Scalable Profiling of Chromatin Architecture in Single Cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.18.590148. [PMID: 38712075 PMCID: PMC11071305 DOI: 10.1101/2024.04.18.590148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Comprehensive analysis of chromatin architecture is crucial for understanding the gene regulatory programs during development and in disease pathogenesis, yet current methods often inadequately address the unique challenges presented by analysis of heterogeneous tissue samples. Here, we introduce Droplet Hi-C, which employs a commercial microfluidic device for high-throughput, single-cell chromatin conformation profiling in droplets. Using Droplet Hi-C, we mapped the chromatin architecture at single-cell resolution from the mouse cortex and analyzed gene regulatory programs in major cortical cell types. Additionally, we used this technique to detect copy number variation (CNV), structural variations (SVs) and extrachromosomal DNA (ecDNA) in cancer cells, revealing clonal dynamics and other oncogenic events during treatment. We further refined this technique to allow for joint profiling of chromatin architecture and transcriptome in single cells, facilitating a more comprehensive exploration of the links between chromatin architecture and gene expression in both normal tissues and tumors. Thus, Droplet Hi-C not only addresses critical gaps in chromatin analysis of heterogeneous tissues but also emerges as a versatile tool enhancing our understanding of gene regulation in health and disease.
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Affiliation(s)
- Lei Chang
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Yang Xie
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA, USA
| | - Brett Taylor
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Medical Scientist Training Program, University of California, San Diego, La Jolla, CA, USA
| | - Zhaoning Wang
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Jiachen Sun
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
- Department of Systems Biology and Bioinformatics, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Tuyet R. Tan
- Moores Cancer Center, UC San Diego, La Jolla, CA, USA
| | - Rafael Bejar
- Moores Cancer Center, UC San Diego, La Jolla, CA, USA
| | - Clark C. Chen
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN, USA
| | - Frank B. Furnari
- Department of Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Ming Hu
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Epigenomics, Institute for Genomic Medicine, Moores Cancer Center, University of California, San Diego, School of Medicine, La Jolla, CA, USA
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24
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Camerino M, Chang W, Cvekl A. Analysis of long-range chromatin contacts, compartments and looping between mouse embryonic stem cells, lens epithelium and lens fibers. Epigenetics Chromatin 2024; 17:10. [PMID: 38643244 PMCID: PMC11031936 DOI: 10.1186/s13072-024-00533-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: 11/15/2023] [Accepted: 03/08/2024] [Indexed: 04/22/2024] Open
Abstract
BACKGROUND Nuclear organization of interphase chromosomes involves individual chromosome territories, "open" and "closed" chromatin compartments, topologically associated domains (TADs) and chromatin loops. The DNA- and RNA-binding transcription factor CTCF together with the cohesin complex serve as major organizers of chromatin architecture. Cellular differentiation is driven by temporally and spatially coordinated gene expression that requires chromatin changes of individual loci of various complexities. Lens differentiation represents an advantageous system to probe transcriptional mechanisms underlying tissue-specific gene expression including high transcriptional outputs of individual crystallin genes until the mature lens fiber cells degrade their nuclei. RESULTS Chromatin organization between mouse embryonic stem (ES) cells, newborn (P0.5) lens epithelium and fiber cells were analyzed using Hi-C. Localization of CTCF in both lens chromatins was determined by ChIP-seq and compared with ES cells. Quantitative analyses show major differences between number and size of TADs and chromatin loop size between these three cell types. In depth analyses show similarities between lens samples exemplified by overlaps between compartments A and B. Lens epithelium-specific CTCF peaks are found in mostly methylated genomic regions while lens fiber-specific and shared peaks occur mostly within unmethylated DNA regions. Major differences in TADs and loops are illustrated at the ~ 500 kb Pax6 locus, encoding the critical lens regulatory transcription factor and within a larger ~ 15 Mb WAGR locus, containing Pax6 and other loci linked to human congenital diseases. Lens and ES cell Hi-C data (TADs and loops) together with ATAC-seq, CTCF, H3K27ac, H3K27me3 and ENCODE cis-regulatory sites are shown in detail for the Pax6, Sox1 and Hif1a loci, multiple crystallin genes and other important loci required for lens morphogenesis. The majority of crystallin loci are marked by unexpectedly high CTCF-binding across their transcribed regions. CONCLUSIONS Our study has generated the first data on 3-dimensional (3D) nuclear organization in lens epithelium and lens fibers and directly compared these data with ES cells. These findings generate novel insights into lens-specific transcriptional gene control, open new research avenues to study transcriptional condensates in lens fiber cells, and enable studies of non-coding genetic variants linked to cataract and other lens and ocular abnormalities.
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Affiliation(s)
- Michael Camerino
- The Departments Genetics, Albert Einstein College of Medicine, NY10461, Bronx, USA
| | - William Chang
- Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, NY10461, Bronx, USA
| | - Ales Cvekl
- The Departments Genetics, Albert Einstein College of Medicine, NY10461, Bronx, USA.
- Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, NY10461, Bronx, USA.
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25
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Choppavarapu L, Fang K, Liu T, Jin VX. Hi-C profiling in tissues reveals 3D chromatin-regulated breast tumor heterogeneity and tumor-specific looping-mediated biological pathways. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.13.584872. [PMID: 38559097 PMCID: PMC10979939 DOI: 10.1101/2024.03.13.584872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Current knowledge in three-dimensional (3D) chromatin regulation in normal and disease states was mostly accumulated through Hi-C profiling in in vitro cell culture system. The limitations include failing to recapitulate disease-specific physiological properties and often lacking clinically relevant disease microenvironment. In this study, we conduct tissue-specific Hi-C profiling in a pilot cohort of 12 breast tissues comprising of two normal tissues (NTs) and ten ER+ breast tumor tissues (TTs) including five primary tumors (PTs), and five tamoxifen-treated recurrent tumors (RTs). We find largely preserved compartments, highly heterogeneous topological associated domains (TADs) and intensively variable chromatin loops among breast tumors, demonstrating 3D chromatin-regulated breast tumor heterogeneity. Further cross-examination identifies RT-specific looping-mediated biological pathways and suggests CA2, an enhancer-promoter looping (EPL)-mediated target gene within the bicarbonate transport metabolism pathway, might play a role in driving the tamoxifen resistance. Remarkably, the inhibition of CA2 not only impedes tumor growth both in vitro and in vivo , but also reverses chromatin looping. Our study thus yields significant mechanistic insights into the role and clinical relevance of 3D chromatin architecture in breast cancer endocrine resistance.
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26
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Rapoport R, Greenberg A, Yakhini Z, Simon I. A Cyclic Permutation Approach to Removing Spatial Dependency between Clustered Gene Ontology Terms. BIOLOGY 2024; 13:175. [PMID: 38534445 PMCID: PMC10967837 DOI: 10.3390/biology13030175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 03/04/2024] [Accepted: 03/05/2024] [Indexed: 03/28/2024]
Abstract
Traditional gene set enrichment analysis falters when applied to large genomic domains, where neighboring genes often share functions. This spatial dependency creates misleading enrichments, mistaking mere physical proximity for genuine biological connections. Here we present Spatial Adjusted Gene Ontology (SAGO), a novel cyclic permutation-based approach, to tackle this challenge. SAGO separates enrichments due to spatial proximity from genuine biological links by incorporating the genes' spatial arrangement into the analysis. We applied SAGO to various datasets in which the identified genomic intervals are large, including replication timing domains, large H3K9me3 and H3K27me3 domains, HiC compartments and lamina-associated domains (LADs). Intriguingly, applying SAGO to prostate cancer samples with large copy number alteration (CNA) domains eliminated most of the enriched GO terms, thus helping to accurately identify biologically relevant gene sets linked to oncogenic processes, free from spatial bias.
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Affiliation(s)
- Rachel Rapoport
- Microbiology and Molecular Genetics, Hebrew University of Jerusalem-IMRIC, Jerusalem 9112102, Israel
| | - Avraham Greenberg
- Microbiology and Molecular Genetics, Hebrew University of Jerusalem-IMRIC, Jerusalem 9112102, Israel
| | - Zohar Yakhini
- Efi Arazi School of Computer Science, Reichman University (IDC Herzliya), Herzliya 4610101, Israel
- Department of Computer Science, Technion-Israel Institute of Technology, Haifa 3200003, Israel
| | - Itamar Simon
- Microbiology and Molecular Genetics, Hebrew University of Jerusalem-IMRIC, Jerusalem 9112102, Israel
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27
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Wall BPG, Nguyen M, Harrell JC, Dozmorov MG. Machine and deep learning methods for predicting 3D genome organization. ARXIV 2024:arXiv:2403.03231v1. [PMID: 38495565 PMCID: PMC10942493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Three-Dimensional (3D) chromatin interactions, such as enhancer-promoter interactions (EPIs), loops, Topologically Associating Domains (TADs), and A/B compartments play critical roles in a wide range of cellular processes by regulating gene expression. Recent development of chromatin conformation capture technologies has enabled genome-wide profiling of various 3D structures, even with single cells. However, current catalogs of 3D structures remain incomplete and unreliable due to differences in technology, tools, and low data resolution. Machine learning methods have emerged as an alternative to obtain missing 3D interactions and/or improve resolution. Such methods frequently use genome annotation data (ChIP-seq, DNAse-seq, etc.), DNA sequencing information (k-mers, Transcription Factor Binding Site (TFBS) motifs), and other genomic properties to learn the associations between genomic features and chromatin interactions. In this review, we discuss computational tools for predicting three types of 3D interactions (EPIs, chromatin interactions, TAD boundaries) and analyze their pros and cons. We also point out obstacles of computational prediction of 3D interactions and suggest future research directions.
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Affiliation(s)
- Brydon P. G. Wall
- Center for Biological Data Science, Virginia Commonwealth University, Richmond, VA, 23284, USA
| | - My Nguyen
- Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, 23298, USA
| | - J. Chuck Harrell
- Department of Pathology, Virginia Commonwealth University, Richmond, VA, 23284, USA
- Massey Comprehensive Cancer Center, Virginia Commonwealth University, Richmond, VA 23298, USA
- Center for Pharmaceutical Engineering, Virginia Commonwealth University, Richmond, VA 23298, USA
| | - Mikhail G. Dozmorov
- Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, 23298, USA
- Department of Pathology, Virginia Commonwealth University, Richmond, VA, 23284, USA
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28
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Marie P, Bazire M, Ladet J, Ameur LB, Chahar S, Fontrodona N, Sexton T, Auboeuf D, Bourgeois CF, Mortreux F. Gene-to-gene coordinated regulation of transcription and alternative splicing by 3D chromatin remodeling upon NF-κB activation. Nucleic Acids Res 2024; 52:1527-1543. [PMID: 38272542 PMCID: PMC10899780 DOI: 10.1093/nar/gkae015] [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: 06/10/2023] [Revised: 12/13/2023] [Accepted: 01/05/2024] [Indexed: 01/27/2024] Open
Abstract
The NF-κB protein p65/RelA plays a pivotal role in coordinating gene expression in response to diverse stimuli, including viral infections. At the chromatin level, p65/RelA regulates gene transcription and alternative splicing through promoter enrichment and genomic exon occupancy, respectively. The intricate ways in which p65/RelA simultaneously governs these functions across various genes remain to be fully elucidated. In this study, we employed the HTLV-1 Tax oncoprotein, a potent activator of NF-κB, to investigate its influence on the three-dimensional organization of the genome, a key factor in gene regulation. We discovered that Tax restructures the 3D genomic landscape, bringing together genes based on their regulation and splicing patterns. Notably, we found that the Tax-induced gene-gene contact between the two master genes NFKBIA and RELA is associated with their respective changes in gene expression and alternative splicing. Through dCas9-mediated approaches, we demonstrated that NFKBIA-RELA interaction is required for alternative splicing regulation and is caused by an intragenic enrichment of p65/RelA on RELA. Our findings shed light on new regulatory mechanisms upon HTLV-1 Tax and underscore the integral role of p65/RelA in coordinated regulation of NF-κB-responsive genes at both transcriptional and splicing levels in the context of the 3D genome.
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Affiliation(s)
- Paul Marie
- Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, Laboratory of Biology and Modelling of the Cell, 46 Allée d’Italie Site Jacques Monod, F-69007 Lyon, France
| | - Matéo Bazire
- Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, Laboratory of Biology and Modelling of the Cell, 46 Allée d’Italie Site Jacques Monod, F-69007 Lyon, France
| | - Julien Ladet
- Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, Laboratory of Biology and Modelling of the Cell, 46 Allée d’Italie Site Jacques Monod, F-69007 Lyon, France
| | - Lamya Ben Ameur
- Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, Laboratory of Biology and Modelling of the Cell, 46 Allée d’Italie Site Jacques Monod, F-69007 Lyon, France
| | - Sanjay Chahar
- Institute of Genetics and Molecular and Cellular Biology (IGBMC), UMR7104, Centre National de la Recherche Scientifique, U1258, Institut National de la Santé et de la Recherche Médicale, University of Strasbourg, 6704 Illkirch, France
| | - Nicolas Fontrodona
- Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, Laboratory of Biology and Modelling of the Cell, 46 Allée d’Italie Site Jacques Monod, F-69007 Lyon, France
| | - Tom Sexton
- Institute of Genetics and Molecular and Cellular Biology (IGBMC), UMR7104, Centre National de la Recherche Scientifique, U1258, Institut National de la Santé et de la Recherche Médicale, University of Strasbourg, 6704 Illkirch, France
| | - Didier Auboeuf
- Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, Laboratory of Biology and Modelling of the Cell, 46 Allée d’Italie Site Jacques Monod, F-69007 Lyon, France
| | - Cyril F Bourgeois
- Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, Laboratory of Biology and Modelling of the Cell, 46 Allée d’Italie Site Jacques Monod, F-69007 Lyon, France
| | - Franck Mortreux
- Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, Laboratory of Biology and Modelling of the Cell, 46 Allée d’Italie Site Jacques Monod, F-69007 Lyon, France
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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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30
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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: 3] [Impact Index Per Article: 3.0] [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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31
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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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32
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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: 15] [Impact Index Per Article: 7.5] [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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33
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Tian W, Zhou J, Bartlett A, Zeng Q, Liu H, Castanon RG, Kenworthy M, Altshul J, Valadon C, Aldridge A, Nery JR, Chen H, Xu J, Johnson ND, Lucero J, Osteen JK, Emerson N, Rink J, Lee J, Li Y, Siletti K, Liem M, Claffey N, O’Connor C, Yanny AM, Nyhus J, Dee N, Casper T, Shapovalova N, Hirschstein D, Ding SL, Hodge R, Levi BP, Keene CD, Linnarsson S, Lein E, Ren B, Behrens MM, Ecker JR. Single-cell DNA methylation and 3D genome architecture in the human brain. Science 2023; 382:eadf5357. [PMID: 37824674 PMCID: PMC10572106 DOI: 10.1126/science.adf5357] [Citation(s) in RCA: 61] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 09/05/2023] [Indexed: 10/14/2023]
Abstract
Delineating the gene-regulatory programs underlying complex cell types is fundamental for understanding brain function in health and disease. Here, we comprehensively examined human brain cell epigenomes by probing DNA methylation and chromatin conformation at single-cell resolution in 517 thousand cells (399 thousand neurons and 118 thousand non-neurons) from 46 regions of three adult male brains. We identified 188 cell types and characterized their molecular signatures. Integrative analyses revealed concordant changes in DNA methylation, chromatin accessibility, chromatin organization, and gene expression across cell types, cortical areas, and basal ganglia structures. We further developed single-cell methylation barcodes that reliably predict brain cell types using the methylation status of select genomic sites. This multimodal epigenomic brain cell atlas provides new insights into the complexity of cell-type-specific gene regulation in adult human brains.
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Affiliation(s)
- Wei Tian
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jingtian Zhou
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92037, USA
| | - Anna Bartlett
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Qiurui Zeng
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92037, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Rosa G. Castanon
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Mia Kenworthy
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jordan Altshul
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Cynthia Valadon
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Andrew Aldridge
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Joseph R. Nery
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Huaming Chen
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jiaying Xu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Nicholas D. Johnson
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jacinta Lucero
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Julia K. Osteen
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Nora Emerson
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jon Rink
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jasper Lee
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Yang Li
- Ludwig Institute for Cancer Research, La Jolla, CA 92037, USA
| | - Kimberly Siletti
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet; 171 77 Stockholm, Sweden
| | - Michelle Liem
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Naomi Claffey
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Caz O’Connor
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | | | - Julie Nyhus
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Nick Dee
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Tamara Casper
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | | | | | - Song-Lin Ding
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Rebecca Hodge
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Boaz P. Levi
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - C. Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - Sten Linnarsson
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet; 171 77 Stockholm, Sweden
| | - Ed Lein
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Bing Ren
- Ludwig Institute for Cancer Research, La Jolla, CA 92037, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA 92037, USA
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA 92037, USA
- Institute of Genomic Medicine, University of California, San Diego School of Medicine, La Jolla, CA 92037, USA
- Moores Cancer Center, University of California, San Diego School of Medicine, La Jolla, CA 92037, USA
| | - M. Margarita Behrens
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Joseph R. Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
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Kai Y, Liu N, Orkin SH, Yuan GC. Identifying quantitatively differential chromosomal compartmentalization changes and their biological significance from Hi-C data using DARIC. BMC Genomics 2023; 24:614. [PMID: 37833630 PMCID: PMC10571287 DOI: 10.1186/s12864-023-09675-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 09/12/2023] [Indexed: 10/15/2023] Open
Abstract
BACKGROUND Chromosomal compartmentalization plays a critical role in maintaining proper transcriptional programs in cell differentiation and oncogenesis. However, currently the prevalent method for comparative analysis of compartmentalization landscapes between different cell types is limited to the qualitative switched compartments. RESULTS To identify genomic regions with quantitatively differential compartmentalization changes from genome-wide chromatin conformation data like Hi-C, we developed a computational framework named DARIC. DARIC includes three modules: compartmentalization quantification, normalization, and differential analysis. Comparing DARIC with the conventional compartment switching analysis reveals substantial regions characterized by quantitatively significant compartmentalization changes without switching. These changes are accompanied by changes in gene expression, chromatin accessibility, H3K27ac intensity, as well as the interactions with nuclear lamina proteins and nuclear positioning, highlighting the functional importance of such quantitative changes in gene regulation. We applied DARIC to dissect the quantitative compartmentalization changes during human cardiomyocyte differentiation and identified two distinct mechanisms for gene activation based on the association with compartmentalization changes. Using the quantitative compartmentalization measurement module from DARIC, we further dissected the compartment variability landscape in the human genome by analyzing a compendium of 32 Hi-C datasets from 4DN. We discovered an interesting correlation between compartmentalization variability and sub-compartments. CONCLUSIONS DARIC is a useful tool for analyzing quantitative compartmentalization changes and mining novel biological insights from increasing Hi-C data. Our results demonstrate the functional significance of quantitative compartmentalization changes in gene regulation, and provide new insights into the relationship between compartmentalization variability and sub-compartments in the human genome.
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Affiliation(s)
- Yan Kai
- Cancer and Blood Disorders Center, Boston Children's Hospital and Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02115, USA
| | - Nan Liu
- Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 311121, China
| | - Stuart H Orkin
- Cancer and Blood Disorders Center, Boston Children's Hospital and Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02115, USA.
- Howards Hughes Medical Institute, Boston, MA, 02115, USA.
| | - Guo-Cheng Yuan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, Charles Bronfman Institute for Precision Medicine, New York, NY, 10029, USA.
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35
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Raffo A, Paulsen J. The shape of chromatin: insights from computational recognition of geometric patterns in Hi-C data. Brief Bioinform 2023; 24:bbad302. [PMID: 37646128 PMCID: PMC10516369 DOI: 10.1093/bib/bbad302] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 07/05/2023] [Accepted: 08/03/2023] [Indexed: 09/01/2023] Open
Abstract
The three-dimensional organization of chromatin plays a crucial role in gene regulation and cellular processes like deoxyribonucleic acid (DNA) transcription, replication and repair. Hi-C and related techniques provide detailed views of spatial proximities within the nucleus. However, data analysis is challenging partially due to a lack of well-defined, underpinning mathematical frameworks. Recently, recognizing and analyzing geometric patterns in Hi-C data has emerged as a powerful approach. This review provides a summary of algorithms for automatic recognition and analysis of geometric patterns in Hi-C data and their correspondence with chromatin structure. We classify existing algorithms on the basis of the data representation and pattern recognition paradigm they make use of. Finally, we outline some of the challenges ahead and promising future directions.
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Affiliation(s)
- Andrea Raffo
- Department of Biosciences, University of Oslo, 0316 Oslo, Norway
| | - Jonas Paulsen
- Department of Biosciences, University of Oslo, 0316 Oslo, Norway
- Centre for Bioinformatics, Department of Informatics, University of Oslo, 0316 Oslo, Norway
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Gregoricchio S, Zwart W. snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis. BIOINFORMATICS ADVANCES 2023; 3:vbad080. [PMID: 37397353 PMCID: PMC10307938 DOI: 10.1093/bioadv/vbad080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 06/12/2023] [Accepted: 06/20/2023] [Indexed: 07/04/2023]
Abstract
Summary Genome-wide chromosome conformation capture (Hi-C) is a technique that allows the study of 3D genome organization. Despite being widely used, analysis of Hi-C data is technically challenging and involves several time-consuming steps that often require manual involvement making it error prone, potentially affecting data reproducibility. In order to facilitate and simplify these analyses we implemented snHiC, a snakemake-based pipeline that allows for the generation of contact matrices at multiple resolutions in one single run, aggregation of individual samples into user-specified groups, detection of domains, compartments, loops and stripes and performance of differential compartment and chromatin interaction analyses. Availability and implementation Source code is freely available at https://github.com/sebastian-gregoricchio/snHiC. A yaml-formatted file (snHiC/workflow/envs/snHiC_conda_env_stable.yaml) is available to build a compatible conda environment. Supplementary information Supplementary data are available at Bioinformatics Advances online.
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Krasikova A, Kulikova T, Rodriguez Ramos JS, Maslova A. Assignment of the somatic A/B compartments to chromatin domains in giant transcriptionally active lampbrush chromosomes. Epigenetics Chromatin 2023; 16:24. [PMID: 37322523 DOI: 10.1186/s13072-023-00499-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 06/04/2023] [Indexed: 06/17/2023] Open
Abstract
BACKGROUND The three-dimensional configuration of the eukaryotic genome is an emerging area of research. Chromosome conformation capture outlined genome segregation into large scale A and B compartments corresponding mainly to transcriptionally active and repressive chromatin. It remains unknown how the compartmentalization of the genome changes in growing oocytes of animals with hypertranscriptional type of oogenesis. Such oocytes are characterized by highly elongated chromosomes, called lampbrush chromosomes, which acquire a typical chromomere-loop appearance, representing one of the classical model systems for exploring the structural and functional organization of chromatin domains. RESULTS Here, we compared the distribution of A/B compartments in chicken somatic cells with chromatin domains in lampbrush chromosomes. We found that in lampbrush chromosomes, the extended chromatin domains, restricted by compartment boundaries in somatic cells, disintegrate into individual chromomeres. Next, we performed FISH-mapping of the genomic loci, which belong to A or B chromatin compartments as well as to A/B compartment transition regions in embryonic fibroblasts on isolated lampbrush chromosomes. We found, that in chicken lampbrush chromosomes, clusters of dense compact chromomeres bearing short lateral loops and enriched with repressive epigenetic modifications generally correspond to constitutive B compartments in somatic cells. A compartments align with lampbrush chromosome segments with smaller, less compact chromomeres, longer lateral loops, and a higher transcriptional status. Clusters of small loose chromomeres with relatively long lateral loops show no obvious correspondence with either A or B compartment identity. Some genes belonging to facultative B (sub-) compartments can be tissue-specifically transcribed during oogenesis, forming distinct lateral loops. CONCLUSIONS Here, we established a correspondence between the A/B compartments in somatic interphase nucleus and chromatin segments in giant lampbrush chromosomes from diplotene stage oocytes. The chromomere-loop structure of the genomic regions corresponding to interphase A and B compartments reveals the difference in how they are organized at the level of chromatin domains. The results obtained also suggest that gene-poor regions tend to be packed into chromomeres.
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Affiliation(s)
- Alla Krasikova
- Saint-Petersburg State University, Saint-Petersburg, Russia.
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Kai Y, Liu N, Orkin SH, Yuan GC. Identifying Quantitatively Differential Chromosomal Compartmentalization Changes and Their Biological Significance from Hi-C data using DARIC. RESEARCH SQUARE 2023:rs.3.rs-2814806. [PMID: 37162846 PMCID: PMC10168473 DOI: 10.21203/rs.3.rs-2814806/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Background Chromosomal compartmentalization plays a critical role in maintaining proper transcriptional programs in cell differentiation and oncogenesis. However, currently the prevalent method for comparative analysis of compartmentalization landscapes between different cell types is limited to the qualitative switched compartments. Results To identify genomic regions with quantitatively differential compartmentalization changes from genome-wide chromatin conformation data like Hi-C, we developed a computational framework named DARIC. DARIC includes three modules: compartmentalization quantification, normalization, and differential analysis. Comparing DARIC with the conventional compartment switching analysis reveals substantial regions characterized by quantitatively significant compartmentalization changes without switching. These changes are accompanied by changes in gene expression, chromatin accessibility, H3K27ac intensity, as well as the interactions with nuclear lamina proteins and nuclear positioning, highlighting the functional importance of such quantitative changes in gene regulation. We applied DARIC to dissect the quantitative compartmentalization changes during human cardiomyocyte differentiation and identified two distinct mechanisms for gene activation based on the association with compartmentalization changes. Using the quantitative compartmentalization measurement module from DARIC, we further dissected the compartment variability landscape in the human genome by analyzing a compendium of 32 Hi-C datasets from 4DN. We discovered an interesting correlation between compartmentalization variability and sub-compartments. Conclusions DARIC is a useful tool for analyzing quantitative compartmentalization changes and mining novel biological insights from increasing Hi-C data. Our results demonstrate the functional significance of quantitative compartmentalization changes in gene regulation, and provide new insights into the relationship between compartmentalization variability and sub-compartments in the human genome.
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Affiliation(s)
| | - Nan Liu
- Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, 310003 Hangzhou, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 311121, China
| | - Stuart H Orkin
- Howards Hughes Medical Institute, Boston MA 02115, USA
- Lead contact
| | - Guo-Cheng Yuan
- Department of Genetics and Genomic Sciences, Charles Bronfman Institute for Precision Medicine, Icahn School of Medicine at Mount Sinai, New York NY 10029, USA
- Lead contact
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Kalluchi A, Harris HL, Reznicek TE, Rowley MJ. Considerations and caveats for analyzing chromatin compartments. Front Mol Biosci 2023; 10:1168562. [PMID: 37091873 PMCID: PMC10113542 DOI: 10.3389/fmolb.2023.1168562] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 03/27/2023] [Indexed: 04/08/2023] Open
Abstract
Genomes are organized into nuclear compartments, separating active from inactive chromatin. Chromatin compartments are readily visible in a large number of species by experiments that map chromatin conformation genome-wide. When analyzing these maps, a common step is the identification of genomic intervals that interact within A (active) and B (inactive) compartments. It has also become increasingly common to identify and analyze subcompartments. We review different strategies to identify A/B and subcompartment intervals, including a discussion of various machine-learning approaches to predict these features. We then discuss the strengths and limitations of current strategies and examine how these aspects of analysis may have impacted our understanding of chromatin compartments.
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Affiliation(s)
| | | | | | - M. Jordan Rowley
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE, United States
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Wang C, Liu X, Liang J, Narita Y, Ding W, Li D, Zhang L, Wang H, Leong MML, Hou I, Gerdt C, Jiang C, Zhong Q, Tang Z, Forney C, Kottyan L, Weirauch MT, Gewurz BE, Zeng MS, Jiang S, Teng M, Zhao B. A DNA tumor virus globally reprograms host 3D genome architecture to achieve immortal growth. Nat Commun 2023; 14:1598. [PMID: 36949074 PMCID: PMC10033825 DOI: 10.1038/s41467-023-37347-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Accepted: 03/13/2023] [Indexed: 03/24/2023] Open
Abstract
Epstein-Barr virus (EBV) immortalization of resting B lymphocytes (RBLs) to lymphoblastoid cell lines (LCLs) models human DNA tumor virus oncogenesis. RBL and LCL chromatin interaction maps are compared to identify the spatial and temporal genome architectural changes during EBV B cell transformation. EBV induces global genome reorganization where contact domains frequently merge or subdivide during transformation. Repressed B compartments in RBLs frequently switch to active A compartments in LCLs. LCLs gain 40% new contact domain boundaries. Newly gained LCL boundaries have strong CTCF binding at their borders while in RBLs, the same sites have much less CTCF binding. Some LCL CTCF sites also have EBV nuclear antigen (EBNA) leader protein EBNALP binding. LCLs have more local interactions than RBLs at LCL dependency factors and super-enhancer targets. RNA Pol II HiChIP and FISH of RBL and LCL further validate the Hi-C results. EBNA3A inactivation globally alters LCL genome interactions. EBNA3A inactivation reduces CTCF and RAD21 DNA binding. EBNA3C inactivation rewires the looping at the CDKN2A/B and AICDA loci. Disruption of a CTCF site at AICDA locus increases AICDA expression. These data suggest that EBV controls lymphocyte growth by globally reorganizing host genome architecture to facilitate the expression of key oncogenes.
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Affiliation(s)
- Chong Wang
- Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA
- Department of Diagnostic and Biological Sciences, School of Dentistry, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Xiang Liu
- Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33612, USA
| | - Jun Liang
- Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Yohei Narita
- Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Weiyue Ding
- Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Difei Li
- Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Luyao Zhang
- Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Hongbo Wang
- Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Merrin Man Long Leong
- Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Isabella Hou
- Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Catherine Gerdt
- Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Chang Jiang
- Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA
- Department of Cancer Physiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33612, USA
| | - Qian Zhong
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Zhonghui Tang
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510060, China
| | - Carmy Forney
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
| | - Leah Kottyan
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
| | - Matthew T Weirauch
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
| | - Benjamin E Gewurz
- Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Mu-Sheng Zeng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Sizun Jiang
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, 02115, USA.
| | - Mingxiang Teng
- Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33612, USA.
| | - Bo Zhao
- Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA.
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Plaza-Jennings AL, Valada A, O'Shea C, Iskhakova M, Hu B, Javidfar B, Ben Hutta G, Lambert TY, Murray J, Kassim B, Chandrasekaran S, Chen BK, Morgello S, Won H, Akbarian S. HIV integration in the human brain is linked to microglial activation and 3D genome remodeling. Mol Cell 2022; 82:4647-4663.e8. [PMID: 36525955 PMCID: PMC9831062 DOI: 10.1016/j.molcel.2022.11.016] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 09/12/2022] [Accepted: 11/17/2022] [Indexed: 12/23/2022]
Abstract
To explore genome organization and function in the HIV-infected brain, we applied single-nuclei transcriptomics, cell-type-specific chromosomal conformation mapping, and viral integration site sequencing (IS-seq) to frontal cortex from individuals with encephalitis (HIVE) and without (HIV+). Derepressive changes in 3D genomic compartment structures in HIVE microglia were linked to the transcriptional activation of interferon (IFN) signaling and cell migratory pathways, while transcriptional downregulation and repressive compartmentalization of neuronal health and signaling genes occurred in both HIVE and HIV+ microglia. IS-seq recovered 1,221 brain integration sites showing distinct genomic patterns compared with peripheral lymphocytes, with enrichment for sequences newly mobilized into a permissive chromatin environment after infection. Viral transcription occurred in a subset of highly activated microglia comprising 0.33% of all nuclei in HIVE brain. Our findings point to disrupted microglia-neuronal interactions in HIV and link retroviral integration to remodeling of the microglial 3D genome during infection.
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Affiliation(s)
- Amara L Plaza-Jennings
- Department of Psychiatry, 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; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Aditi Valada
- Department of Psychiatry, 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; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Callan O'Shea
- Department of Psychiatry, 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; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Marina Iskhakova
- Department of Psychiatry, 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; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Benxia Hu
- UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Behnam Javidfar
- Department of Psychiatry, 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; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Gabriella Ben Hutta
- Department of Psychiatry, 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; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Tova Y Lambert
- Department of Psychiatry, 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; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jacinta Murray
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Bibi Kassim
- Department of Psychiatry, 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; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sandhya Chandrasekaran
- Department of Psychiatry, 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; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Benjamin K Chen
- Division of Infectious Diseases, Department of Medicine, Immunology Institute, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Susan Morgello
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Hyejung Won
- UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
| | - Schahram Akbarian
- Department of Psychiatry, 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; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
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