1
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Ealo T, Sanchez-Gaya V, Respuela P, Muñoz-San Martín M, Martin-Batista E, Haro E, Rada-Iglesias A. Cooperative insulation of regulatory domains by CTCF-dependent physical insulation and promoter competition. Nat Commun 2024; 15:7258. [PMID: 39179577 PMCID: PMC11344162 DOI: 10.1038/s41467-024-51602-4] [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: 01/23/2024] [Accepted: 08/10/2024] [Indexed: 08/26/2024] Open
Abstract
The specificity of gene expression during development requires the insulation of regulatory domains to avoid inappropriate enhancer-gene interactions. In vertebrates, this insulator function is mostly attributed to clusters of CTCF sites located at topologically associating domain (TAD) boundaries. However, TAD boundaries allow some physical crosstalk across regulatory domains, which is at odds with the specific and precise expression of developmental genes. Here we show that developmental genes and nearby clusters of CTCF sites cooperatively foster the robust insulation of regulatory domains. By genetically dissecting a couple of representative loci in mouse embryonic stem cells, we show that CTCF sites prevent undesirable enhancer-gene contacts (i.e. physical insulation), while developmental genes preferentially contribute to regulatory insulation through non-structural mechanisms involving promoter competition rather than enhancer blocking. Overall, our work provides important insights into the insulation of regulatory domains, which in turn might help interpreting the pathological consequences of certain structural variants.
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Affiliation(s)
- Thais Ealo
- Institute of Biomedicine and Biotechnology of Cantabria (IBBTEC), CSIC/Universidad de Cantabria, Santander, Spain
| | - Victor Sanchez-Gaya
- Institute of Biomedicine and Biotechnology of Cantabria (IBBTEC), CSIC/Universidad de Cantabria, Santander, Spain.
| | - Patricia Respuela
- Institute of Biomedicine and Biotechnology of Cantabria (IBBTEC), CSIC/Universidad de Cantabria, Santander, Spain
| | - María Muñoz-San Martín
- Institute of Biomedicine and Biotechnology of Cantabria (IBBTEC), CSIC/Universidad de Cantabria, Santander, Spain
- Service of Neurology, University Hospital Marqués de Valdecilla, Universidad de Cantabria and IDIVAL, Santander, Spain
| | | | - Endika Haro
- Institute of Biomedicine and Biotechnology of Cantabria (IBBTEC), CSIC/Universidad de Cantabria, Santander, Spain.
| | - Alvaro Rada-Iglesias
- Institute of Biomedicine and Biotechnology of Cantabria (IBBTEC), CSIC/Universidad de Cantabria, Santander, Spain.
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2
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Shi C, Liu L, Hyeon C. Hi-C-guided many-polymer model to decipher 3D genome organization. Biophys J 2024; 123:2574-2583. [PMID: 38932457 PMCID: PMC11365109 DOI: 10.1016/j.bpj.2024.06.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/27/2024] [Accepted: 06/21/2024] [Indexed: 06/28/2024] Open
Abstract
We propose a high-throughput chromosome conformation capture data-based many-polymer model that allows us to generate an ensemble of multi-scale genome structures. We demonstrate the efficacy of our model by validating the generated structures against experimental measurements and employ them to address key questions regarding genome organization. Our model first confirms a significant correlation between chromosome size and nuclear positioning. Specifically, smaller chromosomes are distributed at the core region, whereas larger chromosomes are at the periphery, interacting with the nuclear envelope. The spatial distribution of A- and B-type compartments, which is nontrivial to infer from the corresponding high-throughput chromosome conformation capture maps alone, can also be elucidated using our model, accounting for an issue such as the effect of chromatin-lamina interaction on the compartmentalization of conventional and inverted nuclei. In accordance with imaging data, the overall shape of the 3D genome structures generated from our model displays significant variation. As a case study, we apply our method to the yellow fever mosquito genome, finding that the predicted morphology displays, on average, a more globular shape than the previously suggested spindle-like organization and that our prediction better aligns with the fluorescence in situ hybridization data. Our model has great potential to be extended to investigate many outstanding issues concerning 3D genome organization.
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Affiliation(s)
- Chen Shi
- Key Laboratory of Optical Field Manipulation of Zhejiang Province, Department of Physics, Zhejiang Sci-Tech University, Hangzhou, China
| | - Lei Liu
- Key Laboratory of Optical Field Manipulation of Zhejiang Province, Department of Physics, Zhejiang Sci-Tech University, Hangzhou, China.
| | - Changbong Hyeon
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Korea.
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3
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Liu L, Ren D, Li K, Ji L, Feng M, Li Z, Meng L, He G, Shi Y. Unraveling schizophrenia's genetic complexity through advanced causal inference and chromatin 3D conformation. Schizophr Res 2024; 270:476-485. [PMID: 38996525 DOI: 10.1016/j.schres.2024.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 07/01/2024] [Accepted: 07/03/2024] [Indexed: 07/14/2024]
Abstract
Schizophrenia is a polygenic complex disease with a heritability as high as 80 %, yet the mechanism of polygenic interaction in its pathogenesis remains unclear. Studying the interaction and regulation of schizophrenia susceptibility genes is crucial for unraveling the pathogenesis of schizophrenia and developing antipsychotic drugs. Therefore, we developed a bioinformatics method named GRACI (Gene Regulation Analysis based on Causal Inference) based on the principles of information theory, a causal inference model, and high order chromatin 3D conformation. GRACI captures the interaction and regulatory relationships between schizophrenia susceptibility genes by analyzing genotyping data. Two datasets, comprising 1459 and 2065 samples respectively, were analyzed, and the gene networks from both datasets were constructed. GRACI showcased superior accuracy when compared to widely adopted methods for detecting gene-gene interactions and intergenic regulation. This alignment was further substantiated by its correlation with chromatin high-order conformation patterns. Using GRACI, we identified three potential genes-KCNN3, KCNH1, and KCND3-that are directly associated with schizophrenia pathogenesis. Furthermore, the results of GRACI on the standalone dataset illustrated the method's applicability to other complex diseases. GRACI download: https://github.com/liuliangjie19/GRACI.
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Affiliation(s)
- Liangjie Liu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China; Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Decheng Ren
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China; Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Keyi Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China; Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Lei Ji
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China; Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Mofan Feng
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China; Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Zhuoheng Li
- Department of Electrical Engineering and Computer Science, University of Michigan, 1301 Beal Avenue, Ann Arbor, MI 48109, USA
| | - Luming Meng
- Key Laboratory for Biobased Materials and Energy of Ministry of Education, College of Materials and Energy, South China Agricultural University, Guangzhou 510630, China
| | - Guang He
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China; Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Yi Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China; Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China; Research Institute for Doping Control, Shanghai University of Sport, Shanghai 200438, China.
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4
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Lin J, Luo R, Pinello L. EPInformer: a scalable deep learning framework for gene expression prediction by integrating promoter-enhancer sequences with multimodal epigenomic data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.01.606099. [PMID: 39131276 PMCID: PMC11312614 DOI: 10.1101/2024.08.01.606099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Transcriptional regulation, critical for cellular differentiation and adaptation to environmental changes, involves coordinated interactions among DNA sequences, regulatory proteins, and chromatin architecture. Despite extensive data from consortia like ENCODE, understanding the dynamics of cis-regulatory elements (CREs) in gene expression remains challenging. Deep learning is a powerful tool for learning gene expression and epigenomic signals from DNA sequences, exhibiting superior performance compared to conventional machine learning approaches. However, even the most advanced deep learning-based methods may fall short in capturing the regulatory effects of distal elements such as enhancers, limiting their predictive accuracy. In addition, these methods may require significant resources to train or to adapt to newly generated data. To address these challenges, we present EPInformer, a scalable deep-learning framework for predicting gene expression by integrating promoter-enhancer interactions with their sequences, epigenomic signals, and chromatin contacts. Our model outperforms existing gene expression prediction models in rigorous cross-chromosome validation, accurately recapitulates enhancer-gene interactions validated by CRISPR perturbation experiments, and identifies crucial transcription factor motifs within regulatory sequences. EPInformer is available as open-source software at https://github.com/pinellolab/EPInformer.
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Affiliation(s)
- Jiecong Lin
- Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Department of Pathology, Harvard Medical School, Boston, Massachusetts 02129, USA
- Department of Computer Science, The University of Hong Kong, Hong Kong, China
| | - Ruibang Luo
- Department of Computer Science, The University of Hong Kong, Hong Kong, China
| | - Luca Pinello
- Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Department of Pathology, Harvard Medical School, Boston, Massachusetts 02129, USA
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5
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Kuang S, Pollard KS. Exploring the roles of RNAs in chromatin architecture using deep learning. Nat Commun 2024; 15:6373. [PMID: 39075082 PMCID: PMC11286850 DOI: 10.1038/s41467-024-50573-w] [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: 10/23/2023] [Accepted: 07/12/2024] [Indexed: 07/31/2024] Open
Abstract
Recent studies have highlighted the impact of both transcription and transcripts on 3D genome organization, particularly its dynamics. Here, we propose a deep learning framework, called AkitaR, that leverages both genome sequences and genome-wide RNA-DNA interactions to investigate the roles of chromatin-associated RNAs (caRNAs) on genome folding in HFFc6 cells. In order to disentangle the cis- and trans-regulatory roles of caRNAs, we have compared models with nascent transcripts, trans-located caRNAs, open chromatin data, or DNA sequence alone. Both nascent transcripts and trans-located caRNAs improve the models' predictions, especially at cell-type-specific genomic regions. Analyses of feature importance scores reveal the contribution of caRNAs at TAD boundaries, chromatin loops and nuclear sub-structures such as nuclear speckles and nucleoli to the models' predictions. Furthermore, we identify non-coding RNAs (ncRNAs) known to regulate chromatin structures, such as MALAT1 and NEAT1, as well as several new RNAs, RNY5, RPPH1, POLG-DT and THBS1-IT1, that might modulate chromatin architecture through trans-interactions in HFFc6. Our modeling also suggests that transcripts from Alus and other repetitive elements may facilitate chromatin interactions through trans R-loop formation. Our findings provide insights and generate testable hypotheses about the roles of caRNAs in shaping chromatin organization.
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Affiliation(s)
- Shuzhen Kuang
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA
| | - Katherine S Pollard
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA.
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, USA.
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6
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Loers JU, Vermeirssen V. A single-cell multimodal view on gene regulatory network inference from transcriptomics and chromatin accessibility data. Brief Bioinform 2024; 25:bbae382. [PMID: 39207727 PMCID: PMC11359808 DOI: 10.1093/bib/bbae382] [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: 04/05/2024] [Revised: 06/27/2024] [Accepted: 07/23/2024] [Indexed: 09/04/2024] Open
Abstract
Eukaryotic gene regulation is a combinatorial, dynamic, and quantitative process that plays a vital role in development and disease and can be modeled at a systems level in gene regulatory networks (GRNs). The wealth of multi-omics data measured on the same samples and even on the same cells has lifted the field of GRN inference to the next stage. Combinations of (single-cell) transcriptomics and chromatin accessibility allow the prediction of fine-grained regulatory programs that go beyond mere correlation of transcription factor and target gene expression, with enhancer GRNs (eGRNs) modeling molecular interactions between transcription factors, regulatory elements, and target genes. In this review, we highlight the key components for successful (e)GRN inference from (sc)RNA-seq and (sc)ATAC-seq data exemplified by state-of-the-art methods as well as open challenges and future developments. Moreover, we address preprocessing strategies, metacell generation and computational omics pairing, transcription factor binding site detection, and linear and three-dimensional approaches to identify chromatin interactions as well as dynamic and causal eGRN inference. We believe that the integration of transcriptomics together with epigenomics data at a single-cell level is the new standard for mechanistic network inference, and that it can be further advanced with integrating additional omics layers and spatiotemporal data, as well as with shifting the focus towards more quantitative and causal modeling strategies.
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Affiliation(s)
- Jens Uwe Loers
- Lab for Computational Biology, Integromics and Gene Regulation (CBIGR), Cancer Research Institute Ghent (CRIG), Corneel Heymanslaan 10, 9000 Ghent, Belgium
- Department of Biomedical Molecular Biology, Ghent University, Zwijnaarde-Technologiepark 71, 9052 Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Vanessa Vermeirssen
- Lab for Computational Biology, Integromics and Gene Regulation (CBIGR), Cancer Research Institute Ghent (CRIG), Corneel Heymanslaan 10, 9000 Ghent, Belgium
- Department of Biomedical Molecular Biology, Ghent University, Zwijnaarde-Technologiepark 71, 9052 Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium
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7
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Conte M, Abraham A, Esposito A, Yang L, Gibcus JH, Parsi KM, Vercellone F, Fontana A, Pierno FD, Dekker J, Nicodemi M. Polymer physics models reveal structural folding features of single-molecule gene chromatin conformations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.16.603769. [PMID: 39071404 PMCID: PMC11275793 DOI: 10.1101/2024.07.16.603769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Here, we employ polymer physics models of chromatin to investigate the 3D folding of a 2Mb wide genomic region encompassing the human LTN1 gene, a crucial DNA locus involved in key cellular functions. Through extensive Molecular Dynamics simulations, we reconstruct in-silico the ensemble of single-molecule LTN1 3D structures, which we benchmark against recent in-situ Hi-C 2.0 data. The model-derived single molecules are then used to predict structural folding features at the single-cell level, providing testable predictions for super-resolution microscopy experiments.
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Affiliation(s)
- Mattia Conte
- Dipartimento di Fisica, Università di Napoli Federico II, and INFN Napoli, Complesso Universitario di Monte Sant’Angelo, 80126 Naples, Italy
| | - Alex Abraham
- Dipartimento di Fisica, Università di Napoli Federico II, and INFN Napoli, Complesso Universitario di Monte Sant’Angelo, 80126 Naples, Italy
| | - Andrea Esposito
- Dipartimento di Fisica, Università di Napoli Federico II, and INFN Napoli, Complesso Universitario di Monte Sant’Angelo, 80126 Naples, Italy
| | - Liyan Yang
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Johan H. Gibcus
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Krishna M. Parsi
- Diabetes Center of Excellence and Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, MA 01655
| | - Francesca Vercellone
- DIETI, Università di Napoli Federico II, Via Claudio 21, 80125 Naples, and INFN Napoli, Complesso Universitario di Monte Sant’Angelo, 80126 Naples, Italy
| | - Andrea Fontana
- Dipartimento di Fisica, Università di Napoli Federico II, and INFN Napoli, Complesso Universitario di Monte Sant’Angelo, 80126 Naples, Italy
| | - Florinda Di Pierno
- DIETI, Università di Napoli Federico II, Via Claudio 21, 80125 Naples, and INFN Napoli, Complesso Universitario di Monte Sant’Angelo, 80126 Naples, Italy
| | - Job Dekker
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
- Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
| | - Mario Nicodemi
- Dipartimento di Fisica, Università di Napoli Federico II, and INFN Napoli, Complesso Universitario di Monte Sant’Angelo, 80126 Naples, Italy
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8
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Lucini F, Petrini C, Salviato E, Pal K, Rosti V, Gorini F, Santarelli P, Quadri R, Lembo G, Graziano G, Di Patrizio Soldateschi E, Tagliaferri I, Pinatel E, Sebestyén E, Rotta L, Gentile F, Vaira V, Lanzuolo C, Ferrari F. Biochemical properties of chromatin domains define genome compartmentalization. Nucleic Acids Res 2024; 52:e54. [PMID: 38808669 PMCID: PMC11229364 DOI: 10.1093/nar/gkae454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 04/22/2024] [Accepted: 05/16/2024] [Indexed: 05/30/2024] Open
Abstract
Chromatin three-dimensional (3D) organization inside the cell nucleus determines the separation of euchromatin and heterochromatin domains. Their segregation results in the definition of active and inactive chromatin compartments, whereby the local concentration of associated proteins, RNA and DNA results in the formation of distinct subnuclear structures. Thus, chromatin domains spatially confined in a specific 3D nuclear compartment are expected to share similar epigenetic features and biochemical properties, in terms of accessibility and solubility. Based on this rationale, we developed the 4f-SAMMY-seq to map euchromatin and heterochromatin based on their accessibility and solubility, starting from as little as 10 000 cells. Adopting a tailored bioinformatic data analysis approach we reconstruct also their 3D segregation in active and inactive chromatin compartments and sub-compartments, thus recapitulating the characteristic properties of distinct chromatin states. A key novelty of the new method is the capability to map both the linear segmentation of open and closed chromatin domains, as well as their compartmentalization in one single experiment.
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Affiliation(s)
- Federica Lucini
- INGM, Istituto Nazionale di Genetica Molecolare “Romeo ed Enrica Invernizzi”, Milan 20122, Italy
| | - Cristiano Petrini
- IFOM-ETS, The AIRC Institute of Molecular Oncology, Milan 20139, Italy
| | - Elisa Salviato
- IFOM-ETS, The AIRC Institute of Molecular Oncology, Milan 20139, Italy
| | - Koustav Pal
- IFOM-ETS, The AIRC Institute of Molecular Oncology, Milan 20139, Italy
| | - Valentina Rosti
- INGM, Istituto Nazionale di Genetica Molecolare “Romeo ed Enrica Invernizzi”, Milan 20122, Italy
- ITB-CNR, Institute of Biomedical Technologies, National Research Council, Segrate 20054, Italy
| | - Francesca Gorini
- INGM, Istituto Nazionale di Genetica Molecolare “Romeo ed Enrica Invernizzi”, Milan 20122, Italy
| | - Philina Santarelli
- INGM, Istituto Nazionale di Genetica Molecolare “Romeo ed Enrica Invernizzi”, Milan 20122, Italy
| | - Roberto Quadri
- INGM, Istituto Nazionale di Genetica Molecolare “Romeo ed Enrica Invernizzi”, Milan 20122, Italy
| | - Giovanni Lembo
- IFOM-ETS, The AIRC Institute of Molecular Oncology, Milan 20139, Italy
| | - Giulia Graziano
- IFOM-ETS, The AIRC Institute of Molecular Oncology, Milan 20139, Italy
| | - Emanuele Di Patrizio Soldateschi
- INGM, Istituto Nazionale di Genetica Molecolare “Romeo ed Enrica Invernizzi”, Milan 20122, Italy
- ITB-CNR, Institute of Biomedical Technologies, National Research Council, Segrate 20054, Italy
| | | | - Eva Pinatel
- ITB-CNR, Institute of Biomedical Technologies, National Research Council, Segrate 20054, Italy
| | - Endre Sebestyén
- IFOM-ETS, The AIRC Institute of Molecular Oncology, Milan 20139, Italy
| | - Luca Rotta
- IEO, European Institute of Oncology IRCCS, Milan 20141, Italy
| | - Francesco Gentile
- Fondazione IRCCS Ca’ Granda-Ospedale Maggiore Policlinico, Milan 20122, Italy
| | - Valentina Vaira
- Division of Pathology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Chiara Lanzuolo
- INGM, Istituto Nazionale di Genetica Molecolare “Romeo ed Enrica Invernizzi”, Milan 20122, Italy
- ITB-CNR, Institute of Biomedical Technologies, National Research Council, Segrate 20054, Italy
| | - Francesco Ferrari
- IFOM-ETS, The AIRC Institute of Molecular Oncology, Milan 20139, Italy
- IGM-CNR, Institute of Molecular Genetics “Luigi Luca Cavalli-Sforza”, National Research Council, Pavia 27100, Italy
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9
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Szabó D, Franke V, Bianco S, Batiuk MY, Paul EJ, Kukalev A, Pfisterer UG, Irastorza-Azcarate I, Chiariello AM, Demharter S, Zea-Redondo L, Lopez-Atalaya JP, Nicodemi M, Akalin A, Khodosevich K, Ungless MA, Winick-Ng W, Pombo A. A single dose of cocaine rewires the 3D genome structure of midbrain dopamine neurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.10.593308. [PMID: 38766140 PMCID: PMC11100777 DOI: 10.1101/2024.05.10.593308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Midbrain dopamine neurons (DNs) respond to a first exposure to addictive drugs and play key roles in chronic drug usage1-3. As the synaptic and transcriptional changes that follow an acute cocaine exposure are mostly resolved within a few days4,5, the molecular changes that encode the long-term cellular memory of the exposure within DNs remain unknown. To investigate whether a single cocaine exposure induces long-term changes in the 3D genome structure of DNs, we applied Genome Architecture Mapping and single nucleus transcriptomic analyses in the mouse midbrain. We found extensive rewiring of 3D genome architecture at 24 hours past exposure which remains or worsens by 14 days, outlasting transcriptional responses. The cocaine-induced chromatin rewiring occurs at all genomic scales and affects genes with major roles in cocaine-induced synaptic changes. A single cocaine exposure triggers extensive long-lasting changes in chromatin condensation in post-synaptic and post-transcriptional regulatory genes, for example the unfolding of Rbfox1 which becomes most prominent 14 days post exposure. Finally, structurally remodeled genes are most expressed in a specific DN sub-type characterized by low expression of the dopamine auto-receptor Drd2, a key feature of highly cocaine-sensitive cells. These results reveal an important role for long-lasting 3D genome remodelling in the cellular memory of a single cocaine exposure, providing new hypotheses for understanding the inception of drug addiction and 3D genome plasticity.
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Affiliation(s)
- Dominik Szabó
- Max-Delbrück Centre for Molecular Medicine, Berlin Institute for Medical Systems Biology, Epigenetic Regulation and Chromatin Architecture Group, 10115 Berlin, Germany
- Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Vedran Franke
- Bioinformatics & Omics Data Science platform, Max-Delbrück Centre for Molecular Medicine, Berlin Institute for Medical Systems Biology, 10115 Berlin, Germany
| | - Simona Bianco
- Dipartimento di Fisica, Università di Napoli Federico II, and INFN Napoli, Complesso Universitario di Monte Sant’Angelo, 80126 Naples, Italy
| | - Mykhailo Y. Batiuk
- Biotech Research and Innovation Centre, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DK-2200, Denmark
| | - Eleanor J. Paul
- MRC London Institute of Medical Sciences (LMS), London W12 0HS, UK
- Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, London SW7 2AZ, UK
| | - Alexander Kukalev
- Max-Delbrück Centre for Molecular Medicine, Berlin Institute for Medical Systems Biology, Epigenetic Regulation and Chromatin Architecture Group, 10115 Berlin, Germany
| | - Ulrich G. Pfisterer
- Biotech Research and Innovation Centre, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DK-2200, Denmark
| | - Ibai Irastorza-Azcarate
- Max-Delbrück Centre for Molecular Medicine, Berlin Institute for Medical Systems Biology, Epigenetic Regulation and Chromatin Architecture Group, 10115 Berlin, Germany
| | - Andrea M. Chiariello
- Dipartimento di Fisica, Università di Napoli Federico II, and INFN Napoli, Complesso Universitario di Monte Sant’Angelo, 80126 Naples, Italy
| | - Samuel Demharter
- Biotech Research and Innovation Centre, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DK-2200, Denmark
| | - Luna Zea-Redondo
- Max-Delbrück Centre for Molecular Medicine, Berlin Institute for Medical Systems Biology, Epigenetic Regulation and Chromatin Architecture Group, 10115 Berlin, Germany
- Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Jose P. Lopez-Atalaya
- Instituto de Neurociencias, Universidad Miguel Hernández-Consejo Superior de Investigaciones Científicas (UMH-CSIC), 03550, Sant Joan d’Alacant, Spain
| | - Mario Nicodemi
- Dipartimento di Fisica, Università di Napoli Federico II, and INFN Napoli, Complesso Universitario di Monte Sant’Angelo, 80126 Naples, Italy
- Berlin Institute of Health, 10178 Berlin, Germany
| | - Altuna Akalin
- Bioinformatics & Omics Data Science platform, Max-Delbrück Centre for Molecular Medicine, Berlin Institute for Medical Systems Biology, 10115 Berlin, Germany
| | - Konstantin Khodosevich
- Biotech Research and Innovation Centre, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DK-2200, Denmark
| | - Mark A. Ungless
- MRC London Institute of Medical Sciences (LMS), London W12 0HS, UK
- Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, London SW7 2AZ, UK
| | - Warren Winick-Ng
- Max-Delbrück Centre for Molecular Medicine, Berlin Institute for Medical Systems Biology, Epigenetic Regulation and Chromatin Architecture Group, 10115 Berlin, Germany
- Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Toronto, Canada
| | - Ana Pombo
- Max-Delbrück Centre for Molecular Medicine, Berlin Institute for Medical Systems Biology, Epigenetic Regulation and Chromatin Architecture Group, 10115 Berlin, Germany
- Humboldt-Universität zu Berlin, 10117 Berlin, Germany
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10
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Choudhury R, Venkateswaran Venkatasubramani A, Hua J, Borsò M, Franconi C, Kinkley S, Forné I, Imhof A. The role of RNA in the maintenance of chromatin domains as revealed by antibody-mediated proximity labelling coupled to mass spectrometry. eLife 2024; 13:e95718. [PMID: 38717135 PMCID: PMC11147508 DOI: 10.7554/elife.95718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 04/26/2024] [Indexed: 06/04/2024] Open
Abstract
Eukaryotic chromatin is organized into functional domains, that are characterized by distinct proteomic compositions and specific nuclear positions. In contrast to cellular organelles surrounded by lipid membranes, the composition of distinct chromatin domains is rather ill described and highly dynamic. To gain molecular insight into these domains and explore their composition, we developed an antibody-based proximity biotinylation method targeting the RNA and proteins constituents. The method that we termed antibody-mediated proximity labelling coupled to mass spectrometry (AMPL-MS) does not require the expression of fusion proteins and therefore constitutes a versatile and very sensitive method to characterize the composition of chromatin domains based on specific signature proteins or histone modifications. To demonstrate the utility of our approach we used AMPL-MS to characterize the molecular features of the chromocenter as well as the chromosome territory containing the hyperactive X chromosome in Drosophila. This analysis identified a number of known RNA-binding proteins in proximity of the hyperactive X and the centromere, supporting the accuracy of our method. In addition, it enabled us to characterize the role of RNA in the formation of these nuclear bodies. Furthermore, our method identified a new set of RNA molecules associated with the Drosophila centromere. Characterization of these novel molecules suggested the formation of R-loops in centromeres, which we validated using a novel probe for R-loops in Drosophila. Taken together, AMPL-MS improves the selectivity and specificity of proximity ligation allowing for novel discoveries of weak protein-RNA interactions in biologically diverse domains.
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Affiliation(s)
- Rupam Choudhury
- Department of Molecular Biology, Biomedical Center Munich, Ludwig-Maximilians UniversityPlanegg-MartinsriedGermany
| | - Anuroop Venkateswaran Venkatasubramani
- Department of Molecular Biology, Biomedical Center Munich, Ludwig-Maximilians UniversityPlanegg-MartinsriedGermany
- Graduate School of Quantitative Biosciences (QBM), Ludwig-Maximilians-Universität MünchenMunichGermany
| | - Jie Hua
- Department of Molecular Biology, Biomedical Center Munich, Ludwig-Maximilians UniversityPlanegg-MartinsriedGermany
| | - Marco Borsò
- Protein Analysis Unit, Biomedical Center (BMC), Faculty of Medicine, Ludwig-Maximilians, University (LMU) MunichPlanegg-MartinsriedGermany
| | - Celeste Franconi
- Chromatin Structure and Function group, Department of Computational Molecular Biology, Max Planck Institute for Molecular GeneticsBerlinGermany
| | - Sarah Kinkley
- Chromatin Structure and Function group, Department of Computational Molecular Biology, Max Planck Institute for Molecular GeneticsBerlinGermany
| | - Ignasi Forné
- Protein Analysis Unit, Biomedical Center (BMC), Faculty of Medicine, Ludwig-Maximilians, University (LMU) MunichPlanegg-MartinsriedGermany
| | - Axel Imhof
- Department of Molecular Biology, Biomedical Center Munich, Ludwig-Maximilians UniversityPlanegg-MartinsriedGermany
- Protein Analysis Unit, Biomedical Center (BMC), Faculty of Medicine, Ludwig-Maximilians, University (LMU) MunichPlanegg-MartinsriedGermany
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11
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Xiong K, Zhang R, Ma J. scGHOST: identifying single-cell 3D genome subcompartments. Nat Methods 2024; 21:814-822. [PMID: 38589516 PMCID: PMC11127718 DOI: 10.1038/s41592-024-02230-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 03/01/2024] [Indexed: 04/10/2024]
Abstract
Single-cell Hi-C (scHi-C) technologies allow for probing of genome-wide cell-to-cell variability in three-dimensional (3D) genome organization from individual cells. Computational methods have been developed to reveal single-cell 3D genome features based on scHi-C, including A/B compartments, topologically associating domains and chromatin loops. However, no method exists for annotating single-cell subcompartments, which is important for understanding chromosome spatial localization in single cells. Here we present scGHOST, a single-cell subcompartment annotation method using graph embedding with constrained random walk sampling. Applications of scGHOST to scHi-C data and contact maps derived from single-cell 3D genome imaging demonstrate reliable identification of single-cell subcompartments, offering insights into cell-to-cell variability of nuclear subcompartments. Using scHi-C data from complex tissues, scGHOST identifies cell-type-specific or allele-specific subcompartments linked to gene transcription across various cell types and developmental stages, suggesting functional implications of single-cell subcompartments. scGHOST is an effective method for annotating single-cell 3D genome subcompartments in a broad range of biological contexts.
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Affiliation(s)
- Kyle Xiong
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ruochi Zhang
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
- Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jian Ma
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
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12
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Reyna J, Fetter K, Ignacio R, Marandi CCA, Rao N, Jiang Z, Figueroa DS, Bhattacharyya S, Ay F. Loop Catalog: a comprehensive HiChIP database of human and mouse samples. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.26.591349. [PMID: 38746164 PMCID: PMC11092438 DOI: 10.1101/2024.04.26.591349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
HiChIP enables cost-effective and high-resolution profiling of regulatory and structural loops. To leverage the increasing number of publicly available HiChIP datasets from diverse cell lines and primary cells, we developed the Loop Catalog (https://loopcatalog.lji.org), a web-based database featuring HiChIP loop calls for 1319 samples across 133 studies and 44 high-resolution Hi-C loop calls. We demonstrate its utility in interpreting fine-mapped GWAS variants (SNP-to-gene linking), in identifying enriched sequence motifs and motif pairs at loop anchors, and in network-level analysis of loops connecting regulatory elements (community detection). Our comprehensive catalog, spanning over 4M unique 5kb loops, along with the accompanying analysis modalities constitutes an important resource for studies in gene regulation and genome organization.
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Affiliation(s)
- Joaquin Reyna
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Bioinformatics and Systems Biology Graduate Program University of California, San Diego, La Jolla, CA 92093 USA
| | - Kyra Fetter
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093 USA
| | - Romeo Ignacio
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
| | - Cemil Can Ali Marandi
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Bioinformatics and Systems Biology Graduate Program University of California, San Diego, La Jolla, CA 92093 USA
| | - Nikhil Rao
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA 92093 USA
| | - Zichen Jiang
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Department of Mathematics, University of California San Diego, La Jolla, CA 92093 USA
| | - Daniela Salgado Figueroa
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Bioinformatics and Systems Biology Graduate Program University of California, San Diego, La Jolla, CA 92093 USA
| | - Sourya Bhattacharyya
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
| | - Ferhat Ay
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Bioinformatics and Systems Biology Graduate Program University of California, San Diego, La Jolla, CA 92093 USA
- Department of Pediatrics, University of California San Diego, La Jolla, CA 92093 USA
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13
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Min A, Schreiber J, Kundaje A, Noble WS. Predicting chromatin conformation contact maps. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.12.589240. [PMID: 38645064 PMCID: PMC11030330 DOI: 10.1101/2024.04.12.589240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Over the past 15 years, a variety of next-generation sequencing assays have been developed for measuring the 3D conformation of DNA in the nucleus. Each of these assays gives, for a particular cell or tissue type, a distinct picture of 3D chromatin architecture. Accordingly, making sense of the relationship between genome structure and function requires teasing apart two closely related questions: how does chromatin 3D structure change from one cell type to the next, and how do different measurements of that structure differ from one another, even when the two assays are carried out in the same cell type? In this work, we assemble a collection of chromatin 3D datasets-each represented as a 2D contact map- spanning multiple assay types and cell types. We then build a machine learning model that predicts missing contact maps in this collection. We use the model to systematically explore how genome 3D architecture changes, at the level of compartments, domains, and loops, between cell type and between assay types.
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Affiliation(s)
- Alan Min
- Department of Statistics, University of Washington
| | | | | | - William Stafford Noble
- Department of Genome Sciences, University of Washington
- Paul G. Allen School of Computer Science and Engineering, University of Washington
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14
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Pujadas Liwag EM, Wei X, Acosta N, Carter LM, Yang J, Almassalha LM, Jain S, Daneshkhah A, Rao SSP, Seker-Polat F, MacQuarrie KL, Ibarra J, Agrawal V, Aiden EL, Kanemaki MT, Backman V, Adli M. Depletion of lamins B1 and B2 promotes chromatin mobility and induces differential gene expression by a mesoscale-motion-dependent mechanism. Genome Biol 2024; 25:77. [PMID: 38519987 PMCID: PMC10958841 DOI: 10.1186/s13059-024-03212-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 03/07/2024] [Indexed: 03/25/2024] Open
Abstract
BACKGROUND B-type lamins are critical nuclear envelope proteins that interact with the three-dimensional genomic architecture. However, identifying the direct roles of B-lamins on dynamic genome organization has been challenging as their joint depletion severely impacts cell viability. To overcome this, we engineered mammalian cells to rapidly and completely degrade endogenous B-type lamins using Auxin-inducible degron technology. RESULTS Using live-cell Dual Partial Wave Spectroscopic (Dual-PWS) microscopy, Stochastic Optical Reconstruction Microscopy (STORM), in situ Hi-C, CRISPR-Sirius, and fluorescence in situ hybridization (FISH), we demonstrate that lamin B1 and lamin B2 are critical structural components of the nuclear periphery that create a repressive compartment for peripheral-associated genes. Lamin B1 and lamin B2 depletion minimally alters higher-order chromatin folding but disrupts cell morphology, significantly increases chromatin mobility, redistributes both constitutive and facultative heterochromatin, and induces differential gene expression both within and near lamin-associated domain (LAD) boundaries. Critically, we demonstrate that chromatin territories expand as upregulated genes within LADs radially shift inwards. Our results indicate that the mechanism of action of B-type lamins comes from their role in constraining chromatin motion and spatial positioning of gene-specific loci, heterochromatin, and chromatin domains. CONCLUSIONS Our findings suggest that, while B-type lamin degradation does not significantly change genome topology, it has major implications for three-dimensional chromatin conformation at the single-cell level both at the lamina-associated periphery and the non-LAD-associated nuclear interior with concomitant genome-wide transcriptional changes. This raises intriguing questions about the individual and overlapping roles of lamin B1 and lamin B2 in cellular function and disease.
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Affiliation(s)
- Emily M Pujadas Liwag
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA
- IBIS Interdisciplinary Biological Sciences Graduate Program, Northwestern University, Evanston, USA
- Center for Physical Genomics and Engineering, Northwestern University, Evanston, IL, 60208, USA
| | - Xiaolong Wei
- Department of Surgery, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA
| | - Nicolas Acosta
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA
- Center for Physical Genomics and Engineering, Northwestern University, Evanston, IL, 60208, USA
| | - Lucas M Carter
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA
- IBIS Interdisciplinary Biological Sciences Graduate Program, Northwestern University, Evanston, USA
- Center for Physical Genomics and Engineering, Northwestern University, Evanston, IL, 60208, USA
| | - Jiekun Yang
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Luay M Almassalha
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA
- Center for Physical Genomics and Engineering, Northwestern University, Evanston, IL, 60208, USA
- Department of Gastroenterology and Hepatology, Northwestern Memorial Hospital, Chicago, IL, 60611, USA
| | - Surbhi Jain
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA
- Center for Physical Genomics and Engineering, Northwestern University, Evanston, IL, 60208, USA
| | - Ali Daneshkhah
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA
- Center for Physical Genomics and Engineering, Northwestern University, Evanston, IL, 60208, USA
| | - Suhas S P Rao
- The Center for Genome Architecture, Baylor College of Medicine, Houston, TX, 77030, USA
- School of Medicine, Stanford University, Stanford, CA, 94305, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Fidan Seker-Polat
- Feinberg School of Medicine, Robert Lurie Comprehensive Cancer Center, Department of Obstetrics and Gynecology, Northwestern University, Chicago, IL, 60611, USA
| | - Kyle L MacQuarrie
- Feinberg School of Medicine, Robert Lurie Comprehensive Cancer Center, Department of Pediatrics, Northwestern University, Chicago, IL, 60611, USA
- Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA
| | - Joe Ibarra
- Feinberg School of Medicine, Robert Lurie Comprehensive Cancer Center, Department of Pediatrics, Northwestern University, Chicago, IL, 60611, USA
- Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA
| | - Vasundhara Agrawal
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA
- Center for Physical Genomics and Engineering, Northwestern University, Evanston, IL, 60208, USA
| | - Erez Lieberman Aiden
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
- The Center for Genome Architecture, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX, 77030, USA
- Departments of Computer Science and Computational and Applied Mathematics, Rice University, Houston, TX, 77030, USA
| | - Masato T Kanemaki
- Department of Chromosome Science, National Institute of Genetics, Mishima, Shizuoka, 411-8540, Japan
- Graduate Institute for Advanced Studies, SOKENDAI, Mishima, Shizuoka, 411-8540, Japan
- Department of Biological Science, The University of Tokyo, Tokyo, 113-0033, Japan
| | - Vadim Backman
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA.
- Center for Physical Genomics and Engineering, Northwestern University, Evanston, IL, 60208, USA.
| | - Mazhar Adli
- Feinberg School of Medicine, Robert Lurie Comprehensive Cancer Center, Department of Obstetrics and Gynecology, Northwestern University, Chicago, IL, 60611, USA.
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15
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Liu Y, Zhangding Z, Liu X, Gan T, Ai C, Wu J, Liang H, Chen M, Guo Y, Lu R, Jiang Y, Ji X, Gao N, Kong D, Li Q, Hu J. Fork coupling directs DNA replication elongation and termination. Science 2024; 383:1215-1222. [PMID: 38484065 DOI: 10.1126/science.adj7606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 02/09/2024] [Indexed: 03/19/2024]
Abstract
DNA replication is initiated at multiple loci to ensure timely duplication of eukaryotic genomes. Sister replication forks progress bidirectionally, and replication terminates when two convergent forks encounter one another. To investigate the coordination of replication forks, we developed a replication-associated in situ HiC method to capture chromatin interactions involving nascent DNA. We identify more than 2000 fountain-like structures of chromatin contacts in human and mouse genomes, indicative of coupling of DNA replication forks. Replication fork interaction not only occurs between sister forks but also involves forks from two distinct origins to predetermine replication termination. Termination-associated chromatin fountains are sensitive to replication stress and lead to coupled forks-associated genomic deletions in cancers. These findings reveal the spatial organization of DNA replication forks within the chromatin context.
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Affiliation(s)
- Yang Liu
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Genome Editing Research Center, Peking University; Beijing 100871, China
- PKU-THU Center for Life Sciences, Peking University, Beijing 100871, China
| | - Zhengrong Zhangding
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Genome Editing Research Center, Peking University; Beijing 100871, China
| | - Xuhao Liu
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Genome Editing Research Center, Peking University; Beijing 100871, China
| | - Tingting Gan
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Genome Editing Research Center, Peking University; Beijing 100871, China
- PKU-THU Center for Life Sciences, Peking University, Beijing 100871, China
- Peking University ChengDu Academy for Advanced Interdisciplinary Biotechnologies, Chengdu, Sichuan 610213, China
| | - Chen Ai
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Genome Editing Research Center, Peking University; Beijing 100871, China
- PKU-THU Center for Life Sciences, Peking University, Beijing 100871, China
| | - Jinchun Wu
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Genome Editing Research Center, Peking University; Beijing 100871, China
- PKU-THU Center for Life Sciences, Peking University, Beijing 100871, China
| | - Haoxin Liang
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Genome Editing Research Center, Peking University; Beijing 100871, China
| | - Mohan Chen
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Genome Editing Research Center, Peking University; Beijing 100871, China
| | - Yuefeng Guo
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Genome Editing Research Center, Peking University; Beijing 100871, China
| | - Rusen Lu
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Genome Editing Research Center, Peking University; Beijing 100871, China
- PKU-THU Center for Life Sciences, Peking University, Beijing 100871, China
| | - Yongpeng Jiang
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Genome Editing Research Center, Peking University; Beijing 100871, China
- PKU-THU Center for Life Sciences, Peking University, Beijing 100871, China
| | - Xiong Ji
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Genome Editing Research Center, Peking University; Beijing 100871, China
- PKU-THU Center for Life Sciences, Peking University, Beijing 100871, China
| | - Ning Gao
- PKU-THU Center for Life Sciences, Peking University, Beijing 100871, China
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing 100871, China
| | - Daochun Kong
- PKU-THU Center for Life Sciences, Peking University, Beijing 100871, China
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China
| | - Qing Li
- PKU-THU Center for Life Sciences, Peking University, Beijing 100871, China
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China
| | - Jiazhi Hu
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Genome Editing Research Center, Peking University; Beijing 100871, China
- PKU-THU Center for Life Sciences, Peking University, Beijing 100871, China
- Peking University ChengDu Academy for Advanced Interdisciplinary Biotechnologies, Chengdu, Sichuan 610213, China
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16
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Serizay J, Matthey-Doret C, Bignaud A, Baudry L, Koszul R. Orchestrating chromosome conformation capture analysis with Bioconductor. Nat Commun 2024; 15:1072. [PMID: 38316789 PMCID: PMC10844600 DOI: 10.1038/s41467-024-44761-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Accepted: 12/28/2023] [Indexed: 02/07/2024] Open
Abstract
Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data structures, computational methods and visualization tools available in Bioconductor to investigate Hi-C, micro-C and other 3C-related data, in R. An online book ( https://bioconductor.org/books/OHCA/ ) further provides prospective end users with a number of workflows to process, import, analyze and visualize any type of chromosome conformation capture data.
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Affiliation(s)
- Jacques Serizay
- Institut Pasteur, CNRS UMR3525, Université Paris Cité, Unité Régulation Spatiale des Génomes, Paris, France.
| | - Cyril Matthey-Doret
- Institut Pasteur, CNRS UMR3525, Université Paris Cité, Unité Régulation Spatiale des Génomes, Paris, France
- Sorbonne Université, Collège Doctoral, Paris, France
- Swiss Data Science Center, École Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland
| | - Amaury Bignaud
- Institut Pasteur, CNRS UMR3525, Université Paris Cité, Unité Régulation Spatiale des Génomes, Paris, France
- Sorbonne Université, Collège Doctoral, Paris, France
| | - Lyam Baudry
- Institut Pasteur, CNRS UMR3525, Université Paris Cité, Unité Régulation Spatiale des Génomes, Paris, France
- Sorbonne Université, Collège Doctoral, Paris, France
- Université de Lausanne, Center for Integrative Genomics, Quartier Sorge, 1015, Lausanne, Switzerland
| | - Romain Koszul
- Institut Pasteur, CNRS UMR3525, Université Paris Cité, Unité Régulation Spatiale des Génomes, Paris, France
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17
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Zhang Z, Ruf-Zamojski F, Zamojski M, Bernard D, Chen X, Troyanskaya O, Sealfon S. Peak-agnostic high-resolution cis-regulatory circuitry mapping using single cell multiome data. Nucleic Acids Res 2024; 52:572-582. [PMID: 38084892 PMCID: PMC10810203 DOI: 10.1093/nar/gkad1166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 11/15/2023] [Accepted: 11/27/2023] [Indexed: 01/26/2024] Open
Abstract
Single same cell RNAseq/ATACseq multiome data provide unparalleled potential to develop high resolution maps of the cell-type specific transcriptional regulatory circuitry underlying gene expression. We present CREMA, a framework that recovers the full cis-regulatory circuitry by modeling gene expression and chromatin activity in individual cells without peak-calling or cell type labeling constraints. We demonstrate that CREMA overcomes the limitations of existing methods that fail to identify about half of functional regulatory elements which are outside the called chromatin 'peaks'. These circuit sites outside called peaks are shown to be important cell type specific functional regulatory loci, sufficient to distinguish individual cell types. Analysis of mouse pituitary data identifies a Gata2-circuit for the gonadotrope-enriched disease-associated Pcsk1 gene, which is experimentally validated by reduced gonadotrope expression in a gonadotrope conditional Gata2-knockout model. We present a web accessible human immune cell regulatory circuit resource, and provide CREMA as an R package.
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Affiliation(s)
- Zidong Zhang
- Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai (ISMMS), New York, NY, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Frederique Ruf-Zamojski
- Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai (ISMMS), New York, NY, USA
| | - Michel Zamojski
- Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai (ISMMS), New York, NY, USA
| | - Daniel J Bernard
- Department of Pharmacology and Therapeutics, McGill University, Montreal, QC H3G 1Y6, Canada
| | - Xi Chen
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA
| | - Olga G Troyanskaya
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA
- Department of Computer Science, Princeton University, Princeton, NJ, USA
| | - Stuart C Sealfon
- Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai (ISMMS), New York, NY, USA
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18
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Perdyan A, Jąkalski M, Horbacz M, Beheshti A, Mieczkowski J. Chromosomal positioning and epigenetic architecture influence DNA methylation patterns triggered by galactic cosmic radiation. Sci Rep 2024; 14:1324. [PMID: 38225252 PMCID: PMC10789781 DOI: 10.1038/s41598-024-51756-7] [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: 09/27/2023] [Accepted: 01/09/2024] [Indexed: 01/17/2024] Open
Abstract
Despite surging interest in space travel in recent decades, the impacts of prolonged, elevated exposure to galactic cosmic radiation (GCR) on human health remain poorly understood. This form of ionizing radiation causes significant changes to biological systems including damage to DNA structure by altering epigenetic phenotype with emphasis on DNA methylation. Building on previous work by Kennedy et al. (Sci Rep 8(1): 6709. 10.1038/S41598-018-24755-8), we evaluated spatial DNA methylation patterns triggered by high-LET (56Fe, 28Si) and low-LET (X-ray) radiation and the influence of chromosome positioning and epigenetic architecture in distinct radial layers of cell nucleus. Next, we validated our results using gene expression data of mice irradiated with simulated GCR and JAXA astronauts. We showed that primarily 56Fe induces a persistent DNA methylation increase whereas 28Si and X-ray induce a decrease DNA methylation which is not persistent with time. Moreover, we highlighted the role of nuclear chromatin architecture in cell response to external radiation. In summary, our study provides novel insights towards epigenetic and transcriptomic response as well as chromatin multidimensional structure influence on galactic cosmic radiation damage.
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Affiliation(s)
- Adrian Perdyan
- International Research Agenda 3P - Medicine Laboratory, Medical University of Gdansk, Marii Sklodowskiej Curie 3a, 80-210, Gdansk, Poland
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Marcin Jąkalski
- International Research Agenda 3P - Medicine Laboratory, Medical University of Gdansk, Marii Sklodowskiej Curie 3a, 80-210, Gdansk, Poland
| | - Monika Horbacz
- International Research Agenda 3P - Medicine Laboratory, Medical University of Gdansk, Marii Sklodowskiej Curie 3a, 80-210, Gdansk, Poland
| | - Afshin Beheshti
- Space Biosciences Division, NASA Ames Research Center, Blue Marble Space Institute of Science, Moffett Field, CA, 94035, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jakub Mieczkowski
- International Research Agenda 3P - Medicine Laboratory, Medical University of Gdansk, Marii Sklodowskiej Curie 3a, 80-210, Gdansk, Poland.
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19
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Calvo-Roitberg E, Carroll CL, Venev SV, Kim G, Mick ST, Dekker J, Fiszbein A, Pai AA. mRNA initiation and termination are spatially coordinated. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.05.574404. [PMID: 38260419 PMCID: PMC10802295 DOI: 10.1101/2024.01.05.574404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The expression of a precise mRNA transcriptome is crucial for establishing cell identity and function, with dozens of alternative isoforms produced for a single gene sequence. The regulation of mRNA isoform usage occurs by the coordination of co-transcriptional mRNA processing mechanisms across a gene. Decisions involved in mRNA initiation and termination underlie the largest extent of mRNA isoform diversity, but little is known about any relationships between decisions at both ends of mRNA molecules. Here, we systematically profile the joint usage of mRNA transcription start sites (TSSs) and polyadenylation sites (PASs) across tissues and species. Using both short and long read RNA-seq data, we observe that mRNAs preferentially using upstream TSSs also tend to use upstream PASs, and congruently, the usage of downstream sites is similarly paired. This observation suggests that mRNA 5' end choice may directly influence mRNA 3' ends. Our results suggest a novel "Positional Initiation-Termination Axis" (PITA), in which the usage of alternative terminal sites are coupled based on the order in which they appear in the genome. PITA isoforms are more likely to encode alternative protein domains and use conserved sites. PITA is strongly associated with the length of genomic features, such that PITA is enriched in longer genes with more area devoted to regions that regulate alternative 5' or 3' ends. Strikingly, we found that PITA genes are more likely than non-PITA genes to have multiple, overlapping chromatin structural domains related to pairing of ordinally coupled start and end sites. In turn, PITA coupling is also associated with fast RNA Polymerase II (RNAPII) trafficking across these long gene regions. Our findings indicate that a combination of spatial and kinetic mechanisms couple transcription initiation and mRNA 3' end decisions based on ordinal position to define the expression mRNA isoforms.
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Affiliation(s)
| | | | - Sergey V. Venev
- Department of Systems Biology, University Massachusetts Chan Medical School, Worcester, MA
| | - GyeungYun Kim
- Department of Biology, Boston University, Boston, MA
| | | | - Job Dekker
- Department of Systems Biology, University Massachusetts Chan Medical School, Worcester, MA
- Howard Hughes Medical Institute, Chevy Chase, MD
| | - Ana Fiszbein
- Department of Biology, Boston University, Boston, MA
- Center for Computing & Data Sciences, Boston University, Boston, MA
| | - Athma A. Pai
- RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Worcester, MA
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20
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Xie B, Dean A. Noncoding function of super enhancer derived mRNA in modulating neighboring gene expression and TAD interaction. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.05.570115. [PMID: 38105946 PMCID: PMC10723268 DOI: 10.1101/2023.12.05.570115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Super enhancers are important regulators of gene expression that often overlap with protein-coding genes. However, it is unclear whether the overlapping protein-coding genes and the mRNA derived from them contribute to enhancer activity. Using an erythroid-specific super enhancer that overlaps the Cpox gene as a model, we found that Cpox mRNA has a non-coding function in regulating neighboring protein-coding genes, eRNA expression and TAD interactions. Depletion of Cpox mRNA leads to accumulation of H3K27me3 and release of p300 from the Cpox locus, activating an intra-TAD enhancer and gene expression. Additionally, we identified a head-to-tail interaction between the TAD boundary genes Cpox and Dcbld2 that is facilitated by a novel type of repressive loop anchored by p300 and PRC2/H3K27me3. Our results uncover a regulatory role for mRNA transcribed within a super enhancer context and provide insight into head-to-tail inter-gene interaction in the regulation of gene expression and oncogene activation.
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Affiliation(s)
- Bingning Xie
- Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, 20892, USA
| | - Ann Dean
- Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, 20892, USA
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21
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Erdmann-Pham DD, Batra SS, Turkalo TK, Durbin J, Blanchette M, Yeh I, Shain H, Bastian BC, Song YS, Rokhsar DS, Hockemeyer D. Tracing cancer evolution and heterogeneity using Hi-C. Nat Commun 2023; 14:7111. [PMID: 37932252 PMCID: PMC10628133 DOI: 10.1038/s41467-023-42651-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Accepted: 10/09/2023] [Indexed: 11/08/2023] Open
Abstract
Chromosomal rearrangements can initiate and drive cancer progression, yet it has been challenging to evaluate their impact, especially in genetically heterogeneous solid cancers. To address this problem we developed HiDENSEC, a new computational framework for analyzing chromatin conformation capture in heterogeneous samples that can infer somatic copy number alterations, characterize large-scale chromosomal rearrangements, and estimate cancer cell fractions. After validating HiDENSEC with in silico and in vitro controls, we used it to characterize chromosome-scale evolution during melanoma progression in formalin-fixed tumor samples from three patients. The resulting comprehensive annotation of the genomic events includes copy number neutral translocations that disrupt tumor suppressor genes such as NF1, whole chromosome arm exchanges that result in loss of CDKN2A, and whole-arm copy-number neutral loss of homozygosity involving PTEN. These findings show that large-scale chromosomal rearrangements occur throughout cancer evolution and that characterizing these events yields insights into drivers of melanoma progression.
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Affiliation(s)
- Dan Daniel Erdmann-Pham
- Department of Mathematics, University of California, Berkeley, CA, 94720, USA
- Department of Statistics, Stanford University, Stanford, CA, 94305, USA
| | - Sanjit Singh Batra
- Computer Science Division, University of California, Berkeley, CA, 94720, USA
| | - Timothy K Turkalo
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, 94720, USA
| | - James Durbin
- Dovetail Genomics, Enterprise Way, Scotts Valley, CA, 95066, USA
| | - Marco Blanchette
- Dovetail Genomics, Enterprise Way, Scotts Valley, CA, 95066, USA
| | - Iwei Yeh
- Department of Dermatology and Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, 94143, USA
- Department of Pathology, University of California, San Francisco, CA, 94143, USA
| | - Hunter Shain
- Department of Dermatology and Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, 94143, USA
| | - Boris C Bastian
- Department of Dermatology and Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, 94143, USA
- Department of Pathology, University of California, San Francisco, CA, 94143, USA
| | - Yun S Song
- Computer Science Division, University of California, Berkeley, CA, 94720, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, 94158, USA.
- Department of Statistics, University of California, Berkeley, CA, 94720, USA.
| | - Daniel S Rokhsar
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, 94720, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, 94158, USA.
- Innovative Genomics Institute, University of California, Berkeley, CA, 94720, USA.
- Okinawa Institute for Science and Technology, Tancha, Okinawa, Japan.
| | - Dirk Hockemeyer
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, 94720, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, 94158, USA.
- Innovative Genomics Institute, University of California, Berkeley, CA, 94720, USA.
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22
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Kuang S, Pollard KS. Exploring the Roles of RNAs in Chromatin Architecture Using Deep Learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.22.563498. [PMID: 37961712 PMCID: PMC10634726 DOI: 10.1101/2023.10.22.563498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Recent studies have highlighted the impact of both transcription and transcripts on 3D genome organization, particularly its dynamics. Here, we propose a deep learning framework, called AkitaR, that leverages both genome sequences and genome-wide RNA-DNA interactions to investigate the roles of chromatin-associated RNAs (caRNAs) on genome folding in HFFc6 cells. In order to disentangle the cis- and trans-regulatory roles of caRNAs, we compared models with nascent transcripts, trans-located caRNAs, open chromatin data, or DNA sequence alone. Both nascent transcripts and trans-located caRNAs improved the models' predictions, especially at cell-type-specific genomic regions. Analyses of feature importance scores revealed the contribution of caRNAs at TAD boundaries, chromatin loops and nuclear sub-structures such as nuclear speckles and nucleoli to the models' predictions. Furthermore, we identified non-coding RNAs (ncRNAs) known to regulate chromatin structures, such as MALAT1 and NEAT1, as well as several novel RNAs, RNY5, RPPH1, POLG-DT and THBS1-IT, that might modulate chromatin architecture through trans-interactions in HFFc6. Our modeling also suggests that transcripts from Alus and other repetitive elements may facilitate chromatin interactions through trans R-loop formation. Our findings provide new insights and generate testable hypotheses about the roles of caRNAs in shaping chromatin organization.
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Affiliation(s)
- Shuzhen Kuang
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA
| | - Katherine S. Pollard
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
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23
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Sridhar A, More AS, Jadhav AR, Patil K, Mavlankar A, Dixit VM, Bapat SA. Pattern recognition in the landscape of seemingly random chimeric transcripts. Comput Struct Biotechnol J 2023; 21:5153-5164. [PMID: 37920814 PMCID: PMC10618115 DOI: 10.1016/j.csbj.2023.10.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 10/13/2023] [Accepted: 10/16/2023] [Indexed: 11/04/2023] Open
Abstract
The molecular and functional diversity generated by chimeric transcripts (CTs) that are derived from two genes is indicated to contribute to tumor cell survival. Several gaps yet exist. The present research is a systematic study of the spectrum of CTs identified in RNA sequencing datasets of 160 ovarian cancer samples in the The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov). Structural annotation revealed complexities emerging from chromosomal localization of partner genes, differential splicing and inclusion of regulatory, untranslated regions. Identification of phenotype-specific associations further resolved a dynamically modulated mesenchymal signature during transformation. On an evolutionary background, protein-coding CTs were indicated to be highly conserved, while non-coding CTs may have evolved more recently. We also realized that the current premise postulating structural alterations or neighbouring gene readthrough generating CTs is not valid in instances wherein the parental genes are genomically distanced. In addressing this lacuna, we identified the essentiality of specific spatiotemporal arrangements mediated gene proximities in 3D space for the generation of CTs. All these features together suggest non-random mechanisms towards increasing the molecular diversity in a cell through chimera formation either in parallel or with cross-talks with the indigenous regulatory network.
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Affiliation(s)
- Aksheetha Sridhar
- Open Health Systems Laboratory, 9601 Medical Centre Drive, Rockville, MD 20850, US
| | - Ankita S. More
- National Centre for Cell Science, Savitribai Phule Pune University, Ganeshkhind, Pune 411 007, Maharashtra, India
| | - Amruta R. Jadhav
- National Centre for Cell Science, Savitribai Phule Pune University, Ganeshkhind, Pune 411 007, Maharashtra, India
| | - Komal Patil
- National Centre for Cell Science, Savitribai Phule Pune University, Ganeshkhind, Pune 411 007, Maharashtra, India
| | - Anuj Mavlankar
- National Centre for Cell Science, Savitribai Phule Pune University, Ganeshkhind, Pune 411 007, Maharashtra, India
| | - Vaishnavi M. Dixit
- National Centre for Cell Science, Savitribai Phule Pune University, Ganeshkhind, Pune 411 007, Maharashtra, India
| | - Sharmila A. Bapat
- Open Health Systems Laboratory, 9601 Medical Centre Drive, Rockville, MD 20850, US
- National Centre for Cell Science, Savitribai Phule Pune University, Ganeshkhind, Pune 411 007, Maharashtra, India
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24
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Hristov BH, Noble WS, Bertero A. Systematic identification of inter-chromosomal interaction networks supports the existence of RNA factories. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.21.558852. [PMID: 37790381 PMCID: PMC10542540 DOI: 10.1101/2023.09.21.558852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Most studies of genome organization have focused on intra-chromosomal (cis) contacts because they harbor key features such as DNA loops and topologically associating domains. Inter-chromosomal (trans) contacts have received much less attention, and tools for interrogating potential biologically relevant trans structures are lacking. Here, we develop a computational framework to identify sets of loci that jointly interact in trans from Hi-C data. This method, trans-C, initiates probabilistic random walks with restarts from a set of seed loci to traverse an input Hi-C contact network, thereby identifying sets of trans-contacting loci. We validate trans-C in three increasingly complex models of established trans contacts: the Plasmodium falciparum var genes, the mouse olfactory receptor "Greek islands", and the human RBM20 cardiac splicing factory. We then apply trans-C to systematically test the hypothesis that genes co-regulated by the same trans-acting element (i.e., a transcription or splicing factor) co-localize in three dimensions to form "RNA factories" that maximize the efficiency and accuracy of RNA biogenesis. We find that many loci with multiple binding sites of the same transcription factor interact with one another in trans, especially those bound by transcription factors with intrinsically disordered domains. Similarly, clustered binding of a subset of RNA binding proteins correlates with trans interaction of the encoding loci. These findings support the existence of trans interacting chromatin domains (TIDs) driven by RNA biogenesis. Trans-C provides an efficient computational framework for studying these and other types of trans interactions, empowering studies of a poorly understood aspect of genome architecture.
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Affiliation(s)
| | - William Stafford Noble
- Department of Genome Sciences, University of Washington, Seattle, USA
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, USA
| | - Alessandro Bertero
- Molecular Biotechnology Center “Guido Tarone”, Dept. of Molecular Biotechnology and Health Sciences, University of Turin, Torino, Italy
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25
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Wang T, Shi S, Shi Y, Jiang P, Hu G, Ye Q, Shi Z, Yu K, Wang C, Fan G, Zhao S, Ma H, Chang ACY, Li Z, Bian Q, Lin CP. Chemical-induced phase transition and global conformational reorganization of chromatin. Nat Commun 2023; 14:5556. [PMID: 37689690 PMCID: PMC10492836 DOI: 10.1038/s41467-023-41340-4] [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] [Accepted: 08/29/2023] [Indexed: 09/11/2023] Open
Abstract
Chemicals or drugs can accumulate within biomolecular condensates formed through phase separation in cells. Here, we use super-resolution imaging to search for chemicals that induce phase transition within chromatin at the microscale. This microscopic screening approach reveals that adriamycin (doxorubicin) - a widely used anticancer drug that is known to interact with chromatin - specifically induces visible local condensation and global conformational change of chromatin in cancer and primary cells. Hi-C and ATAC-seq experiments systematically and quantitatively demonstrate that adriamycin-induced chromatin condensation is accompanied by weakened chromatin interaction within topologically associated domains, compartment A/B switching, lower chromatin accessibility, and corresponding transcriptomic changes. Mechanistically, adriamycin complexes with histone H1 and induces phase transition of H1, forming fibrous aggregates in vitro. These results reveal a phase separation-driven mechanism for a chemotherapeutic drug.
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Affiliation(s)
- Tengfei Wang
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
| | - Shuxiang Shi
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
- Lingang Laboratory, 200031, Shanghai, China
| | - Yuanyuan Shi
- Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 200125, Shanghai, China
- Shanghai Key Laboratory of Reproductive Medicine, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
| | - Peipei Jiang
- Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 200125, Shanghai, China
- Shanghai Key Laboratory of Reproductive Medicine, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
| | - Ganlu Hu
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, 201210, Shanghai, China
| | - Qinying Ye
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
| | - Zhan Shi
- School of Physical Science and Technology, ShanghaiTech University, 201210, Shanghai, China
| | - Kexin Yu
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
- iHuman Institute, ShanghaiTech University, 201010, Shanghai, China
| | - Chenguang Wang
- Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 200125, Shanghai, China
- Shanghai Key Laboratory of Reproductive Medicine, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
- Department of Cardiology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guoping Fan
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, 201210, Shanghai, China
| | - Suwen Zhao
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
- iHuman Institute, ShanghaiTech University, 201010, Shanghai, China
| | - Hanhui Ma
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
| | - Alex C Y Chang
- Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 200125, Shanghai, China
- Shanghai Key Laboratory of Reproductive Medicine, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
- Department of Cardiology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhi Li
- School of Physical Science and Technology, ShanghaiTech University, 201210, Shanghai, China
| | - Qian Bian
- Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 200125, Shanghai, China.
- Shanghai Key Laboratory of Reproductive Medicine, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China.
| | - Chao-Po Lin
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China.
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26
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Fu Y, Wang X, Yue F. EagleC Explorer: A desktop application for interactively detecting and visualizing SVs and enhancer hijacking on Hi-C contact maps. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.07.552228. [PMID: 37609202 PMCID: PMC10441372 DOI: 10.1101/2023.08.07.552228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
It has been shown that Hi-C can be used as a powerful tool to detect structural variations (SVs) and enhancer hijacking events. However, there has been no existing programs that can directly visualize and detect such events on a personal computer, which hinders the broad adaption of the technology for intuitive discovery in cancer studies. Here, we introduce the EagleC Explorer, a desktop software that is specifically designed for exploring Hi-C and other chromatin contact data in cancer genomes. EagleC Explorer has a set of unique features, including 1) conveniently visualizing global and local Hi-C data; 2) interactively detecting SVs on a Hi-C map for any user-selected region on screen within seconds, using a deep-learning model; 3) reconstructing local Hi-C map surrounding user-provided SVs and generating publication-quality figures; 4) detecting enhancer hijacking events for any user-suggested regions on screen. In addition, EagleC Explorer can also incorporate other genomic tracks such as RNA-Seq or ChIP-Seq to facilitate scientists for integrative data analysis and making novel discoveries.
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27
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Dekker J, Alber F, Aufmkolk S, Beliveau BJ, Bruneau BG, Belmont AS, Bintu L, Boettiger A, Calandrelli R, Disteche CM, Gilbert DM, Gregor T, Hansen AS, Huang B, Huangfu D, Kalhor R, Leslie CS, Li W, Li Y, Ma J, Noble WS, Park PJ, Phillips-Cremins JE, Pollard KS, Rafelski SM, Ren B, Ruan Y, Shav-Tal Y, Shen Y, Shendure J, Shu X, Strambio-De-Castillia C, Vertii A, Zhang H, Zhong S. Spatial and temporal organization of the genome: Current state and future aims of the 4D nucleome project. Mol Cell 2023; 83:2624-2640. [PMID: 37419111 PMCID: PMC10528254 DOI: 10.1016/j.molcel.2023.06.018] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 06/10/2023] [Accepted: 06/12/2023] [Indexed: 07/09/2023]
Abstract
The four-dimensional nucleome (4DN) consortium studies the architecture of the genome and the nucleus in space and time. We summarize progress by the consortium and highlight the development of technologies for (1) mapping genome folding and identifying roles of nuclear components and bodies, proteins, and RNA, (2) characterizing nuclear organization with time or single-cell resolution, and (3) imaging of nuclear organization. With these tools, the consortium has provided over 2,000 public datasets. Integrative computational models based on these data are starting to reveal connections between genome structure and function. We then present a forward-looking perspective and outline current aims to (1) delineate dynamics of nuclear architecture at different timescales, from minutes to weeks as cells differentiate, in populations and in single cells, (2) characterize cis-determinants and trans-modulators of genome organization, (3) test functional consequences of changes in cis- and trans-regulators, and (4) develop predictive models of genome structure and function.
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Affiliation(s)
- Job Dekker
- University of Massachusetts Chan Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA.
| | - Frank Alber
- University of California, Los Angeles, Los Angeles, CA, USA
| | | | | | - Benoit G Bruneau
- Gladstone Institutes, San Francisco, CA, USA; University of California, San Francisco, San Francisco, CA, USA
| | | | | | | | | | | | | | | | | | - Bo Huang
- University of California, San Francisco, San Francisco, CA, USA
| | - Danwei Huangfu
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Reza Kalhor
- Johns Hopkins University, Baltimore, MD, USA
| | | | - Wenbo Li
- University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yun Li
- University of North Carolina, Gillings School of Global Public Health, Chapel Hill, NC, USA
| | - Jian Ma
- Carnegie Mellon University, Pittsburgh, PA, USA
| | | | | | | | - Katherine S Pollard
- Gladstone Institutes, San Francisco, CA, USA; University of California, San Francisco, San Francisco, CA, USA; Chan Zuckerberg Biohub, San Francisco, San Francisco, CA, USA
| | | | - Bing Ren
- University of California, San Diego, La Jolla, CA, USA
| | - Yijun Ruan
- Zhejiang University, Hangzhou, Zhejiang, China
| | | | - Yin Shen
- University of California, San Francisco, San Francisco, CA, USA
| | | | - Xiaokun Shu
- University of California, San Francisco, San Francisco, CA, USA
| | | | | | | | - Sheng Zhong
- University of California, San Diego, La Jolla, CA, USA.
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28
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Buckberry S, Liu X, Poppe D, Tan JP, Sun G, Chen J, Nguyen TV, de Mendoza A, Pflueger J, Frazer T, Vargas-Landín DB, Paynter JM, Smits N, Liu N, Ouyang JF, Rossello FJ, Chy HS, Rackham OJL, Laslett AL, Breen J, Faulkner GJ, Nefzger CM, Polo JM, Lister R. Transient naive reprogramming corrects hiPS cells functionally and epigenetically. Nature 2023; 620:863-872. [PMID: 37587336 PMCID: PMC10447250 DOI: 10.1038/s41586-023-06424-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 07/11/2023] [Indexed: 08/18/2023]
Abstract
Cells undergo a major epigenome reconfiguration when reprogrammed to human induced pluripotent stem cells (hiPS cells). However, the epigenomes of hiPS cells and human embryonic stem (hES) cells differ significantly, which affects hiPS cell function1-8. These differences include epigenetic memory and aberrations that emerge during reprogramming, for which the mechanisms remain unknown. Here we characterized the persistence and emergence of these epigenetic differences by performing genome-wide DNA methylation profiling throughout primed and naive reprogramming of human somatic cells to hiPS cells. We found that reprogramming-induced epigenetic aberrations emerge midway through primed reprogramming, whereas DNA demethylation begins early in naive reprogramming. Using this knowledge, we developed a transient-naive-treatment (TNT) reprogramming strategy that emulates the embryonic epigenetic reset. We show that the epigenetic memory in hiPS cells is concentrated in cell of origin-dependent repressive chromatin marked by H3K9me3, lamin-B1 and aberrant CpH methylation. TNT reprogramming reconfigures these domains to a hES cell-like state and does not disrupt genomic imprinting. Using an isogenic system, we demonstrate that TNT reprogramming can correct the transposable element overexpression and differential gene expression seen in conventional hiPS cells, and that TNT-reprogrammed hiPS and hES cells show similar differentiation efficiencies. Moreover, TNT reprogramming enhances the differentiation of hiPS cells derived from multiple cell types. Thus, TNT reprogramming corrects epigenetic memory and aberrations, producing hiPS cells that are molecularly and functionally more similar to hES cells than conventional hiPS cells. We foresee TNT reprogramming becoming a new standard for biomedical and therapeutic applications and providing a novel system for studying epigenetic memory.
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Affiliation(s)
- Sam Buckberry
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, Western Australia, Australia
- ARC Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
- Telethon Kids Institute, Perth, Western Australia, Australia
- John Curtin School of Medical Research, College of Health and Medicine, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Xiaodong Liu
- Department of Anatomy and Developmental Biology, Monash University, Melbourne, Victoria, Australia
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Melbourne, Victoria, Australia
- Australian Regenerative Medicine Institute, Monash University, Melbourne, Victoria, Australia
- School of Life Sciences, Westlake University, Hangzhou, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
- Westlake Institute for Advanced Study, Hangzhou, China
| | - Daniel Poppe
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, Western Australia, Australia
- ARC Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Jia Ping Tan
- Department of Anatomy and Developmental Biology, Monash University, Melbourne, Victoria, Australia
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Melbourne, Victoria, Australia
- Australian Regenerative Medicine Institute, Monash University, Melbourne, Victoria, Australia
| | - Guizhi Sun
- Department of Anatomy and Developmental Biology, Monash University, Melbourne, Victoria, Australia
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Melbourne, Victoria, Australia
- Australian Regenerative Medicine Institute, Monash University, Melbourne, Victoria, Australia
| | - Joseph Chen
- Department of Anatomy and Developmental Biology, Monash University, Melbourne, Victoria, Australia
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Melbourne, Victoria, Australia
- Australian Regenerative Medicine Institute, Monash University, Melbourne, Victoria, Australia
| | - Trung Viet Nguyen
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, Western Australia, Australia
- ARC Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Alex de Mendoza
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, Western Australia, Australia
- ARC Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - Jahnvi Pflueger
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, Western Australia, Australia
- ARC Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Thomas Frazer
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, Western Australia, Australia
- ARC Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Dulce B Vargas-Landín
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, Western Australia, Australia
- ARC Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Jacob M Paynter
- Department of Anatomy and Developmental Biology, Monash University, Melbourne, Victoria, Australia
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Melbourne, Victoria, Australia
- Australian Regenerative Medicine Institute, Monash University, Melbourne, Victoria, Australia
| | - Nathan Smits
- Mater Research Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Ning Liu
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - John F Ouyang
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Fernando J Rossello
- Department of Anatomy and Developmental Biology, Monash University, Melbourne, Victoria, Australia
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Melbourne, Victoria, Australia
- Australian Regenerative Medicine Institute, Monash University, Melbourne, Victoria, Australia
- Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Hun S Chy
- Australian Regenerative Medicine Institute, Monash University, Melbourne, Victoria, Australia
- Biomedical Manufacturing, Commonwealth Scientific and Industrial Research Organisation, Melbourne, Victoria, Australia
| | - Owen J L Rackham
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore Medical School, Singapore, Singapore
- School of Biological Sciences, University of Southampton, Southampton, UK
| | - Andrew L Laslett
- Australian Regenerative Medicine Institute, Monash University, Melbourne, Victoria, Australia
- Biomedical Manufacturing, Commonwealth Scientific and Industrial Research Organisation, Melbourne, Victoria, Australia
| | - James Breen
- John Curtin School of Medical Research, College of Health and Medicine, Australian National University, Canberra, Australian Capital Territory, Australia
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Geoffrey J Faulkner
- Mater Research Institute, University of Queensland, Brisbane, Queensland, Australia
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Christian M Nefzger
- Department of Anatomy and Developmental Biology, Monash University, Melbourne, Victoria, Australia
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Melbourne, Victoria, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Jose M Polo
- Department of Anatomy and Developmental Biology, Monash University, Melbourne, Victoria, Australia.
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Melbourne, Victoria, Australia.
- Australian Regenerative Medicine Institute, Monash University, Melbourne, Victoria, Australia.
- Adelaide Centre for Epigenetics, School of Biomedicine, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia.
- The South Australian Immunogenomics Cancer Institute, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia.
| | - Ryan Lister
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, Western Australia, Australia.
- ARC Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia.
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Chiliński M, Lipiński J, Agarwal A, Ruan Y, Plewczynski D. Enhanced performance of gene expression predictive models with protein-mediated spatial chromatin interactions. Sci Rep 2023; 13:11693. [PMID: 37474564 PMCID: PMC10359366 DOI: 10.1038/s41598-023-38865-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 07/16/2023] [Indexed: 07/22/2023] Open
Abstract
There have been multiple attempts to predict the expression of the genes based on the sequence, epigenetics, and various other factors. To improve those predictions, we have decided to investigate adding protein-specific 3D interactions that play a significant role in the condensation of the chromatin structure in the cell nucleus. To achieve this, we have used the architecture of one of the state-of-the-art algorithms, ExPecto, and investigated the changes in the model metrics upon adding the spatially relevant data. We have used ChIA-PET interactions that are mediated by cohesin (24 cell lines), CTCF (4 cell lines), and RNAPOL2 (4 cell lines). As the output of the study, we have developed the Spatial Gene Expression (SpEx) algorithm that shows statistically significant improvements in most cell lines. We have compared ourselves to the baseline ExPecto model, which obtained a 0.82 Spearman's rank correlation coefficient (SCC) score, and 0.85, which is reported by newer Enformer were able to obtain the average correlation score of 0.83. However, in some cases (e.g. RNAPOL2 on GM12878), our improvement reached 0.04, and in some cases (e.g. RNAPOL2 on H1), we reached an SCC of 0.86.
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Affiliation(s)
- Mateusz Chiliński
- Laboratory of Bioinformatics and Computational Genomics, Faculty of Mathematics and Information Science, Warsaw University of Technology, 00-662, Warsaw, Poland
- Laboratory of Functional and Structural Genomics, Centre of New Technologies, University of Warsaw, 02-097, Warsaw, Poland
| | | | - Abhishek Agarwal
- Laboratory of Functional and Structural Genomics, Centre of New Technologies, University of Warsaw, 02-097, Warsaw, Poland
| | - Yijun Ruan
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT, 06030, USA
- Life Sciences Institute, Zhejiang University, Zhejiang, Hangzhou, China
| | - Dariusz Plewczynski
- Laboratory of Bioinformatics and Computational Genomics, Faculty of Mathematics and Information Science, Warsaw University of Technology, 00-662, Warsaw, Poland.
- Laboratory of Functional and Structural Genomics, Centre of New Technologies, University of Warsaw, 02-097, Warsaw, Poland.
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30
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Li K, Zhang P, Wang Z, Shen W, Sun W, Xu J, Wen Z, Li L. iEnhance: a multi-scale spatial projection encoding network for enhancing chromatin interaction data resolution. Brief Bioinform 2023; 24:bbad245. [PMID: 37381618 DOI: 10.1093/bib/bbad245] [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: 03/21/2023] [Revised: 06/06/2023] [Accepted: 06/12/2023] [Indexed: 06/30/2023] Open
Abstract
Although sequencing-based high-throughput chromatin interaction data are widely used to uncover genome-wide three-dimensional chromatin architecture, their sparseness and high signal-noise-ratio greatly restrict the precision of the obtained structural elements. To improve data quality, we here present iEnhance (chromatin interaction data resolution enhancement), a multi-scale spatial projection and encoding network, to predict high-resolution chromatin interaction matrices from low-resolution and noisy input data. Specifically, iEnhance projects the input data into matrix spaces to extract multi-scale global and local feature sets, then hierarchically fused these features by attention mechanism. After that, dense channel encoding and residual channel decoding are used to effectively infer robust chromatin interaction maps. iEnhance outperforms state-of-the-art Hi-C resolution enhancement tools in both visual and quantitative evaluation. Comprehensive analysis shows that unlike other tools, iEnhance can recover both short-range structural elements and long-range interaction patterns precisely. More importantly, iEnhance can be transferred to data enhancement of other tissues or cell lines of unknown resolution. Furthermore, iEnhance performs robustly in enhancement of diverse chromatin interaction data including those from single-cell Hi-C and Micro-C experiments.
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Affiliation(s)
- Kai Li
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Ping Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Zilin Wang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Wei Shen
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Weicheng Sun
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Jinsheng Xu
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Zi Wen
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Li Li
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
- Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
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31
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Pulecio J, Tayyebi Z, Liu D, Wong W, Luo R, Damodaran JR, Kaplan S, Cho H, Yan J, Murphy D, Rickert RW, Shukla A, Zhong A, González F, Yang D, Li W, Zhou T, Apostolou E, Leslie CS, Huangfu D. Discovery of Competent Chromatin Regions in Human Embryonic Stem Cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.14.544990. [PMID: 37398096 PMCID: PMC10312725 DOI: 10.1101/2023.06.14.544990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
The mechanisms underlying the ability of embryonic stem cells (ESCs) to rapidly activate lineage-specific genes during differentiation remain largely unknown. Through multiple CRISPR-activation screens, we discovered human ESCs have pre-established transcriptionally competent chromatin regions (CCRs) that support lineage-specific gene expression at levels comparable to differentiated cells. CCRs reside in the same topological domains as their target genes. They lack typical enhancer-associated histone modifications but show enriched occupancy of pluripotent transcription factors, DNA demethylation factors, and histone deacetylases. TET1 and QSER1 protect CCRs from excessive DNA methylation, while HDAC1 family members prevent premature activation. This "push and pull" feature resembles bivalent domains at developmental gene promoters but involves distinct molecular mechanisms. Our study provides new insights into pluripotency regulation and cellular plasticity in development and disease. One sentence summary We report a class of distal regulatory regions distinct from enhancers that confer human embryonic stem cells with the competence to rapidly activate the expression of lineage-specific genes.
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32
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Wang X, Yue F. HiCLift: a fast and efficient tool for converting chromatin interaction data between genome assemblies. Bioinformatics 2023; 39:btad389. [PMID: 37335863 PMCID: PMC10313346 DOI: 10.1093/bioinformatics/btad389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/30/2023] [Accepted: 06/15/2023] [Indexed: 06/21/2023] Open
Abstract
MOTIVATION With the continuous effort to improve the quality of human reference genome and the generation of more and more personal genomes, the conversion of genomic coordinates between genome assemblies is critical in many integrative and comparative studies. While tools have been developed for such task for linear genome signals such as ChIP-Seq, no tool exists to convert genome assemblies for chromatin interaction data, despite the importance of three-dimensional genome organization in gene regulation and disease. RESULTS Here, we present HiCLift, a fast and efficient tool that can convert the genomic coordinates of chromatin contacts such as Hi-C and Micro-C from one assembly to another, including the latest T2T-CHM13 genome. Comparing with the strategy of directly remapping raw reads to a different genome, HiCLift runs on average 42 times faster (hours vs. days), while outputs nearly identical contact matrices. More importantly, as HiCLift does not need to remap the raw reads, it can directly convert human patient sample data, where the raw sequencing reads are sometimes hard to acquire or not available. AVAILABILITY AND IMPLEMENTATION HiCLift is publicly available at https://github.com/XiaoTaoWang/HiCLift.
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Affiliation(s)
- Xiaotao Wang
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, United States
| | - Feng Yue
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, United States
- Robert H. Lurie Comprehensive Cancer Center of Northwestern University, Chicago, IL 60611, United States
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33
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Cosma MP, Neguembor MV. The magic of unraveling genome architecture and function. Cell Rep 2023; 42:112361. [PMID: 37059093 DOI: 10.1016/j.celrep.2023.112361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 02/20/2023] [Accepted: 03/22/2023] [Indexed: 04/16/2023] Open
Abstract
Over the last decades, technological breakthroughs in super-resolution microscopy have allowed us to reach molecular resolution and design experiments of unprecedented complexity. Investigating how chromatin is folded in 3D, from the nucleosome level up to the entire genome, is becoming possible by "magic" (imaging genomic), i.e., the combination of imaging and genomic approaches. This offers endless opportunities to delve into the relationship between genome structure and function. Here, we review recently achieved objectives and the conceptual and technical challenges the field of genome architecture is currently undertaking. We discuss what we have learned so far and where we are heading. We elucidate how the different super-resolution microscopy approaches and, more specifically, live-cell imaging have contributed to the understanding of genome folding. Moreover, we discuss how future technical developments could address remaining open questions.
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Affiliation(s)
- Maria Pia Cosma
- Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 106 Zhongshan Er Road, Yuexiu District, 510080 Guangzhou, China; Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Spain; ICREA, Pg. Lluís Companys 23, 08010 Barcelona, Spain.
| | - Maria Victoria Neguembor
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, 08003 Barcelona, Spain.
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34
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Tan ZW, Toong PJ, Guarnera E, Berezovsky IN. Disrupted chromatin architecture in olfactory sensory neurons: looking for the link from COVID-19 infection to anosmia. Sci Rep 2023; 13:5906. [PMID: 37041182 PMCID: PMC10088727 DOI: 10.1038/s41598-023-32896-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 04/04/2023] [Indexed: 04/13/2023] Open
Abstract
We tackle here genomic mechanisms of a rapid onset and recovery from anosmia-a potential diagnostic indicator for early-stage COVID-19 infection. Based on previous observations on how olfactory receptor (OR) gene expression is regulated via chromatin structure in mice, we hypothesized that the disruption of the OR gene expression and, respectively, deficiency of the OR function can be caused by chromatin reorganization taking place upon SARS-CoV-2 infection. We obtained chromatin ensemble reconstructions from COVID-19 patients and control samples using our original computational framework for the whole-genome 3D chromatin ensemble reconstruction. Specifically, we used megabase-scale structural units and effective interactions between them obtained in the Markov State modelling of the Hi-C contact network as an unput in the stochastic embedding procedure of the whole-genome 3D chromatin ensemble reconstruction. We have also developed here a new procedure for analyzing fine structural hierarchy with (sub)TAD-size units in local chromatin regions, which we apply here to parts of chromosomes containing OR genes and corresponding regulatory elements. We observed structural modifications in COVID-19 patients on different levels of chromatin organization, from the alteration of whole genome structure and chromosomal intermingling to reorganization of contacts between chromatin loops at the level of topologically associating domains. While complementary data on known regulatory elements point to potential pathology-associated changes within the overall picture of chromatin alterations, further investigation using additional epigenetic factors mapped on 3D reconstructions with improved resolution will be required for better understanding of anosmia caused by SARS-CoV-2 infection.
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Affiliation(s)
- Zhen Wah Tan
- Agency for Science, Technology and Research (A*STAR), Bioinformatics Institute (BII), 30 Biopolis Street, Matrix, Singapore, 138671, Republic of Singapore
| | - Ping Jing Toong
- Agency for Science, Technology and Research (A*STAR), Bioinformatics Institute (BII), 30 Biopolis Street, Matrix, Singapore, 138671, Republic of Singapore
| | - Enrico Guarnera
- Agency for Science, Technology and Research (A*STAR), Bioinformatics Institute (BII), 30 Biopolis Street, Matrix, Singapore, 138671, Republic of Singapore
- Computational Drug Discovery, EMD Serono Research and Development Institute, Merck KGaA, 45A Middlesex Tpke, Billerica, MA, 01821, USA
| | - Igor N Berezovsky
- Agency for Science, Technology and Research (A*STAR), Bioinformatics Institute (BII), 30 Biopolis Street, Matrix, Singapore, 138671, Republic of Singapore.
- Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, Singapore, 117597, Singapore.
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35
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Balasooriya GI, Spector DL. Allele pairing at Sun1-enriched domains at the nuclear periphery via T1A3 tandem DNA repeats. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.07.536031. [PMID: 37066204 PMCID: PMC10104147 DOI: 10.1101/2023.04.07.536031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Spatiotemporal gene regulation is fundamental to the biology of diploid cells. Therefore, effective communication between two alleles and their geometry in the nucleus is important. However, the mechanism that fine-tunes the expression from each of the two alleles of an autosome is enigmatic. Establishing an allele-specific gene expression visualization system in living cells, we show that alleles of biallelically expressed Cth and Ttc4 genes are paired prior to acquiring monoallelic expression. We found that active alleles of monoallelic genes are preferentially localized at Sun1-enriched domains at the nuclear periphery. These peripherally localized active DNA loci are enriched with adenine-thymidine-rich tandem repeats that interact with Hnrnpd and reside in a Hi-C-defined A compartment within the B compartment. Our results demonstrate the biological significance of T 1 A 3 tandem repeat sequences in genome organization and how the regulation of gene expression, at the level of individual alleles, relates to their spatial arrangement.
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36
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Chiliński M, Lipiński J, Agarwal A, Ruan Y, Plewczynski D. Enhanced performance of gene expression predictive models with protein-mediated spatial chromatin interactions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.06.535849. [PMID: 37066361 PMCID: PMC10104055 DOI: 10.1101/2023.04.06.535849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
There have been multiple attempts to predict the expression of the genes based on the sequence, epigenetics, and various other factors. To improve those predictions, we have decided to investigate adding protein-specific 3D interactions that play a major role in the compensation of the chromatin structure in the cell nucleus. To achieve this, we have used the architecture of one of the state-of-the-art algorithms, ExPecto (J. Zhou et al., 2018), and investigated the changes in the model metrics upon adding the spatially relevant data. We have used ChIA-PET interactions that are mediated by cohesin (24 cell lines), CTCF (4 cell lines), and RNAPOL2 (4 cell lines). As the output of the study, we have developed the Spatial Gene Expression (SpEx) algorithm that shows statistically significant improvements in most cell lines.
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37
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Zhan Y, Yildirim A, Boninsegna L, Alber F. Conformational analysis of chromosome structures reveals vital role of chromosome morphology in gene function. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.18.528138. [PMID: 36824908 PMCID: PMC9949133 DOI: 10.1101/2023.02.18.528138] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/21/2023]
Abstract
The 3D conformations of chromosomes are highly variant and stochastic between single cells. Recent progress in multiplexed 3D FISH imaging, single cell Hi-C and genome structure modeling allows a closer analysis of the structural variations of chromosomes between cells to infer the functional implications of structural heterogeneity. Here, we introduce a two-step dimensionality reduction method to classify a population of single cell 3D chromosome structures, either from simulation or imaging experiment, into dominant conformational clusters with distinct chromosome morphologies. We found that almost half of all structures for each chromosome can be described by 5-10 dominant chromosome morphologies, which play a fundamental role in establishing conformational variation of chromosomes. These morphologies are conserved in different cell types, but vary in their relative proportion of structures. Chromosome morphologies are distinguished by the presence or absence of characteristic chromosome territory domains, which expose some chromosomal regions to varying nuclear environments in different morphologies, such as nuclear positions and associations to nuclear speckles, lamina, and nucleoli. These observations point to distinct functional variations for the same chromosomal region in different chromosome morphologies. We validated chromosome conformational clusters and their associated subnuclear locations with data from DNA-MERFISH imaging and single cell sci-HiC data. Our method provides an important approach to assess the variation of chromosome structures between cells and link differences in conformational states with distinct gene functions.
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38
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Li Z, Gao E, Zhou J, Han W, Xu X, Gao X. Applications of deep learning in understanding gene regulation. CELL REPORTS METHODS 2023; 3:100384. [PMID: 36814848 PMCID: PMC9939384 DOI: 10.1016/j.crmeth.2022.100384] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
Gene regulation is a central topic in cell biology. Advances in omics technologies and the accumulation of omics data have provided better opportunities for gene regulation studies than ever before. For this reason deep learning, as a data-driven predictive modeling approach, has been successfully applied to this field during the past decade. In this article, we aim to give a brief yet comprehensive overview of representative deep-learning methods for gene regulation. Specifically, we discuss and compare the design principles and datasets used by each method, creating a reference for researchers who wish to replicate or improve existing methods. We also discuss the common problems of existing approaches and prospectively introduce the emerging deep-learning paradigms that will potentially alleviate them. We hope that this article will provide a rich and up-to-date resource and shed light on future research directions in this area.
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Affiliation(s)
- Zhongxiao Li
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
- KAUST Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Elva Gao
- The KAUST School, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Juexiao Zhou
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
- KAUST Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Wenkai Han
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
- KAUST Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Xiaopeng Xu
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
- KAUST Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Xin Gao
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
- KAUST Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
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39
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Wang X, Yue F. HiCLift: A fast and efficient tool for converting chromatin interaction data between genome assemblies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.17.524475. [PMID: 36712087 PMCID: PMC9882170 DOI: 10.1101/2023.01.17.524475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Motivation With the continuous effort to improve the quality of human reference genome and the generation of more and more personal genomes, the conversion of genomic coordinates between genome assemblies is critical in many integrative and comparative studies. While tools have been developed for such task for linear genome signals such as ChIP-Seq, no tool exists to convert genome assemblies for chromatin interaction data, despite the importance of three-dimensional (3D) genome organization in gene regulation and disease. Results Here, we present HiCLift, a fast and efficient tool that can convert the genomic coordinates of chromatin contacts such as Hi-C and Micro-C from one assembly to another, including the latest T2T genome. Comparing with the strategy of directly re-mapping raw reads to a different genome, HiCLift runs on average 42 times faster (hours vs. days), while outputs nearly identical contact matrices. More importantly, as HiCLift does not need to re-map the raw reads, it can directly convert human patient sample data, where the raw sequencing reads are sometimes hard to acquire or not available. Availability HiCLift is publicly available at https://github.com/XiaoTaoWang/HiCLift .
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40
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Meroni A, Grosser J, Agashe S, Ramakrishnan N, Jackson J, Verma P, Baranello L, Vindigni A. NEDDylated Cullin 3 mediates the adaptive response to topoisomerase 1 inhibitors. SCIENCE ADVANCES 2022; 8:eabq0648. [PMID: 36490343 PMCID: PMC9733930 DOI: 10.1126/sciadv.abq0648] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 10/26/2022] [Indexed: 05/30/2023]
Abstract
DNA topoisomerase 1 (TOP11) inhibitors are mainstays of anticancer therapy. These drugs trap TOP1 on DNA, stabilizing the TOP1-cleavage complex (TOP1-cc). The accumulation of TOP1-ccs perturbs DNA replication fork progression, leading to DNA breaks and cell death. By analyzing the genomic occupancy and activity of TOP1, we show that cells adapt to treatment with multiple doses of TOP1 inhibitor by promoting the degradation of TOP1-ccs, allowing cells to better tolerate subsequent doses of TOP1 inhibitor. The E3-RING Cullin 3 ligase in complex with the BTBD1 and BTBD2 adaptor proteins promotes TOP1-cc ubiquitination and subsequent proteasomal degradation. NEDDylation of Cullin 3 activates this pathway, and inhibition of protein NEDDylation or depletion of Cullin 3 sensitizes cancer cells to TOP1 inhibitors. Collectively, our data uncover a previously unidentified NEDD8-Cullin 3 pathway involved in the adaptive response to TOP1 inhibitors, which can be targeted to improve the efficacy of TOP1 drugs in cancer therapy.
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Affiliation(s)
- Alice Meroni
- Division of Oncology, Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jan Grosser
- Karolinska Institutet, CMB, 171 65 Solna, Sweden
| | - Sumedha Agashe
- Division of Oncology, Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Natasha Ramakrishnan
- Division of Oncology, Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jessica Jackson
- Division of Oncology, Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Priyanka Verma
- Division of Oncology, Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA
| | | | - Alessandro Vindigni
- Division of Oncology, Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA
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Integrating extrusion complex-associated pattern to predict cell type-specific long-range chromatin loops. iScience 2022; 25:105687. [PMID: 36567710 PMCID: PMC9768375 DOI: 10.1016/j.isci.2022.105687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 11/10/2022] [Accepted: 11/25/2022] [Indexed: 12/07/2022] Open
Abstract
The chromatin loop plays a critical role in the study of gene expression and disease. Supervised learning-based algorithms to predict the chromatin loops require large priori information to satisfy the model construction, while the prediction sensitivity of unsupervised learning-based algorithms is still unsatisfactory. Therefore, we propose an unsupervised algorithm, Ecomap-loop. It takes advantage of extrusion complex-associated patterns, including CTCF, RAD21, and SMC enrichments, as well as the orientation distribution of CTCF motif of loops to build feature matrices; then the eigen decomposition model is employed to obtain the cell type-specific loops. We compare the performance of Ecomap-loop with the state-of-the-art unsupervised algorithm using Hi-C, ChIA-PET, expression quantitative trait locus (eQTL), and CRISPR interference (CRISPRi) screen data; the results show that Ecomap-loop achieves the best in four cell types. In addition, the functional analysis reveals the ability of Ecomap-loop to predict active functionality-related and cell type-specific loops.
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42
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Finn EH, Misteli T. Nuclear position modulates long-range chromatin interactions. PLoS Genet 2022; 18:e1010451. [PMID: 36206323 PMCID: PMC9581366 DOI: 10.1371/journal.pgen.1010451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 10/19/2022] [Accepted: 09/28/2022] [Indexed: 11/18/2022] Open
Abstract
The human genome is non-randomly organized within the cell nucleus. Spatial mapping of genome folding by biochemical methods and imaging has revealed extensive variation in locus interaction frequencies between cells in a population and between homologs within an individual cell. Commonly used mapping approaches typically examine either the relative position of genomic sites to each other or the position of individual loci relative to nuclear landmarks. Whether the frequency of specific chromatin-chromatin interactions is affected by where in the nuclear space a locus is located is unknown. Here, we have simultaneously mapped at the single cell level the interaction frequencies and radial position of more than a hundred locus pairs using high-throughput imaging to ask whether the location within the nucleus affects interaction frequency. We find strong enrichment of many interactions at specific radial positions. Position-dependency of interactions was cell-type specific, correlated with local chromatin type, and cell-type-specific enriched associations were marked by increased variability, sometimes without a significant decrease in mean spatial distance. These observations demonstrate that the folding of the chromatin fiber, which brings genomically distant loci into proximity, and the position of that chromatin fiber relative to nuclear landmarks, are closely linked.
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Affiliation(s)
- Elizabeth H. Finn
- Program in Cell Cycle and Cancer Biology, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, United States of America
| | - Tom Misteli
- National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
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43
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Friskes A, Koob L, Krenning L, Severson TM, Koeleman E, Vergara X, Schubert M, van den Berg J, Evers B, Manjón AG, Joosten S, Kim Y, Zwart W, Medema R. Double-strand break toxicity is chromatin context independent. Nucleic Acids Res 2022; 50:9930-9947. [PMID: 36107780 PMCID: PMC9508844 DOI: 10.1093/nar/gkac758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 08/09/2022] [Accepted: 08/26/2022] [Indexed: 11/19/2022] Open
Abstract
Cells respond to double-strand breaks (DSBs) by activating DNA damage response pathways, including cell cycle arrest. We have previously shown that a single double-strand break generated via CRISPR/Cas9 is sufficient to delay cell cycle progression and compromise cell viability. However, we also found that the cellular response to DSBs can vary, independent of the number of lesions. This implies that not all DSBs are equally toxic, and raises the question if the location of a single double-strand break could influence its toxicity. To systematically investigate if DSB-location is a determinant of toxicity we performed a CRISPR/Cas9 screen targeting 6237 single sites in the human genome. Next, we developed a data-driven framework to design CRISPR/Cas9 sgRNA (crRNA) pools targeting specific chromatin features. The chromatin context was defined using ChromHMM states, Lamin-B1 DAM-iD, DNAseI hypersensitivity, and RNA-sequencing data. We computationally designed 6 distinct crRNA pools, each containing 10 crRNAs targeting the same chromatin state. We show that the toxicity of a DSB is highly similar across the different ChromHMM states. Rather, we find that the major determinants of toxicity of a sgRNA are cutting efficiency and off-target effects. Thus, chromatin features have little to no effect on the toxicity of a single CRISPR/Cas9-induced DSB.
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Affiliation(s)
- Anoek Friskes
- Oncode Institute, Division of Cell Biology, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Lisa Koob
- Oncode Institute, Division of Cell Biology, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Lenno Krenning
- Oncode Institute, Division of Cell Biology, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Tesa M Severson
- Oncode Institute, Division of Oncogenomics, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Emma S Koeleman
- Oncode Institute, Division of Cell Biology, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Xabier Vergara
- Oncode Institute, Division of Cell Biology, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Oncode Institute, Division of Gene Regulation, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Michael Schubert
- Oncode Institute, Division of Cell Biology, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Jeroen van den Berg
- Oncode Institute, Division of Cell Biology, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Bastiaan Evers
- Oncode Institute, Division of Molecular Carcinogenesis and NKI Robotics and Screening Center, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Anna G Manjón
- Oncode Institute, Division of Cell Biology, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Stacey Joosten
- Oncode Institute, Division of Oncogenomics, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Yongsoo Kim
- Oncode Institute, Division of Oncogenomics, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Wilbert Zwart
- Oncode Institute, Division of Oncogenomics, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - René H Medema
- Oncode Institute, Division of Cell Biology, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
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44
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Zhang S, Plummer D, Lu L, Cui J, Xu W, Wang M, Liu X, Prabhakar N, Shrinet J, Srinivasan D, Fraser P, Li Y, Li J, Jin F. DeepLoop robustly maps chromatin interactions from sparse allele-resolved or single-cell Hi-C data at kilobase resolution. Nat Genet 2022; 54:1013-1025. [PMID: 35817982 PMCID: PMC10082397 DOI: 10.1038/s41588-022-01116-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 05/30/2022] [Indexed: 11/09/2022]
Abstract
Mapping chromatin loops from noisy Hi-C heatmaps remains a major challenge. Here we present DeepLoop, which performs rigorous bias correction followed by deep-learning-based signal enhancement for robust chromatin interaction mapping from low-depth Hi-C data. DeepLoop enables loop-resolution, single-cell Hi-C analysis. It also achieves a cross-platform convergence between different Hi-C protocols and micrococcal nuclease (micro-C). DeepLoop allowed us to map the genetic and epigenetic determinants of allele-specific chromatin interactions in the human genome. We nominate new loci with allele-specific interactions governed by imprinting or allelic DNA methylation. We also discovered that, in the inactivated X chromosome (Xi), local loops at the DXZ4 'megadomain' boundary escape X-inactivation but the FIRRE 'superloop' locus does not. Importantly, DeepLoop can pinpoint heterozygous single-nucleotide polymorphisms and large structure variants that cause allelic chromatin loops, many of which rewire enhancers with transcription consequences. Taken together, DeepLoop expands the use of Hi-C to provide loop-resolution insights into the genetics of the three-dimensional genome.
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Affiliation(s)
- Shanshan Zhang
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.,The Biomedical Sciences Training Program, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Dylan Plummer
- Department of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Leina Lu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Jian Cui
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Wanying Xu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.,The Biomedical Sciences Training Program, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Miao Wang
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Xiaoxiao Liu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Nachiketh Prabhakar
- Department of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Jatin Shrinet
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Divyaa Srinivasan
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Peter Fraser
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Yan Li
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
| | - Jing Li
- Department of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH, USA. .,Department of Population and Quantitative Health Sciences, Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, USA.
| | - Fulai Jin
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA. .,Department of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH, USA. .,Department of Population and Quantitative Health Sciences, Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, USA.
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