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Fu Z, Jiang S, Sun Y, Zheng S, Zong L, Li P. Cut&tag: a powerful epigenetic tool for chromatin profiling. Epigenetics 2024; 19:2293411. [PMID: 38105608 PMCID: PMC10730171 DOI: 10.1080/15592294.2023.2293411] [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: 09/07/2023] [Accepted: 12/05/2023] [Indexed: 12/19/2023] Open
Abstract
Analysis of transcription factors and chromatin modifications at the genome-wide level provides insights into gene regulatory processes, such as transcription, cell differentiation and cellular response. Chromatin immunoprecipitation is the most popular and powerful approach for mapping chromatin, and other enzyme-tethering techniques have recently become available for living cells. Among these, Cleavage Under Targets and Tagmentation (CUT&Tag) is a relatively novel chromatin profiling method that has rapidly gained popularity in the field of epigenetics since 2019. It has also been widely adapted to map chromatin modifications and TFs in different species, illustrating the association of these chromatin epitopes with various physiological and pathological processes. Scalable single-cell CUT&Tag can be combined with distinct platforms to distinguish cellular identity, epigenetic features and even spatial chromatin profiling. In addition, CUT&Tag has been developed as a strategy for joint profiling of the epigenome, transcriptome or proteome on the same sample. In this review, we will mainly consolidate the applications of CUT&Tag and its derivatives on different platforms, give a detailed explanation of the pros and cons of this technique as well as the potential development trends and applications in the future.
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Affiliation(s)
- Zhijun Fu
- BGI Tech Solutions Co, Ltd. BGI-Shenzhen, Shenzhen, China
| | - Sanjie Jiang
- BGI Tech Solutions Co, Ltd. BGI-Shenzhen, Shenzhen, China
| | - Yiwen Sun
- BGI Tech Solutions Co, Ltd. BGI-Shenzhen, Shenzhen, China
| | - Shanqiao Zheng
- BGI Tech Solutions Co, Ltd. BGI-Shenzhen, Shenzhen, China
| | - Liang Zong
- BGI Tech Solutions Co, Ltd. BGI-Wuhan, Wuhan, China
| | - Peipei Li
- BGI Tech Solutions Co, Ltd. BGI-Shenzhen, Shenzhen, China
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de Mello FN, Tahira AC, Berzoti-Coelho MG, Verjovski-Almeida S. The CUT&RUN greenlist: genomic regions of consistent noise are effective normalizing factors for quantitative epigenome mapping. Brief Bioinform 2024; 25:bbad538. [PMID: 38279652 PMCID: PMC10818165 DOI: 10.1093/bib/bbad538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 12/14/2023] [Accepted: 12/25/2023] [Indexed: 01/28/2024] Open
Abstract
Cleavage Under Targets and Release Using Nuclease (CUT&RUN) is a recent development for epigenome mapping, but its unique methodology can hamper proper quantitative analyses. As traditional normalization approaches have been shown to be inaccurate, we sought to determine endogenous normalization factors based on the human genome regions of constant nonspecific signal. This constancy was determined by applying Shannon's information entropy, and the set of normalizer regions, which we named the 'Greenlist', was extensively validated using publicly available datasets. We demonstrate here that the greenlist normalization outperforms the current top standards, and remains consistent across different experimental setups, cell lines and antibodies; the approach can even be applied to different species or to CUT&Tag. Requiring no additional experimental steps and no added cost, this approach can be universally applied to CUT&RUN experiments to greatly minimize the interference of technical variation over the biological epigenome changes of interest.
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Affiliation(s)
- Fabio N de Mello
- Cell Cycle Laboratory, Instituto Butantan, São Paulo, Brazil
- Interunit Bioinformatics Graduate Program, Universidade de São Paulo, São Paulo, Brazil
| | - Ana C Tahira
- Cell Cycle Laboratory, Instituto Butantan, São Paulo, Brazil
| | - Maria Gabriela Berzoti-Coelho
- Cell Cycle Laboratory, Instituto Butantan, São Paulo, Brazil
- Instituto de Química, Universidade de São Paulo, São Paulo, Brazil
| | - Sergio Verjovski-Almeida
- Cell Cycle Laboratory, Instituto Butantan, São Paulo, Brazil
- Instituto de Química, Universidade de São Paulo, São Paulo, Brazil
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Takeuchi F, Liang YQ, Shimizu-Furusawa H, Isono M, Ang MY, Mori K, Mori T, Kakazu E, Yoshio S, Kato N. Gene-regulation modules in nonalcoholic fatty liver disease revealed by single-nucleus ATAC-seq. Life Sci Alliance 2023; 6:e202301988. [PMID: 37491046 PMCID: PMC10368228 DOI: 10.26508/lsa.202301988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 07/14/2023] [Accepted: 07/14/2023] [Indexed: 07/27/2023] Open
Abstract
We investigated the progression of nonalcoholic fatty liver disease from fatty liver to steatohepatitis using single-nucleus and bulk ATAC-seq on the livers of rats fed a high-fat diet (HFD). Rats fed HFD for 4 wk developed fatty liver, and those fed HFD for 8 wk further progressed to steatohepatitis. We observed an increase in the proportion of inflammatory macrophages, consistent with the pathological progression. Utilizing machine learning, we divided global gene regulation into modules, wherein transcription factors within a module could regulate genes within the same module, reaffirming known regulatory relationships between transcription factors and biological processes. We identified core genes-central to co-expression and protein-protein interaction-for the biological processes discovered. Notably, a large part of the core genes overlapped with genes previously implicated in nonalcoholic fatty liver disease. Single-nucleus ATAC-seq, combined with data-driven statistical analysis, offers insight into in vivo global gene regulation as a combination of modules and assists in identifying core genes of relevant biological processes.
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Affiliation(s)
- Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
- Medical Genomics Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
- Systems Genomics Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Yi-Qiang Liang
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Hana Shimizu-Furusawa
- Department of Hygiene and Public Health, School of Medicine, Teikyo University, Tokyo, Japan
| | - Masato Isono
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Mia Yang Ang
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
- Department of Clinical Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kotaro Mori
- Medical Genomics Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Taizo Mori
- Department of Liver Diseases, The Research Center for Hepatitis and Immunology, National Center for Global Health and Medicine, Chiba, Japan
| | - Eiji Kakazu
- Department of Liver Diseases, The Research Center for Hepatitis and Immunology, National Center for Global Health and Medicine, Chiba, Japan
| | - Sachiyo Yoshio
- Department of Liver Diseases, The Research Center for Hepatitis and Immunology, National Center for Global Health and Medicine, Chiba, Japan
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
- Medical Genomics Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
- Department of Clinical Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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Deleuze V, Garcia L, Rouaisnel B, Salma M, Kinoo A, Andrieu-Soler C, Soler E. Efficient genome editing in erythroid cells unveils novel MYB target genes and regulatory functions. iScience 2023; 26:107641. [PMID: 37670779 PMCID: PMC10475484 DOI: 10.1016/j.isci.2023.107641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 07/09/2023] [Accepted: 08/11/2023] [Indexed: 09/07/2023] Open
Abstract
Targeted genome editing holds great promise in biology. However, efficient genome modification, including gene knock-in (KI), remains an unattained goal in multiple cell types and loci due to poor transfection efficiencies and low target genes expression, impeding the positive selection of recombined cells. Here, we describe a genome editing approach to achieve efficient gene targeting using hard to transfect erythroid cell lines. We demonstrate robust fluorescent protein KI efficiency in low expressed transcription factor (TF) genes (e.g., Myb or Zeb1). We further show the ability to target two independent loci in individual cells, exemplified by MYB-GFP and NuMA-Cherry double KI, allowing multicolor labeling of regulatory factors at physiological endogenous levels. Our KI tagging approach allowed us to perform genome-wide TF analysis at increased signal-to-noise ratios, and highlighted previously unidentified MYB target genes and pathways. Overall, we establish a versatile CRISPR-Cas9-based platform, offering attractive opportunities for the dissection of the erythroid differentiation process.
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Affiliation(s)
| | - Leonor Garcia
- IGMM, University Montpellier, CNRS, Montpellier, France
| | | | - Mohammad Salma
- IGMM, University Montpellier, CNRS, Montpellier, France
- Laboratory of Excellence GR-Ex, Université de Paris, Paris, France
| | - Alexia Kinoo
- IGMM, University Montpellier, CNRS, Montpellier, France
| | - Charlotte Andrieu-Soler
- IGMM, University Montpellier, CNRS, Montpellier, France
- Laboratory of Excellence GR-Ex, Université de Paris, Paris, France
| | - Eric Soler
- IGMM, University Montpellier, CNRS, Montpellier, France
- Laboratory of Excellence GR-Ex, Université de Paris, Paris, France
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