1
|
Huang H, Zhou F, Jia J, Zhang H. DTC-m6Am: A Framework for Recognizing N6,2'-O-dimethyladenosine Sites in Unbalanced Classification Patterns Based on DenseNet and Attention Mechanisms. FRONT BIOSCI-LANDMRK 2025; 30:36603. [PMID: 40302345 DOI: 10.31083/fbl36603] [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: 12/26/2024] [Revised: 03/12/2025] [Accepted: 03/25/2025] [Indexed: 05/02/2025]
Abstract
BACKGROUND m6Am is a specific RNA modification that plays an important role in regulating mRNA stability, translational efficiency, and cellular stress response. m6Am's precise identification is essential to gain insight into its functional mechanisms at transcriptional and post-transcriptional levels. Due to the limitations of experimental assays, the development of efficient computational tools to predict m6Am sites has become a major focus of research, offering potential breakthroughs in RNA epigenetics. In this study, we present a robust and reliable deep learning model, DTC-m6Am, for identifying m6Am sites across the transcriptome. METHODS Our proposed DTC-m6Am model first represents RNA sequences by One-Hot coding to capture base-based features and provide structured inputs for subsequent deep learning models. The model then combines densely connected convolutional networks (DenseNet) and temporal convolutional network (TCN). The DenseNet module leverages its dense connectivity property to effectively extract local features and enhance information flow, whereas the TCN module focuses on capturing global time series dependencies to enhance the modeling capability for long sequence features. To further optimize feature extraction, the Convolutional Block Attention Module (CBAM) is used to focus on key regions through spatial and channel attention mechanisms. Finally, a fully connected layer is used for the classification task to achieve accurate prediction of the m6Am site. For the data imbalance problem, we use the focal loss function to balance the learning effect of positive and negative samples and improve the performance of the model on imbalanced data. RESULTS The deep learning-based DTC-m6Am model performs well on all evaluation metrics, achieving 87.8%, 50.3%, 69.1%, 41.1%, and 76.5% for sensitivity (Sn), specificity (Sp), accuracy (ACC), Mathew's correlation coefficient (MCC), and area under the curve (AUC), respectively, on the independent test set. CONCLUSIONS We critically evaluated the performance of DTC-m6Am using 10-fold cross-validation and independent testing and compared it to existing methods. The MCC value of 41.1% was achieved when using the independent test, which is 19.7% higher than the current state-of-the-art prediction method, m6Aminer. The results indicate that the DTC-m6Am model has high accuracy and stability and is an effective tool for predicting m6Am sites.
Collapse
Affiliation(s)
- Hui Huang
- School of Information Engineering, Jingdezhen Ceramic University, 333403 Jingdezhen, Jiangxi, China
| | - Fenglin Zhou
- School of Information Engineering, Jingdezhen Ceramic University, 333403 Jingdezhen, Jiangxi, China
| | - Jianhua Jia
- School of Information Engineering, Jingdezhen Ceramic University, 333403 Jingdezhen, Jiangxi, China
| | - Huachun Zhang
- School of Information Engineering, Jingdezhen Ceramic University, 333403 Jingdezhen, Jiangxi, China
| |
Collapse
|
2
|
Spangenberg J, Mündnich S, Busch A, Pastore S, Wierczeiko A, Goettsch W, Dietrich V, Pryszcz LP, Cruciani S, Novoa EM, Joshi K, Perera R, Di Giorgio S, Arrubarrena P, Tellioglu I, Poon CL, Wan YK, Göke J, Hildebrandt A, Dieterich C, Helm M, Marz M, Gerber S, Alagna N. The RMaP challenge of predicting RNA modifications by nanopore sequencing. Commun Chem 2025; 8:115. [PMID: 40221591 PMCID: PMC11993749 DOI: 10.1038/s42004-025-01507-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2024] [Accepted: 03/24/2025] [Indexed: 04/14/2025] Open
Abstract
The field of epitranscriptomics is undergoing a technology-driven revolution. During past decades, RNA modifications like N6-methyladenosine (m6A), pseudouridine (ψ), and 5-methylcytosine (m5C) became acknowledged for playing critical roles in cellular processes. Direct RNA sequencing by Oxford Nanopore Technologies (ONT) enabled the detection of modifications in native RNA, by detecting noncanonical RNA nucleosides properties in raw data. Consequently, the field's cutting edge has a heavy component in computer science, opening new avenues of cooperation across the community, as exchanging data is as impactful as exchanging samples. Therefore, we seize the occasion to bring scientists together within the RNA Modification and Processing (RMaP) challenge to advance solutions for RNA modification detection and discuss ideas, problems and approaches. We show several computational methods to detect the most researched mRNA modifications (m6A, ψ, and m5C). Results demonstrate that a low prediction error and a high prediction accuracy can be achieved on these modifications across different approaches and algorithms. The RMaP challenge marks a substantial step towards improving algorithms' comparability, reliability, and consistency in RNA modification prediction. It points out the deficits in this young field that need to be addressed in further challenges.
Collapse
Affiliation(s)
- Jannes Spangenberg
- RNA Bioinformatics, Friedrich-Schiller-University Jena, Leutragraben 1, 07743, Jena, Germany
| | - Stefan Mündnich
- Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Mainz, 55128, Mainz, Germany
| | - Anne Busch
- Institute for Informatics, Johannes Gutenberg-University Mainz, 55128, Mainz, Germany
| | - Stefan Pastore
- Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Mainz, 55128, Mainz, Germany
- Institute for Human Genetics, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Anna Wierczeiko
- Institute for Human Genetics, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Winfried Goettsch
- RNA Bioinformatics, Friedrich-Schiller-University Jena, Leutragraben 1, 07743, Jena, Germany
- Fritz Lipmann Institute-Leibniz Institute on Aging, 07745, Jena, Germany
| | - Vincent Dietrich
- Institute for Human Genetics, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Leszek P Pryszcz
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona, 08003, Spain
| | - Sonia Cruciani
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona, 08003, Spain
| | - Eva Maria Novoa
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona, 08003, Spain
- Universitat Pompeu Fabra, Barcelona, 08003, Spain
- ICREA, Pg Lluis Companys 23, Barcelona, 08010, Spain
| | - Kandarp Joshi
- Department of Neurosurgery, Oncology, Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, 1650 Orleans St, Baltimore, MD, 21231, USA
- Johns Hopkins All Children's Hospital, 600 5th St. South, St.Petersburg, FL, 33701, USA
| | - Ranjan Perera
- Department of Neurosurgery, Oncology, Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, 1650 Orleans St, Baltimore, MD, 21231, USA
- Johns Hopkins All Children's Hospital, 600 5th St. South, St.Petersburg, FL, 33701, USA
| | - Salvatore Di Giorgio
- Division of Immune Diversity, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Paola Arrubarrena
- Department of Mathematics at Imperial College London, London, SW7 2AZ, UK
- The Alan Turing Institute, London, NW1 2DB, UK
| | - Irem Tellioglu
- Division of Immune Diversity, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- Graduate Program of the Faculty of Biosciences, Heidelberg University, Heidelberg, 69120, Germany
| | - Chi-Lam Poon
- Computational Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Yuk Kei Wan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, 138672, Republic of Singapore
| | - Jonathan Göke
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, 138672, Republic of Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Republic of Singapore
| | - Andreas Hildebrandt
- Institute for Informatics, Johannes Gutenberg-University Mainz, 55128, Mainz, Germany
| | - Christoph Dieterich
- Klaus Tschira Institute for Integrative Computational Cardiology, University Hospital Heidelberg, Im Neuenheimer Feld 669, 69120, Heidelberg, Germany.
| | - Mark Helm
- Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Mainz, 55128, Mainz, Germany.
| | - Manja Marz
- RNA Bioinformatics, Friedrich-Schiller-University Jena, Leutragraben 1, 07743, Jena, Germany.
- Fritz Lipmann Institute-Leibniz Institute on Aging, 07745, Jena, Germany.
- Balance of the Microverse, Fürstengraben 1, 07743, Jena, Germany.
| | - Susanne Gerber
- Institute for Human Genetics, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
- Institute for Quantitative and Computational Biosciences (IQCB), Mainz, Germany.
| | - Nicolo Alagna
- Institute for Human Genetics, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
| |
Collapse
|
3
|
Chen Y, Davidson NM, Wan YK, Yao F, Su Y, Gamaarachchi H, Sim A, Patel H, Low HM, Hendra C, Wratten L, Hakkaart C, Sawyer C, Iakovleva V, Lee PL, Xin L, Ng HEV, Loo JM, Ong X, Ng HQA, Wang J, Koh WQC, Poon SYP, Stanojevic D, Tran HD, Lim KHE, Toh SY, Ewels PA, Ng HH, Iyer NG, Thiery A, Chng WJ, Chen L, DasGupta R, Sikic M, Chan YS, Tan BOP, Wan Y, Tam WL, Yu Q, Khor CC, Wüstefeld T, Lezhava A, Pratanwanich PN, Love MI, Goh WSS, Ng SB, Oshlack A, Göke J. A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines. Nat Methods 2025; 22:801-812. [PMID: 40082608 PMCID: PMC11978509 DOI: 10.1038/s41592-025-02623-4] [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: 10/18/2021] [Accepted: 02/04/2025] [Indexed: 03/16/2025]
Abstract
The human genome contains instructions to transcribe more than 200,000 RNAs. However, many RNA transcripts are generated from the same gene, resulting in alternative isoforms that are highly similar and that remain difficult to quantify. To evaluate the ability to study RNA transcript expression, we profiled seven human cell lines with five different RNA-sequencing protocols, including short-read cDNA, Nanopore long-read direct RNA, amplification-free direct cDNA and PCR-amplified cDNA sequencing, and PacBio IsoSeq, with multiple spike-in controls, and additional transcriptome-wide N6-methyladenosine profiling data. We describe differences in read length, coverage, throughput and transcript expression, reporting that long-read RNA sequencing more robustly identifies major isoforms. We illustrate the value of the SG-NEx data to identify alternative isoforms, novel transcripts, fusion transcripts and N6-methyladenosine RNA modifications. Together, the SG-NEx data provide a comprehensive resource enabling the development and benchmarking of computational methods for profiling complex transcriptional events at isoform-level resolution.
Collapse
Affiliation(s)
- Ying Chen
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore.
| | - Nadia M Davidson
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Parkville, Victoria, Australia
- Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Yuk Kei Wan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Fei Yao
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Yan Su
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Hasindu Gamaarachchi
- School of Computer Science and Engineering, UNSW Sydney, Sydney, New South Wales, Australia
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Andre Sim
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | | | - Hwee Meng Low
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Christopher Hendra
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- Institute of Data Science, National University of Singapore, Singapore, Singapore
| | - Laura Wratten
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | | | - Chelsea Sawyer
- Bioinformatics and Biostatistics, The Francis Crick Institute, London, UK
| | - Viktoriia Iakovleva
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- Division of Gastroenterology and Hepatology, Weill Cornell Medicine, New York, NY, USA
| | - Puay Leng Lee
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Lixia Xin
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- Cardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, Singapore, Singapore
| | - Hui En Vanessa Ng
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Jia Min Loo
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Xuewen Ong
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore, Singapore
| | - Hui Qi Amanda Ng
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Jiaxu Wang
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Wei Qian Casslynn Koh
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Suk Yeah Polly Poon
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Dominik Stanojevic
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- Department of Electronic Systems and Information Processing, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia
| | - Hoang-Dai Tran
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Kok Hao Edwin Lim
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Shen Yon Toh
- National Cancer Centre Singapore, Singapore, Singapore
| | | | - Huck-Hui Ng
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - N Gopalakrishna Iyer
- National Cancer Centre Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Alexandre Thiery
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
| | - Wee Joo Chng
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
- Department of Hematology-Oncology, National University Cancer Institute of Singapore, National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Leilei Chen
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
- Department of Anatomy, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ramanuj DasGupta
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Mile Sikic
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- Department of Electronic Systems and Information Processing, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia
| | - Yun-Shen Chan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Boon Ooi Patrick Tan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore, Singapore
| | - Yue Wan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Wai Leong Tam
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Qiang Yu
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Chiea Chuan Khor
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Singapore Eye Research Institute, Singapore, Singapore
| | - Torsten Wüstefeld
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- National Cancer Centre Singapore, Singapore, Singapore
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Alexander Lezhava
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Ploy N Pratanwanich
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok, Thailand
- Chula Intelligent and Complex Systems Research Unit, Chulalongkorn University, Bangkok, Thailand
| | - Michael I Love
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Wee Siong Sho Goh
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, China
| | - Sarah B Ng
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Alicia Oshlack
- Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- School of Mathematics and Statistics, University of Melbourne, Parkville, Victoria, Australia
| | - Jonathan Göke
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore.
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore.
| |
Collapse
|
4
|
Liu JF, Hawley BR, Nicholson LS, Jaffrey SR. Decoding m 6Am by simultaneous transcription-start mapping and methylation quantification. eLife 2025; 13:RP104139. [PMID: 40162895 PMCID: PMC11957539 DOI: 10.7554/elife.104139] [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] [Indexed: 04/02/2025] Open
Abstract
N 6,2'-O-dimethyladenosine (m6Am) is a modified nucleotide located at the first transcribed position in mRNA and snRNA that is essential for diverse physiological processes. m6Am mapping methods assume each gene uses a single start nucleotide. However, gene transcription usually involves multiple start sites, generating numerous 5' isoforms. Thus, gene-level annotations cannot capture the diversity of m6Am modification in the transcriptome. Here, we describe CROWN-seq, which simultaneously identifies transcription-start nucleotides and quantifies m6Am stoichiometry for each 5' isoform that initiates with adenosine. Using CROWN-seq, we map the m6Am landscape in nine human cell lines. Our findings reveal that m6Am is nearly always a high stoichiometry modification, with only a small subset of cellular mRNAs showing lower m6Am stoichiometry. We find that m6Am is associated with increased transcript expression and provide evidence that m6Am may be linked to transcription initiation associated with specific promoter sequences and initiation mechanisms. These data suggest a potential new function for m6Am in influencing transcription.
Collapse
Affiliation(s)
- Jianheng Fox Liu
- Department of Pharmacology, Weill Cornell Medicine, Cornell UniversityNew YorkUnited States
| | - Ben R Hawley
- Department of Pharmacology, Weill Cornell Medicine, Cornell UniversityNew YorkUnited States
| | - Luke S Nicholson
- Department of Pharmacology, Weill Cornell Medicine, Cornell UniversityNew YorkUnited States
| | - Samie R Jaffrey
- Department of Pharmacology, Weill Cornell Medicine, Cornell UniversityNew YorkUnited States
| |
Collapse
|
5
|
Guo W, Ren Z, Huang X, Liu J, Shao J, Ma X, Wei C, Cun Y, He J, Zhang J, Wu Z, Guo Y, Zhang Z, Feng Z, He J, Wang J. Single-molecule m 6A detection empowered by endogenous labeling unveils complexities across RNA isoforms. Mol Cell 2025; 85:1233-1246.e7. [PMID: 39922195 DOI: 10.1016/j.molcel.2025.01.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 12/26/2024] [Accepted: 01/15/2025] [Indexed: 02/10/2025]
Abstract
The landscape of N6-methyadenosine (m6A) on different RNA isoforms is still incompletely understood. Here, in HEK293T cells, we endogenously label the methylated m6A sites on single Oxford Nanopore Technology (ONT) direct RNA sequencing (DRS) reads by APOBEC1-YTH-induced C-to-U mutations 10-100 nt away, obtaining 1,020,237 5-mer single-read m6A signals. We then trained m6Aiso, a deep residual neural network model that accurately identifies and quantifies m6A at single-read resolution. Analyzing m6Aiso-determined m6A on single reads and isoforms uncovers distance-dependent linkages of m6A sites along single molecules. It also uncovers specific methylation of identical m6A sites on intron-retained isoforms, partly due to their differential distances to exon junctions and isoform-specific binding of TARBP2. Moreover, we find that transcription factor SMAD3 promotes m6A deposition on its transcribed RNA isoforms during epithelial-mesenchymal transition, resulting in isoform-specific regulation of m6A on isoforms with alternative promoters. Our study underscores the effectiveness of m6Aiso in elucidating the intricate dynamics and complexities of m6A across RNA isoforms.
Collapse
Affiliation(s)
- Wenbing Guo
- Department of Histoembryology and Cell Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou 510080, China; Medical College of Jiaying University, Meizhou 514031, China
| | - Zhijun Ren
- Department of Histoembryology and Cell Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou 510080, China; Medical College of Jiaying University, Meizhou 514031, China
| | - Xiang Huang
- Department of Histoembryology and Cell Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou 510080, China; Medical College of Jiaying University, Meizhou 514031, China
| | - Jiayin Liu
- Department of Histoembryology and Cell Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou 510080, China
| | - Jingwen Shao
- Department of Histoembryology and Cell Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiaojun Ma
- Department of Histoembryology and Cell Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou 510080, China
| | - Chuanchuan Wei
- Department of Histoembryology and Cell Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou 510080, China; Medical College of Jiaying University, Meizhou 514031, China
| | - Yixian Cun
- Department of Histoembryology and Cell Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou 510080, China
| | - Jialiang He
- Department of Histoembryology and Cell Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou 510080, China
| | - Jie Zhang
- Department of Histoembryology and Cell Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou 510080, China
| | - Zehong Wu
- Department of Histoembryology and Cell Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou 510080, China
| | - Yang Guo
- School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Zijun Zhang
- Division of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Zhengming Feng
- Department of Histoembryology and Cell Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou 510080, China
| | - Jianbo He
- GeneMind Biosciences Company Limited, Shenzhen 518000, China
| | - Jinkai Wang
- Department of Histoembryology and Cell Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou 510080, China.
| |
Collapse
|
6
|
Verhamme R, Jansens RJJ, Liu J, Van Raemdonck F, Van Waesberghe C, Nicholson L, Jaffrey SR, Favoreel HW. The pseudorabies virus UL13 protein kinase triggers phosphorylation of the RNA demethylase FTO, which is associated with FTO-dependent suppression of interferon-stimulated gene expression. J Virol 2025; 99:e0201924. [PMID: 39791911 PMCID: PMC11852732 DOI: 10.1128/jvi.02019-24] [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: 11/13/2024] [Accepted: 12/11/2024] [Indexed: 01/12/2025] Open
Abstract
Alpha-ketoglutarate-dependent dioxygenase, also known as fat mass and obesity-associated protein (FTO), is an RNA demethylase that mediates the demethylation of N6,2-O-dimethyladenosine (m6Am) and N6-methyladenosine (m6A). Both m6Am and m6A are prevalent modifications in mRNA and affect different aspects of transcript biology, including splicing, nuclear export, translation efficiency, and degradation. The role of FTO during (herpes) virus infection remains largely unexplored. In this study, we show that the UL13 protein kinase of the alphaherpesvirus pseudorabies virus (PRV) triggers phosphorylation of FTO. In primary epithelial cells, depletion of FTO leads to increased expression of antiviral interferon-stimulated genes (ISGs) and UL13 triggers FTO-dependent suppression of ISG expression. Although PRV infection suppresses m6Am levels in host small nuclear RNA, this is independent of UL13. The current data highlight FTO as an important regulator of antiviral ISG expression and suggest that UL13-mediated phosphorylation of FTO may serve as a previously unrecognized viral strategy to suppress the antiviral interferon response.IMPORTANCERNA modification pathways play important roles in diverse cellular processes and virus life cycles. Although previous studies have demonstrated that alphaherpesviruses can substantially influence cellular RNA modifications, such as m6A, the impact on the m6Am epitranscriptome machinery remains largely unexplored. The present work reports that the UL13 protein kinase of pseudorabies virus (PRV), an alphaherpesvirus, mediates phosphorylation of the m6Am/m6A eraser FTO and that this correlates with a UL13- and FTO-dependent suppression of antiviral interferon-stimulated gene (ISG) expression. Furthermore, PRV infection leads to a pronounced reduction in m6Am levels in host snRNA and also induces phosphorylation of the m6Am writer PCIF1. These data highlight FTO as an important regulator of ISG expression and reveal that viral manipulation of FTO, such as UL13-induced phosphorylation of FTO, may serve as a previously unrecognized interferon evasion strategy.
Collapse
Affiliation(s)
- Ruth Verhamme
- Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Robert J. J. Jansens
- Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Jianheng Liu
- Department of Pharmacology, Weill Medical College, Cornell University, New York, New York, USA
| | - Fien Van Raemdonck
- Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Cliff Van Waesberghe
- Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Luke Nicholson
- Department of Pharmacology, Weill Medical College, Cornell University, New York, New York, USA
| | - Samie R. Jaffrey
- Department of Pharmacology, Weill Medical College, Cornell University, New York, New York, USA
| | - Herman W. Favoreel
- Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| |
Collapse
|
7
|
Liu JF, Hawley BR, Nicholson LS, Jaffrey SR. Decoding m 6Am by simultaneous transcription-start mapping and methylation quantification. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.10.16.618717. [PMID: 39677659 PMCID: PMC11642800 DOI: 10.1101/2024.10.16.618717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2024]
Abstract
N 6,2'-O-dimethyladenosine (m6Am) is a modified nucleotide located at the first transcribed position in mRNA and snRNA that is essential for diverse physiological processes. m6Am mapping methods assume each gene uses a single start nucleotide. However, gene transcription usually involves multiple start sites, generating numerous 5' isoforms. Thus, gene levels annotations cannot capture the diversity of m6Am modification in the transcriptome. Here we describe CROWN-seq, which simultaneously identifies transcription-start nucleotides and quantifies m6Am stoichiometry for each 5' isoform that initiates with adenosine. Using CROWN-seq, we map the m6Am landscape in nine human cell lines. Our findings reveal that m6Am is nearly always a high stoichiometry modification, with only a small subset of cellular mRNAs showing lower m6Am stoichiometry. We find that m6Am is associated with increased transcript expression and provide evidence that m6Am may be linked to transcription initiation associated with specific promoter sequences and initiation mechanisms. These data suggest a potential new function for m6Am in influencing transcription.
Collapse
Affiliation(s)
- Jianheng Fox Liu
- Department of Pharmacology, Weill Cornell Medicine, Cornell University, New York, NY 10065, USA
| | - Ben R. Hawley
- Department of Pharmacology, Weill Cornell Medicine, Cornell University, New York, NY 10065, USA
- Present address: Engage Bio, San Carlos, CA, USA
| | - Luke S. Nicholson
- Department of Pharmacology, Weill Cornell Medicine, Cornell University, New York, NY 10065, USA
| | - Samie R. Jaffrey
- Department of Pharmacology, Weill Cornell Medicine, Cornell University, New York, NY 10065, USA
| |
Collapse
|
8
|
Li P, Lin Y, Ma H, Zhang J, Zhang Q, Yan R, Fan Y. Epigenetic regulation in female reproduction: the impact of m6A on maternal-fetal health. Cell Death Discov 2025; 11:43. [PMID: 39904996 PMCID: PMC11794895 DOI: 10.1038/s41420-025-02324-z] [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: 09/02/2024] [Revised: 01/09/2025] [Accepted: 01/24/2025] [Indexed: 02/06/2025] Open
Abstract
With the development of public health, female diseases have become the focus of current concern. The unique reproductive anatomy of women leads to the development of gynecological diseases gradually become an important part of the socio-economic burden. Epigenetics plays an irreplaceable role in gynecologic diseases. As an important mRNA modification, m6A is involved in the maturation of ovum cells and maternal-fetal microenvironment. At present, researchers have found that m6A is involved in the regulation of gestational diabetes and other reproductive system diseases, but the specific mechanism is not clear. In this manuscript, we summarize the components of m6A, the biological function of m6A, the progression of m6A in the maternal-fetal microenvironment and a variety of gynecological diseases as well as the progression of targeted m6A treatment-related diseases, providing a new perspective for clinical treatment-related diseases.
Collapse
Affiliation(s)
- Peipei Li
- Department of Obstetrics and Gynecology, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China
| | - Yumeng Lin
- Health Management Center, Nanjing Tongren Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Hongyun Ma
- Department of Obstetrics and Gynecology, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China
| | - Jiao Zhang
- Department of Obstetrics and Gynecology, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China
| | - Qiaorui Zhang
- Department of Obstetrics and Gynecology, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China
| | - Ruihua Yan
- Department of Obstetrics and Gynecology, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China
| | - Yang Fan
- Department of Obstetrics and Gynecology, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China.
| |
Collapse
|
9
|
Liu C, Liang H, Wan AH, Xiao M, Sun L, Yu Y, Yan S, Deng Y, Liu R, Fang J, Wang Z, He W, Wan G. Decoding the m 6A epitranscriptomic landscape for biotechnological applications using a direct RNA sequencing approach. Nat Commun 2025; 16:798. [PMID: 39824841 PMCID: PMC11742432 DOI: 10.1038/s41467-025-56173-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Accepted: 01/09/2025] [Indexed: 01/20/2025] Open
Abstract
Epitranscriptomic modifications, particularly N6-methyladenosine (m6A), are crucial regulators of gene expression, influencing processes such as RNA stability, splicing, and translation. Traditional computational methods for detecting m6A from Nanopore direct RNA sequencing (DRS) data are constrained by their reliance on experimentally validated labels, often resulting in the underestimation of modification sites. Here, we introduce pum6a, an innovative attention-based framework that integrates positive and unlabeled multi-instance learning (MIL) to address the challenges of incomplete labeling and missing read-level annotations. By combining electrical signal features with base alignment data and employing a weighted Noisy-OR probability mechanism, pum6a achieves enhanced sensitivity and accuracy in m6A detection, particularly in low-coverage loci. Pum6a outperforms existing methods in identifying m6A sites across various cell lines and species, without requiring extensive parameter tuning. We further apply pum6a to study the dynamic regulation of m6A demethylases in gastric cancer under hypoxia, revealing distinct roles for FTO and ALKBH5 in modulating m6A modifications and uncovering key insights into m6A -mediated transcript stability. Our findings highlight the potential of pum6a as a powerful tool for advancing the understanding of epitranscriptomic regulation in health and disease, paving the way for biotechnological and therapeutic applications.
Collapse
Affiliation(s)
- Chuwei Liu
- Department of Gastrointestinal Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Heng Liang
- National-Local Joint Engineering Laboratory of Druggability and New Drug Evaluation, National Engineering Research Center for New Drug and Druggability (cultivation), Guangdong Province Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Arabella H Wan
- Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Min Xiao
- National-Local Joint Engineering Laboratory of Druggability and New Drug Evaluation, National Engineering Research Center for New Drug and Druggability (cultivation), Guangdong Province Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Lei Sun
- National-Local Joint Engineering Laboratory of Druggability and New Drug Evaluation, National Engineering Research Center for New Drug and Druggability (cultivation), Guangdong Province Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Yiling Yu
- School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Shijia Yan
- National-Local Joint Engineering Laboratory of Druggability and New Drug Evaluation, National Engineering Research Center for New Drug and Druggability (cultivation), Guangdong Province Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Yuan Deng
- National-Local Joint Engineering Laboratory of Druggability and New Drug Evaluation, National Engineering Research Center for New Drug and Druggability (cultivation), Guangdong Province Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Ruonian Liu
- National-Local Joint Engineering Laboratory of Druggability and New Drug Evaluation, National Engineering Research Center for New Drug and Druggability (cultivation), Guangdong Province Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Juan Fang
- Hospital of Stomatology, Guanghua School of Stomatology, Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-Sen University, Guangzhou, 510055, China
| | - Zhi Wang
- Hospital of Stomatology, Guanghua School of Stomatology, Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-Sen University, Guangzhou, 510055, China.
| | - Weiling He
- Department of Gastrointestinal Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China.
- Department of Gastrointestinal Surgery, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, XIamen, 361000, China.
| | - Guohui Wan
- National-Local Joint Engineering Laboratory of Druggability and New Drug Evaluation, National Engineering Research Center for New Drug and Druggability (cultivation), Guangdong Province Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, 510006, China.
| |
Collapse
|
10
|
Diensthuber G, Novoa EM. Charting the epitranscriptomic landscape across RNA biotypes using native RNA nanopore sequencing. Mol Cell 2025; 85:276-289. [PMID: 39824168 DOI: 10.1016/j.molcel.2024.12.014] [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: 09/10/2024] [Revised: 12/04/2024] [Accepted: 12/11/2024] [Indexed: 01/20/2025]
Abstract
RNA modifications are conserved chemical features found in all domains of life and across diverse RNA biotypes, shaping gene expression profiles and enabling rapid responses to environmental changes. Their broad chemical diversity and dynamic nature pose significant challenges for studying them comprehensively. These limitations can now be addressed through direct RNA nanopore sequencing (DRS), which allows simultaneous identification of diverse RNA modification types at single-molecule and single-nucleotide resolution. Here, we review recent efforts pioneering the use of DRS to better understand the epitranscriptomic landscape. We highlight how DRS can be applied to investigate different RNA biotypes, emphasizing the use of specialized library preparation protocols and downstream bioinformatic workflows to detect both natural and synthetic RNA modifications. Finally, we provide a perspective on the future role of DRS in epitranscriptomic research, highlighting remaining challenges and emerging opportunities from improved sequencing yields and accuracy enabled by the latest DRS chemistry.
Collapse
Affiliation(s)
- Gregor Diensthuber
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain; Universitat Pompeu Fabra, Barcelona 08003, Spain
| | - Eva Maria Novoa
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain; Universitat Pompeu Fabra, Barcelona 08003, Spain; ICREA, Pg. Lluís Companys 23, Barcelona 08010, Spain.
| |
Collapse
|
11
|
Cui X, Li H, Huang X, Xue T, Wang S, Zhu X, Jing X. N 6-Methyladenosine Modification on the Function of Female Reproductive Development and Related Diseases. Immun Inflamm Dis 2024; 12:e70089. [PMID: 39660878 PMCID: PMC11632877 DOI: 10.1002/iid3.70089] [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: 08/18/2024] [Revised: 10/17/2024] [Accepted: 11/20/2024] [Indexed: 12/12/2024] Open
Abstract
BACKGROUND N6-methyladenosine (m6A) modification is a widespread and reversible epigenetic alteration in eukaryotic mRNA, playing a pivotal role in various biological functions. Its significance in female reproductive development and associated diseases has recently become a focal point of research. OBJECTIVE This review aims to consolidate current knowledge of the role of m6A modification in female reproductive tissues, emphasizing its regulatory dynamics, functional significance, and implications in reproductive health and disease. METHODS A comprehensive analysis of recent studies focusing on m6A modification in ovarian development, oocyte maturation, embryo development, and the pathogenesis of reproductive diseases. RESULTS m6A modification exhibits dynamic regulation in female reproductive tissues, influencing key developmental stages and processes. It plays critical roles in ovarian development, oocyte maturation, and embryo development, underpinning essential aspects of reproductive health. m6A modification is intricately involved in the pathogenesis of several reproductive diseases, including polycystic ovary syndrome (PCOS), premature ovarian failure (POF), and endometriosis, offering insights into potential molecular mechanisms and therapeutic targets. CONCLUSION The review highlights the crucial role of m6A modification in female reproductive development and related diseases. It underscores the need for further research to explore innovative diagnostic and therapeutic strategies for reproductive disorders, leveraging the insights gained from understanding m6A modification's impact on reproductive health.
Collapse
Affiliation(s)
- Xiangrong Cui
- Reproductive Medicine CenterThe affiliated Children's Hospital of Shanxi Medical University, Children's Hospital of Shanxi, Shanxi Maternal and Child Health HospitalTaiyuanChina
| | - Huihui Li
- Reproductive Medicine CenterThe affiliated Children's Hospital of Shanxi Medical University, Children's Hospital of Shanxi, Shanxi Maternal and Child Health HospitalTaiyuanChina
| | - Xia Huang
- Department of Clinical LaboratoryShanxi Provincial People's Hospital, Shanxi Medical UniversityTaiyuanChina
| | - Tingting Xue
- Department of Clinical LaboratoryShanxi Provincial People's Hospital, Shanxi Medical UniversityTaiyuanChina
| | - Shu Wang
- Department of Clinical LaboratoryShanxi Provincial People's Hospital, Shanxi Medical UniversityTaiyuanChina
| | - Xinyu Zhu
- Department of Clinical LaboratoryShanxi Provincial People's Hospital, Shanxi Medical UniversityTaiyuanChina
| | - Xuan Jing
- Department of Clinical LaboratoryShanxi Provincial People's Hospital, Shanxi Medical UniversityTaiyuanChina
| |
Collapse
|
12
|
Teng H, Stoiber M, Bar-Joseph Z, Kingsford C. Detecting m6A RNA modification from nanopore sequencing using a semisupervised learning framework. Genome Res 2024; 34:1987-1999. [PMID: 39406497 DOI: 10.1101/gr.278960.124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 10/03/2024] [Indexed: 10/23/2024]
Abstract
Direct nanopore-based RNA sequencing can be used to detect posttranscriptional base modifications, such as N6-methyladenosine (m6A) methylation, based on the electric current signals produced by the distinct chemical structures of modified bases. A key challenge is the scarcity of adequate training data with known methylation modifications. We present Xron, a hybrid encoder-decoder framework that delivers a direct methylation-distinguishing basecaller by training on synthetic RNA data and immunoprecipitation (IP)-based experimental data in two steps. First, we generate data with more diverse modification combinations through in silico cross-linking. Second, we use this data set to train an end-to-end neural network basecaller followed by fine-tuning on IP-based experimental data with label smoothing. The trained neural network basecaller outperforms existing methylation detection methods on both read-level and site-level prediction scores. Xron is a standalone, end-to-end m6A-distinguishing basecaller capable of detecting methylated bases directly from raw sequencing signals, enabling de novo methylome assembly.
Collapse
Affiliation(s)
- Haotian Teng
- Ray and Stephanie Lane Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Marcus Stoiber
- Oxford Nanopore Technologies, Alameda, California 94501-1170, USA
| | - Ziv Bar-Joseph
- Ray and Stephanie Lane Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Carl Kingsford
- Ray and Stephanie Lane Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA;
| |
Collapse
|
13
|
Li Q, Liu J, Guo L, Zhang Y, Chen Y, Liu H, Cheng H, Deng L, Qiu J, Zhang K, Goh WSS, Wang Y, Peng Q. Decoding the interplay between m 6A modification and stress granule stability by live-cell imaging. SCIENCE ADVANCES 2024; 10:eadp5689. [PMID: 39546601 PMCID: PMC11566999 DOI: 10.1126/sciadv.adp5689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 10/16/2024] [Indexed: 11/17/2024]
Abstract
N6-methyladenosine (m6A)-modified mRNAs and their cytoplasmic reader YTHDFs are colocalized with stress granules (SGs) under stress conditions, but the interplay between m6A modification and SG stability remains unclear. Here, we presented a spatiotemporal m6A imaging system (SMIS) that can monitor the m6A modification and the translation of mRNAs with high specificity and sensitivity in a single live cell. SMIS showed that m6A-modified reporter mRNAs dynamically enriched into SGs under arsenite stress and gradually partitioned into the cytosol as SG disassembled. SMIS revealed that knockdown of YTHDF2 contributed to SG disassembly, resulting in the fast redistribution of mRNAs from SGs and rapid recovery of stalled translation. The mechanism is that YTHDF2 can regulate SG stability through the interaction with G3BP1 in m6A-modified RNA-dependent manner. Our results suggest a mechanism for the interplay between m6A modification and SG through YTHDF2 regulation.
Collapse
Affiliation(s)
- Qianqian Li
- Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Jian Liu
- Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Liping Guo
- Shenzhen Bay Laboratory, Shenzhen 518132, China
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | - Yi Zhang
- Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Yanwei Chen
- Shenzhen Bay Laboratory, Shenzhen 518132, China
- Department of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
| | - Huijuan Liu
- Shenzhen Bay Laboratory, Shenzhen 518132, China
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Life Sciences, Northwest A&F University, Yangling 712100, Shaanxi, China
| | - Hongyu Cheng
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, College of Bioengineering, Chongqing University, Chongqing 400030, China
| | - Lin Deng
- Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Juhui Qiu
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, College of Bioengineering, Chongqing University, Chongqing 400030, China
| | - Ke Zhang
- Shenzhen Bay Laboratory, Shenzhen 518132, China
| | | | - Yingxiao Wang
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
| | - Qin Peng
- Shenzhen Bay Laboratory, Shenzhen 518132, China
| |
Collapse
|
14
|
An H, Hong Y, Goh YT, Koh CWQ, Kanwal S, Zhang Y, Lu Z, Yap PML, Neo SP, Wong CM, Wong AST, Yu Y, Ho JSY, Gunaratne J, Goh WSS. m 6Am sequesters PCF11 to suppress premature termination and drive neuroblastoma differentiation. Mol Cell 2024; 84:4142-4157.e14. [PMID: 39481383 DOI: 10.1016/j.molcel.2024.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Revised: 08/08/2024] [Accepted: 10/01/2024] [Indexed: 11/02/2024]
Abstract
N6,2'-O-dimethyladenosine (m6Am) is an abundant mRNA modification that impacts multiple diseases, but its function remains controversial because the m6Am reader is unknown. Using quantitative proteomics, we identified transcriptional terminator premature cleavage factor II (PCF11) as a m6Am-specific reader in human cells. Direct quantification of mature versus nascent RNAs reveals that m6Am does not regulate mRNA stability but promotes nascent transcription. Mechanistically, m6Am functions by sequestering PCF11 away from proximal RNA polymerase II (RNA Pol II). This suppresses PCF11 from dissociating RNA Pol II near transcription start sites, thereby promoting full-length transcription of m6Am-modified RNAs. m6Am's unique relationship with PCF11 means m6Am function is enhanced when PCF11 is reduced, which occurs during all-trans-retinoic-acid (ATRA)-induced neuroblastoma-differentiation therapy. Here, m6Am promotes expression of ATF3, which represses neuroblastoma biomarker MYCN. Depleting m6Am suppresses MYCN repression in ATRA-treated neuroblastoma and maintains their tumor-stem-like properties. Collectively, we characterize m6Am as an anti-terminator RNA modification that suppresses premature termination and modulates neuroblastoma's therapeutic response.
Collapse
Affiliation(s)
- Huihui An
- Shenzhen Bay Laboratory, Shenzhen, China; School of Biological Sciences, University of Hong Kong, Hong Kong, China; Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
| | - Yifan Hong
- Shenzhen Bay Laboratory, Shenzhen, China
| | | | | | | | - Yi Zhang
- Shenzhen Bay Laboratory, Shenzhen, China
| | - Zhaoqi Lu
- Shenzhen Bay Laboratory, Shenzhen, China
| | | | - Suat Peng Neo
- Institute of Molecular and Cell Biology, Singapore, Singapore
| | - Chun-Ming Wong
- Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
| | - Alice S T Wong
- School of Biological Sciences, University of Hong Kong, Hong Kong, China
| | - Yang Yu
- Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Jessica Sook Yuin Ho
- Programme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore, Singapore
| | | | | |
Collapse
|
15
|
Fang X, Lu Z, Wang Y, Zhao R, Mo J, Yang W, Sun M, Zhou X, Weng X. Exonuclease-assisted enrichment and base resolution analysis of pseudouridine in single-stranded RNA. Chem Sci 2024:d4sc03576c. [PMID: 39479159 PMCID: PMC11515940 DOI: 10.1039/d4sc03576c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Accepted: 10/20/2024] [Indexed: 11/02/2024] Open
Abstract
Pseudouridine (Ψ) is one of the most abundant RNA modifications, playing crucial roles in various biological processes. Identifying Ψ sites is vital for understanding their functions. In this study, we proposed a novel method for identifying Ψ sites with an improved signal-to-noise ratio. This method, called RNA exonuclease-assisted identification of pseudouridine sites (RIPS), combines specific CMC-labeling of Ψ sites with an exonuclease-assisted digestion strategy for the detection of Ψ sites. Utilizing exonuclease XRN1 to digest RNA strands not labeled by CMC, RIPS significantly reduces the background signal from unlabeled strands and enhances the positive signal of Ψ sites labeled by CMC, which terminates exonuclease digestion. As a result, we can enrich Ψ sites and identify them at single-base resolution. Considering the unique functions of single-stranded RNA (ssRNA), we employed RIPS to distinguish Ψ sites in single-stranded and double-stranded regions of RNA. Our results indicated that CMC could specifically label Ψ sites in ssRNA under natural conditions, enabling RIPS to selectively identify Ψ sites in ssRNA, which may facilitate the study on the functions of Ψ sites.
Collapse
Affiliation(s)
- Xin Fang
- College of Chemistry and Molecular Sciences, Key Laboratory of Biomedical Polymers-Ministry of Education, Wuhan University Wuhan Hubei 430072 P. R. China
| | - Ziang Lu
- College of Chemistry and Molecular Sciences, Key Laboratory of Biomedical Polymers-Ministry of Education, Wuhan University Wuhan Hubei 430072 P. R. China
| | - Yafen Wang
- School of Public Health, Wuhan University Wuhan Hubei 430071 P. R. China
| | - Ruiqi Zhao
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University Wuhan Hubei 430071 P. R. China
| | - Jing Mo
- College of Chemistry and Molecular Sciences, Key Laboratory of Biomedical Polymers-Ministry of Education, Wuhan University Wuhan Hubei 430072 P. R. China
| | - Wei Yang
- College of Chemistry and Molecular Sciences, Key Laboratory of Biomedical Polymers-Ministry of Education, Wuhan University Wuhan Hubei 430072 P. R. China
| | - Mei Sun
- College of Chemistry and Molecular Sciences, Key Laboratory of Biomedical Polymers-Ministry of Education, Wuhan University Wuhan Hubei 430072 P. R. China
| | - Xiang Zhou
- College of Chemistry and Molecular Sciences, Key Laboratory of Biomedical Polymers-Ministry of Education, Wuhan University Wuhan Hubei 430072 P. R. China
- TaiKang Center for Life and Medical Sciences, Wuhan University Wuhan Hubei 430071 P. R. China
| | - Xiaocheng Weng
- College of Chemistry and Molecular Sciences, Key Laboratory of Biomedical Polymers-Ministry of Education, Wuhan University Wuhan Hubei 430072 P. R. China
- TaiKang Center for Life and Medical Sciences, Wuhan University Wuhan Hubei 430071 P. R. China
- Department of Otorhinolaryngology-Head and Neck Surgery, Zhongnan Hospital of Wuhan University Wuhan Hubei P. R. China
| |
Collapse
|
16
|
Yu B, Nagae G, Midorikawa Y, Tatsuno K, Dasgupta B, Aburatani H, Ueda H. m6ATM: a deep learning framework for demystifying the m6A epitranscriptome with Nanopore long-read RNA-seq data. Brief Bioinform 2024; 25:bbae529. [PMID: 39438075 PMCID: PMC11495873 DOI: 10.1093/bib/bbae529] [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: 06/24/2024] [Revised: 09/16/2024] [Accepted: 10/07/2024] [Indexed: 10/25/2024] Open
Abstract
N6-methyladenosine (m6A) is one of the most abundant and well-known modifications in messenger RNAs since its discovery in the 1970s. Recent studies have demonstrated that m6A is involved in various biological processes, such as alternative splicing and RNA degradation, playing an important role in a variety of diseases. To better understand the role of m6A, transcriptome-wide m6A profiling data are indispensable. In recent years, the Oxford Nanopore Technology Direct RNA Sequencing (DRS) platform has shown promise for RNA modification detection based on current disruptions measured in transcripts. However, decoding current intensity data into modification profiles remains a challenging task. Here, we introduce the m6A Transcriptome-wide Mapper (m6ATM), a novel Python-based computational pipeline that applies deep neural networks to predict m6A sites at a single-base resolution using DRS data. The m6ATM model architecture incorporates a WaveNet encoder and a dual-stream multiple-instance learning model to extract features from specific target sites and characterize the m6A epitranscriptome. For validation, m6ATM achieved an accuracy of 80% to 98% across in vitro transcription datasets containing varying m6A modification ratios and outperformed other tools in benchmarking with human cell line data. Moreover, we demonstrated the versatility of m6ATM in providing reliable stoichiometric information and used it to pinpoint PEG10 as a potential m6A target transcript in liver cancer cells. In conclusion, m6ATM is a high-performance m6A detection tool, and our results pave the way for future advancements in epitranscriptomic research.
Collapse
Affiliation(s)
- Boyi Yu
- Advanced Data Science Division, Research Center of Advanced Science and Technology, The University of Tokyo, 4-6-1 Komaba, Meguro-ku 153-8904, Tokyo, Japan
| | - Genta Nagae
- Genome Science & Medicine Division, Research Center of Advanced Science and Technology, The University of Tokyo, 4-6-1 Komaba, Meguro-ku 153-8904, Tokyo, Japan
| | - Yutaka Midorikawa
- Department of Digestive Surgery, Nihon University School of Medicine, 30-1 Oyaguchi Kami-cho, Itabashi-ku 173-8601, Tokyo, Japan
| | - Kenji Tatsuno
- Genome Science & Medicine Division, Research Center of Advanced Science and Technology, The University of Tokyo, 4-6-1 Komaba, Meguro-ku 153-8904, Tokyo, Japan
| | - Bhaskar Dasgupta
- Advanced Data Science Division, Research Center of Advanced Science and Technology, The University of Tokyo, 4-6-1 Komaba, Meguro-ku 153-8904, Tokyo, Japan
| | - Hiroyuki Aburatani
- Genome Science & Medicine Division, Research Center of Advanced Science and Technology, The University of Tokyo, 4-6-1 Komaba, Meguro-ku 153-8904, Tokyo, Japan
| | - Hiroki Ueda
- Advanced Data Science Division, Research Center of Advanced Science and Technology, The University of Tokyo, 4-6-1 Komaba, Meguro-ku 153-8904, Tokyo, Japan
| |
Collapse
|
17
|
YuYan, Yuan E. Regulatory effect of N6-methyladenosine on tumor angiogenesis. Front Immunol 2024; 15:1453774. [PMID: 39295872 PMCID: PMC11408240 DOI: 10.3389/fimmu.2024.1453774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Accepted: 08/19/2024] [Indexed: 09/21/2024] Open
Abstract
Previous studies have demonstrated that genetic alterations governing epigenetic processes frequently drive tumor development and that modifications in RNA may contribute to these alterations. In the 1970s, researchers discovered that N6-methyladenosine (m6A) is the most prevalent form of RNA modification in advanced eukaryotic messenger RNA (mRNA) and noncoding RNA (ncRNA). This modification is involved in nearly all stages of the RNA life cycle. M6A modification is regulated by enzymes known as m6A methyltransferases (writers) and demethylases (erasers). Numerous studies have indicated that m6A modification can impact cancer progression by regulating cancer-related biological functions. Tumor angiogenesis, an important and unregulated process, plays a pivotal role in tumor initiation, growth, and metastasis. The interaction between m6A and ncRNAs is widely recognized as a significant factor in proliferation and angiogenesis. Therefore, this article provides a comprehensive review of the regulatory mechanisms underlying m6A RNA modifications and ncRNAs in tumor angiogenesis, as well as the latest advancements in molecular targeted therapy. The aim of this study is to offer novel insights for clinical tumor therapy.
Collapse
Affiliation(s)
- YuYan
- Department of Laboratory Medicine, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Enwu Yuan
- Department of Laboratory Medicine, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| |
Collapse
|
18
|
Cao Y, Jia M, Duan C, Yang Z, Cheng B, Wang R. The m 6A regulators in prostate cancer: molecular basis and clinical perspective. Front Pharmacol 2024; 15:1448872. [PMID: 39268470 PMCID: PMC11391310 DOI: 10.3389/fphar.2024.1448872] [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: 06/14/2024] [Accepted: 08/14/2024] [Indexed: 09/15/2024] Open
Abstract
Prostate cancer (PCa) is the second leading cause of cancer-related death among men in western countries. Evidence has indicated the significant role of the androgen receptor (AR) as the main driving factor in controlling the development of PCa, making androgen receptor inhibition (ARI) therapy a pivotal management approach. In addition, AR independent signaling pathways also contribute to PCa progression. One such signaling pathway that has garnered our attention is N6-Methyladenosine (m6A) signaling, which refers to a chemical modification on RNA with crucial roles in RNA metabolism and disease progression, including PCa. It is important to comprehensively summarize the role of each individual m6A regulator in PCa development and understand its interaction with AR signaling. This review aims to provide a thorough summary of the involvement of m6A regulators in PCa development, shedding light on their upstream and downstream signaling pathways. This summary sets the stage for a comprehensive review that would benefit the scientific community and clinical practice by enhancing our understanding of the biology of m6A regulators in the context of PCa.
Collapse
Affiliation(s)
- Yu Cao
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southwest Medical University, Luzhou, China
| | - Man Jia
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southwest Medical University, Luzhou, China
| | - Chunyan Duan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southwest Medical University, Luzhou, China
| | - Zhihui Yang
- Department of Pathology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - Bo Cheng
- Department of Urology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - Ronghao Wang
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southwest Medical University, Luzhou, China
| |
Collapse
|
19
|
Jin H, Shi Z, Zhou T, Xie S. Regulation of m6Am RNA modification and its implications in human diseases. J Mol Cell Biol 2024; 16:mjae012. [PMID: 38509021 PMCID: PMC11345611 DOI: 10.1093/jmcb/mjae012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 03/06/2024] [Accepted: 03/19/2024] [Indexed: 03/22/2024] Open
Abstract
N 6,2'-O-dimethyladenosine (m6Am) is a prevalent modification frequently found at the 5' cap-adjacent adenosine of messenger RNAs (mRNAs) and small nuclear RNAs (snRNAs) and the internal adenosine of snRNAs. This dynamic and reversible modification is under the regulation of methyltransferases phosphorylated CTD interacting factor 1 and methyltransferase-like protein 4, along with the demethylase fat mass and obesity-associated protein. m6Am RNA modification plays a crucial role in the regulation of pre-mRNA splicing, mRNA stability, and translation, thereby influencing gene expression. In recent years, there has been growing interest in exploring the functions of m6Am and its relevance to human diseases. In this review, we provide a comprehensive overview of the current knowledge concerning m6Am, with a focus on m6Am-modifying enzymes, sequencing approaches for its detection, and its impacts on pre-mRNA splicing, mRNA stability, and translation regulation. Furthermore, we highlight the roles of m6Am in the context of obesity, viral infections, and cancers, unravelling its underlying regulatory mechanisms.
Collapse
Affiliation(s)
- Hao Jin
- Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
- Department of Cell Biology, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Zhouyuanjing Shi
- Department of Gastroenterology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310020, China
| | - Tianhua Zhou
- Department of Cell Biology, Zhejiang University School of Medicine, Hangzhou 310058, China
- Department of Gastroenterology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310020, China
- Center for Medical Research and Innovation in Digestive System Tumors, Ministry of Education, Hangzhou 310020, China
| | - Shanshan Xie
- Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
| |
Collapse
|
20
|
Wang Z, Fang Y, Liu Z, Hao N, Zhang HH, Sun X, Que J, Ding H. Adapting nanopore sequencing basecalling models for modification detection via incremental learning and anomaly detection. Nat Commun 2024; 15:7148. [PMID: 39169028 PMCID: PMC11339354 DOI: 10.1038/s41467-024-51639-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 08/12/2024] [Indexed: 08/23/2024] Open
Abstract
We leverage machine learning approaches to adapt nanopore sequencing basecallers for nucleotide modification detection. We first apply the incremental learning (IL) technique to improve the basecalling of modification-rich sequences, which are usually of high biological interest. With sequence backbones resolved, we further run anomaly detection (AD) on individual nucleotides to determine their modification status. By this means, our pipeline promises the single-molecule, single-nucleotide, and sequence context-free detection of modifications. We benchmark the pipeline using control oligos, further apply it in the basecalling of densely-modified yeast tRNAs and E.coli genomic DNAs, the cross-species detection of N6-methyladenosine (m6A) in mammalian mRNAs, and the simultaneous detection of N1-methyladenosine (m1A) and m6A in human mRNAs. Our IL-AD workflow is available at: https://github.com/wangziyuan66/IL-AD .
Collapse
Affiliation(s)
- Ziyuan Wang
- Department of Pharmacy Practice and Science, University of Arizona, Tucson, AZ, USA
| | - Yinshan Fang
- Columbia Center for Human Development, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Ziyang Liu
- Department of Pharmacy Practice and Science, University of Arizona, Tucson, AZ, USA
- Statistics and Data Science GIDP, University of Arizona, Tucson, AZ, USA
| | - Ning Hao
- Statistics and Data Science GIDP, University of Arizona, Tucson, AZ, USA
- Department of Mathematics, University of Arizona, Tucson, AZ, USA
| | - Hao Helen Zhang
- Statistics and Data Science GIDP, University of Arizona, Tucson, AZ, USA
- Department of Mathematics, University of Arizona, Tucson, AZ, USA
| | - Xiaoxiao Sun
- Statistics and Data Science GIDP, University of Arizona, Tucson, AZ, USA
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, USA
| | - Jianwen Que
- Columbia Center for Human Development, Department of Medicine, Columbia University Medical Center, New York, NY, USA.
| | - Hongxu Ding
- Department of Pharmacy Practice and Science, University of Arizona, Tucson, AZ, USA.
- Statistics and Data Science GIDP, University of Arizona, Tucson, AZ, USA.
| |
Collapse
|
21
|
Wang K, Wang Y, Li Y, Fang B, Li B, Cheng W, Wang K, Yang S. The potential of RNA methylation in the treatment of cardiovascular diseases. iScience 2024; 27:110524. [PMID: 39165846 PMCID: PMC11334793 DOI: 10.1016/j.isci.2024.110524] [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] [Indexed: 08/22/2024] Open
Abstract
RNA methylation has emerged as a dynamic regulatory mechanism that impacts gene expression and protein synthesis. Among the known RNA methylation modifications, N6-methyladenosine (m6A), 5-methylcytosine (m5C), 3-methylcytosine (m3C), and N7-methylguanosine (m7G) have been studied extensively. In particular, m6A is the most abundant RNA modification and has attracted significant attention due to its potential effect on multiple biological processes. Recent studies have demonstrated that RNA methylation plays an important role in the development and progression of cardiovascular disease (CVD). To identify key pathogenic genes of CVD and potential therapeutic targets, we reviewed several common RNA methylation and summarized the research progress of RNA methylation in diverse CVDs, intending to inspire effective treatment strategies.
Collapse
Affiliation(s)
- Kai Wang
- Department of Cardiovascular Surgery, The Affiliated Hospital of Qingdao University, Qingdao 266003, China
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, Qingdao 266021, China
| | - YuQin Wang
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, Qingdao 266021, China
| | - YingHui Li
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, Qingdao 266021, China
| | - Bo Fang
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, Qingdao 266021, China
| | - Bo Li
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, Qingdao 266021, China
| | - Wei Cheng
- Department of Cardiovascular Surgery, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing 100045, China
| | - Kun Wang
- Department of Cardiovascular Surgery, The Affiliated Hospital of Qingdao University, Qingdao 266003, China
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, Qingdao 266021, China
| | - SuMin Yang
- Department of Cardiovascular Surgery, The Affiliated Hospital of Qingdao University, Qingdao 266003, China
| |
Collapse
|
22
|
Yang Y, Lu Y, Wang Y, Wen X, Qi C, Piao W, Jin H. Current progress in strategies to profile transcriptomic m 6A modifications. Front Cell Dev Biol 2024; 12:1392159. [PMID: 39055651 PMCID: PMC11269109 DOI: 10.3389/fcell.2024.1392159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 06/18/2024] [Indexed: 07/27/2024] Open
Abstract
Various methods have been developed so far for detecting N 6-methyladenosine (m6A). The total m6A level or the m6A status at individual positions on mRNA can be detected and quantified through some sequencing-independent biochemical methods, such as LC/MS, SCARLET, SELECT, and m6A-ELISA. However, the m6A-detection techniques relying on high-throughput sequencing have more effectively advanced the understanding about biological significance of m6A-containing mRNA and m6A pathway at a transcriptomic level over the past decade. Various SGS-based (Second Generation Sequencing-based) methods with different detection principles have been widely employed for this purpose. These principles include m6A-enrichment using antibodies, discrimination of m6A from unmodified A-base by nucleases, a fusion protein strategy relying on RNA-editing enzymes, and marking m6A with chemical/biochemical reactions. Recently, TGS-based (Third Generation Sequencing-based) methods have brought a new trend by direct m6A-detection. This review first gives a brief introduction of current knowledge about m6A biogenesis and function, and then comprehensively describes m6A-profiling strategies including their principles, procedures, and features. This will guide users to pick appropriate methods according to research goals, give insights for developing novel techniques in varying areas, and continue to expand our boundary of knowledge on m6A.
Collapse
Affiliation(s)
- Yuening Yang
- Laboratory of Genetics and Disorders, Key Laboratory of Molecular Medicine and Biotherapy, Aerospace Center Hospital, School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Yanming Lu
- Laboratory of Genetics and Disorders, Key Laboratory of Molecular Medicine and Biotherapy, Aerospace Center Hospital, School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Yan Wang
- Laboratory of Genetics and Disorders, Key Laboratory of Molecular Medicine and Biotherapy, Aerospace Center Hospital, School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Xianghui Wen
- Laboratory of Genetics and Disorders, Key Laboratory of Molecular Medicine and Biotherapy, Aerospace Center Hospital, School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Changhai Qi
- Department of Pathology, Aerospace Center Hospital, Beijing, China
| | - Weilan Piao
- Laboratory of Genetics and Disorders, Key Laboratory of Molecular Medicine and Biotherapy, Aerospace Center Hospital, School of Life Science, Beijing Institute of Technology, Beijing, China
- Advanced Technology Research Institute, Beijing Institute of Technology, Jinan, China
| | - Hua Jin
- Laboratory of Genetics and Disorders, Key Laboratory of Molecular Medicine and Biotherapy, Aerospace Center Hospital, School of Life Science, Beijing Institute of Technology, Beijing, China
- Advanced Technology Research Institute, Beijing Institute of Technology, Jinan, China
| |
Collapse
|
23
|
Zheng Y, Lin S, Chen M, Xu L, Huang H. Regulation of N 6-methyladenosine modification in erythropoiesis and thalassemia. Clin Genet 2024; 106:3-12. [PMID: 38488342 DOI: 10.1111/cge.14518] [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: 11/23/2023] [Revised: 02/21/2024] [Accepted: 02/23/2024] [Indexed: 06/04/2024]
Abstract
In eukaryotic RNA, N6-methyladenosine (m6A) is a prevalent form of methylation modification. The m6A modification process is reversible and dynamic, written by m6A methyltransferase complex, erased by m6A demethylase, and recognized by m6A binding proteins. Through mediating RNA stability, decay, alternative splicing, and translation processes, m6A modification regulates gene expression at the post-transcriptional level. Erythropoiesis is the process of hematopoietic stem cells undergoing proliferation, a series of differentiation and maturation to form red blood cells (RBCs). Thalassemia is a common monogenic disease characterized by excessive production of ineffective RBCs in the peripheral circulation, resulting in hemolytic anemia. Increasing evidence suggests that m6A modification plays a crucial role in erythropoiesis. In this review, we comprehensively summarize the function of m6A modification in erythropoiesis and further generalize the mechanism of m6A modification regulating ineffective erythropoiesis and fetal hemoglobin expression. The purpose is to improve the understanding of the pathogenesis of erythroid dysplasia and offer new perspectives for the diagnosis and treatment of thalassemia.
Collapse
Affiliation(s)
- Yanping Zheng
- Medical Genetic Diagnosis and Therapy Center of Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Provincial Key Laboratory of Prenatal Diagnosis and Birth Defect, Fujian Medical University, Fuzhou, China
| | - Siyang Lin
- Medical Genetic Diagnosis and Therapy Center of Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Provincial Key Laboratory of Prenatal Diagnosis and Birth Defect, Fujian Medical University, Fuzhou, China
- The School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China
| | - Meihuan Chen
- Medical Genetic Diagnosis and Therapy Center of Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Provincial Key Laboratory of Prenatal Diagnosis and Birth Defect, Fujian Medical University, Fuzhou, China
- The School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China
- Fujian Clinical Research Center for Maternal-Fetal Medicine, Fuzhou, China
- National Key Obstetric Clinical Specialty Construction Institution of China, Fuzhou, China
| | - Liangpu Xu
- Medical Genetic Diagnosis and Therapy Center of Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Provincial Key Laboratory of Prenatal Diagnosis and Birth Defect, Fujian Medical University, Fuzhou, China
- The School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China
- Fujian Clinical Research Center for Maternal-Fetal Medicine, Fuzhou, China
- National Key Obstetric Clinical Specialty Construction Institution of China, Fuzhou, China
| | - Hailong Huang
- Medical Genetic Diagnosis and Therapy Center of Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Provincial Key Laboratory of Prenatal Diagnosis and Birth Defect, Fujian Medical University, Fuzhou, China
- The School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China
- Fujian Clinical Research Center for Maternal-Fetal Medicine, Fuzhou, China
- National Key Obstetric Clinical Specialty Construction Institution of China, Fuzhou, China
| |
Collapse
|
24
|
XIONG J, FENG T, YUAN BF. [Advances in mapping analysis of ribonucleic acid modifications through sequencing]. Se Pu 2024; 42:632-645. [PMID: 38966972 PMCID: PMC11224946 DOI: 10.3724/sp.j.1123.2023.12025] [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: 12/20/2023] [Indexed: 07/06/2024] Open
Abstract
Over 170 chemical modifications have been discovered in various types of ribonucleic acids (RNAs), including messenger RNA (mRNA), ribosomal RNA (rRNA), transfer RNA (tRNA), and small nuclear RNA (snRNA). These RNA modifications play crucial roles in a wide range of biological processes such as gene expression regulation, RNA stability maintenance, and protein translation. RNA modifications represent a new dimension of gene expression regulation known as the "epitranscriptome". The discovery of RNA modifications and the relevant writers, erasers, and readers provides an important basis for studies on the dynamic regulation and physiological functions of RNA modifications. Owing to the development of detection technologies for RNA modifications, studies on RNA epitranscriptomes have progressed to the single-base resolution, multilayer, and full-coverage stage. Transcriptome-wide methods help discover new RNA modification sites and are of great importance for elucidating the molecular regulatory mechanisms of epitranscriptomics, exploring the disease associations of RNA modifications, and understanding their clinical applications. The existing RNA modification sequencing technologies can be categorized according to the pretreatment approach and sequencing principle as direct high-throughput sequencing, antibody-enrichment sequencing, enzyme-assisted sequencing, chemical labeling-assisted sequencing, metabolic labeling sequencing, and nanopore sequencing technologies. These methods, as well as studies on the functions of RNA modifications, have greatly expanded our understanding of epitranscriptomics. In this review, we summarize the recent progress in RNA modification detection technologies, focusing on the basic principles, advantages, and limitations of different methods. Direct high-throughput sequencing methods do not require complex RNA pretreatment and allow for the mapping of RNA modifications using conventional RNA sequencing methods. However, only a few RNA modifications can be analyzed by high-throughput sequencing. Antibody enrichment followed by high-throughput sequencing has emerged as a crucial approach for mapping RNA modifications, significantly advancing the understanding of RNA modifications and their regulatory functions in different species. However, the resolution of antibody-enrichment sequencing is limited to approximately 100-200 bp. Although chemical crosslinking techniques can achieve single-base resolution, these methods are often complex, and the specificity of the antibodies used in these methods has raised concerns. In particular, the issue of off-target binding by the antibodies requires urgent attention. Enzyme-assisted sequencing has improved the accuracy of the localization analysis of RNA modifications and enables stoichiometric detection with single-base resolution. However, the enzymes used in this technique show poor reactivity, specificity, and sequence preference. Chemical labeling sequencing has become a widely used approach for profiling RNA modifications, particularly by altering reverse transcription (RT) signatures such as RT stops, misincorporations, and deletions. Chemical-assisted sequencing provides a sequence-independent RNA modification detection strategy that enables the localization of multiple RNA modifications. Additionally, when combined with the biotin-streptavidin affinity method, low-abundance RNA modifications can be enriched and detected. Nevertheless, the specificity of many chemical reactions remains problematic, and the development of specific reaction probes for particular modifications should continue in the future to achieve the precise localization of RNA modifications. As an indirect localization method, metabolic labeling sequencing specifically localizes the sites at which modifying enzymes act, which is of great significance in the study of RNA modification functions. However, this method is limited by the intracellular labeling of RNA and cannot be applied to biological samples such as clinical tissues and blood samples. Nanopore sequencing is a direct RNA-sequencing method that does not require RT or the polymerase chain reaction (PCR). However, challenges in analyzing the data obtained from nanopore sequencing, such as the high rate of false positives, must be resolved. Discussing sequencing analysis methods for various types of RNA modifications is instructive for the future development of novel RNA modification mapping technologies, and will aid studies on the functions of RNA modifications across the entire transcriptome.
Collapse
|
25
|
Relier S, Schiffers S, Beiki H, Oberdoerffer S. Enhanced ac4C detection in RNA via chemical reduction and cDNA synthesis with modified dNTPs. RNA (NEW YORK, N.Y.) 2024; 30:938-953. [PMID: 38697668 PMCID: PMC11182010 DOI: 10.1261/rna.079863.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 04/04/2024] [Indexed: 05/05/2024]
Abstract
The functional analysis of epitranscriptomic modifications in RNA is constrained by a lack of methods that accurately capture their locations and levels. We previously demonstrated that the RNA modification N4-acetylcytidine (ac4C) can be mapped at base resolution through sodium borohydride reduction to tetrahydroacetylcytidine (tetrahydro-ac4C), followed by cDNA synthesis to misincorporate adenosine opposite reduced ac4C sites, culminating in C:T mismatches at acetylated cytidines (RedaC:T). However, this process is relatively inefficient, resulting in <20% C:T mismatches at a fully modified ac4C site in 18S rRNA. Considering that ac4C locations in other substrates including mRNA are unlikely to reach full penetrance, this method is not ideal for comprehensive mapping. Here, we introduce "RetraC:T" (reduction to tetrahydro-ac4C and reverse transcription with amino-dATP to induce C:T mismatches) as a method with enhanced ability to detect ac4C in cellular RNA. In brief, RNA is reduced through NaBH4 or the closely related reagent sodium cyanoborohydride (NaCNBH3) followed by cDNA synthesis in the presence of a modified DNA nucleotide, 2-amino-dATP, that preferentially binds to tetrahydro-ac4C. Incorporation of the modified dNTP substantially improved C:T mismatch rates, reaching stoichiometric detection of ac4C in 18S rRNA. Importantly, 2-amino-dATP did not result in truncated cDNA products nor increase mismatches at other locations. Thus, modified dNTPs are introduced as a new addition to the toolbox for detecting ac4C at base resolution.
Collapse
Affiliation(s)
- Sebastien Relier
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Sarah Schiffers
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Hamid Beiki
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Shalini Oberdoerffer
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA
| |
Collapse
|
26
|
Xue H, Ma Y, Guan K, Zhou Y, Liu Y, Cao F, Kang X. The role of m6A methylation in targeted therapy resistance in lung cancer. Am J Cancer Res 2024; 14:2994-3009. [PMID: 39005690 PMCID: PMC11236795 DOI: 10.62347/lxos2662] [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: 01/18/2024] [Accepted: 05/28/2024] [Indexed: 07/16/2024] Open
Abstract
Targeted therapies have greatly improved clinical outcomes for patients with lung cancer (LC), but acquired drug resistance and disease relapse inevitably occur. Increasingly, the role of epigenetic mechanisms in driving acquired drug resistance is appreciated. In particular, N6-methyladenosine (m6A), one of the most prevalent RNA modifications, has several roles regulating RNA stability, splicing, transcription, translation, and destruction. Numerous studies have demonstrated that m6A RNA methylation can modulate the growth and invasion of cancer cells as well as contribute to targeted therapy resistance in LC. In this study, we outline what is known regarding the function of m6A in the acquisition of targeted therapy resistance in LC.
Collapse
Affiliation(s)
- Huange Xue
- Department of Radiation Oncology, The First Affiliated Hospital of Xinxiang Medical University Xinxiang, Henan, China
| | - Yufei Ma
- Life Science Research Center, The First Affiliated Hospital of Xinxiang Medical College Xinxiang, Henan, China
| | - Kaiwen Guan
- Department of Radiation Oncology, The First Affiliated Hospital of Xinxiang Medical University Xinxiang, Henan, China
| | - Yueyang Zhou
- Department of Radiation Oncology, The First Affiliated Hospital of Xinxiang Medical University Xinxiang, Henan, China
| | - Yang Liu
- Department of Radiation Oncology, The First Affiliated Hospital of Xinxiang Medical University Xinxiang, Henan, China
| | - Fei Cao
- Department of Radiation Oncology, The First Affiliated Hospital of Xinxiang Medical University Xinxiang, Henan, China
| | - Xiaohong Kang
- Department of Radiation Oncology, The First Affiliated Hospital of Xinxiang Medical University Xinxiang, Henan, China
| |
Collapse
|
27
|
Ni P, Xu J, Zhong Z, Luo F, Wang J. RNA m6A detection using raw current signals and basecalling errors from Nanopore direct RNA sequencing reads. Bioinformatics 2024; 40:btae375. [PMID: 38889266 PMCID: PMC11211211 DOI: 10.1093/bioinformatics/btae375] [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: 01/26/2024] [Revised: 05/28/2024] [Accepted: 06/16/2024] [Indexed: 06/20/2024] Open
Abstract
MOTIVATION Nanopore direct RNA sequencing (DRS) enables the detection of RNA N6-methyladenosine (m6A) without extra laboratory techniques. A number of supervised or comparative approaches have been developed to identify m6A from Nanopore DRS reads. However, existing methods typically utilize either statistical features of the current signals or basecalling-error features, ignoring the richer information of the raw signals of DRS reads. RESULTS Here, we propose RedNano, a deep-learning method designed to detect m6A from Nanopore DRS reads by utilizing both raw signals and basecalling errors. RedNano processes the raw-signal feature and basecalling-error feature through residual networks. We validated the effectiveness of RedNano using synthesized, Arabidopsis, and human DRS data. The results demonstrate that RedNano surpasses existing methods by achieving higher area under the ROC curve (AUC) and area under the precision-recall curve (AUPRs) in all three datasets. Furthermore, RedNano performs better in cross-species validation, demonstrating its robustness. Additionally, when detecting m6A from an independent dataset of Populus trichocarpa, RedNano achieves the highest AUC and AUPR, which are 3.8%-9.9% and 5.5%-13.8% higher than other methods, respectively. AVAILABILITY AND IMPLEMENTATION The source code of RedNano is freely available at https://github.com/Derryxu/RedNano.
Collapse
Affiliation(s)
- Peng Ni
- School of Computer Science and Engineering, Central South University, Changsha 410083, China
- Xiangjiang Laboratory, Changsha 410205, China
- Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, China
| | - Jinrui Xu
- School of Computer Science and Engineering, Central South University, Changsha 410083, China
- Xiangjiang Laboratory, Changsha 410205, China
- Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, China
| | - Zeyu Zhong
- School of Computer Science and Engineering, Central South University, Changsha 410083, China
- Xiangjiang Laboratory, Changsha 410205, China
- Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, China
| | - Feng Luo
- School of Computing, Clemson University, Clemson, SC 29634-0974, United States
| | - Jianxin Wang
- School of Computer Science and Engineering, Central South University, Changsha 410083, China
- Xiangjiang Laboratory, Changsha 410205, China
- Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, China
| |
Collapse
|
28
|
Knight HM, Demirbugen Öz M, PerezGrovas-Saltijeral A. Dysregulation of RNA modification systems in clinical populations with neurocognitive disorders. Neural Regen Res 2024; 19:1256-1261. [PMID: 37905873 PMCID: PMC11467953 DOI: 10.4103/1673-5374.385858] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 07/05/2023] [Accepted: 08/10/2023] [Indexed: 11/02/2023] Open
Abstract
ABSTRACT The study of modified RNA known as epitranscriptomics has become increasingly relevant in our understanding of disease-modifying mechanisms. Methylation of N6 adenosine (m6A) and C5 cytosine (m5C) bases occur on mRNAs, tRNA, mt-tRNA, and rRNA species as well as non-coding RNAs. With emerging knowledge of RNA binding proteins that act as writer, reader, and eraser effector proteins, comes a new understanding of physiological processes controlled by these systems. Such processes when spatiotemporally disrupted within cellular nanodomains in highly specialized tissues such as the brain, give rise to different forms of disease. In this review, we discuss accumulating evidence that changes in the m6A and m5C methylation systems contribute to neurocognitive disorders. Early studies first identified mutations within FMR1 to cause intellectual disability Fragile X syndromes several years before FMR1 was identified as an m6A RNA reader protein. Subsequently, familial mutations within the m6A writer gene METTL5, m5C writer genes NSUN2, NSUN3, NSUN5, and NSUN6, as well as THOC2 and THOC6 that form a protein complex with the m5C reader protein ALYREF, were recognized to cause intellectual development disorders. Similarly, differences in expression of the m5C writer and reader effector proteins, NSUN6, NSUN7, and ALYREF in brain tissue are indicated in individuals with Alzheimer's disease, individuals with a high neuropathological load or have suffered traumatic brain injury. Likewise, an abundance of m6A reader and anti-reader proteins are reported to change across brain regions in Lewy bodies diseases, Alzheimer's disease, and individuals with high cognitive reserve. m6A-modified RNAs are also reported significantly more abundant in dementia with Lewy bodies brain tissue but significantly reduced in Parkinson's disease tissue, whilst modified RNAs are misplaced within diseased cells, particularly where synapses are located. In parahippocampal brain tissue, m6A modification is enriched in transcripts associated with psychiatric disorders including conditions with clear cognitive deficits. These findings indicate a diverse set of molecular mechanisms are influenced by RNA methylation systems that can cause neuronal and synaptic dysfunction underlying neurocognitive disorders. Targeting these RNA modification systems brings new prospects for neural regenerative therapies.
Collapse
Affiliation(s)
- Helen M. Knight
- Division of Cells, Organisms and Molecular Genetics, School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Merve Demirbugen Öz
- Department of Pharmaceutical Toxicology, Faculty of Pharmacy, Ankara University, Ankara, Turkey
| | | |
Collapse
|
29
|
Wu Y, Shao W, Yan M, Wang Y, Xu P, Huang G, Li X, Gregory BD, Yang J, Wang H, Yu X. Transfer learning enables identification of multiple types of RNA modifications using nanopore direct RNA sequencing. Nat Commun 2024; 15:4049. [PMID: 38744925 PMCID: PMC11094168 DOI: 10.1038/s41467-024-48437-4] [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: 11/08/2023] [Accepted: 04/26/2024] [Indexed: 05/16/2024] Open
Abstract
Nanopore direct RNA sequencing (DRS) has emerged as a powerful tool for RNA modification identification. However, concurrently detecting multiple types of modifications in a single DRS sample remains a challenge. Here, we develop TandemMod, a transferable deep learning framework capable of detecting multiple types of RNA modifications in single DRS data. To train high-performance TandemMod models, we generate in vitro epitranscriptome datasets from cDNA libraries, containing thousands of transcripts labeled with various types of RNA modifications. We validate the performance of TandemMod on both in vitro transcripts and in vivo human cell lines, confirming its high accuracy for profiling m6A and m5C modification sites. Furthermore, we perform transfer learning for identifying other modifications such as m7G, Ψ, and inosine, significantly reducing training data size and running time without compromising performance. Finally, we apply TandemMod to identify 3 types of RNA modifications in rice grown in different environments, demonstrating its applicability across species and conditions. In summary, we provide a resource with ground-truth labels that can serve as benchmark datasets for nanopore-based modification identification methods, and TandemMod for identifying diverse RNA modifications using a single DRS sample.
Collapse
Affiliation(s)
- You Wu
- Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Wenna Shao
- Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Mengxiao Yan
- Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, Shanghai, 201602, China
| | - Yuqin Wang
- Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, Shanghai, 201602, China
| | - Pengfei Xu
- Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Guoqiang Huang
- Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Xiaofei Li
- Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Brian D Gregory
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Jun Yang
- Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, Shanghai, 201602, China.
- Chenshan Scientific Research Center of CAS Center for Excellence in Molecular Plant Sciences, Shanghai, 201602, China.
| | - Hongxia Wang
- Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, Shanghai, 201602, China.
- Chenshan Scientific Research Center of CAS Center for Excellence in Molecular Plant Sciences, Shanghai, 201602, China.
| | - Xiang Yu
- Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
| |
Collapse
|
30
|
Acera Mateos P, J Sethi A, Ravindran A, Srivastava A, Woodward K, Mahmud S, Kanchi M, Guarnacci M, Xu J, W S Yuen Z, Zhou Y, Sneddon A, Hamilton W, Gao J, M Starrs L, Hayashi R, Wickramasinghe V, Zarnack K, Preiss T, Burgio G, Dehorter N, E Shirokikh N, Eyras E. Prediction of m6A and m5C at single-molecule resolution reveals a transcriptome-wide co-occurrence of RNA modifications. Nat Commun 2024; 15:3899. [PMID: 38724548 PMCID: PMC11082244 DOI: 10.1038/s41467-024-47953-7] [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: 02/23/2024] [Accepted: 04/15/2024] [Indexed: 05/12/2024] Open
Abstract
The epitranscriptome embodies many new and largely unexplored functions of RNA. A significant roadblock hindering progress in epitranscriptomics is the identification of more than one modification in individual transcript molecules. We address this with CHEUI (CH3 (methylation) Estimation Using Ionic current). CHEUI predicts N6-methyladenosine (m6A) and 5-methylcytosine (m5C) in individual molecules from the same sample, the stoichiometry at transcript reference sites, and differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals to achieve high single-molecule, transcript-site, and stoichiometry accuracies in multiple tests using synthetic RNA standards and cell line data. CHEUI's capability to identify two modification types in the same sample reveals a co-occurrence of m6A and m5C in individual mRNAs in cell line and tissue transcriptomes. CHEUI provides new avenues to discover and study the function of the epitranscriptome.
Collapse
Affiliation(s)
- P Acera Mateos
- EMBL Australia Partner Laboratory Network at the Australian National University, Canberra, ACT, 2601, Australia
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
- The Centre for Computational Biomedical Sciences, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
| | - A J Sethi
- EMBL Australia Partner Laboratory Network at the Australian National University, Canberra, ACT, 2601, Australia
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
- The Centre for Computational Biomedical Sciences, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
| | - A Ravindran
- EMBL Australia Partner Laboratory Network at the Australian National University, Canberra, ACT, 2601, Australia
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
- The Centre for Computational Biomedical Sciences, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
| | - A Srivastava
- EMBL Australia Partner Laboratory Network at the Australian National University, Canberra, ACT, 2601, Australia
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
- The Centre for Computational Biomedical Sciences, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
| | - K Woodward
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
| | - S Mahmud
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
| | - M Kanchi
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
| | - M Guarnacci
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
| | - J Xu
- EMBL Australia Partner Laboratory Network at the Australian National University, Canberra, ACT, 2601, Australia
| | - Z W S Yuen
- EMBL Australia Partner Laboratory Network at the Australian National University, Canberra, ACT, 2601, Australia
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
- The Centre for Computational Biomedical Sciences, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
| | - Y Zhou
- Buchmann Institute for Molecular Life Sciences (BMLS) & Faculty of Biological Sciences, Goethe University Frankfurt, 60438, Frankfurt am Main, Germany
| | - A Sneddon
- EMBL Australia Partner Laboratory Network at the Australian National University, Canberra, ACT, 2601, Australia
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
- The Centre for Computational Biomedical Sciences, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
| | - W Hamilton
- Peter MacCallum Cancer Centre, Melbourne, VIC, 3052, Australia
| | - J Gao
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
| | - L M Starrs
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
| | - R Hayashi
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
| | | | - K Zarnack
- Buchmann Institute for Molecular Life Sciences (BMLS) & Faculty of Biological Sciences, Goethe University Frankfurt, 60438, Frankfurt am Main, Germany
| | - T Preiss
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
- Victor Chang Cardiac Research Institute, Sydney, NSW, 2010, Australia
| | - G Burgio
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
- The Centre for Computational Biomedical Sciences, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
| | - N Dehorter
- The Eccles Institute of Neuroscience, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
- The Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - N E Shirokikh
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia.
| | - E Eyras
- EMBL Australia Partner Laboratory Network at the Australian National University, Canberra, ACT, 2601, Australia.
- The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia.
- The Centre for Computational Biomedical Sciences, The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia.
- Catalan Institution for Research and Advanced Studies (ICREA), 08010, Barcelona, Spain.
| |
Collapse
|
31
|
Pang J, Kuang TD, Yu XY, Novák P, Long Y, Liu M, Deng WQ, Zhu X, Yin K. N6-methyladenosine in myeloid cells: a novel regulatory factor for inflammation-related diseases. J Physiol Biochem 2024; 80:249-260. [PMID: 38158555 DOI: 10.1007/s13105-023-01002-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: 04/20/2023] [Accepted: 12/04/2023] [Indexed: 01/03/2024]
Abstract
N6-methyladenosine (m6A) is one of the most abundant epitranscriptomic modifications on eukaryotic mRNA. Evidence has highlighted that m6A is altered in response to inflammation-related factors and it is closely associated with various inflammation-related diseases. Multiple subpopulations of myeloid cells, such as macrophages, dendritic cells, and granulocytes, are crucial for the regulating of immune process in inflammation-related diseases. Recent studies have revealed that m6A plays an important regulatory role in the functional of multiple myeloid cells. In this review, we comprehensively summarize the function of m6A modification in myeloid cells from the perspective of myeloid cell production, activation, polarization, and migration. Furthermore, we discuss how m6A-mediated myeloid cell function affects the progression of inflammation-related diseases, including autoimmune diseases, chronic metabolic diseases, and malignant tumors. Finally, we discuss the challenges encountered in the study of m6A in myeloid cells, intended to provide a new direction for the study of the pathogenesis of inflammation-related diseases.
Collapse
Affiliation(s)
- Jin Pang
- Guangxi Key Laboratory of Diabetic Systems Medicine, Guilin Medical University, Guilin, Guangxi, China
| | - Tong-Dong Kuang
- Guangxi Key Laboratory of Diabetic Systems Medicine, Guilin Medical University, Guilin, Guangxi, China
| | - Xin-Yuan Yu
- Guangxi Key Laboratory of Diabetic Systems Medicine, Guilin Medical University, Guilin, Guangxi, China
| | - Petr Novák
- Guangxi Key Laboratory of Diabetic Systems Medicine, Guilin Medical University, Guilin, Guangxi, China
| | - Yuan Long
- Department of General Practice, The Fifth Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China
| | - Min Liu
- Department of General Practice, The Fifth Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China
| | - Wei-Qian Deng
- Department of General Practice, The Fifth Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China
| | - Xiao Zhu
- Guangxi Key Laboratory of Diabetic Systems Medicine, Guilin Medical University, Guilin, Guangxi, China.
| | - Kai Yin
- Department of General Practice, The Fifth Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| |
Collapse
|
32
|
Chan A, Naarmann-de Vries IS, Scheitl CPM, Höbartner C, Dieterich C. Detecting m 6A at single-molecular resolution via direct RNA sequencing and realistic training data. Nat Commun 2024; 15:3323. [PMID: 38637518 PMCID: PMC11026524 DOI: 10.1038/s41467-024-47661-2] [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: 08/28/2023] [Accepted: 04/05/2024] [Indexed: 04/20/2024] Open
Abstract
Direct RNA sequencing offers the possibility to simultaneously identify canonical bases and epi-transcriptomic modifications in each single RNA molecule. Thus far, the development of computational methods has been hampered by the lack of biologically realistic training data that carries modification labels at molecular resolution. Here, we report on the synthesis of such samples and the development of a bespoke algorithm, mAFiA (m6A Finding Algorithm), that accurately detects single m6A nucleotides in both synthetic RNAs and natural mRNA on single read level. Our approach uncovers distinct modification patterns in single molecules that would appear identical at the ensemble level. Compared to existing methods, mAFiA also demonstrates improved accuracy in measuring site-level m6A stoichiometry in biological samples.
Collapse
Affiliation(s)
- Adrian Chan
- Klaus Tschira Institute for Integrative Computational Cardiology, University of Heidelberg, Heidelberg, Germany
| | - Isabel S Naarmann-de Vries
- Klaus Tschira Institute for Integrative Computational Cardiology, University of Heidelberg, Heidelberg, Germany
- German Centre for Cardiovascular Research (DZHK)-Partner Site Heidelberg/Mannheim, Heidelberg, Germany
| | | | - Claudia Höbartner
- Institute of Organic Chemistry, University of Würzburg, Würzburg, Germany
| | - Christoph Dieterich
- Klaus Tschira Institute for Integrative Computational Cardiology, University of Heidelberg, Heidelberg, Germany.
- German Centre for Cardiovascular Research (DZHK)-Partner Site Heidelberg/Mannheim, Heidelberg, Germany.
| |
Collapse
|
33
|
Andersson D, Kebede FT, Escobar M, Österlund T, Ståhlberg A. Principles of digital sequencing using unique molecular identifiers. Mol Aspects Med 2024; 96:101253. [PMID: 38367531 DOI: 10.1016/j.mam.2024.101253] [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: 11/16/2023] [Revised: 01/26/2024] [Accepted: 02/03/2024] [Indexed: 02/19/2024]
Abstract
Massively parallel sequencing technologies have long been used in both basic research and clinical routine. The recent introduction of digital sequencing has made previously challenging applications possible by significantly improving sensitivity and specificity to now allow detection of rare sequence variants, even at single molecule level. Digital sequencing utilizes unique molecular identifiers (UMIs) to minimize sequencing-induced errors and quantification biases. Here, we discuss the principles of UMIs and how they are used in digital sequencing. We outline the properties of different UMI types and the consequences of various UMI approaches in relation to experimental protocols and bioinformatics. Finally, we describe how digital sequencing can be applied in specific research fields, focusing on cancer management where it can be used in screening of asymptomatic individuals, diagnosis, treatment prediction, prognostication, monitoring treatment efficacy and early detection of treatment resistance as well as relapse.
Collapse
Affiliation(s)
- Daniel Andersson
- Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 413 90, Gothenburg, Sweden
| | - Firaol Tamiru Kebede
- Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 413 90, Gothenburg, Sweden
| | - Mandy Escobar
- Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 413 90, Gothenburg, Sweden
| | - Tobias Österlund
- Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 413 90, Gothenburg, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, 413 90, Gothenburg, Sweden; Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, 413 45, Gothenburg, Sweden
| | - Anders Ståhlberg
- Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 413 90, Gothenburg, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, 413 90, Gothenburg, Sweden; Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, 413 45, Gothenburg, Sweden.
| |
Collapse
|
34
|
Liu WW, Zheng SQ, Li T, Fei YF, Wang C, Zhang S, Wang F, Jiang GM, Wang H. RNA modifications in cellular metabolism: implications for metabolism-targeted therapy and immunotherapy. Signal Transduct Target Ther 2024; 9:70. [PMID: 38531882 DOI: 10.1038/s41392-024-01777-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 02/08/2024] [Accepted: 02/19/2024] [Indexed: 03/28/2024] Open
Abstract
Cellular metabolism is an intricate network satisfying bioenergetic and biosynthesis requirements of cells. Relevant studies have been constantly making inroads in our understanding of pathophysiology, and inspiring development of therapeutics. As a crucial component of epigenetics at post-transcription level, RNA modification significantly determines RNA fates, further affecting various biological processes and cellular phenotypes. To be noted, immunometabolism defines the metabolic alterations occur on immune cells in different stages and immunological contexts. In this review, we characterize the distribution features, modifying mechanisms and biological functions of 8 RNA modifications, including N6-methyladenosine (m6A), N6,2'-O-dimethyladenosine (m6Am), N1-methyladenosine (m1A), 5-methylcytosine (m5C), N4-acetylcytosine (ac4C), N7-methylguanosine (m7G), Pseudouridine (Ψ), adenosine-to-inosine (A-to-I) editing, which are relatively the most studied types. Then regulatory roles of these RNA modification on metabolism in diverse health and disease contexts are comprehensively described, categorized as glucose, lipid, amino acid, and mitochondrial metabolism. And we highlight the regulation of RNA modifications on immunometabolism, further influencing immune responses. Above all, we provide a thorough discussion about clinical implications of RNA modification in metabolism-targeted therapy and immunotherapy, progression of RNA modification-targeted agents, and its potential in RNA-targeted therapeutics. Eventually, we give legitimate perspectives for future researches in this field from methodological requirements, mechanistic insights, to therapeutic applications.
Collapse
Affiliation(s)
- Wei-Wei Liu
- Department of Laboratory Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- School of Clinical Medicine, Shandong University, Jinan, China
| | - Si-Qing Zheng
- Department of Laboratory Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Core Unit of National Clinical Research Center for Laboratory Medicine, Hefei, China
| | - Tian Li
- Department of Laboratory Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Core Unit of National Clinical Research Center for Laboratory Medicine, Hefei, China
| | - Yun-Fei Fei
- Department of Laboratory Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Core Unit of National Clinical Research Center for Laboratory Medicine, Hefei, China
| | - Chen Wang
- Department of Laboratory Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Core Unit of National Clinical Research Center for Laboratory Medicine, Hefei, China
| | - Shuang Zhang
- Department of Laboratory Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Core Unit of National Clinical Research Center for Laboratory Medicine, Hefei, China
| | - Fei Wang
- Neurosurgical Department, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
| | - Guan-Min Jiang
- Department of Clinical Laboratory, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China.
| | - Hao Wang
- Department of Laboratory Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
- Core Unit of National Clinical Research Center for Laboratory Medicine, Hefei, China.
| |
Collapse
|
35
|
Warminski M, Trepkowska E, Smietanski M, Sikorski PJ, Baranowski MR, Bednarczyk M, Kedzierska H, Majewski B, Mamot A, Papiernik D, Popielec A, Serwa RA, Shimanski BA, Sklepkiewicz P, Sklucka M, Sokolowska O, Spiewla T, Toczydlowska-Socha D, Warminska Z, Wolosewicz K, Zuberek J, Mugridge JS, Nowis D, Golab J, Jemielity J, Kowalska J. Trinucleotide mRNA Cap Analogue N6-Benzylated at the Site of Posttranscriptional m6A m Mark Facilitates mRNA Purification and Confers Superior Translational Properties In Vitro and In Vivo. J Am Chem Soc 2024; 146:8149-8163. [PMID: 38442005 PMCID: PMC10979456 DOI: 10.1021/jacs.3c12629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 02/12/2024] [Accepted: 02/12/2024] [Indexed: 03/07/2024]
Abstract
Eukaryotic mRNAs undergo cotranscriptional 5'-end modification with a 7-methylguanosine cap. In higher eukaryotes, the cap carries additional methylations, such as m6Am─a common epitranscriptomic mark unique to the mRNA 5'-end. This modification is regulated by the Pcif1 methyltransferase and the FTO demethylase, but its biological function is still unknown. Here, we designed and synthesized a trinucleotide FTO-resistant N6-benzyl analogue of the m6Am-cap-m7GpppBn6AmpG (termed AvantCap) and incorporated it into mRNA using T7 polymerase. mRNAs carrying Bn6Am showed several advantages over typical capped transcripts. The Bn6Am moiety was shown to act as a reversed-phase high-performance liquid chromatography (RP-HPLC) purification handle, allowing the separation of capped and uncapped RNA species, and to produce transcripts with lower dsRNA content than reference caps. In some cultured cells, Bn6Am mRNAs provided higher protein yields than mRNAs carrying Am or m6Am, although the effect was cell-line-dependent. m7GpppBn6AmpG-capped mRNAs encoding reporter proteins administered intravenously to mice provided up to 6-fold higher protein outputs than reference mRNAs, while mRNAs encoding tumor antigens showed superior activity in therapeutic settings as anticancer vaccines. The biochemical characterization suggests several phenomena potentially underlying the biological properties of AvantCap: (i) reduced propensity for unspecific interactions, (ii) involvement in alternative translation initiation, and (iii) subtle differences in mRNA impurity profiles or a combination of these effects. AvantCapped-mRNAs bearing the Bn6Am may pave the way for more potent mRNA-based vaccines and therapeutics and serve as molecular tools to unravel the role of m6Am in mRNA.
Collapse
Affiliation(s)
- Marcin Warminski
- Division
of Biophysics, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, 02-089 Warsaw, Poland
| | - Edyta Trepkowska
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
| | | | - Pawel J. Sikorski
- Centre
of New Technologies, University of Warsaw, 02-089 Warsaw, Poland
- Laboratory
of Epitranscriptomics, Department of Environmental Microbiology and
Biotechnology, Institute of Microbiology, Faculty of Biology, Biological
and Chemical Research Centre, University
of Warsaw, 02-089 Warsaw, Poland
| | | | - Marcelina Bednarczyk
- Centre
of New Technologies, University of Warsaw, 02-089 Warsaw, Poland
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
| | - Hanna Kedzierska
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
| | - Bartosz Majewski
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
| | - Adam Mamot
- Centre
of New Technologies, University of Warsaw, 02-089 Warsaw, Poland
| | - Diana Papiernik
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
| | - Agnieszka Popielec
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
| | - Remigiusz A. Serwa
- Proteomics
Core Facility, IMol Polish Academy of Sciences, 02-247 Warsaw, Poland
| | - Brittany A. Shimanski
- Department
of Chemistry & Biochemistry, University
of Delaware, Newark, Delaware 19716, United States
| | - Piotr Sklepkiewicz
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
| | - Marta Sklucka
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
| | - Olga Sokolowska
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
| | - Tomasz Spiewla
- Division
of Biophysics, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, 02-089 Warsaw, Poland
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
| | | | - Zofia Warminska
- Centre
of New Technologies, University of Warsaw, 02-089 Warsaw, Poland
| | - Karol Wolosewicz
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
| | - Joanna Zuberek
- Division
of Biophysics, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, 02-089 Warsaw, Poland
| | - Jeffrey S. Mugridge
- Department
of Chemistry & Biochemistry, University
of Delaware, Newark, Delaware 19716, United States
| | - Dominika Nowis
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
- Laboratory
of Experimental Medicine, Faculty of Medicine, Medical University of Warsaw, 02-097 Warsaw, Poland
| | - Jakub Golab
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
- Laboratory
of Experimental Medicine, Faculty of Medicine, Medical University of Warsaw, 02-097 Warsaw, Poland
| | - Jacek Jemielity
- Centre
of New Technologies, University of Warsaw, 02-089 Warsaw, Poland
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
| | - Joanna Kowalska
- Division
of Biophysics, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, 02-089 Warsaw, Poland
- Explorna
Therapeutics sp. z o.o. Zwirki i Wigury 93, 02-089 Warsaw, Poland
| |
Collapse
|
36
|
Goh WSS, Kuang Y. Heterogeneity of chemical modifications on RNA. Biophys Rev 2024; 16:79-87. [PMID: 38495447 PMCID: PMC10937866 DOI: 10.1007/s12551-023-01128-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 08/27/2023] [Indexed: 03/19/2024] Open
Abstract
The chemical modifications of RNAs broadly impact almost all cellular events and influence various diseases. The rapid advance of sequencing and other technologies opened the door to global methods for profiling all RNA modifications, namely the "epitranscriptome." The mapping of epitranscriptomes in different cells and tissues unveiled that RNA modifications exhibit extensive heterogeneity, in type, amount, and in location. In this mini review, we first introduce the current understanding of modifications on major types of RNAs and the methods that enabled their discovery. We next discuss the tissue and cell heterogeneity of RNA modifications and briefly address the limitations of current technologies. With much still remaining unknown, the development of the epitranscriptomic field lies in the further developments of novel technologies.
Collapse
Affiliation(s)
- W. S. Sho Goh
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, China
| | - Yi Kuang
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
| |
Collapse
|
37
|
Liang Z, Ye H, Ma J, Wei Z, Wang Y, Zhang Y, Huang D, Song B, Meng J, Rigden DJ, Chen K. m6A-Atlas v2.0: updated resources for unraveling the N6-methyladenosine (m6A) epitranscriptome among multiple species. Nucleic Acids Res 2024; 52:D194-D202. [PMID: 37587690 PMCID: PMC10768109 DOI: 10.1093/nar/gkad691] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 08/02/2023] [Accepted: 08/10/2023] [Indexed: 08/18/2023] Open
Abstract
N 6-Methyladenosine (m6A) is one of the most abundant internal chemical modifications on eukaryote mRNA and is involved in numerous essential molecular functions and biological processes. To facilitate the study of this important post-transcriptional modification, we present here m6A-Atlas v2.0, an updated version of m6A-Atlas. It was expanded to include a total of 797 091 reliable m6A sites from 13 high-resolution technologies and two single-cell m6A profiles. Additionally, three methods (exomePeaks2, MACS2 and TRESS) were used to identify >16 million m6A enrichment peaks from 2712 MeRIP-seq experiments covering 651 conditions in 42 species. Quality control results of MeRIP-seq samples were also provided to help users to select reliable peaks. We also estimated the condition-specific quantitative m6A profiles (i.e. differential methylation) under 172 experimental conditions for 19 species. Further, to provide insights into potential functional circuitry, the m6A epitranscriptomics were annotated with various genomic features, interactions with RNA-binding proteins and microRNA, potentially linked splicing events and single nucleotide polymorphisms. The collected m6A sites and their functional annotations can be freely queried and downloaded via a user-friendly graphical interface at: http://rnamd.org/m6a.
Collapse
Affiliation(s)
- Zhanmin Liang
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian 350004, China
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
| | - Haokai Ye
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Jiongming Ma
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian 350004, China
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Zhen Wei
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L69 7ZB, UK
| | - Yue Wang
- Department of Mathematical Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Department of Computer Science, University of Liverpool, Liverpool L69 7ZB, UK
| | - Yuxin Zhang
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian 350004, China
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Daiyun Huang
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Department of Computer Science, University of Liverpool, Liverpool L69 7ZB, UK
| | - Bowen Song
- Department of Public Health, School of Medicine & Holistic Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Jia Meng
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- AI University Research Centre, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Daniel J Rigden
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Kunqi Chen
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian 350004, China
| |
Collapse
|
38
|
Wang Z, Fang Y, Liu Z, Hao N, Zhang HH, Sun X, Que J, Ding H. Adapting Nanopore Sequencing Basecalling Models for Modification Detection via Incremental Learning and Anomaly Detection. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.19.572449. [PMID: 38187611 PMCID: PMC10769248 DOI: 10.1101/2023.12.19.572431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
We leverage machine learning approaches to adapt nanopore sequencing basecallers for nucleotide modification detection. We first apply the incremental learning technique to improve the basecalling of modification-rich sequences, which are usually of high biological interests. With sequence backbones resolved, we further run anomaly detection on individual nucleotides to determine their modification status. By this means, our pipeline promises the single-molecule, single-nucleotide and sequence context-free detection of modifications. We benchmark the pipeline using control oligos, further apply it in the basecalling of densely-modified yeast tRNAs and E.coli genomic DNAs, the cross-species detection of N6-methyladenosine (m6A) in mammalian mRNAs, and the simultaneous detection of N1-methyladenosine (m1A) and m6A in human mRNAs. Our IL-AD workflow is available at: https://github.com/wangziyuan66/IL-AD.
Collapse
Affiliation(s)
- Ziyuan Wang
- Department of Pharmacy Practice and Science, University of Arizona, Tucson, Arizona, USA
- These authors contributed equally to this work
| | - Yinshan Fang
- Columbia Center for Human Development, Department of Medicine, Columbia University Medical Center, New York, New York, USA
- These authors contributed equally to this work
| | - Ziyang Liu
- Department of Pharmacy Practice and Science, University of Arizona, Tucson, Arizona, USA
- Statistics and Data Science GIDP, University of Arizona, Tucson, Arizona, USA
| | - Ning Hao
- Statistics and Data Science GIDP, University of Arizona, Tucson, Arizona, USA
- Department of Mathematics, University of Arizona, Tucson, Arizona, USA
| | - Hao Helen Zhang
- Statistics and Data Science GIDP, University of Arizona, Tucson, Arizona, USA
- Department of Mathematics, University of Arizona, Tucson, Arizona, USA
| | - Xiaoxiao Sun
- Statistics and Data Science GIDP, University of Arizona, Tucson, Arizona, USA
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona, USA
| | - Jianwen Que
- Columbia Center for Human Development, Department of Medicine, Columbia University Medical Center, New York, New York, USA
| | - Hongxu Ding
- Department of Pharmacy Practice and Science, University of Arizona, Tucson, Arizona, USA
- Statistics and Data Science GIDP, University of Arizona, Tucson, Arizona, USA
| |
Collapse
|
39
|
Bi CF, Liu J, Hu XD, Yang LS, Zhang JF. Novel insights into the regulatory role of N6-methyladenosine methylation modified autophagy in sepsis. Aging (Albany NY) 2023; 15:15676-15700. [PMID: 38112620 PMCID: PMC10781468 DOI: 10.18632/aging.205312] [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: 07/16/2023] [Accepted: 10/23/2023] [Indexed: 12/21/2023]
Abstract
Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. It is characterized by high morbidity and mortality and one of the major diseases that seriously hang over global human health. Autophagy is a crucial regulator in the complicated pathophysiological processes of sepsis. The activation of autophagy is known to be of great significance for protecting sepsis induced organ dysfunction. Recent research has demonstrated that N6-methyladenosine (m6A) methylation is a well-known post-transcriptional RNA modification that controls epigenetic and gene expression as well as a number of biological processes in sepsis. In addition, m6A affects the stability, export, splicing and translation of transcripts involved in the autophagic process. Although it has been suggested that m6A methylation regulates the biological metabolic processes of autophagy and is more frequently seen in the progression of sepsis pathogenesis, the underlying molecular mechanisms of m6A-modified autophagy in sepsis have not been thoroughly elucidated. The present article fills this gap by providing an epigenetic review of the processes of m6A-modified autophagy in sepsis and its potential role in the development of novel therapeutics.
Collapse
Affiliation(s)
- Cheng-Fei Bi
- Department of Emergency Medical, General Hospital of Ningxia Medical University, Yinchuan 750000, Ningxia, China
- School of Clinical Medicine, Ningxia Medical University, Yinchuan 750000, Ningxia, China
| | - Jia Liu
- Medical Experimental Center, General Hospital of Ningxia Medical University, Yinchuan 750000, Ningxia, China
| | - Xiao-Dong Hu
- Department of Emergency Medical, General Hospital of Ningxia Medical University, Yinchuan 750000, Ningxia, China
| | - Li-Shan Yang
- Department of Emergency Medical, General Hospital of Ningxia Medical University, Yinchuan 750000, Ningxia, China
| | - Jun-Fei Zhang
- Department of Emergency Medical, General Hospital of Ningxia Medical University, Yinchuan 750000, Ningxia, China
- Medical Experimental Center, General Hospital of Ningxia Medical University, Yinchuan 750000, Ningxia, China
| |
Collapse
|
40
|
Ren J, Chen X, Zhang Z, Shi H, Wu S. DPred_3S: identifying dihydrouridine (D) modification on three species epitranscriptome based on multiple sequence-derived features. Front Genet 2023; 14:1334132. [PMID: 38169665 PMCID: PMC10758487 DOI: 10.3389/fgene.2023.1334132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 11/29/2023] [Indexed: 01/05/2024] Open
Abstract
Introduction: Dihydrouridine (D) is a conserved modification of tRNA among all three life domains. D modification enhances the flexibility of a single nucleotide base in the spatial structure and is disease- and evolution-associated. Recent studies have also suggested the presence of dihydrouridine on mRNA. Methods: To identify D in epitranscriptome, we provided a prediction framework named "DPred_3S" based on the machine learning approach for three species D epitranscriptome, which used epitranscriptome sequencing data as training data for the first time. Results: The optimal features were evaluated by the F-score and integration of different features; our model achieved area under the receiver operating characteristic curve (AUROC) scores 0.955, 0.946, and 0.905 for Saccharomyces cerevisiae, Escherichia coli, and Schizosaccharomyces pombe, respectively. The performances of different machine learning algorithms were also compared in this study. Discussion: The high performances of our model suggest the D sites can be distinguished based on their surrounding sequence, but the lower performance of cross-species prediction may be limited by technique preferences.
Collapse
Affiliation(s)
- Jinjin Ren
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian, China
- Fujian Key Laboratory of Tumor Microbiology, Department of Medical Microbiology, Fujian Medical University, Fuzhou, Fujian, China
| | - Xiaozhen Chen
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian, China
| | - Zhengqian Zhang
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian, China
| | - Haoran Shi
- Institute of Applied Microbiology, Research Center for BioSystems, Land Use, and Nutrition (IFZ), Justus-Liebig-University Giessen, Giessen, Germany
| | - Shuxiang Wu
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian, China
- Fujian Key Laboratory of Tumor Microbiology, Department of Medical Microbiology, Fujian Medical University, Fuzhou, Fujian, China
| |
Collapse
|
41
|
Benak D, Kolar F, Zhang L, Devaux Y, Hlavackova M. RNA modification m 6Am: the role in cardiac biology. Epigenetics 2023; 18:2218771. [PMID: 37331009 DOI: 10.1080/15592294.2023.2218771] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 05/19/2023] [Accepted: 05/23/2023] [Indexed: 06/20/2023] Open
Abstract
Epitranscriptomic modifications have recently emerged into the spotlight of researchers due to their vast regulatory effects on gene expression and thereby cellular physiology and pathophysiology. N6,2'-O-dimethyladenosine (m6Am) is one of the most prevalent chemical marks on RNA and is dynamically regulated by writers (PCIF1, METTL4) and erasers (FTO). The presence or absence of m6Am in RNA affects mRNA stability, regulates transcription, and modulates pre-mRNA splicing. Nevertheless, its functions in the heart are poorly known. This review summarizes the current knowledge and gaps about m6Am modification and its regulators in cardiac biology. It also points out technical challenges and lists the currently available techniques to measure m6Am. A better understanding of epitranscriptomic modifications is needed to improve our knowledge of the molecular regulations in the heart which may lead to novel cardioprotective strategies.
Collapse
Affiliation(s)
- Daniel Benak
- Laboratory of Developmental Cardiology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
- Department of Physiology, Faculty of Science, Charles University, Prague, Czech Republic
| | - Frantisek Kolar
- Laboratory of Developmental Cardiology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
| | - Lu Zhang
- Bioinformatics Platform, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Yvan Devaux
- Cardiovascular Research Unit, Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Marketa Hlavackova
- Laboratory of Developmental Cardiology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
| |
Collapse
|
42
|
Zhang M, Xiao Y, Jiang Z, Yi C. Quantifying m 6A and Ψ Modifications in the Transcriptome via Chemical-Assisted Approaches. Acc Chem Res 2023; 56:2980-2991. [PMID: 37851547 DOI: 10.1021/acs.accounts.3c00436] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2023]
Abstract
Since the discovery of the first chemically modified RNA nucleotide in 1951, more than 170 types of chemical modifications have been characterized in RNA so far. Since the discovery of the reversible and dynamic nature of N6-methyladenosine (m6A) in mRNA modification, researchers have identified about ten modifications in eukaryotic mRNA; together with modifications on the noncoding RNAs, the term "epitranscriptome" has been coined to describe the ensemble of various chemical RNA modifications. The past decade has witnessed the discovery of many novel molecular functions of mRNA modifications, demonstrating their crucial roles in gene expression regulation. As the most abundant modifications in mRNA, the study of m6A and Ψ has been facilitated by innovative high-throughput sequencing technologies, which can be based on antibodies, enzymes, or novel chemistry. Among them, chemical-assisted methods utilize selective chemistry that can discriminate modified versus unmodified nucleotides, enabling the transcriptome-wide mapping of m6A and Ψ modifications and functional studies.Our group has developed several sequencing technologies to investigate these epitranscriptomic marks including m6A, Ψ, m1A, and m6Am. Among them, we have recently developed two methods for absolute quantification of m6A and Ψ in the transcriptome based on chemical reactivity to distinguish and measure the two modifications. In GLORI, we used glyoxal and nitrite to mediate efficient deamination of regular adenosine, while m6A remained unaffected, thereby enabling efficient and unbiased detection of single-base resolution and absolute quantification of m6A modification. In CeU-seq and PRAISE, we used different chemistry to achieve selective labeling and detection of transcriptome-wide Ψ. CeU-seq is based on an azido-derivatized carbodiimide compound, while PRAISE utilizes the unique activity of bisulfite to Ψ. PRAISE results in the formation of ring-opening Ψ-bisulfite adduct and quantitatively detects Ψ as 1-2 nt deletion signatures during sequencing. The resulting base-resolution and stoichiometric information expanded our understanding to the profiles of RNA modifications in the transcriptome. In particular, the quantitative information on RNA methylome is critical for characterizing the dynamic and reversible nature of RNA modifications, for instance, under environmental stress or during development. Additionally, base-resolution and stoichiometric information can greatly facilitate the analysis and characterization of functional modification sites that are important for gene expression regulation, especially when one modification type may have multiple or even opposing functions within a specific transcript. Together, the quantitative profiling methods provide the modification stoichiometry information, which is critical to study the regulatory roles of RNA modifications.In this Account, we will focus on the quantitative sequencing technologies of m6A and Ψ developed in our group, review recent advances in chemical-assisted reactions for m6A and Ψ detection, and discuss the challenges and future opportunities of transcriptome-wide mapping technologies for RNA modifications.
Collapse
Affiliation(s)
- Meiling Zhang
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China
| | - Ye Xiao
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
| | - Zhe Jiang
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China
| | - Chengqi Yi
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
- Department of Chemical Biology and Synthetic and Functional Biomolecules Center, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| |
Collapse
|
43
|
Jia J, Wei Z, Sun M. EMDL_m6Am: identifying N6,2'-O-dimethyladenosine sites based on stacking ensemble deep learning. BMC Bioinformatics 2023; 24:397. [PMID: 37880673 PMCID: PMC10598967 DOI: 10.1186/s12859-023-05543-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 10/20/2023] [Indexed: 10/27/2023] Open
Abstract
BACKGROUND N6, 2'-O-dimethyladenosine (m6Am) is an abundant RNA methylation modification on vertebrate mRNAs and is present in the transcription initiation region of mRNAs. It has recently been experimentally shown to be associated with several human disorders, including obesity genes, and stomach cancer, among others. As a result, N6,2'-O-dimethyladenosine (m6Am) site will play a crucial part in the regulation of RNA if it can be correctly identified. RESULTS This study proposes a novel deep learning-based m6Am prediction model, EMDL_m6Am, which employs one-hot encoding to expressthe feature map of the RNA sequence and recognizes m6Am sites by integrating different CNN models via stacking. Including DenseNet, Inflated Convolutional Network (DCNN) and Deep Multiscale Residual Network (MSRN), the sensitivity (Sn), specificity (Sp), accuracy (ACC), Mathews correlation coefficient (MCC) and area under the curve (AUC) of our model on the training data set reach 86.62%, 88.94%, 87.78%, 0.7590 and 0.8778, respectively, and the prediction results on the independent test set are as high as 82.25%, 79.72%, 80.98%, 0.6199, and 0.8211. CONCLUSIONS In conclusion, the experimental results demonstrated that EMDL_m6Am greatly improved the predictive performance of the m6Am sites and could provide a valuable reference for the next part of the study. The source code and experimental data are available at: https://github.com/13133989982/EMDL-m6Am .
Collapse
Affiliation(s)
- Jianhua Jia
- School of Information Engineering, Jingdezhen Ceramic University, Jingdezhen, 333403, China.
| | - Zhangying Wei
- School of Information Engineering, Jingdezhen Ceramic University, Jingdezhen, 333403, China.
| | - Mingwei Sun
- School of Information Engineering, Jingdezhen Ceramic University, Jingdezhen, 333403, China
| |
Collapse
|
44
|
Wu Y, Pu X, Wu S, Zhang Y, Fu S, Tang H, Wang X, Xu M. PCIF1, the only methyltransferase of N6,2-O-dimethyladenosine. Cancer Cell Int 2023; 23:226. [PMID: 37779183 PMCID: PMC10544176 DOI: 10.1186/s12935-023-03066-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 09/14/2023] [Indexed: 10/03/2023] Open
Abstract
N6-methyladenosine(m6A), is the most abundant post-transcriptional modification of mRNA in biology. When the first nucleotide after the m7G cap is adenosine, it is methylated at the N6 position to form N6,2-O-dimethyladenosine (m6Am). m6Am is a reversible modification located at the first transcribed nucleotide, which is present in about 30% of cellular mRNAs, thus m6Am can have a significant impact on gene expression in the transcriptome. Phosphorylated CTD interaction factor 1(PCIF1), the unique and specific methyltransferase of m6Am, has been shown to affect mRNA stability, transcription, and translation. Several studies have shown that PCIF1 is clearly associated with tumor, viral, and endocrine diseases. Moreover, PCIF1 may be related to the tumor microenvironment, immune cell typing, and programmed cell death protein 1(PD-1) drug resistance. Here, we summarize the mechanism of PCIF1 involvement in mRNA modifications, and outline m6Am modifications and diseases in which PCIF1 is involved. We also summarized the role of PCIF1 in immune and immune checkpoint blockade(ICB) treatment, and predicted the possibility of PCIF1 as a biomarker and therapeutic target.
Collapse
Affiliation(s)
- Yuting Wu
- Department of Gastroenterology, Affiliated Hospital of Jiangsu University, Jiangsu University, Zhenjiang, 212001, Jiangsu, China
| | - Xi Pu
- Department of Gastroenterology, Affiliated Hospital of Jiangsu University, Jiangsu University, Zhenjiang, 212001, Jiangsu, China
| | - Sihui Wu
- Department of Gastroenterology, Affiliated Hospital of Jiangsu University, Jiangsu University, Zhenjiang, 212001, Jiangsu, China
| | - Yiran Zhang
- Department of Gastroenterology, Affiliated Hospital of Jiangsu University, Jiangsu University, Zhenjiang, 212001, Jiangsu, China
| | - Shengqiao Fu
- Department of Radiation Oncology, Institute of Oncology, Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, Jiangsu, China
| | - Haowen Tang
- Department of Radiation Oncology, Institute of Oncology, Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, Jiangsu, China
| | - Xu Wang
- Department of Radiation Oncology, Institute of Oncology, Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, Jiangsu, China.
| | - Min Xu
- Department of Gastroenterology, Affiliated Hospital of Jiangsu University, Jiangsu University, Zhenjiang, 212001, Jiangsu, China.
- Digestive Disease Research Institute of Jiangsu University, Zhenjiang, 212001, Jiangsu, China.
| |
Collapse
|
45
|
Liu J, Huang T, Yao J, Zhao T, Zhang Y, Zhang R. Epitranscriptomic subtyping, visualization, and denoising by global motif visualization. Nat Commun 2023; 14:5944. [PMID: 37741827 PMCID: PMC10517956 DOI: 10.1038/s41467-023-41653-4] [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: 01/01/2023] [Accepted: 09/13/2023] [Indexed: 09/25/2023] Open
Abstract
Advances in sequencing technologies have empowered epitranscriptomic profiling at the single-base resolution. Putative RNA modification sites identified from a single high-throughput experiment may contain one type of modification deposited by different writers or different types of modifications, along with false positive results because of the challenge of distinguishing signals from noise. However, current tools are insufficient for subtyping, visualization, and denoising these signals. Here, we present iMVP, which is an interactive framework for epitranscriptomic analysis with a nonlinear dimension reduction technique and density-based partition. As exemplified by the analysis of mRNA m5C and ModTect variant data, we show that iMVP allows the identification of previously unknown RNA modification motifs and writers and the discovery of false positives that are undetectable by traditional methods. Using putative m6A/m6Am sites called from 8 profiling approaches, we illustrate that iMVP enables comprehensive comparison of different approaches and advances our understanding of the difference and pattern of true positives and artifacts in these methods. Finally, we demonstrate the ability of iMVP to analyze an extremely large human A-to-I editing dataset that was previously unmanageable. Our work provides a general framework for the visualization and interpretation of epitranscriptomic data.
Collapse
Affiliation(s)
- Jianheng Liu
- MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, P. R. China.
- Department of Pharmacology, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA.
| | - Tao Huang
- Department of Pathology and Pathophysiology, Shantou University Medical College, Shantou, 515041, P. R. China
| | - Jing Yao
- MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, P. R. China
| | - Tianxuan Zhao
- MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, P. R. China
| | - Yusen Zhang
- MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, P. R. China
| | - Rui Zhang
- MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, P. R. China.
| |
Collapse
|
46
|
Breger K, Kunkler CN, O'Leary NJ, Hulewicz JP, Brown JA. Ghost authors revealed: The structure and function of human N 6 -methyladenosine RNA methyltransferases. WILEY INTERDISCIPLINARY REVIEWS. RNA 2023; 15:e1810. [PMID: 37674370 PMCID: PMC10915109 DOI: 10.1002/wrna.1810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 07/14/2023] [Accepted: 07/15/2023] [Indexed: 09/08/2023]
Abstract
Despite the discovery of modified nucleic acids nearly 75 years ago, their biological functions are still being elucidated. N6 -methyladenosine (m6 A) is the most abundant modification in eukaryotic messenger RNA (mRNA) and has also been detected in non-coding RNAs, including long non-coding RNA, ribosomal RNA, and small nuclear RNA. In general, m6 A marks can alter RNA secondary structure and initiate unique RNA-protein interactions that can alter splicing, mRNA turnover, and translation, just to name a few. Although m6 A marks in human RNAs have been known to exist since 1974, the structures and functions of methyltransferases responsible for writing m6 A marks have been established only recently. Thus far, there are four confirmed human methyltransferases that catalyze the transfer of a methyl group from S-adenosylmethionine (SAM) to the N6 position of adenosine, producing m6 A: methyltransferase-like protein (METTL) 3/METTL14 complex, METTL16, METTL5, and zinc-finger CCHC-domain-containing protein 4. Though the methyltransferases have unique RNA targets, all human m6 A RNA methyltransferases contain a Rossmann fold with a conserved SAM-binding pocket, suggesting that they utilize a similar catalytic mechanism for methyl transfer. For each of the human m6 A RNA methyltransferases, we present the biological functions and links to human disease, RNA targets, catalytic and kinetic mechanisms, and macromolecular structures. We also discuss m6 A marks in human viruses and parasites, assigning m6 A marks in the transcriptome to specific methyltransferases, small molecules targeting m6 A methyltransferases, and the enzymes responsible for hypermodified m6 A marks and their biological functions in humans. Understanding m6 A methyltransferases is a critical steppingstone toward establishing the m6 A epitranscriptome and more broadly the RNome. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications.
Collapse
Affiliation(s)
- Kurtis Breger
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana, USA
| | - Charlotte N Kunkler
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana, USA
| | - Nathan J O'Leary
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana, USA
| | - Jacob P Hulewicz
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana, USA
| | - Jessica A Brown
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana, USA
| |
Collapse
|
47
|
Li K, Peng J, Yi C. Sequencing methods and functional decoding of mRNA modifications. FUNDAMENTAL RESEARCH 2023; 3:738-748. [PMID: 38933299 PMCID: PMC11197720 DOI: 10.1016/j.fmre.2023.05.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 04/27/2023] [Accepted: 05/07/2023] [Indexed: 06/28/2024] Open
Abstract
More than 160 types of post-transcriptional RNA modifications have been reported; there is substantial variation in modification type, abundance, site, and function across species, tissues, and RNA type. The recent development of high-throughput detection technology has enabled identification of diverse dynamic and reversible RNA modifications, including N6,2'-O-dimethyladenosine (m6Am), N1-methyladenosine (m1A), 5-methylcytosine (m5C), N6-methyladenosine (m6A), pseudouridine (Ψ), and inosine (I). In this review, we focus on eukaryotic mRNA modifications. We summarize their biogenesis, regulatory mechanisms, and biological functions, as well as high-throughput methods for detection of mRNA modifications. We also discuss challenges that must be addressed in mRNA modification research.
Collapse
Affiliation(s)
- Kai Li
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Jinying Peng
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China
| | - Chengqi Yi
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
- Department of Chemical Biology and Synthetic and Functional Biomolecules Center, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| |
Collapse
|
48
|
Zhao Y, Luo Q, Wang W, Geng S, Sun Y, Xu T. METTL16, an evolutionarily conserved m6A methyltransferase member, inhibits the antiviral immune response of miiuy croaker (Miichthys miiuy). DEVELOPMENTAL AND COMPARATIVE IMMUNOLOGY 2023; 145:104713. [PMID: 37085020 DOI: 10.1016/j.dci.2023.104713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 04/17/2023] [Accepted: 04/17/2023] [Indexed: 05/03/2023]
Abstract
Methyltransferase like-16 (METTL16) is an m6A RNA methylation transferase that is known to methylate U6 snRNA and pre-mRNA of S-adenosylmethionine synthase but has been poorly studied in fish. In this study, METTL16 was identified in miiuy croaker (Miichthys miiuy). We first performed bioinformatics analysis of the miiuy croaker METTL16 (mmiMETTL16). MmiMETTL16 and other vertebrates METTL16 have a relatively conserved MTD structural domain and gene structure, suggesting that their methylase activity may also be conservative. In healthy miiuy croaker, mmiMETTL16 was commonly expressed in the tested tissues. Expression of mmiMETTL16 in kidney, liver, and spleen tissues was significantly increased after poly(I:C) stimulation. Consistently, mmiMETTL16 was sensitive to poly(I:C) stimulation in miiuy croaker kidney cell (MKC), suggesting that METTL16 might participate in antiviral immunity. For further functional experiments, immunofluorescence of mmiMETTL16 presents in the nucleus in kidney cells. In addition, the overexpression of mmiMETTL16 could significantly increase the overall m6A level of MKC cells, which shows that the function of METTL16 as methyltransferase is conservative in miiuy croaker. Last, mmiMETTL16 can inhibit the expression of TNF-α, IFN-1, Mx1, and ISG15, suggesting that mmiMETTL16 can suppress the immune response caused by viral stimulation. In summary, studies on mmiMETTL16 will contribute to future studies on the role of METTL16 and potential mechanisms of the m6A regulation network in the teleost immune system.
Collapse
Affiliation(s)
- Yan Zhao
- Laboratory of Fish Molecular Immunology, College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, China
| | - Qiang Luo
- Laboratory of Fish Molecular Immunology, College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, China
| | - Wansu Wang
- Laboratory of Fish Molecular Immunology, College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, China
| | - Shang Geng
- Laboratory of Fish Molecular Immunology, College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, China
| | - Yuena Sun
- Laboratory of Fish Molecular Immunology, College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, China; National Pathogen Collection Center for Aquatic Animals, Shanghai Ocean University, China; Key Laboratory of Freshwater Aquatic Genetic Resources, Ministry of Agriculture and Rural Affairs, Shanghai Ocean University, China.
| | - Tianjun Xu
- Laboratory of Fish Molecular Immunology, College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, China; Laboratory of Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.
| |
Collapse
|
49
|
Deng X, Qing Y, Horne D, Huang H, Chen J. The roles and implications of RNA m 6A modification in cancer. Nat Rev Clin Oncol 2023; 20:507-526. [PMID: 37221357 DOI: 10.1038/s41571-023-00774-x] [Citation(s) in RCA: 161] [Impact Index Per Article: 80.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/25/2023] [Indexed: 05/25/2023]
Abstract
N6-Methyladenosine (m6A), the most prevalent internal modification in eukaryotic mRNA, has been extensively and increasingly studied over the past decade. Dysregulation of RNA m6A modification and its associated machinery, including writers, erasers and readers, is frequently observed in various cancer types, and the dysregulation profiles might serve as diagnostic, prognostic and/or predictive biomarkers. Dysregulated m6A modifiers have been shown to function as oncoproteins or tumour suppressors with essential roles in cancer initiation, progression, metastasis, metabolism, therapy resistance and immune evasion as well as in cancer stem cell self-renewal and the tumour microenvironment, highlighting the therapeutic potential of targeting the dysregulated m6A machinery for cancer treatment. In this Review, we discuss the mechanisms by which m6A modifiers determine the fate of target RNAs and thereby influence protein expression, molecular pathways and cell phenotypes. We also describe the state-of-the-art methodologies for mapping global m6A epitranscriptomes in cancer. We further summarize discoveries regarding the dysregulation of m6A modifiers and modifications in cancer, their pathological roles, and the underlying molecular mechanisms. Finally, we discuss m6A-related prognostic and predictive molecular biomarkers in cancer as well as the development of small-molecule inhibitors targeting oncogenic m6A modifiers and their activity in preclinical models.
Collapse
Affiliation(s)
- Xiaolan Deng
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, USA.
| | - Ying Qing
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, USA
| | - David Horne
- City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA, USA
- Department of Molecular Medicine, Beckman Research Institute of City of Hope, Duarte, CA, USA
| | - Huilin Huang
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
| | - Jianjun Chen
- Department of Systems Biology, Beckman Research Institute of City of Hope, Monrovia, CA, USA.
- City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA, USA.
- Gehr Family Center for Leukemia Research & City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA, USA.
| |
Collapse
|
50
|
Abstract
Over the past decade, mRNA modifications have emerged as important regulators of gene expression control in cells. Fueled in large part by the development of tools for detecting RNA modifications transcriptome wide, researchers have uncovered a diverse epitranscriptome that serves as an additional layer of gene regulation beyond simple RNA sequence. Here, we review the proteins that write, read, and erase these marks, with a particular focus on the most abundant internal modification, N6-methyladenosine (m6A). We first describe the discovery of the key enzymes that deposit and remove m6A and other modifications and discuss how our understanding of these proteins has shaped our views of modification dynamics. We then review current models for the function of m6A reader proteins and how our knowledge of these proteins has evolved. Finally, we highlight important future directions for the field and discuss key questions that remain unanswered.
Collapse
Affiliation(s)
- Mathieu N Flamand
- Department of Biochemistry, Duke University School of Medicine, Durham, North Carolina, USA;
| | - Matthew Tegowski
- Department of Biochemistry, Duke University School of Medicine, Durham, North Carolina, USA;
| | - Kate D Meyer
- Department of Biochemistry, Duke University School of Medicine, Durham, North Carolina, USA;
- Department of Neurobiology, Duke University School of Medicine, Durham, North Carolina, USA
| |
Collapse
|