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Wang X, Zhang Y, Chen K, Liang Z, Ma J, Xia R, de Magalhães JP, Rigden DJ, Meng J, Song B. m7GHub V2.0: an updated database for decoding the N7-methylguanosine (m7G) epitranscriptome. Nucleic Acids Res 2024; 52:D203-D212. [PMID: 37811871 PMCID: PMC10767970 DOI: 10.1093/nar/gkad789] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 08/18/2023] [Accepted: 09/18/2023] [Indexed: 10/10/2023] Open
Abstract
With recent progress in mapping N7-methylguanosine (m7G) RNA methylation sites, tens of thousands of experimentally validated m7G sites have been discovered in various species, shedding light on the significant role of m7G modification in regulating numerous biological processes including disease pathogenesis. An integrated resource that enables the sharing, annotation and customized analysis of m7G data will greatly facilitate m7G studies under various physiological contexts. We previously developed the m7GHub database to host mRNA m7G sites identified in the human transcriptome. Here, we present m7GHub v.2.0, an updated resource for a comprehensive collection of m7G modifications in various types of RNA across multiple species: an m7GDB database containing 430 898 putative m7G sites identified in 23 species, collected from both widely applied next-generation sequencing (NGS) and the emerging Oxford Nanopore direct RNA sequencing (ONT) techniques; an m7GDiseaseDB hosting 156 206 m7G-associated variants (involving addition or removal of an m7G site), including 3238 disease-relevant m7G-SNPs that may function through epitranscriptome disturbance; and two enhanced analysis modules to perform interactive analyses on the collections of m7G sites (m7GFinder) and functional variants (m7GSNPer). We expect that m7Ghub v.2.0 should serve as a valuable centralized resource for studying m7G modification. It is freely accessible at: www.rnamd.org/m7GHub2.
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Affiliation(s)
- Xuan Wang
- Department of Public Health, School of Medicine & Holistic Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
| | - Yuxin Zhang
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L7 8TX, Liverpool, UK
| | - Kunqi Chen
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350004, China
| | - Zhanmin Liang
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
| | - Jiongming Ma
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L7 8TX, Liverpool, UK
| | - Rong Xia
- Department of Financial and Actuarial Mathematics, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
| | | | - Daniel J Rigden
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L7 8TX, Liverpool, UK
| | - Jia Meng
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L7 8TX, Liverpool, UK
- AI University Research Centre, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China
| | - Bowen Song
- Department of Public Health, School of Medicine & Holistic Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China
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de Magalhães JP, Abidi Z, dos Santos GA, Avelar RA, Barardo D, Chatsirisupachai K, Clark P, De-Souza EA, Johnson EJ, Lopes I, Novoa G, Senez L, Talay A, Thornton D, To P. Human Ageing Genomic Resources: updates on key databases in ageing research. Nucleic Acids Res 2024; 52:D900-D908. [PMID: 37933854 PMCID: PMC10767973 DOI: 10.1093/nar/gkad927] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 10/06/2023] [Accepted: 10/09/2023] [Indexed: 11/08/2023] Open
Abstract
Ageing is a complex and multifactorial process. For two decades, the Human Ageing Genomic Resources (HAGR) have aided researchers in the study of various aspects of ageing and its manipulation. Here, we present the key features and recent enhancements of these resources, focusing on its six main databases. One database, GenAge, focuses on genes related to ageing, featuring 307 genes linked to human ageing and 2205 genes associated with longevity and ageing in model organisms. AnAge focuses on ageing, longevity, and life-history across animal species, containing data on 4645 species. DrugAge includes information about 1097 longevity drugs and compounds in model organisms such as mice, rats, flies, worms and yeast. GenDR provides a list of 214 genes associated with the life-extending benefits of dietary restriction in model organisms. CellAge contains a catalogue of 866 genes associated with cellular senescence. The LongevityMap serves as a repository for genetic variants associated with human longevity, encompassing 3144 variants pertaining to 884 genes. Additionally, HAGR provides various tools as well as gene expression signatures of ageing, dietary restriction, and replicative senescence based on meta-analyses. Our databases are integrated, regularly updated, and manually curated by experts. HAGR is freely available online (https://genomics.senescence.info/).
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Affiliation(s)
- João Pedro de Magalhães
- Genomics of Ageing and Rejuvenation Lab, Institute of Inflammation and Ageing, University of Birmingham, Birmingham B15 2WB, UK
| | - Zoya Abidi
- Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L7 8TX, UK
| | - Gabriel Arantes dos Santos
- Genomics of Ageing and Rejuvenation Lab, Institute of Inflammation and Ageing, University of Birmingham, Birmingham B15 2WB, UK
| | - Roberto A Avelar
- Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L7 8TX, UK
| | - Diogo Barardo
- NOVOS Labs, 100 Park Avenue, 16th Fl, New York, NY 10017, USA
| | - Kasit Chatsirisupachai
- Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L7 8TX, UK
| | - Peter Clark
- Genomics of Ageing and Rejuvenation Lab, Institute of Inflammation and Ageing, University of Birmingham, Birmingham B15 2WB, UK
| | - Evandro A De-Souza
- Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas, Campinas 13083-970, SP, Brazil
| | - Emily J Johnson
- Computational Biology Facility, Liverpool Shared Research Facilities, Faculty of Health and Life Sciences, University of Liverpool, Liverpool L69 7ZB, UK
| | - Inês Lopes
- Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L7 8TX, UK
| | - Guy Novoa
- Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L7 8TX, UK
| | - Ludovic Senez
- Genomics of Ageing and Rejuvenation Lab, Institute of Inflammation and Ageing, University of Birmingham, Birmingham B15 2WB, UK
| | - Angelo Talay
- Genomics of Ageing and Rejuvenation Lab, Institute of Inflammation and Ageing, University of Birmingham, Birmingham B15 2WB, UK
| | - Daniel Thornton
- Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L7 8TX, UK
| | - Paul Ka Po To
- Genomics of Ageing and Rejuvenation Lab, Institute of Inflammation and Ageing, University of Birmingham, Birmingham B15 2WB, UK
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Bennett DF, Goyala A, Statzer C, Beckett CW, Tyshkovskiy A, Gladyshev VN, Ewald CY, de Magalhães JP. Rilmenidine extends lifespan and healthspan in Caenorhabditis elegans via a nischarin I1-imidazoline receptor. Aging Cell 2023; 22:e13774. [PMID: 36670049 PMCID: PMC9924948 DOI: 10.1111/acel.13774] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 12/02/2022] [Accepted: 12/09/2022] [Indexed: 01/22/2023] Open
Abstract
Repurposing drugs capable of extending lifespan and health span has a huge untapped potential in translational geroscience. Here, we searched for known compounds that elicit a similar gene expression signature to caloric restriction and identified rilmenidine, an I1-imidazoline receptor agonist and prescription medication for the treatment of hypertension. We then show that treating Caenorhabditis elegans with rilmenidine at young and older ages increases lifespan. We also demonstrate that the stress-resilience, health span, and lifespan benefits of rilmenidine treatment in C. elegans are mediated by the I1-imidazoline receptor nish-1, implicating this receptor as a potential longevity target. Consistent with the shared caloric-restriction-mimicking gene signature, supplementing rilmenidine to calorically restricted C. elegans, genetic reduction of TORC1 function, or rapamycin treatment did not further increase lifespan. The rilmenidine-induced longevity required the transcription factors FOXO/DAF-16 and NRF1,2,3/SKN-1. Furthermore, we find that autophagy, but not AMPK signaling, was needed for rilmenidine-induced longevity. Moreover, transcriptional changes similar to caloric restriction were observed in liver and kidney tissues in mice treated with rilmenidine. Together, these results reveal a geroprotective and potential caloric restriction mimetic effect by rilmenidine that warrant fresh lines of inquiry into this compound.
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Affiliation(s)
- Dominic F. Bennett
- Integrative Genomics of Ageing GroupInstitute of Ageing and Chronic Disease, University of LiverpoolLiverpoolUK
| | - Anita Goyala
- Department of Health Sciences and Technology, Laboratory of Extracellular Matrix RegenerationInstitute of Translational Medicine, ETH ZürichSchwerzenbachSwitzerland
| | - Cyril Statzer
- Department of Health Sciences and Technology, Laboratory of Extracellular Matrix RegenerationInstitute of Translational Medicine, ETH ZürichSchwerzenbachSwitzerland
| | - Charles W. Beckett
- Integrative Genomics of Ageing GroupInstitute of Ageing and Chronic Disease, University of LiverpoolLiverpoolUK
| | - Alexander Tyshkovskiy
- Division of Genetics, Department of MedicineBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA,Belozersky Institute of Physico‐Chemical BiologyMoscow State UniversityMoscowRussia
| | - Vadim N. Gladyshev
- Division of Genetics, Department of MedicineBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Collin Y. Ewald
- Department of Health Sciences and Technology, Laboratory of Extracellular Matrix RegenerationInstitute of Translational Medicine, ETH ZürichSchwerzenbachSwitzerland
| | - João Pedro de Magalhães
- Integrative Genomics of Ageing GroupInstitute of Ageing and Chronic Disease, University of LiverpoolLiverpoolUK,Present address:
Institute of Inflammation and AgeingUniversity of Birmingham, Queen Elizabeth HospitalBirminghamUK
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Raina P, Guinea R, Chatsirisupachai K, Lopes I, Farooq Z, Guinea C, Solyom CA, de Magalhães JP. GeneFriends: gene co-expression databases and tools for humans and model organisms. Nucleic Acids Res 2022; 51:D145-D158. [PMID: 36454018 PMCID: PMC9825523 DOI: 10.1093/nar/gkac1031] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 10/17/2022] [Accepted: 10/21/2022] [Indexed: 12/05/2022] Open
Abstract
Gene co-expression analysis has emerged as a powerful method to provide insights into gene function and regulation. The rapid growth of publicly available RNA-sequencing (RNA-seq) data has created opportunities for researchers to employ this abundant data to help decipher the complexity and biology of genomes. Co-expression networks have proven effective for inferring the relationship between the genes, for gene prioritization and for assigning function to poorly annotated genes based on their co-expressed partners. To facilitate such analyses we created previously an online co-expression tool for humans and mice entitled GeneFriends. To continue providing a valuable tool to the scientific community, we have now updated the GeneFriends database and website. Here, we present the new version of GeneFriends, which includes gene and transcript co-expression networks based on RNA-seq data from 46 475 human and 34 322 mouse samples. The new database also encompasses tissue-specific gene co-expression networks for 20 human and 21 mouse tissues, dataset-specific gene co-expression maps based on TCGA and GTEx projects and gene co-expression networks for additional seven model organisms (fruit fly, zebrafish, worm, rat, yeast, cow and chicken). GeneFriends is freely available at http://www.genefriends.org/.
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Affiliation(s)
- Priyanka Raina
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
| | - Rodrigo Guinea
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
| | - Kasit Chatsirisupachai
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
| | - Inês Lopes
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
| | - Zoya Farooq
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
| | - Cristina Guinea
- UCAL - Universidad de Ciencias y Artes de América Latina, Faculty of Design, Lima 15026, Perú
| | - Csaba-Attila Solyom
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
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Zhang Y, Jiang J, Ma J, Wei Z, Wang Y, Song B, Meng J, Jia G, de Magalhães JP, Rigden D, Hang D, Chen K. DirectRMDB: a database of post-transcriptional RNA modifications unveiled from direct RNA sequencing technology. Nucleic Acids Res 2022; 51:D106-D116. [PMID: 36382409 PMCID: PMC9825532 DOI: 10.1093/nar/gkac1061] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 10/20/2022] [Accepted: 10/25/2022] [Indexed: 11/17/2022] Open
Abstract
With advanced technologies to map RNA modifications, our understanding of them has been revolutionized, and they are seen to be far more widespread and important than previously thought. Current next-generation sequencing (NGS)-based modification profiling methods are blind to RNA modifications and thus require selective chemical treatment or antibody immunoprecipitation methods for particular modification types. They also face the problem of short read length, isoform ambiguities, biases and artifacts. Direct RNA sequencing (DRS) technologies, commercialized by Oxford Nanopore Technologies (ONT), enable the direct interrogation of any given modification present in individual transcripts and promise to address the limitations of previous NGS-based methods. Here, we present the first ONT-based database of quantitative RNA modification profiles, DirectRMDB, which includes 16 types of modification and a total of 904,712 modification sites in 25 species identified from 39 independent studies. In addition to standard functions adopted by existing databases, such as gene annotations and post-transcriptional association analysis, we provide a fresh view of RNA modifications, which enables exploration of the epitranscriptome in an isoform-specific manner. The DirectRMDB database is freely available at: http://www.rnamd.org/directRMDB/.
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Affiliation(s)
| | | | | | - Zhen Wei
- Correspondence may also be addressed to Zhen Wei.
| | - Yue Wang
- Department of Mathematical Sciences, Xi’anJiaotong-Liverpool University, Suzhou, Jiangsu 215123, China,Department of Computer Science, University of Liverpool, L69 7ZB, Liverpool, UK
| | - Bowen Song
- Department of Mathematical Sciences, Xi’anJiaotong-Liverpool University, Suzhou, Jiangsu 215123, China,Institute of Systems, Molecular and Integrative Biology, Xi’anJiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
| | - Jia Meng
- Department of Biological Sciences, Xi’anJiaotong-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, Xi’anJiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
| | - Guifang Jia
- Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - João Pedro de Magalhães
- Institute of Life Course and Medical Sciences, Xi’anJiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
| | - Daniel J Rigden
- Institute of Systems, Molecular and Integrative Biology, Xi’anJiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
| | - Daiyun Hang
- Correspondence may also be addressed to Daiyun Hang.
| | - Kunqi Chen
- To whom correspondence should be addressed. Tel: +86 0591 22862299;
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Song B, Wang X, Liang Z, Ma J, Huang D, Wang Y, de Magalhães JP, Rigden DJ, Meng J, Liu G, Chen K, Wei Z. RMDisease V2.0: an updated database of genetic variants that affect RNA modifications with disease and trait implication. Nucleic Acids Res 2022; 51:D1388-D1396. [PMID: 36062570 PMCID: PMC9825452 DOI: 10.1093/nar/gkac750] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/02/2022] [Accepted: 08/24/2022] [Indexed: 01/30/2023] Open
Abstract
Recent advances in epitranscriptomics have unveiled functional associations between RNA modifications (RMs) and multiple human diseases, but distinguishing the functional or disease-related single nucleotide variants (SNVs) from the majority of 'silent' variants remains a major challenge. We previously developed the RMDisease database for unveiling the association between genetic variants and RMs concerning human disease pathogenesis. In this work, we present RMDisease v2.0, an updated database with expanded coverage. Using deep learning models and from 873 819 experimentally validated RM sites, we identified a total of 1 366 252 RM-associated variants that may affect (add or remove an RM site) 16 different types of RNA modifications (m6A, m5C, m1A, m5U, Ψ, m6Am, m7G, A-to-I, ac4C, Am, Cm, Um, Gm, hm5C, D and f5C) in 20 organisms (human, mouse, rat, zebrafish, maize, fruit fly, yeast, fission yeast, Arabidopsis, rice, chicken, goat, sheep, pig, cow, rhesus monkey, tomato, chimpanzee, green monkey and SARS-CoV-2). Among them, 14 749 disease- and 2441 trait-associated genetic variants may function via the perturbation of epitranscriptomic markers. RMDisease v2.0 should serve as a useful resource for studying the genetic drivers of phenotypes that lie within the epitranscriptome layer circuitry, and is freely accessible at: www.rnamd.org/rmdisease2.
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Affiliation(s)
| | | | | | | | - Daiyun Huang
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China,Department of Computer Science, University of Liverpool, Liverpool L7 8TX, UK
| | - Yue Wang
- Department of Mathematical Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China,Department of Computer Science, University of Liverpool, Liverpool L7 8TX, UK
| | - João Pedro de Magalhães
- Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
| | - Daniel J Rigden
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L7 8TX, UK
| | - Jia Meng
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China,Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L7 8TX, UK,AI University Research Centre, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
| | - Gang Liu
- Correspondence may also be addressed to Gang Liu.
| | - Kunqi Chen
- Correspondence may also be addressed to Kunqi Chen.
| | - Zhen Wei
- To whom correspondence should be addressed.
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