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tModBase: deciphering the landscape of tRNA modifications and their dynamic changes from epitranscriptome data
tRNA molecules contain dense, abundant modifications that affect tRNA structure, stability, mRNA decoding and tsRNA formation. tRNA modifications and related enzymes are responsive to environmental cues and are associated with a range of physiological and pathological processes. However, there is a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825477/ https://www.ncbi.nlm.nih.gov/pubmed/36408909 http://dx.doi.org/10.1093/nar/gkac1087 |
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author | Lei, Hao-Tian Wang, Zhang-Hao Li, Bin Sun, Yang Mei, Shi-Qiang Yang, Jian-Hua Qu, Liang-Hu Zheng, Ling-Ling |
author_facet | Lei, Hao-Tian Wang, Zhang-Hao Li, Bin Sun, Yang Mei, Shi-Qiang Yang, Jian-Hua Qu, Liang-Hu Zheng, Ling-Ling |
author_sort | Lei, Hao-Tian |
collection | PubMed |
description | tRNA molecules contain dense, abundant modifications that affect tRNA structure, stability, mRNA decoding and tsRNA formation. tRNA modifications and related enzymes are responsive to environmental cues and are associated with a range of physiological and pathological processes. However, there is a lack of resources that can be used to mine and analyse these dynamically changing tRNA modifications. In this study, we established tModBase (https://www.tmodbase.com/) for deciphering the landscape of tRNA modification profiles from epitranscriptome data. We analysed 103 datasets generated with second- and third-generation sequencing technologies and illustrated the misincorporation and termination signals of tRNA modification sites in ten species. We thus systematically demonstrate the modification profiles across different tissues/cell lines and summarize the characteristics of tRNA-associated human diseases. By integrating transcriptome data from 32 cancers, we developed novel tools for analysing the relationships between tRNA modifications and RNA modification enzymes, the expression of 1442 tRNA-derived small RNAs (tsRNAs), and 654 DNA variations. Our database will provide new insights into the features of tRNA modifications and the biological pathways in which they participate. |
format | Online Article Text |
id | pubmed-9825477 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98254772023-01-10 tModBase: deciphering the landscape of tRNA modifications and their dynamic changes from epitranscriptome data Lei, Hao-Tian Wang, Zhang-Hao Li, Bin Sun, Yang Mei, Shi-Qiang Yang, Jian-Hua Qu, Liang-Hu Zheng, Ling-Ling Nucleic Acids Res Database Issue tRNA molecules contain dense, abundant modifications that affect tRNA structure, stability, mRNA decoding and tsRNA formation. tRNA modifications and related enzymes are responsive to environmental cues and are associated with a range of physiological and pathological processes. However, there is a lack of resources that can be used to mine and analyse these dynamically changing tRNA modifications. In this study, we established tModBase (https://www.tmodbase.com/) for deciphering the landscape of tRNA modification profiles from epitranscriptome data. We analysed 103 datasets generated with second- and third-generation sequencing technologies and illustrated the misincorporation and termination signals of tRNA modification sites in ten species. We thus systematically demonstrate the modification profiles across different tissues/cell lines and summarize the characteristics of tRNA-associated human diseases. By integrating transcriptome data from 32 cancers, we developed novel tools for analysing the relationships between tRNA modifications and RNA modification enzymes, the expression of 1442 tRNA-derived small RNAs (tsRNAs), and 654 DNA variations. Our database will provide new insights into the features of tRNA modifications and the biological pathways in which they participate. Oxford University Press 2022-11-21 /pmc/articles/PMC9825477/ /pubmed/36408909 http://dx.doi.org/10.1093/nar/gkac1087 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Database Issue Lei, Hao-Tian Wang, Zhang-Hao Li, Bin Sun, Yang Mei, Shi-Qiang Yang, Jian-Hua Qu, Liang-Hu Zheng, Ling-Ling tModBase: deciphering the landscape of tRNA modifications and their dynamic changes from epitranscriptome data |
title | tModBase: deciphering the landscape of tRNA modifications and their dynamic changes from epitranscriptome data |
title_full | tModBase: deciphering the landscape of tRNA modifications and their dynamic changes from epitranscriptome data |
title_fullStr | tModBase: deciphering the landscape of tRNA modifications and their dynamic changes from epitranscriptome data |
title_full_unstemmed | tModBase: deciphering the landscape of tRNA modifications and their dynamic changes from epitranscriptome data |
title_short | tModBase: deciphering the landscape of tRNA modifications and their dynamic changes from epitranscriptome data |
title_sort | tmodbase: deciphering the landscape of trna modifications and their dynamic changes from epitranscriptome data |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825477/ https://www.ncbi.nlm.nih.gov/pubmed/36408909 http://dx.doi.org/10.1093/nar/gkac1087 |
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