tModBase v2.0: an expanded database of tRNA modifications with an AI-powered assistant
- 1School of Agriculture and Biotechnology, Sun Yat-Sen University Shenzhen Campus , Shenzhen 518107 ,
- 2MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, Guangdong Provincial Key Laboratory of Plant Stress, Innovation Center for Evolutionary Synthetic Biology, School of Life Sciences, Sun Yat-Sen University , Guangzhou 510275 ,
Abstract
Chemical modifications of transfer RNAs (tRNAs) are crucial for tRNA stability, codon decoding, translational fidelity, and tRNA-derived small RNA (tsRNA) biogenesis. Changes in these modifications are associated with stress responses, physiological regulation, and human disease, underscoring the need to integrate modification information with experimental evidence and biological context. We previously established tModBase, a web resource to organize and explore tRNA modification-related data. Its first release integrated modification sites, high-throughput sequencing-derived signals, and condition-dependent changes. Since then, tRNA profiling has expanded through modification-specific and direct RNA sequencing strategies, with rapidly growing datasets across species and conditions. Here, we present tModBase v2.0 (http://www.tmodbase2.com/), containing 528 datasets across 23 species, 40 sequencing and library-preparation methods, and 42 modification types. It includes 68 third-generation and 210 modification-specific sequencing datasets, extending coverage of direct-RNA and modification-specific approaches. tModBase v2.0 further integrates sequencing-derived signals, condition-dependent information, and biological annotations linking modifications with enzymes, genetic variants, tsRNAs, diseases, and expression profiles. The LLM- and retrieval-augmented generation-powered assistant tModBot enables natural-language exploration across database modules while grounding responses in retrieved tModBase evidence. tModBase v2.0 therefore provides an expanded resource for investigating the diversity, dynamics, and biological context of tRNA modifications.
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BibTeX
@article{tan2026tmodbase,
title = {{tModBase v2.0: an expanded database of tRNA modifications with an AI-powered assistant}},
author = {Yi Tan and Ni-Na Xin and Tian Wu and Qing- Yu Tan and Xuan-Ni Zheng and Zi-Man Chen and Xiao Feng and Liang-Hu Qu and Ling-Ling Zheng},
journal = {Nucleic Acids Research},
year = {2026},
month = nov,
doi = {10.1093/nar/gkag1092},
url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1092/9006190},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - tModBase v2.0: an expanded database of tRNA modifications with an AI-powered assistant
AU - Yi Tan
AU - Ni-Na Xin
AU - Tian Wu
AU - Qing- Yu Tan
AU - Xuan-Ni Zheng
AU - Zi-Man Chen
AU - Xiao Feng
AU - Liang-Hu Qu
AU - Ling-Ling Zheng
PY - 2026
DA - 2026/11/02
JO - Nucleic Acids Research
DO - 10.1093/nar/gkag1092
UR - https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1092/9006190
AB - Chemical modifications of transfer RNAs (tRNAs) are crucial for tRNA stability, codon decoding, translational fidelity, and tRNA-derived small RNA (tsRNA) biogenesis. Changes in these modifications are associated with stress responses, physiological regulation, and human disease, underscoring the need to integrate modification information with experimental evidence and biological context. We previously established tModBase, a web resource to organize and explore tRNA modification-related data. Its first release integrated modification sites, high-throughput sequencing-derived signals, and condition-dependent changes. Since then, tRNA profiling has expanded through modification-specific and direct RNA sequencing strategies, with rapidly growing datasets across species and conditions. Here, we present tModBase v2.0 (http://www.tmodbase2.com/), containing 528 datasets across 23 species, 40 sequencing and library-preparation methods, and 42 modification types. It includes 68 third-generation and 210 modification-specific sequencing datasets, extending coverage of direct-RNA and modification-specific approaches. tModBase v2.0 further integrates sequencing-derived signals, condition-dependent information, and biological annotations linking modifications with enzymes, genetic variants, tsRNAs, diseases, and expression profiles. The LLM- and retrieval-augmented generation-powered assistant tModBot enables natural-language exploration across database modules while grounding responses in retrieved tModBase evidence. tModBase v2.0 therefore provides an expanded resource for investigating the diversity, dynamics, and biological context of tRNA modifications.
SN - 0305-1048
SN - 1362-4962
ER -