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Updated: Oct 14, 2025
Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
Published on: August 4, 2016
tsRFun: a comprehensive platform for decoding human tsRNA expression, functions and prognostic value by
Jun-Hao Wang1,2, Wen-Xin Chen1, Shi-Qiang Mei1
1MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, Sun Yat-sen University, Guangzhou 510275, P.R. China.
This study introduces tsRFun, a platform for researching tRNA-derived small RNAs (tsRNAs). It analyzes tsRNA expression, predicts targets, and builds interaction networks, aiding disease mechanism investigation.
Area of Science:
- Molecular Biology
- Bioinformatics
- Genomics
Background:
- tRNA-derived small RNAs (tsRNAs) are emerging regulatory molecules with incompletely understood functions in cellular processes and disease.
- Limited knowledge exists regarding the precise mechanisms of tsRNA action and their involvement in disease pathogenesis.
Purpose of the Study:
- To develop a comprehensive platform, tsRFun, for facilitating tsRNA research.
- To integrate multi-omics data for a deeper understanding of tsRNA functions and roles in diseases.
Main Methods:
- Integrated transcriptome, epitranscriptome, and targetome data.
- Developed novel computational tools for tsRNA analysis.
- Utilized high-throughput sequencing data (CLASH/CLEAR, CLIP) for target identification.
Main Results:
- Established tsRFun, a web-based platform (http://rna.sysu.edu.cn/tsRFun/ or http://biomed.nscc-gz.cn/DB/tsRFun/).
- Evaluated tsRNA expression profiles and prognostic values across 32 cancer types.
- Identified tsRNA targets and constructed interaction networks involving tsRNAs, microRNAs, and mRNAs.
- Provided online tools for tsRNA identification, target prediction, and functional enrichment analysis.
Conclusions:
- tsRFun serves as a valuable resource for tsRNA research.
- The platform offers integrated data and analytical tools to advance the investigation of tsRNA functions and disease relevance.
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