ArticleScientific reports2021
Integrated genomic analysis reveals regulatory pathways and dynamic landscapes of the tRNA transcriptome.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- tRNA-derived fragments: mechanism of gene regulation and clinical application in lung cancer.Cellular oncology (Dordrecht, Netherlands) · 2024Pooled it
- TRMT1-mediated tRNA mCell death & disease · 2026Article
- High-fidelity and differential nonsense suppression in live cells and a frontotemporal dementia allele with human transfer RNAs.Nucleic acids research · 2025Article
- Changes in the Repertoire of tRNA-Derived Fragments in Different Blood Cell Populations.Life (Basel, Switzerland) · 2024Article
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Authors and funding
17 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
tRNAs and tRNA-derived RNA fragments (tRFs) play various roles in many cellular processes outside of protein synthesis. However, comprehensive investigations of tRNA/tRF regulation are rare. In this study, we used new algorithms to extensively analyze the publicly available data from 1332 ChIP-Seq and 42 small-RNA-Seq experiments in human cell lines and tissues to investigate the transcriptional and posttranscriptional regulatory mechanisms of tRNAs. We found that histone acetylation, cAMP, and pluripotency pathways play important roles in the regulation of the tRNA gene transcription in a cell-specific manner. Analysis of RNA-Seq data identified 950 high-confidence tRFs, and the results suggested that tRNA pools are dramatically distinct across the samples in terms of expression profiles and tRF composition. The mismatch analysis identified new potential modification sites and specific modification patterns in tRNA families. The results also show that RNA library preparation technologies have a considerable impact on tRNA profiling and need to be optimized in the future.
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