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Related Concept Videos

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Related Experiment Video

Updated: Aug 9, 2025

Translating Ribosome Affinity Purification TRAP to Investigate Arabidopsis thaliana Root Development at a Cell Type-Specific Scale
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ALL-tRNAseq enables robust tRNA profiling in tissue samples.

Chantal Scheepbouwer1,2,3, Ernesto Aparicio-Puerta4, Cristina Gomez-Martin3

  • 1Department of Neurosurgery, Cancer Center Amsterdam, Amsterdam University Medical Center (UMC) location Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands; c.scheepbouwer@amsterdamumc.nl d.koppers@math.leidenuniv.nl.

Genes & Development
|February 22, 2023
PubMed
Summary

A new method, ALL-tRNAseq, accurately profiles transfer RNA (tRNA) expression in tissues. This approach improves cancer signature classification, even in fragmented samples, advancing translational research.

Keywords:
cancerhigh-throughput sequencingtissue samplestransfer RNA

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Area of Science:

  • Molecular Biology
  • Genomics
  • Cancer Research

Background:

  • Transfer RNAs (tRNAs) are crucial for protein synthesis, and their altered levels are linked to cancer progression.
  • Existing sequencing methods struggle to accurately quantify tRNAs due to their structure and modifications, especially in clinical tissue samples with variable RNA quality.

Purpose of the Study:

  • To develop a robust sequencing protocol for accurately assessing tRNA expression and fragmentation in diverse biological samples.
  • To evaluate the utility of the new protocol for classifying oncogenic signatures in cancer tissues.

Main Methods:

  • Developed ALL-tRNAseq, integrating MarathonRT, RNA demethylation, and a randomized adapter ligation strategy.
  • Applied the method to cell lines and clinical tissue samples, including glioblastoma and diffuse large B-cell lymphoma.
  • Assessed tRNA expression, fragmentation levels, and their impact on sample integrity and classification.

Main Results:

  • ALL-tRNAseq provides a robust assessment of tRNA expression, overcoming challenges posed by RNA structure and modifications.
  • Incorporation of tRNA fragment analysis improved tRNA profiling, particularly for fragmented tissue samples.
  • The method enhanced the classification of oncogenic signatures in glioblastoma and diffuse large B-cell lymphoma tissues.

Conclusions:

  • ALL-tRNAseq offers a reliable method for tRNA profiling in both cell lines and clinical tissues, improving accuracy with fragmented samples.
  • This technique is valuable for translational research, aiding in the classification of cancer subtypes and potentially informing therapeutic strategies.