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A robust method for measuring aminoacylation through tRNA-Seq.

Kristian DavidsenLucas B Sullivan
Published in: bioRxiv : the preprint server for biology (2023)
Current methods to quantify the fraction of aminoacylated tRNAs, also known as the tRNA charge, are limited by issues with either low throughput, precision, and/or accuracy. Here, we present an optimized charge tRNA-Seq method that combines previous developments with newly described approaches to establish a protocol for precise and accurate tRNA charge measurements. We verify that this protocol provides robust quantification of tRNA aminoacylation and we provide an end-to-end method that scales to hundreds of samples including software for data processing. Additionally, we show that this method supports measurements of relative tRNA expression levels and can be used to infer tRNA modifications through reverse transcription misincorporations, thereby supporting multipurpose applications in tRNA biology.
Keyphrases
  • randomized controlled trial
  • single cell
  • transcription factor
  • mass spectrometry
  • electronic health record
  • artificial intelligence
  • big data
  • electron transfer