Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, United States.
Molecular and Cellular Biology Program, University of Washington, Seattle, United States.
Elife. 2024 Jul 30;12:RP91554. doi: 10.7554/eLife.91554.
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 transfer RNA sequencing (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.
目前用于定量氨酰化 tRNA 分数(也称为 tRNA 电荷)的方法受到通量低、精度和/或准确性等问题的限制。在这里,我们提出了一种经过优化的电荷转移 RNA 测序(tRNA-Seq)方法,该方法结合了以前的发展和新描述的方法,建立了一个精确和准确测量 tRNA 电荷的方案。我们验证了该方案能够提供可靠的 tRNA 氨酰化定量,并且提供了一种端到端的方法,可以扩展到数百个样本,包括用于数据处理的软件。此外,我们还表明,该方法支持相对 tRNA 表达水平的测量,并可用于通过逆转录错误掺入推断 tRNA 修饰,从而支持 tRNA 生物学的多种用途。