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A robust method for measuring aminoacylation through tRNA-Seq
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 es...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10418082/ https://www.ncbi.nlm.nih.gov/pubmed/37577502 http://dx.doi.org/10.1101/2023.07.31.551363 |
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author | Davidsen, Kristian Sullivan, Lucas B |
author_facet | Davidsen, Kristian Sullivan, Lucas B |
author_sort | Davidsen, Kristian |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10418082 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-104180822023-08-12 A robust method for measuring aminoacylation through tRNA-Seq Davidsen, Kristian Sullivan, Lucas B bioRxiv Article 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. Cold Spring Harbor Laboratory 2023-08-01 /pmc/articles/PMC10418082/ /pubmed/37577502 http://dx.doi.org/10.1101/2023.07.31.551363 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Davidsen, Kristian Sullivan, Lucas B A robust method for measuring aminoacylation through tRNA-Seq |
title | A robust method for measuring aminoacylation through tRNA-Seq |
title_full | A robust method for measuring aminoacylation through tRNA-Seq |
title_fullStr | A robust method for measuring aminoacylation through tRNA-Seq |
title_full_unstemmed | A robust method for measuring aminoacylation through tRNA-Seq |
title_short | A robust method for measuring aminoacylation through tRNA-Seq |
title_sort | robust method for measuring aminoacylation through trna-seq |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10418082/ https://www.ncbi.nlm.nih.gov/pubmed/37577502 http://dx.doi.org/10.1101/2023.07.31.551363 |
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