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Experimental and computational workflow for the analysis of tRNA pools from eukaryotic cells by mim-tRNAseq

Quantifying tRNAs is crucial for understanding how they regulate mRNA translation but is hampered by their extensive sequence similarity and premature termination of reverse transcription at multiple modified nucleotides. Here, we describe the use of modification-induced misincorporation tRNA sequen...

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Autores principales: Behrens, Andrew, Nedialkova, Danny D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9356165/
https://www.ncbi.nlm.nih.gov/pubmed/35942339
http://dx.doi.org/10.1016/j.xpro.2022.101579
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author Behrens, Andrew
Nedialkova, Danny D.
author_facet Behrens, Andrew
Nedialkova, Danny D.
author_sort Behrens, Andrew
collection PubMed
description Quantifying tRNAs is crucial for understanding how they regulate mRNA translation but is hampered by their extensive sequence similarity and premature termination of reverse transcription at multiple modified nucleotides. Here, we describe the use of modification-induced misincorporation tRNA sequencing (mim-tRNAseq), which overcomes these limitations with optimized library construction and a comprehensive toolkit for data analysis and visualization. We outline algorithm improvements that enhance the efficiency and accuracy of read alignment and provide details on data analysis outputs using example datasets. For complete details on the use and execution of this protocol, please refer to Behrens et al. (2021).
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spelling pubmed-93561652022-08-07 Experimental and computational workflow for the analysis of tRNA pools from eukaryotic cells by mim-tRNAseq Behrens, Andrew Nedialkova, Danny D. STAR Protoc Protocol Quantifying tRNAs is crucial for understanding how they regulate mRNA translation but is hampered by their extensive sequence similarity and premature termination of reverse transcription at multiple modified nucleotides. Here, we describe the use of modification-induced misincorporation tRNA sequencing (mim-tRNAseq), which overcomes these limitations with optimized library construction and a comprehensive toolkit for data analysis and visualization. We outline algorithm improvements that enhance the efficiency and accuracy of read alignment and provide details on data analysis outputs using example datasets. For complete details on the use and execution of this protocol, please refer to Behrens et al. (2021). Elsevier 2022-07-31 /pmc/articles/PMC9356165/ /pubmed/35942339 http://dx.doi.org/10.1016/j.xpro.2022.101579 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Behrens, Andrew
Nedialkova, Danny D.
Experimental and computational workflow for the analysis of tRNA pools from eukaryotic cells by mim-tRNAseq
title Experimental and computational workflow for the analysis of tRNA pools from eukaryotic cells by mim-tRNAseq
title_full Experimental and computational workflow for the analysis of tRNA pools from eukaryotic cells by mim-tRNAseq
title_fullStr Experimental and computational workflow for the analysis of tRNA pools from eukaryotic cells by mim-tRNAseq
title_full_unstemmed Experimental and computational workflow for the analysis of tRNA pools from eukaryotic cells by mim-tRNAseq
title_short Experimental and computational workflow for the analysis of tRNA pools from eukaryotic cells by mim-tRNAseq
title_sort experimental and computational workflow for the analysis of trna pools from eukaryotic cells by mim-trnaseq
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9356165/
https://www.ncbi.nlm.nih.gov/pubmed/35942339
http://dx.doi.org/10.1016/j.xpro.2022.101579
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