Cargando…
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...
Autores principales: | , |
---|---|
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 |
_version_ | 1784763456473268224 |
---|---|
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). |
format | Online Article Text |
id | pubmed-9356165 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT behrensandrew experimentalandcomputationalworkflowfortheanalysisoftrnapoolsfromeukaryoticcellsbymimtrnaseq AT nedialkovadannyd experimentalandcomputationalworkflowfortheanalysisoftrnapoolsfromeukaryoticcellsbymimtrnaseq |