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Ribosome profiling of HEK293T cells overexpressing codon optimized coagulation factor IX

Ribosome profiling provides the opportunity to evaluate translation kinetics at codon level resolution. Here, we describe ribosome profiling data, generated from two HEK293T cell lines. The ribosome profiling data are composed of Ribo-seq (mRNA sequencing data from ribosome protected fragments) and...

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Autores principales: Alexaki, Aikaterini, Kames, Jacob, Hettiarachchi, Gaya K., Athey, John C., Katneni, Upendra K., Hunt, Ryan C., Hamasaki-Katagiri, Nobuko, Holcomb, David D., DiCuccio, Michael, Bar, Haim, Komar, Anton A., Kimchi-Sarfaty, Chava
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7509596/
https://www.ncbi.nlm.nih.gov/pubmed/33014344
http://dx.doi.org/10.12688/f1000research.22400.2
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author Alexaki, Aikaterini
Kames, Jacob
Hettiarachchi, Gaya K.
Athey, John C.
Katneni, Upendra K.
Hunt, Ryan C.
Hamasaki-Katagiri, Nobuko
Holcomb, David D.
DiCuccio, Michael
Bar, Haim
Komar, Anton A.
Kimchi-Sarfaty, Chava
author_facet Alexaki, Aikaterini
Kames, Jacob
Hettiarachchi, Gaya K.
Athey, John C.
Katneni, Upendra K.
Hunt, Ryan C.
Hamasaki-Katagiri, Nobuko
Holcomb, David D.
DiCuccio, Michael
Bar, Haim
Komar, Anton A.
Kimchi-Sarfaty, Chava
author_sort Alexaki, Aikaterini
collection PubMed
description Ribosome profiling provides the opportunity to evaluate translation kinetics at codon level resolution. Here, we describe ribosome profiling data, generated from two HEK293T cell lines. The ribosome profiling data are composed of Ribo-seq (mRNA sequencing data from ribosome protected fragments) and RNA-seq data (total RNA sequencing). The two HEK293T cell lines each express a version of the F9 gene, both of which are translated into identical proteins in terms of their amino acid sequences. However, these F9 genes vary drastically in their codon usage and predicted mRNA structure. We also provide the pipeline that we used to analyze the data. Further analyzing this dataset holds great potential as it can be used i) to unveil insights into the composition and regulation of the transcriptome, ii) for comparison with other ribosome profiling datasets, iii) to measure the rate of protein synthesis across the proteome and identify differences in elongation rates, iv) to discover previously unidentified translation of peptides, v) to explore the effects of codon usage or codon context in translational kinetics and vi) to investigate cotranslational folding. Importantly, a unique feature of this dataset, compared to other available ribosome profiling data, is the presence of the F9 gene in two very distinct coding sequences.
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spelling pubmed-75095962020-10-01 Ribosome profiling of HEK293T cells overexpressing codon optimized coagulation factor IX Alexaki, Aikaterini Kames, Jacob Hettiarachchi, Gaya K. Athey, John C. Katneni, Upendra K. Hunt, Ryan C. Hamasaki-Katagiri, Nobuko Holcomb, David D. DiCuccio, Michael Bar, Haim Komar, Anton A. Kimchi-Sarfaty, Chava F1000Res Data Note Ribosome profiling provides the opportunity to evaluate translation kinetics at codon level resolution. Here, we describe ribosome profiling data, generated from two HEK293T cell lines. The ribosome profiling data are composed of Ribo-seq (mRNA sequencing data from ribosome protected fragments) and RNA-seq data (total RNA sequencing). The two HEK293T cell lines each express a version of the F9 gene, both of which are translated into identical proteins in terms of their amino acid sequences. However, these F9 genes vary drastically in their codon usage and predicted mRNA structure. We also provide the pipeline that we used to analyze the data. Further analyzing this dataset holds great potential as it can be used i) to unveil insights into the composition and regulation of the transcriptome, ii) for comparison with other ribosome profiling datasets, iii) to measure the rate of protein synthesis across the proteome and identify differences in elongation rates, iv) to discover previously unidentified translation of peptides, v) to explore the effects of codon usage or codon context in translational kinetics and vi) to investigate cotranslational folding. Importantly, a unique feature of this dataset, compared to other available ribosome profiling data, is the presence of the F9 gene in two very distinct coding sequences. F1000 Research Limited 2020-09-21 /pmc/articles/PMC7509596/ /pubmed/33014344 http://dx.doi.org/10.12688/f1000research.22400.2 Text en Copyright: © 2020 Alexaki A et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions.
spellingShingle Data Note
Alexaki, Aikaterini
Kames, Jacob
Hettiarachchi, Gaya K.
Athey, John C.
Katneni, Upendra K.
Hunt, Ryan C.
Hamasaki-Katagiri, Nobuko
Holcomb, David D.
DiCuccio, Michael
Bar, Haim
Komar, Anton A.
Kimchi-Sarfaty, Chava
Ribosome profiling of HEK293T cells overexpressing codon optimized coagulation factor IX
title Ribosome profiling of HEK293T cells overexpressing codon optimized coagulation factor IX
title_full Ribosome profiling of HEK293T cells overexpressing codon optimized coagulation factor IX
title_fullStr Ribosome profiling of HEK293T cells overexpressing codon optimized coagulation factor IX
title_full_unstemmed Ribosome profiling of HEK293T cells overexpressing codon optimized coagulation factor IX
title_short Ribosome profiling of HEK293T cells overexpressing codon optimized coagulation factor IX
title_sort ribosome profiling of hek293t cells overexpressing codon optimized coagulation factor ix
topic Data Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7509596/
https://www.ncbi.nlm.nih.gov/pubmed/33014344
http://dx.doi.org/10.12688/f1000research.22400.2
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