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STATR: A simple analysis pipeline of Ribo-Seq in bacteria

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Abstract

Gene expression changes in response to diverse environmental stimuli to regulate numerous cellular functions. Genes are expressed into their functional products with the help of messenger RNA (mRNA). Thus, measuring levels of mRNA in cells is important to understand cellular functions. With advances in next-generation sequencing (NGS), the abundance of cellular mRNA has been elucidated via transcriptome sequencing. However, several studies have found a discrepancy between mRNA abundance and protein levels induced by translational regulation, including different rates of ribosome entry and translational pausing. As such, the levels of mRNA are not necessarily a direct representation of the protein levels found in a cell. To determine a more precise way to measure protein expression in cells, the analysis of the levels of mRNA associated with ribosomes is being adopted. With an aid of NGS techniques, a single nucleotide resolution footprint of the ribosome was determined using a method known as Ribo-Seq or ribosome profiling. This method allows for the high-throughput measurement of translation in vivo, which was further analyzed to determine the protein synthesis rate, translational pausing, and cellular responses toward a variety of environmental changes. Here, we describe a simple analysis pipeline for Ribo-Seq in bacteria, so-called simple translatome analysis tool for Ribo-Seq (STATR). STATR can be used to carry out the primary processing of Ribo-Seq data, subsequently allowing for multiple levels of translatome study, from experimental validation to in-depth analyses. A command-by-command explanation is provided here to allow a broad spectrum of biologists to easily reproduce the analysis.

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Acknowledgments

This work was supported by the Korea Bio Grand Challenge (2018M3A9H3024759 to B-KC) and the Basic Core Technology Development Program for the Oceans and the Polar Regions (2016M1A5A1027458 to B-KC) through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT. This work was also funded by National Institutes of Health/National Institute of General Medical Sciences Grant (1R01GM098105 and 1-U01-AI124316-01 to BOP).

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Authors and Affiliations

  1. Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea

    Donghui Choe & Byung-Kwan Cho

  2. Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093, USA

    Bernhard Palsson

  3. Department of Pediatrics, University of California San Diego, La Jolla, CA, 92093, USA

    Bernhard Palsson

  4. KI for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea

    Byung-Kwan Cho

  5. Intelligent Synthetic Biology Center, Daejeon, 34141, Republic of Korea

    Byung-Kwan Cho

Authors
  1. Donghui Choe
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  2. Bernhard Palsson
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  3. Byung-Kwan Cho
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Corresponding author

Correspondence to Byung-Kwan Cho.

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Data and Material Availability

All the scripts and example files of the STATR pipeline are freely available through the Github repository (https://github.com/robinald/STATR) under the GNU General Public License v 3.0 (https://www.gnu.org/licenses/gpl-3.0.en.html) and may be reused by Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0).

Conflicts of Interest

The authors declare that there are no conflicts of interest.

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Choe, D., Palsson, B. & Cho, BK. STATR: A simple analysis pipeline of Ribo-Seq in bacteria. J Microbiol. 58, 217–226 (2020). https://doi.org/10.1007/s12275-020-9536-2

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  • DOI: https://doi.org/10.1007/s12275-020-9536-2

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