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A Chemical Kinetic Basis for Measuring Translation Initiation and Elongation Rates from Ribosome Profiling data
Open accessPreprint — published as 10.1371/journal.pcbi.1007070 · Paper page
Abstract
Analysis methods based on simulations and optimization have been previously developed to estimate relative translation rates from next-generation sequencing data. Translation involves molecules and chemical reactions; hence, bioinformatics methods consistent with the laws of chemistry and physics are more likely to produce accurate results. Here, we derive simple equations based on chemical kinetic principles to measure the translation-initiation rate, transcriptome-wide elongation rate, and individual codon translation rates from ribosome profiling experiments. Our methods reproduce the known rates from ribosome profiles generated from detailed simulations of translation. Applying our methods to data from S. cerevisiae and mouse embryonic stem cells we find that the extracted rates reproduce expected correlations with various molecular properties. A codon can exhibit up to 26-fold variability in its translation rate depending upon its context within a transcript. This broad distribution means that the average translation rate of a codon is not representative of the rate at which most instances of that codon are translated. We also find that mouse embryonic stem cells have a global translation speed of 5.2 AA/s, is similar to what has been previous reported using another analysis method. This large variability in translation rates suggests that translational regulation might be used by cells to a greater degree than previously thought.
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Metadata
- Authors
- Sharma, A. K., Sormanni, P., Ahmed, N., Ciryam, P., Friedrich, U. A., Kramer, G., & O’Brien, E. P.
- Affiliations
- Pennsylvania State University (US)
- University of Cambridge (GB)
- Northwestern University (US)
- German Cancer Research Center (DE)
- Corresponding author
- O’Brien, Edward P.
- ORCID
- Venue
- PLoS Computational Biology
- Publisher
- openRxiv
- Published
- 2018-12-08
- Volume
- 15
- Issue
- 5
- Pages
- e1007070-e1007070
- ISSN
- 1553-734X (ISSN-L)
- PMC
- PMC6559674
- OpenAlex
- W2952639737
- Cited by
- 68
- References
- 1
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 9 · 2023: 7 · 2022: 12 · 2021: 11 · 2020: 14 · 2019: 2 · 2018: 2
- FWCI
- 3.23
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- National Science Foundation (CAREER, 1759860)
- Pennsylvania State University
- University of Cambridge
- National Institutes of Health
- Directorate for Biological Sciences (1759860)
- Institute for Computational and Data Sciences, Pennsylvania State University
- National Institute of General Medical Sciences (R35GM124818)
- Office of Advanced Cyberinfrastructure
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA modifications and cancer
- Keywords
- translation initiation rate, translation elongation rate, ribosome profiling, reaction kinetics, translation speed, translational regulation, Saccharomyces cerevisiae, mouse embryonic stem cells, protein synthesis
- MeSH terms
- Mouse Embryonic Stem Cells, Animals, Codon, Computer Simulation, Kinetics, Models, Biological, Nucleic Acid Conformation, Peptide Chain Elongation, Translational, Peptide Chain Initiation, Translational, Ribosomes, RNA Caps, RNA, Fungal, Saccharomyces cerevisiae, Computational Biology, Mice, Transcriptome
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