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A chemical kinetic basis for measuring translation initiation and elongation rates from ribosome profiling data.


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. By 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, and we also find that mouse embryonic stem cells have a global translation speed of 5.2 AA/s, in agreement with previous reports that used other approaches. Our analysis further reveals that 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, and it suggests that translational regulation might be used by cells to a greater degree than previously thought.

SUBMITTER: Sharma AK 

PROVIDER: S-EPMC6559674 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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A chemical kinetic basis for measuring translation initiation and elongation rates from ribosome profiling data.

Sharma Ajeet K AK   Sormanni Pietro P   Ahmed Nabeel N   Ciryam Prajwal P   Friedrich Ulrike A UA   Kramer Günter G   O'Brien Edward P EP  

PLoS computational biology 20190523 5


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 indi  ...[more]

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