PreprintCited by 68RNA and protein synthesis mechanismsGenomics and Phylogenetic StudiesRNA modifications and cancer

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A Chemical Kinetic Basis for Measuring Translation Initiation and Elongation Rates from Ribosome Profiling data

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Preprint — 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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Research works printed but not linked: 77

  1. 10.1016/j.physrep.2013.03.005 · DOI
  2. 10.1146/annurev.biochem.77.070606.101431 · DOI
  3. 10.1142/S1793048012300083 · DOI
  4. 10.1038/nrm2838 · DOI · Paper page
  5. 10.1146/annurev-biochem-060713-035802 · DOI · Paper page
  6. 10.1021/jacs.6b01453 · DOI
  7. 10.1016/j.molcel.2010.09.028 · DOI
  8. 10.1186/gb-2004-5-12-359 · DOI
  9. 10.1016/J.SBI.2018.01.005 · DOI
  10. 10.1371/journal.pcbi.1002866 · DOI
  11. 10.1534/g3.114.015099 · DOI
  12. 10.1371/journal.pcbi.1004336 · DOI
  13. 10.15252/msb.20145524 · DOI
  14. 10.1371/journal.pgen.1007166 · DOI
  15. 10.1126/science.1168978 · DOI · Paper page
  16. 10.1016/j.celrep.2016.01.043 · DOI · Paper page
  17. 10.1101/gr.175893.114 · DOI
  18. 10.7554/eLife.03735 · DOI
  19. 10.1371/journal.pgen.1002603 · DOI
  20. 10.1371/journal.pbio.1001508 · DOI
  21. 10.1016/j.cell.2013.05.049 · DOI · Paper page
  22. 10.1080/15476286.2016.1172755 · DOI
  23. 10.1016/j.cell.2011.10.002 · DOI · Paper page
  24. 10.1371/journal.pcbi.1002755 · DOI
  25. 10.1002/bip.1968.360060102 · DOI
  26. 10.1073/pnas.0635171100 · DOI · Paper page
  27. 2018, Determinants of translation speed are randomly distributed across transcripts resulting in a universal scaling of protein synthesis times, Phys Rev E. American Physical Society, 97, 22409, 10.1103/PhysRevE.97.022409 · DOI
  28. 10.1016/j.cell.2011.10.044 · DOI
  29. 10.1038/nprot.2012.086 · DOI
  30. 10.1016/j.compbiolchem.2007.07.003 · DOI
  31. 10.1021/j100540a008 · DOI
  32. 10.1007/s10955-011-0183-1 · DOI
  33. 10.1088/1478-3975/8/2/026005 · DOI
  34. 10.1016/j.jtbi.2011.08.023 · DOI
  35. 10.1101/gr.150342.112 · DOI
  36. 10.1186/1748-7188-6-26 · DOI · Paper page
  37. 10.1038/nbt1270 · DOI · Paper page
  38. 10.1016/S0092-8674(00)81845-0 · DOI
  39. 10.1016/S0092-8674(00)81641-4 · DOI · Paper page
  40. 10.1073/pnas.092538799 · DOI
  41. 10.1038/nature04785 · DOI · Paper page
  42. 10.1038/nature02046 · DOI · Paper page
  43. 10.1128/MCB.19.11.7357 · DOI · Paper page
  44. 10.1038/ncomms10341 · DOI
  45. 10.1126/science.1257522 · DOI · Paper page
  46. Ahmed N , Sormanni P , Ciryam P , Vendruscolo M , Dobson CM , O’Brien EP . Identifying A- and P-site locations on ribosome-protected mRNA fragments using Linear Programming (Under review). 2018; · DOI
  47. 10.1126/science.1257522 · DOI · Paper page
  48. 10.1016/j.cell.2017.06.038 · DOI
  49. 10.1007/BF00337800 · DOI
  50. 10.1186/1741-7007-4-30 · DOI
  51. 10.1093/nar/15.8.3581 · DOI
  52. 10.1038/nature12894 · DOI
  53. 10.1038/nmeth.1923 · DOI · Paper page
  54. 10.1186/gb-2013-14-4-r36 · DOI · Paper page
  55. 10.1038/nature09322 · DOI
  56. 10.1074/mcp.M300129-MCP200 · DOI
  57. 10.1038/s41598-017-17618-1 · DOI
  58. 10.1002/bies.20771 · DOI
  59. 10.1146/annurev.micro.62.081307.162835 · DOI
  60. 10.1073/pnas.1222534110 · DOI · Paper page
  61. 10.3389/fbioe.2014.00001 · DOI
  62. 10.1371/journal.pgen.1005732 · DOI
  63. 10.1073/pnas.0809211106 · DOI
  64. 10.1038/nature10126 · DOI
  65. 10.1016/0022-2836(91)90211-N · DOI
  66. 10.1261/rna.02890211 · DOI
  67. 10.1016/j.cell.2016.09.022 · DOI
  68. 10.1371/journal.pcbi.1005951 · DOI
  69. 10.1016/j.cell.2014.02.033 · DOI
  70. 10.1103/PhysRevE.68.021910 · DOI
  71. 10.1016/j.cell.2016.02.066 · DOI
  72. 10.1016/j.ymeth.2016.07.011 · DOI
  73. 10.1093/nar/gkw822 · DOI
  74. 10.1002/0471142727.mb2604s72 · DOI
  75. 10.1038/nmeth.1491 · DOI · Paper page
  76. 10.1093/nar/gkw764 · DOI
  77. 10.1016/j.cell.2010.02.036 · DOI · Paper page

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.
Venue
PLoS Computational Biology
Publisher
openRxiv
Published
2018-12-08
Volume
15
Issue
5
Pages
e1007070-e1007070
ISSN
1553-734X (ISSN-L)
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
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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