Cited by 15RNA and protein synthesis mechanismsProtein Structure and DynamicsGenomics and Phylogenetic Studies

Codon usage is less optimized in eukaryotic gene segments encoding intrinsically disordered regions than in those encoding structural domains

Open access
Homma, Keiichi, Noguchi, Tamotsu, Fukuchi, Satoshi·2016·Nucleic Acids Research

Abstract

Codon usage tends to be optimized in highly expressed genes. A plausible explanation for this phenomenon is that translational accuracy is increased in highly expressed genes with infrequent use of rare codons. Besides structural domains (SDs), eukaryotic proteins generally have intrinsically disordered regions (IDRs) that by themselves do not assume unique three-dimensional structures. As IDRs are free from structural constraint, they can probably accommodate more translational errors than SDs can. Thus, codon usage in IDRs is likely to be less optimized than that in SDs. Codon usage in all the genes of seven eukaryotes was examined in terms of both tRNA adaptation index and codon adaptation index. Different amino acid compositions in different protein regions were taken into account in calculating expected adaptation indices, to which observed indices were compared. Codon usage is less optimized in gene regions encoding IDRs than in those corresponding to SDs. The finding does not depend on whether IDRs are located at the N-terminus, in the middle, or at the C-terminus of proteins. Furthermore, the observation remains unchanged in two different algorithms used to predict IDRs in proteins. The result is consistent with the idea that IDRs tolerate more translational errors than SDs.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/nar/gkw899

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Increasing the G-C fraction of mRNA improves mRNA stability.

    “Furthermore, increasing the G-C fraction of mRNA improves mRNA stability (Homma et al. 2016).”

    From Modifications of mRNA vaccine structural elements for improving mRNA stability and translation efficiency (2022) · cites this paper as Homma et al. 2016

    The Introduction and Discussion address codon usage, translation speed, and translational accuracy, not mRNA stability. Searches for increased G-C fraction, GC content, and mRNA stability found no passage in our copy supporting the claimed effect. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 32

  1. [1]Ikemura T. Correlation between the abundance of Escherichia coli transfer RNAs and the occurrence of the respective codons in its protein genes J. Mol. Biol. 1981 145 1 21 6167728
  2. [2]Ikemura T. Codon usage and tRNA content in unicellular and multicellular organisms Mol. Biol. Evol. 1985 2 13 34 3916708
  3. [3]Ingolia N.T. Ghaemmaghami S. Newman J.R. Weissman J.S. Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling Science 2009 324 218 223 19213877 PMC2746483
  4. [4]Ingolia N.T. Lareau L.F. Weissman J.S. Ribosome profiling of mouse embryonic stem cells reveals the complexity and dynamics of mammalian proteomes Cell 2011 147 789 802 22056041 PMC3225288
  5. [5]Qian W. Yang J.R. Pearson N.M. Maclean C. Zhang J. Balanced codon usage optimizes eukaryotic translational efficiency PLoS Genet. 2012 8 e1002603 22479199 PMC3315465
  6. [6]Charneski C.A. Hurst L.D. Positively charged residues are the major determinants of ribosomal velocity PLoS Biol. 2013 11 e1001508 23554576 PMC3595205
  7. [7]Akashi H. Synonymous codon usage in Drosophila melanogaster: natural selection and translationalaccuracy Genetics 1994 136 927 935 8005445 PMC1205897
  8. [8]Stoletzki N. Eyre-Walker A. Synonymous codon usage in Escherichia coli: selection for translational accuracy Mol. Biol. Evol. 2007 24 374 381 17101719
  9. [9]Drummond D.A. Wilke C.O. Mistranslation-induced protein misfolding as a dominant constraint on coding-sequence evolution Cell 2008 134 341 352 18662548 PMC2696314
  10. [10]Zhou T. Weems M. Wilke C.O. Translationally optimal codons associate with structurally sensitive sites in proteins Mol. Biol. Evol. 2009 26 1571 1580 19349643 PMC2734146
  11. [11]Agashe D. Martinez-Gomez N.C. Drummond D.A. Marx C.J. Good codons, bad transcript: Large reductions in gene expression and fitness arising from synonymous mutations in a key enzyme Mol. Biol. Evol. 2012 30 549 560 23223712 PMC3563975
  12. [12]Sharp P.M. Li W.H. The codon Adaptation Index–a measure of directional synonymous codon usage bias, and its potential applications Nucleic Acids Res. 1987 15 1281 1295 3547335 PMC340524
  13. [13]Dong H. Nilsson L. Kurland C.G. Co-variation of tRNA abundance and codon usage in Escherichia coli at different growth rates J. Mol. Biol. 1996 260 649 663 8709146
  14. [14]Percudani R. Pavesi A. Ottonello S. Transfer RNA gene redundancy and translational selection in Saccharomyces cerevisiae J. Mol. Biol. 1997 268 322 330 9159473
  15. [15]Kanaya S. Yamada Y. Kudo Y. Ikemura T. Studies of codon usage and tRNA genes of 18 unicellular organisms and quantification of Bacillus subtilis tRNAs: gene expression level and species-specific diversity of codon usage based on multivariate analysis Gene 1999 238 143 155 10570992
  16. [16]dos Reis M. Savva R. Wernisch L. Solving the riddle of codon usage preferences: a test for translational selection Nucleic Acids Res. 2004 32 5036 5044 15448185 PMC521650
  17. [17]Wright P.E. Dyson H.J. Intrinsically unstructured proteins: Re-assessing the protein structure-function paradigm J. Mol. Biol. 1999 293 321 331 10550212
  18. [18]van der Lee R. Buljan M. Lang B. Weatheritt R.J. Daughdrill G.W. Dunker A.K. Fuxreiter M. Gough J. Gsponer J. Jones D.T. Classification of intrinsically disordred regions and proteins Chem. Rev. 2014 114 6589 6531 24773235 PMC4095912
  19. [19]Payjos M. Mészáros B. Simon I. Dosztányi Z. Is there a biological cost of protein disorder? Anaysis of cancer-associated mutations Mol. BioSyst. 2012 8 296 307 21918772
  20. [20]Fukuchi S. Homma K. Sakamoto S. Sugawara H. Tateno Y. Gojobori T. Nishikawa K. The GTOP database in 2009: updated content and novel features to expand and deepen insights into protein structures and functions Nucleic Acids Res. 2009 37 D333 D337 18987007 PMC2686575
  21. [21]Chan P.P. Lowe T.M. GtRNAdb: A database of transfer RNA genes detected in genomic sequence Nucleic Acids Res. 2009 37 D93 D97 18984615 PMC2686519
  22. [22]Nakamura Y. Gojobori T. Ikemura T. Codon usage tabulated from international DNA sequence databases: Status for the year 2000 Nucleic Acids Res. 2000 28 292 10592250 PMC102460
  23. [23]Fukuchi S. Homma K. Minezaki Y. Gojobori T. Nishikawa K. Development of an accurate classification system of proteins into structured and unstructured regions that uncovers novel structural domains: its application to human transcription factors BMC Struct. Biol. 2009 9 26 19402914 PMC2687452
  24. [24]Hirose S. Shimizu K. Kanai S. Kuroda Y. Noguchi T. POODLE-L: A two-level SVM prediction system for reliably predicting long disordered regions Bioinformatics 2007 23 2046 2053 17545177
  25. [25]Bellay J. Han S. Michaut M. Kim T. Constanzo M. Andrews B.J. Boone C. Bader G.D. Myers C.L. Kim P.M. Bringing order to protein disorder through comparative genomics and genetic interactions Genome Biol. 2011 12 R14 21324131 PMC3188796
  26. [26]Vavouri T Semple J.I. Garcia-Verdugo R. Lehner B. Intrinsic protein disorder and interaction promiscuity are widely associated with dosage sensitivity Cell 2009 138 198 208 19596244
  27. [27]Zhang Y. Wölfle T. Rospert S. Interaction of nascent chains with the ribosomal tunnel proteins Rpl4, Rpl17, and Rpl39 of Saccharomyces cerevisiae J. Biol. Chem. 2013 288 33697 33707 24072706 PMC3837115
  28. [28]Macossay-Castillo M. Kosol S. Tompa P. Pancsa R. Synonymous constraint show a tendency to encode intrinsically disordered protein segments PLoS Comp. Biol. 2014 16 589 597 PMC4014394 24809503
  29. [29]Warnecke T. Hurst L.D. Evidence for a trade-off between translational efficiency and splicing regulation in determinig synonymous codon usage in Drosophila melanogaster Mol. Biol. Evol. 2007 24 2755 2762 17905999
  30. [30]Hegyi H. Kalmar L. Horvath T. Tompa P. Verification of alternative variants based on domain integrity, truncation length and intrinsic protein disorder Nucleic Acids Res. 2011 39 1208 1219 20972208 PMC3045584
  31. [31]Smithers B. Oates M.E. Gough J. Splice junctions are constrained by protein disorder Nucleic Acids Res. 2015 43 4814 4822 25934802 PMC4446445
  32. [32]Light S. Sagit R. Sachenkova O. Ekman D. Elofsson A. Protein expansion is primarily due to indels in intrinsically disordered regions Mol. Biol. Evol. 2013 30 2645 2653 24037790

Cited by

Sorted by citations

Authors
Homma, K., Noguchi, T., & Fukuchi, S.
Affiliations
  • Maebashi Institute of Technology (JP)
  • Meiji Pharmaceutical University (JP)
Corresponding author
Homma, Keiichi
Venue
Nucleic Acids Research
Published
2016-10-05
Volume
44
Issue
21
Pages
gkw899
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
OpenAlex
W2529831450
Cited by
15
References
1
Citations by year
2026: 1 · 2025: 1 · 2024: 3 · 2023: 1 · 2022: 3 · 2021: 3 · 2019: 1 · 2018: 1 · 2017: 1
FWCI
0.52
Type
journal article
Language
en
Open access
Locations
  • Nucleic Acids Research (publishedVersion, cc-by-nc)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords
codon usage, intrinsically disordered regions, structural domains, codon adaptation index, tRNA adaptation index, translational errors, rare codons, eukaryotic genes, protein structure, amino acid composition
MeSH terms
Amino Acids, Codon, Humans, Plant Proteins, Proteins, Oryza, RNA, Transfer, Protein Biosynthesis, Gene Expression, Arabidopsis Proteins, Saccharomyces cerevisiae Proteins, Schizosaccharomyces pombe Proteins, Drosophila Proteins, Eukaryota

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review