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The codon adaptation index-a measure of directional synonymous codon usage bias, and its potential applications
Open accessAbstract
A simple, effective measure of synonymous codon usage bias, the Codon Adaptation Index, is detailed. The index uses a reference set of highly expressed genes from a species to assess the relative merits of each codon, and a score for a gene is calculated from the frequency of use of all codons in that gene. The index assesses the extent to which selection has been effective in moulding the pattern of codon usage. In that respect it is useful for predicting the level of expression of a gene, for assessing the adaptation of viral genes to their hosts, and for making comparisons of codon usage in different organisms. The index may also give an approximate indication of the likely success of heterologous gene expression.
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“The codon optimization applied to BNT-162b2 and mRNA-1273 leads to a much increased codon adaptation index (CAI) [21,22] and index of translation efficiency (ITE) [11,36] for the two vaccine mRNAs.”
From Detailed Dissection and Critical Evaluation of the Pfizer/BioNTech and Moderna mRNA Vaccines (2021) · cites this paper as [21]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Usually, the frequencies of the peptides displayed on phages are not even in the library. There were some reasons for the heterogenous phage amount, such as biases in library construction, variance in the use of cryptography,45,46 the different growth rates of phages and peptide degradation by protease.47”
From Identification of heptapeptides targeting a lethal bacterial strain in septic mice through an integrative approach (2022) · cites this paper as [45]
Experimental — accuracy not yet measuredIn the citing paper
“Codon preference varies extensively in different organisms,249 therefore adjusting the balance between codon usage frequency and host tRNA availability can significantly improve translation efficiency and in vivo expression of the target antigen.250,251”
From Advances in COVID-19 mRNA vaccine development (2022) · cites this paper as [249]
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Gao, B., Yuan, L., Tang, T., Hou, J., Pan, K., & Wei, N. (2019) · PLoS ONE · doi:10.1371/journal.pone.0218817 · Cited by 45
Dubeau, M.-P., Ghinet, M. G., Jacques, P., Clermont, N., Beaulieu, C., & Brzeziński, R. (2008) · Applied and Environmental Microbiology · doi:10.1128/aem.02139-08 · Cited by 45
Metadata
- Authors
- Sharp, P. M., & Li, W.-H.
- Affiliations
- The University of Texas System (US)
- Corresponding author
- Sharp, Paul M.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 1987
- Volume
- 15
- Issue
- 3
- Pages
- 1281-1295
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC340524
- OpenAlex
- W2018590530
- Cited by
- 3,992
- References
- 30
- Citations by year
- 2026: 223 · 2025: 203 · 2024: 205 · 2023: 177 · 2022: 198 · 2021: 239 · 2020: 212 · 2019: 147 · 2018: 155 · 2017: 120 · 2016: 133 · 2015: 112 · 2014: 147 · 2013: 145 · 2012: 137
- FWCI
- 7.58
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nucleic Acids Research (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- Funders
- National Institutes of Health
- National Institute of General Medical Sciences (GM30998)
- 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 › Genetics › Evolution and Genetic Dynamics
- Keywords
- codon adaptation index, codon usage bias, codon usage, gene expression prediction, heterologous expression, highly expressed genes, natural selection
- MeSH terms
- Animals, Base Sequence, Cattle, Codon, Escherichia coli, Biological Evolution, Genes, Genes, Bacterial, Genes, Fungal, Humans, Mathematics, Models, Genetic, RNA, Messenger, Saccharomyces cerevisiae
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