ArticleDNA research : an international journal for rapid publication of reports on genes and genomes2009
Predicting gene expression level from relative codon usage bias: an application to Escherichia coli genome.
Article in DNA research : an international journal for rapid publication of reports on genes and genomes, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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39 citing papers in PubMed.
- From nucleotides to numbers: a comprehensive review of RNA feature extraction methods for computational modelling.Briefings in bioinformatics · 2025Review
- AI-directed gene fusing prolongs the evolutionary half-life of synthetic gene circuits.Science advances · 2025Article
- Comprehensive analysis of orthologous genes reveals functional dynamics and energy metabolism in the rhizospheric microbiome of Moringa oleifera.Functional & integrative genomics · 2025Article
- Link Between Individual Codon Frequencies and Protein Expression: Going Beyond Codon Adaptation Index.International journal of molecular sciences · 2024Article
- GenRCA: a user-friendly rare codon analysis tool for comprehensive evaluation of codon usage preferences based on coding sequences in genomes.BMC bioinformatics · 2024Article
- Codon usage and expression-based features significantly improve prediction of CRISPR efficiency.NPJ systems biology and applications · 2024Article
- Codon-optimization in gene therapy: promises, prospects and challenges.Frontiers in bioengineering and biotechnology · 2024Review
- Dicodon-based measures for modeling gene expression.Bioinformatics (Oxford, England) · 2023Article
- Reading Frame Retrieval of Genes: A New Parameter of Codon Usage Based on the Circular Code Theory.Bulletin of mathematical biology · 2023Article
- Determinants of associations between codon and amino acid usage patterns of microbial communities and the environment inferred based on a cross-biome metagenomic analysis.NPJ biofilms and microbiomes · 2023Article
- Evolution and codon usage bias of mitochondrial and nuclear genomes in Aspergillus section Flavi.G3 (Bethesda, Md.) · 2023Article
- gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.Frontiers in molecular biosciences · 2023Article
- The pattern of coding sequences in the chloroplast genome of Atropa belladonna and a comparative analysis with other related genomes in the nightshade family.Genomics & informatics · 2022Article
- LncDC: a machine learning-based tool for long non-coding RNA detection from RNA-Seq data.Scientific reports · 2022Article
- Article
- Composition and Codon Usage Pattern Results in Divergence of theJournal of fungi (Basel, Switzerland) · 2022Article
- tRNA copy number and codon usage in the sea cucumber genome provide insights into adaptive translation for saponin biosynthesis.Open biology · 2021Article
- Analysis of chromosomes and nucleotides in rice to predict gene expression through codon usage pattern.Saudi journal of biological sciences · 2021Article
- Signatures of optimal codon usage in metabolic genes inform budding yeast ecology.PLoS biology · 2021Article
- Massively parallel gene expression variation measurement of a synonymous codon library.BMC genomics · 2021Article
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3 authors.
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Abstract
We present an expression measure of a gene, devised to predict the level of gene expression from relative codon bias (RCB). There are a number of measures currently in use that quantify codon usage in genes. Based on the hypothesis that gene expressivity and codon composition is strongly correlated, RCB has been defined to provide an intuitively meaningful measure of an extent of the codon preference in a gene. We outline a simple approach to assess the strength of RCB (RCBS) in genes as a guide to their likely expression levels and illustrate this with an analysis of Escherichia coli (E. coli) genome. Our efforts to quantitatively predict gene expression levels in E. coli met with a high level of success. Surprisingly, we observe a strong correlation between RCBS and protein length indicating natural selection in favour of the shorter genes to be expressed at higher level. The agreement of our result with high protein abundances, microarray data and radioactive data demonstrates that the genomic expression profile available in our method can be applied in a meaningful way to the study of cell physiology and also for more detailed studies of particular genes of interest.
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