ArticleGene2019
Codon usage pattern and predicted gene expression in Arabidopsis thaliana.
Article in Gene, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Limited directional selection but coevolutionary signals among imprinted genes inbioRxiv : the preprint server for biology · 2026Article
- Patterns and drivers of genome-wide codon usage bias in the fungal order Sordariales.DNA research : an international journal for rapid publication of reports on genes and genomes · 2025Article
- Codon usage bias is presumably affected by tRNA selection effects in Actinidia polyploidization events.BMC genomics · 2025Article
- Selection on synonymous codon usage in soybean (Glycine max) WRKY genes.Scientific reports · 2024Article
- Exploring recent progress of molecular farming for therapeutic and recombinant molecules in plant systems.Heliyon · 2024Review
- Article
- Synonymous Codon Variant Analysis for Autophagic Genes Dysregulated in Neurodegeneration.Molecular neurobiology · 2023Article
- Codon Usage Provide Insights into the Adaptation of Rice Genes under Stress Condition.International journal of molecular sciences · 2023Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The extensive research for predicting highly expressed genes in plant genome sequences has been going on for decades. The codon usage pattern of genes in Arabidopsis thaliana genome is a classical topic for plant biologists for its significance in the understanding of molecular plant biology. Here we have used a gene expression profiling methodology based on the score of modified relative codon bias (MRCBS) to elucidate expression pattern of genes in Arabidopsis thaliana. MRCBS relies exclusively on sequence features for identifying the highly expressed genes. In this study, a critical analysis of predicted highly expressed (PHE) genes in Arabidopsis thaliana has been performed using MRCBS as a numerical estimator of gene expression level. Consistent with previous other results, our study indicates that codon composition plays an important role in the regulation of gene expression. We found a systematic strong correlation between MRCBS and CAI (codon adaptation index) or other expression-measures. Additionally, MRCBS correlates well with experimental gene expression data. Our study highlights the relationship between gene expression and compositional signature in relation to codon usage bias and sets the ground for the further investigation of the evolution of the protein-coding genes in the plant genome.
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Registered trials
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