ArticleBMC genomics2019
Pathological changes are associated with shifts in the employment of synonymous codons at the transcriptome level.
Article in BMC genomics, 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, 16 citations in OpenAlex.
- Uncovering codon usage patterns during murine embryogenesis and tissue-specific developmental diseases.Frontiers in genetics · 2025Article
- Mouse embryo CoCoPUTs: novel murine transcriptomic-weighted usage website featuring multiple strains, tissues, and stages.BMC bioinformatics · 2024Article
- The interplay between translational efficiency, poly(A) tails, microRNAs, and neuronal activation.RNA (New York, N.Y.) · 2022Article
- Pan-cancer analyses of synonymous mutations based on tissue-specific codon optimality.Computational and structural biotechnology journal · 2022Article
- Codon usage bias analysis of genes linked with esophagus cancer.Bioinformation · 2021Article
- CUBAP: an interactive web portal for analyzing codon usage biases across populations.Nucleic acids research · 2020Article
- A comparative analysis of the mobility of 45 proteins in the synaptic bouton.The EMBO journal · 2020Article
- Translational efficiency across healthy and tumor tissues is proliferation-related.Molecular systems biology · 2020Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
backgroundThe usage of different synonymous codons reflects the genome organization and has been connected to parameters such as mRNA abundance and protein folding. It is also been established that mutations targeting specific synonymous codons can trigger disease.
resultsWe performed a systematic meta-analysis of transcriptome results from 75 datasets representing 40 pathologies. We found that a subset of codons was preferentially employed in abundant transcripts, while other codons were preferentially found in low-abundance transcripts. By comparing control and pathological transcriptomes, we observed a shift in the employment of synonymous codons for every analyzed disease. For example, cancerous tissue employed preferentially A- or U-ending codons, shifting from G- or C-ending codons, which were preferred by control tissues. This analysis was able to discriminate patients and controls with high specificity and sensitivity.
conclusionsHere we show that the employment of specific synonymous codons, quantified at the whole transcriptome level, changes profoundly in many diseases. We propose that the changes in codon employment offer a novel perspective for disease studies, and could be used to design new diagnostic tools.
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