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iCodon customizes gene expression based on the codon composition

Messenger RNA (mRNA) stability substantially impacts steady-state gene expression levels in a cell. mRNA stability is strongly affected by codon composition in a translation-dependent manner across species, through a mechanism termed codon optimality. We have developed iCodon (www.iCodon.org), an al...

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Detalles Bibliográficos
Autores principales: Diez, Michay, Medina-Muñoz, Santiago Gerardo, Castellano, Luciana Andrea, da Silva Pescador, Gabriel, Wu, Qiushuang, Bazzini, Ariel Alejandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9287306/
https://www.ncbi.nlm.nih.gov/pubmed/35840631
http://dx.doi.org/10.1038/s41598-022-15526-7
Descripción
Sumario:Messenger RNA (mRNA) stability substantially impacts steady-state gene expression levels in a cell. mRNA stability is strongly affected by codon composition in a translation-dependent manner across species, through a mechanism termed codon optimality. We have developed iCodon (www.iCodon.org), an algorithm for customizing mRNA expression through the introduction of synonymous codon substitutions into the coding sequence. iCodon is optimized for four vertebrate transcriptomes: mouse, human, frog, and fish. Users can predict the mRNA stability of any coding sequence based on its codon composition and subsequently generate more stable (optimized) or unstable (deoptimized) variants encoding for the same protein. Further, we show that codon optimality predictions correlate with both mRNA stability using a massive reporter library and expression levels using fluorescent reporters and analysis of endogenous gene expression in zebrafish embryos and/or human cells. Therefore, iCodon will benefit basic biological research, as well as a wide range of applications for biotechnology and biomedicine.