iCodon: ideal codon design for customized gene expression
Messenger RNA (mRNA) stability substantially impacts steady-state gene expression levels in a cell. mRNA stability, in turn, 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 expression levels using fluorescent reporters and endogenous genes in human cells and zebrafish embryos. Therefore, iCodon will benefit basic biological research, as well as a wide range of applications for biotechnology and biomedicine.