Poster abstracts
Poster number 26 submitted by Michay Diez
iCodon: Harnessing mRNA stability to customize gene expression
Michay Diez (Stowers Institute for Medical Research), Santiago Gerardo Medina-Muoz (Stowers Institute for Medical Research), Luciana Andrea Castellano (Stowers Institute for Medical Research), Gabriel da Silva Pescador (Stowers Institute for Medical Research), Qiushuang Wu (Stowers Institute for Medical Research), Ariel Alejandro Bazzini (Stowers Institute for Medical Research)
Abstract:
The codon composition of messenger RNA (mRNA) imposes regulatory information that strongly affects mRNA stability and fine-tunes protein expression. Current codon optimization methods revolve around codon usage frequency, despite the fact that it weakly correlates with stability. Here, we trained a machine learning model to predict mRNA stability based on the regulatory properties of codon composition. Using this model, we developed www.iCodon.org, a web interface that predicts stability, and customizes gene expression for vertebrate systems by introducing synonymous codon substitutions. To validate the potential of iCodon, we constructed twelve EGFP variants ranging in levels of predicted mRNA stability. Transfection of these variants in human cells revealed that our stability predictions correlated with fluorescence intensity and captured a range of nearly 50-fold differences in gene expression. Additionally, zebrafish embryos injected with these EGFP variants recapitulated the human cells results, demonstrating that iCodon can also modulate gene expression in vivo. Next, we explored potential applications of iCodon for basic biological research. First, we revealed how the estimated stability of gene families can be used to predict gene function and evolution. For example, core circadian genes displayed a significantly lower stability score compared to the stability of the transcriptome. Second, we showed that for heterologous gene expression in vertebrate systems iCodon outperforms gene optimization based on codon usage frequency by at least 3-fold. Finally, we found that iCodon stabilization improves in vivo loss-of-function phenotype rescues in later developmental stages in zebrafish embryos. In conclusion, iCodon provides a powerful tool to interrogate mRNA stability and design strategies to modulate gene expression in vertebrates, for a wide range of applications for research, and for the potential optimization of RNA-based therapeutics and vaccines.
Keywords: codon optimization, mRNA stability, evolutionary algorithm