ChimeraUGEM: unsupervised gene expression modeling in any given organism

Abstract

Abstract Motivation Regulation of the amount of protein that is synthesized from genes has proved to be a serious challenge in terms of analysis and prediction, and in terms of engineering and optimization, due to the large diversity in expression machinery across species. Results To address this challenge, we developed a methodology and a software tool (ChimeraUGEM) for predicting gene expression as well as adapting the coding sequence of a target gene to any host organism. We demonstrate these methods by predicting protein levels in seven organisms, in seven human tissues, and by increasing in vivo the expression of a synthetic gene up to 26-fold in the single-cell green alga Chlamydomonas reinhardtii. The underlying model is designed to capture sequence patterns and regulatory signals with minimal prior knowledge on the host organism and can be applied to a multitude of species and applications. Availability and implementation Source code (MATLAB, C) and binaries are freely available for download for non-commercial use at http://www.cs.tau.ac.il/~tamirtul/ChimeraUGEM/, and supported on macOS, Linux and Windows. Supplementary information Supplementary data are available at Bioinformatics online.