ChimeraUGEM: unsupervised gene expression modeling in any given organism
ChimeraUGEM: unsupervised gene expression modeling in any given organism
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DOI：
10.1093/bioinformatics/btz080
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发表时间：
2019-09-15
期刊：
影响因子：
5.8
通讯作者：
Tuller, Tamir
中科院分区：
文献类型：
--
作者：
Diament, Alon;Weiner, Iddo;Tuller, Tamir
动机：由于物种间表达机制的巨大多样性，从基因合成的蛋白质的量的调节在分析和预测方面以及在工程和优化方面已被证明是一个严峻的挑战。为了应付这一挑战，我们开发了一种方法和软件工具，（ChimeraUGEM）用于预测基因表达以及使靶基因的编码序列适应任何宿主生物体。我们证明了这些方法，通过预测蛋白质水平在7种生物体中，在7个人体组织中，并通过增加在体内的合成基因的表达高达26倍的单细胞绿色衣藻reinhardtii。基础模型的设计是为了捕捉序列模式和调节信号与宿主生物体的最小先验知识，并可以应用于多种物种和应用。
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.