Predicting gene expression level from codon usage bias
Predicting gene expression level from codon usage bias
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DOI：
10.1093/molbev/msl148
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发表时间：
2007-01-01
影响因子：
10.7
通讯作者：
Sharp, Paul M.
中科院分区：
文献类型：
--
作者：
Henry, Ian;Sharp, Paul M.
基因的“表达测量”E(g)是一种统计数据，用于预测密码子使用偏差的基因表达水平。E(g)已广泛用于分析原核生物基因组序列。我们用这种方法讨论两个问题。首先，E(g)的公式是这样的，具有最强选择密码子使用偏差的基因不太可能具有最高的预测表达水平；事实上，E(g)与表达水平之间的相关性在中等至高表达基因中较弱。其次，在一些物种中，高表达的基因没有不寻常的密码子使用，因此密码子使用不能用来预测表达水平。我们概述了一种简单的方法，首先检查基因组是否显示选择性密码子使用偏差的证据，然后评估基因偏差的强度，作为其可能表达水平的指导；我们通过对希瓦氏菌的分析来说明这一点。
The "expression measure" of a gene, E(g), is a statistic devised to predict the level of gene expression from codon usage bias. E(g) has been used extensively to analyze prokaryotic genome sequences. We discuss 2 problems with this approach. First, the formulation of E(g) is such that genes with the strongest selected codon usage bias are not likely to have the highest predicted expression levels; indeed the correlation between E(g) and expression level is weak among moderate to highly expressed genes. Second, in some species, highly expressed genes do not have unusual codon usage, and so codon usage cannot be used to predict expression levels. We outline a simple approach, first to check whether a genome shows evidence of selected codon usage bias and then to assess the strength of bias in genes as a guide to their likely expression level; we illustrate this with an analysis of Shewanella oneidensis.