State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, Jiangsu Province, China.
PLoS One. 2011;6(7):e22714. doi: 10.1371/journal.pone.0022714. Epub 2011 Jul 28.
A correlation method was recently adopted to identify selection-favored 'optimal' codons from 675 bacterial genomes. Surprisingly, the identities of these optimal codons were found to track the bacterial GC content, leading to a conclusion that selection would generally shape the codon usages to the same direction as the overall mutation does. Raising several concerns, here we report a thorough comparative study on 203 well-selected bacterial species, which strongly suggest that the previous conclusion is likely an illusion. Firstly, the previous study did not preclude species that are suffering weak or no selection pressures on their codon usages. For these species, as showed in this study, the optimal codon identities are prone to be incorrect and follow GC content. Secondly, the previous study only adopted the correlation method, without considering another method to test the reliability of inferred optimal codons. Actually by definition, optimal codons can also be identified by simply comparing codon usages between high- and low-expression genes. After using both methods to identify optimal codons for the selected species, we obtained highly conflicting results, suggesting at least one method is misleading. Further we found a critical problem of correlation method at the step of calculating gene bias level. Due to a failure of accurately defining the background mutation, the problem would result in wrong optimal codon identities. In other words, partial mutational effects on codon choices were mistakenly regarded as selective influences, leading to incorrect and biased optimal codon identities. Finally, considering the translational dynamics, optimal codons identified by comparison method can be well-explained by tRNA compositions, whereas optimal codons identified by correlation method can not be. For all above reasons, we conclude that real optimal codons actually do not track the genomic GC content, and correlation method is misleading in identifying optimal codons and better be avoided.
最近采用了一种相关方法从 675 个细菌基因组中鉴定出选择有利的“最佳”密码子。令人惊讶的是，这些最佳密码子的身份被发现与细菌 GC 含量相关，这导致了这样的结论：选择通常会使密码子的使用朝着与整体突变相同的方向发展。在这里，我们报告了对 203 个经过精心选择的细菌物种的彻底比较研究，该研究强烈表明，先前的结论可能是一种错觉。首先，先前的研究并没有排除那些在密码子使用上受到较弱或没有选择压力的物种。对于这些物种，正如本研究所示，最佳密码子的身份容易出现错误并遵循 GC 含量。其次，先前的研究仅采用了相关方法，而没有考虑另一种方法来测试推断出的最佳密码子的可靠性。实际上，根据定义，也可以通过简单比较高表达和低表达基因之间的密码子使用来识别最佳密码子。在使用这两种方法为所选物种识别最佳密码子后，我们得到了高度冲突的结果，表明至少有一种方法是有误导性的。此外，我们在计算基因偏向水平的步骤中发现了相关方法的一个关键问题。由于未能准确定义背景突变，该问题将导致错误的最佳密码子身份。换句话说，部分突变对密码子选择的影响被错误地视为选择影响，导致错误和有偏差的最佳密码子身份。最后，考虑到翻译动力学，通过比较方法识别的最佳密码子可以很好地用 tRNA 组成来解释，而通过相关方法识别的最佳密码子则不能。基于以上所有原因，我们得出结论，实际的最佳密码子实际上并不跟踪基因组 GC 含量，相关方法在识别最佳密码子方面具有误导性，最好避免使用。
