Variation in Mutational Robustness between Different Proteins and the Predictability of Fitness Effects
Variation in Mutational Robustness between Different Proteins and the Predictability of Fitness Effects
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DOI：
10.1093/molbev/msw239
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发表时间：
2017-02-01
影响因子：
10.7
通讯作者：
Andersson, Dan I.
中科院分区：
文献类型：
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作者：
Lind, Peter A.;Arvidsson, Lars;Andersson, Dan I.
不同蛋白质类基因的随机突变可能具有不同的适应度效应(DFE)分布，这取决于不同的结构、功能和进化约束。我们测量了用于细菌生长的AraC(转录因子)、AraD(酶)和AraE(转运体)基因的156个单一突变在L-阿拉伯糖上的适合度效应。尽管它们的分子功能不同，但这些基因都具有双峰DFE，大多数突变要么是中性的，要么是强烈有害的，这为DFE提供了一个普遍的预期。这与以前获得的核糖体蛋白基因的单峰DFES形成对比，在那里大多数突变都是轻微有害的。基于理论考虑，我们认为核糖体蛋白平均突变稳健性提高33倍是由于更强的选择能力，从而降低了翻译和转录错误的成本。虽然绝大多数同义突变对核糖体蛋白基因是有害的，但没有检测到Aracde基因的适合性影响。AraC和AraE中的四个突变增加了适合度，这表明略有优势的突变在DFE中占很大比例，但由于常用适合度分析的灵敏度有限，它们经常逃脱检测。我们表明，氨基酸替换的适合度效应可以基于进化守恒来预测，但那些弱有害突变的检测可靠性较低。这表明，大效应突变和高度有害突变的比例可以通过计算进行预测，但需要实验来表征DFE接近中性，在那里将出现许多最终固定在种群中的突变。
Random mutations in genes from disparate protein classes may have different distributions of fitness effects (DFEs) depending on different structural, functional, and evolutionary constraints. We measured the fitness effects of 156 single mutations in the genes encoding AraC (transcription factor), AraD (enzyme), and AraE (transporter) used for bacterial growth on L-arabinose. Despite their different molecular functions these genes all had bimodal DFEs with most mutations either being neutral or strongly deleterious, providing a general expectation for the DFE. This contrasts with the unimodal DFEs previously obtained for ribosomal protein genes where most mutations were slightly deleterious. Based on theoretical considerations, we suggest that the 33-fold higher average mutational robustness of ribosomal proteins is due to stronger selection for reduced costs of translational and transcriptional errors. Whereas the large majority of synonymous mutations were deleterious for ribosomal proteins genes, no fitness effects could be detected for the AraCDE genes. Four mutations in AraC and AraE increased fitness, suggesting that slightly advantageous mutations make up a significant fraction of the DFE, but that they often escape detection due to the limited sensitivity of commonly used fitness assays. We show that the fitness effects of amino acid substitutions can be predicted based on evolutionary conservation, but those weakly deleterious mutations are less reliably detected. This suggests that large-effect mutations and the fraction of highly deleterious mutations can be computationally predicted, but that experiments are required to characterize the DFE close to neutrality, where many mutations ultimately fixed in a population will occur.