利用重构祖先识别功能蛋白进化的遗传基础
Identifying the Genetic Basis of Functional Protein Evolution Using Reconstructed Ancestors
摘要：
蛋白质进化研究中的一个中心挑战是鉴定在当今蛋白质中观察到的负责创造新功能的历史氨基酸序列变化。为了解决这个问题，我们开发了一种新的方法来识别和排名祖先蛋白质序列中的氨基酸突变，根据其功能转移的潜力。我们的方法扫描两个重建的祖先序列之间的变化，以找到（1）序列变化显著偏离我们基于模型的概率预期的位点，（2）表现出互信息极端变化的位点，以及（3）信息内容极端增益或损失的位点。通过这些统计信号的重叠，该方法准确地识别了隐藏的进化模式，这些模式在只检查现代蛋白质序列的保守性时往往不明显。我们用动物和真菌中三个基本蛋白质家族中先前发现的功能转移突变的训练集验证了这种方法，这些蛋白质家族的进化历史是系统分子生物学研究的优先主题。我们的方法以非常低的假阳性发现率鉴定了训练集中已知的功能转移突变。此外，我们的方法显着优于其他方法，使用进化速率的变化来检测功能基因座。我们的方法的准确性表明，它可能是一个有用的工具，用于产生特定的可测试的假设，关于收购的新功能，在广泛的蛋白质家族。
英文摘要：
A central challenge in the study of protein evolution is the identification of historic amino acid sequence changes responsible for creating novel functions observed in present-day proteins. To address this problem, we developed a new method to identify and rank amino acid mutations in ancestral protein sequences according to their function-shifting potential. Our approach scans the changes between two reconstructed ancestral sequences in order to find (1) sites with sequence changes that significantly deviate from our model-based probabilistic expectations, (2) sites that demonstrate extreme changes in mutual information, and (3) sites with extreme gains or losses of information content. By taking the overlaps of these statistical signals, the method accurately identifies cryptic evolutionary patterns that are often not obvious when examining only the conservation of modern-day protein sequences. We validated this method with a training set of previously-discovered function-shifting mutations in three essential protein families in animals and fungi, whose evolutionary histories were the prior subject of systematic molecular biological investigation. Our method identified the known function-shifting mutations in the training set with a very low rate of false positive discovery. Further, our approach significantly outperformed other methods that use variability in evolutionary rates to detect functional loci. The accuracy of our approach indicates it could be a useful tool for generating specific testable hypotheses regarding the acquisition of new functions across a wide range of protein families.
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