Department of Genome Sciences, University of Washington, USA.
Mol Biol Evol. 2010 Oct;27(10):2406-16. doi: 10.1093/molbev/msq132. Epub 2010 May 31.
Accurate reconstruction of the divergence times among individuals is an essential step toward inferring population parameters from genetic data. However, our ability to reconstruct accurate genealogies is often thwarted by the evolutionary forces we hope to detect, most prominently natural selection. Here, I demonstrate that purifying selection acting at many linked sites can systematically bias current methods of genealogical reconstruction, and I present a new method that corrects for this bias by allowing a class of sites to have a time-dependent rate. The parameters influencing the time dependency can be estimated from the data, allowing for a general method to detect the presence of selected sites and correcting for their distortion of the apparent mutation rate. The method works well under a variety of scenarios, including gamma-distributed selection coefficients as well as entirely neutral evolution. I also compare the performance of the new method to relaxed clock models, and I demonstrate the method on a data set from the mitochondrion of the North Atlantic whale-"louse" Cyamus ovalis.
准确重建个体间的分歧时间对于从遗传数据推断群体参数至关重要。然而，我们重建准确系统发育的能力经常受到我们希望检测的进化力量的阻碍，最突出的是自然选择。在这里，我证明了作用于许多连锁位点的净化选择可以系统地偏向当前的系统发育重建方法，并且我提出了一种新的方法，通过允许一类位点具有时变率来纠正这种偏差。影响时变率的参数可以从数据中估计出来，从而提供了一种通用的方法来检测选择位点的存在，并纠正它们对明显突变率的扭曲。该方法在各种情况下都能很好地工作，包括伽马分布的选择系数以及完全中性的进化。我还将新方法的性能与松弛时钟模型进行了比较，并在来自北大西洋鲸鱼“虱子”Cyamus ovalis 的线粒体数据集上演示了该方法。
