Zhang Jianzhi
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA.
Mol Biol Evol. 2004 Jul;21(7):1332-9. doi: 10.1093/molbev/msh117. Epub 2004 Mar 10.
Positive Darwinian selection promotes fixations of advantageous mutations during gene evolution and is probably responsible for most adaptations. Detecting positive selection at the DNA sequence level is of substantial interest because such information provides significant insights into possible functional alterations during gene evolution as well as important nucleotide substitutions involved in adaptation. Efficient detection of positive selection, however, has been difficult because selection often operates on only a few sites in a short period of evolutionary time. A likelihood-based method with branch-site models was recently introduced to overcome such difficulties. Here I examine the accuracy of the method using computer simulation. I find that the method detects positive selection in 20%-70% of cases when the DNA sequences are generated by computer simulation under no positive selection. Although the frequency of such false detection varies depending on, among other things, the tree topology, branch length, and selection scheme, the branch-site likelihood method generally gives misleading results. Thus, detection of positive selection by this method alone is unreliable. This unreliability may have resulted from its over-sensitivity to violations of assumptions made in the method, such as certain distributions of selective strength among sites and equal transition/transversion ratios for synonymous and nonsynonymous substitutions.
正向达尔文选择在基因进化过程中促进有利突变的固定,可能是大多数适应性的原因。在DNA序列水平上检测正向选择具有重大意义,因为此类信息能深入了解基因进化过程中可能的功能改变以及与适应性相关的重要核苷酸替换。然而,由于选择通常在较短的进化时间内仅作用于少数位点,高效检测正向选择一直很困难。最近引入了一种基于分支位点模型的似然法来克服这些困难。在此,我通过计算机模拟检验该方法的准确性。我发现,当在无正向选择的情况下通过计算机模拟生成DNA序列时,该方法在20% - 70%的案例中检测到正向选择。尽管这种错误检测的频率因树拓扑结构、分支长度和选择方案等因素而异,但分支位点似然法通常会给出误导性结果。因此,仅通过该方法检测正向选择是不可靠的。这种不可靠性可能源于其对该方法所做假设的违反过于敏感,例如位点间选择强度的某些分布以及同义替换和非同义替换的等转换/颠换比率。