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通过分支位点法和位点预测法识别正选择的可靠性。

Reliabilities of identifying positive selection by the branch-site and the site-prediction methods.

作者信息

Nozawa Masafumi, Suzuki Yoshiyuki, Nei Masatoshi

机构信息

Institute of Molecular Evolutionary Genetics and Department of Biology, Pennsylvania State University, USA.

出版信息

Proc Natl Acad Sci U S A. 2009 Apr 21;106(16):6700-5. doi: 10.1073/pnas.0901855106. Epub 2009 Apr 1.

Abstract

Natural selection operating in protein-coding genes is often studied by examining the ratio (omega) of the rates of nonsynonymous to synonymous nucleotide substitution. The branch-site method (BSM) based on a likelihood ratio test is one of such tests to detect positive selection for a predetermined branch of a phylogenetic tree. However, because the number of nucleotide substitutions involved is often very small, we conducted a computer simulation to examine the reliability of BSM in comparison with the small-sample method (SSM) based on Fisher's exact test. The results indicate that BSM often generates false positives compared with SSM when the number of nucleotide substitutions is approximately 80 or smaller. Because the omega value is also used for predicting positively selected sites, we examined the reliabilities of the site-prediction methods, using nucleotide sequence data for the dim-light and color vision genes in vertebrates. The results showed that the site-prediction methods have a low probability of identifying functional changes of amino acids experimentally determined and often falsely identify other sites where amino acid substitutions are unlikely to be important. This low rate of predictability occurs because most of the current statistical methods are designed to identify codon sites with high omega values, which may not have anything to do with functional changes. The codon sites showing functional changes generally do not show a high omega value. To understand adaptive evolution, some form of experimental confirmation is necessary.

摘要

在蛋白质编码基因中起作用的自然选择通常通过检查非同义核苷酸替换率与同义核苷酸替换率的比值(ω)来进行研究。基于似然比检验的分支位点法(BSM)是检测系统发育树预定分支上正选择的此类检验方法之一。然而,由于所涉及的核苷酸替换数量通常非常少,我们进行了计算机模拟,以检验BSM与基于费舍尔精确检验的小样本方法(SSM)相比的可靠性。结果表明,当核苷酸替换数量约为80或更少时,与SSM相比,BSM经常产生假阳性。由于ω值也用于预测正选择位点,我们使用脊椎动物暗视觉和色觉基因的核苷酸序列数据检验了位点预测方法的可靠性。结果表明,位点预测方法识别实验确定的氨基酸功能变化的概率较低,并且经常错误地识别其他氨基酸替换不太可能重要的位点。这种低预测率的出现是因为当前大多数统计方法旨在识别具有高ω值的密码子位点,而这些位点可能与功能变化无关。显示功能变化的密码子位点通常不会显示高ω值。为了理解适应性进化,某种形式的实验验证是必要的。

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