MBE Advance Access originally published online on March 10, 2004
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Mol. Biol. Evol. 21(7):1332-1339. 2004
DOI: 10.1093/molbev/msh117
© 2004 by the Society for Molecular Biology and Evolution. ISSN: 0737-4038
Research Article |
Frequent False Detection of Positive Selection by the Likelihood Method with Branch-Site Models
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor
E-mail: jianzhi{at}umich.edu.
Abstract
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.
Key Words: likelihood • computer simulation • positive selection • branch-site model • molecular evolution
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