Scientists at Penn State and the National Institute of Genetics in Japan have demonstrated that several statistical methods commonly used by biologists to detect natural selection at the molecular level tend to produce incorrect results.”Our finding means that hundreds of published studies on natural selection may have drawn incorrect conclusions,” said Masatoshi Nei, Penn State Evan Pugh Professor of Biology and the team’s leader.
… “Of course, we would never say that natural selection is not happening, but we are saying that these statistical methods can lead scientists to make erroneous inferences,” he said.
… “The methods assume that when natural selection occurs the number of nucleotide substitutions that lead to changes in amino acids is significantly higher than the number of nucleotide substitutions that do not result in amino acid changes,” he said. “But this assumption may be wrong. Actually, the majority of amino acid substitutions do not lead to functional changes, and the adaptive change of a protein often occurs by a rare amino acid substitution. For this reason, statistical methods may give erroneous conclusions.”
… To demonstrate the faultiness of the statistical methods, Nei’s team compiled data collected by their Emory University colleague, Shozo Yokoyama, on the genes that control the abilities of fish to see light at different water depths and on the genes that control color vision in a variety of animals. The team used these data to compare statistically predicted sites of natural selection with experimentally determined sites. They found that the statistical methods rarely predicted the actual sites of natural selection, which had been identified by Yokoyama through experime “In some cases, statistical method completely failed to identify the true sites where natural selection occurred …