Nature Genetics
37, 441 - 444 (2005)
Published online: 20 March 2005; | doi:10.1038/ng1535
An empirical test of the mutational landscape model of adaptation using a single-stranded DNA virusDarin R Rokyta1, 2, 3, Paul Joyce2, 3, 4, 5, S Brian Caudle1, 6
& Holly A Wichman1, 2, 31
Department of Biological Sciences, University of Idaho, Moscow, Idaho 83844, USA. 2
Program in Bioinformatics and Computational Biology, University of Idaho, Moscow, Idaho 83844, USA. 3
Initiative for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, Idaho 83844, USA. 4
Department of Mathematics, University of Idaho, Moscow, Idaho 83844, USA. 5
Department of Statistics, University of Idaho, Moscow, Idaho 83844, USA. 6
Present address: Department of Biological Sciences, Section of Integrative Biology, University of Texas, Austin, Texas 78712, USA.
Correspondence should be addressed to Holly A Wichman hwichman@uidaho.eduThe primary impediment to formulating a general theory for adaptive evolution has been the unknown distribution of fitness effects for new beneficial mutations1. By applying extreme value theory2, Gillespie circumvented this issue in his mutational landscape model for the adaptation of DNA sequences3,
4,
5, and Orr recently extended Gillespie's model1,
6, generating testable predictions regarding the course of adaptive evolution. Here we provide the first empirical examination of this model, using a single-stranded DNA bacteriophage related to  X174, and find that our data are consistent with Orr's predictions, provided that the model is adjusted to incorporate mutation bias. Orr's work suggests that there may be generalities in adaptive molecular evolution that transcend the biological details of a system, but we show that for the model to be useful as a predictive or inferential tool, some adjustments for the biology of the system will be necessary.
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