Biological Evolution and Statistical Physics

Volume 585 of the series Lecture Notes in Physics pp 148-161


Accounting for phylogenetic uncertainty in comparative studies of evolution and adaptation

  • Mark PagelAffiliated withSchool of Animal and Microbial Sciences, University of Reading
  • , François LutzoniAffiliated withDepartment of Biology, Duke University

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We describe the application of Markov Chain Monte Carlo (MCMC) methods to two fundamental problems in evolutionary biology. Evolutionary biologists frequently wish to investigate the evolution of traits across a range of species. This is known as a comparative study. Comparative studies require constructing a phylogeny of the species and then investigating the evolutionary transitions in the trait on that phylogeny. A difficulty with this approach is that phylogenies themselves are seldom known with certainty and different phylogenies can give different answers to the comparative hypotheses. MCMC methods make it possible to avoid both of these problems by constructing a random sample of phylogenies from the universe of possible phylogenetic trees for a given data set. Once this sample is obtained the comparative hypotheses can be investigated separately in each tree in the MCMC sample. Given the statistical properties of the sample of trees - trees are sampled in proportion to the probability under a model of evolution - the combined results across trees can be interpreted as being independent of the underlying phylogeny. Thus, investigators can test comparative hypotheses without the real concern that results are valid only for the particular tree used in the investigation. We illustrate these ideas with an example from the evolution of lichen formation in fungi.