A Bayesian approach to the estimation of ancestral genome arrangements

We describe a Bayesian approach to estimate phylogeny and ancestral genome arrangements on the basis of genome arrangement data using a model in which gene inversion is the sole mechanism of change. While we have described a similar method to estimate phylogenetic relationships in the statistics literature, the novel contribution of the present work is the description of a method to compute probability distributions of ancestral genome arrangements. We assess the robustness of posterior distributions to different specifications of prior distributions and provide an empirical means to selecting a prior distribution. We note that parsimony approaches to ancestral reconstruction in the literature focus on the development of computationally efficient algorithms for searching for optimal ancestral genome arrangements, but, unlike Bayesian approaches, do not include assessment of uncertainty in these estimates. We compare and contrast a Bayesian approach with a parsimony approach to infer phylogenies and ancestral arrangements from genome arrangement data by reanalyzing a number of previously published data sets.