title: A model-based approach for detecting coevolving positions in a molecule.
abstract: We present a new method for detecting coevolving sites in molecules. The method relies on a set of aligned sequences (nucleic acid or protein) and uses Markov models of evolution to map the substitutions that occurred at each site onto the branches of the underlying phylogenetic tree. This mapping takes into account the uncertainty over ancestral states and among-site rate variation. We then build, for each site, a "substitution vector" containing the posterior estimates of the number of substitutions in each branch. The amount of coevolution for a pair of sites is then measured as the Pearson correlation coefficient between the two corresponding substitution vectors and compared to the expectation under the null hypothesis of independence. We applied the method to a 79-species bacterial ribosomal RNA data set, for which extensive structural characterization has been done over the last 30 years. More than 95% of the intramolecular predicted pairs of sites correspond to known interacting site pairs.
authors.affiliation: CNRS UMR 5171 Laboratoire Génome, Populations, Interactions, Adaptation, Université Montpellier II, Montpellier Cedex, France. julien.dutheil@univ-montp2.fr
authors.forename: Julien
authors.initials: J
authors.lastname: Dutheil
authors.forename: Tal
authors.initials: T
authors.lastname: Pupko
authors.forename: Alain
authors.initials: A
authors.lastname: Jean-Marie
authors.forename: Nicolas
authors.initials: N
authors.lastname: Galtier
mesh_terms: D001483:Base Sequence; D001499:Bayes Theorem; D003198:Computer Simulation; D004926:Escherichia coli; D019143:Evolution, Molecular; D014644:Genetic Variation; D008390:Markov Chains; D008957:Models, Genetic; D011487:Protein Conformation; D012335:RNA, Ribosomal; D012641:Selection, Genetic
chemical_list: D012335:RNA, Ribosomal