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Compositional statistics: An improvement of evolutionary parsimony and its application to deep branches in the tree of life
Authors:Arend Sidow  Allan C Wilson
Institution:(1) Division of Biochemistry and Molecular Biology, University of California, 94720 Berkeley, California, USA
Abstract:Summary We present compositional statistics, a new method of phylogenetic inference, which is an extension of evolutionary parsimony. Compositional statistics takes account of the base composition of the compared sequences by using nucleotide positions that evolutionary parsimony ignores. It shares with evolutionary parsimony the features of rate invariance and the fundamental distinction between transitions and transversions. Of the presently available methods of phylogenetic inference, compositional statistics is based on the fewest and mildest assumptions about the mode of DNA sequence evolution. It is therefore applicable to phylogenetic studies of the most distantly related organisms or molecules. This was illustrated by analyzing conservative positions in the DNA sequences of the large subunit of RNA polymerase from three archaebacterial groups, a eubacterium, a chloroplast, and the three eukaryotic polymerases. Internally consistent results, which are in accord with our knowledge of organelle origin and archaebacterial physiology, were achieved.
Keywords:Evolutionary trees  Base composition  Transversional equilibrium  Endosymbiont hypothesis  Statistical testing  RNA polymerase  Archaebacteria  Eubacteria  Eukaryotes
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