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Reconstruction of ancestral nucleotide sequences and estimation of substitution frequencies in a star phylogeny

Summary: Reconstruction of ancestral nucleotide sequences and estimation of
substitution frequencies in a star phylogeny
Peter F. Arndt
Max Planck Institute for Molecular Genetics, Ihnestr. 63, 14195 Berlin, Germany
Received 13 June 2006; received in revised form 15 November 2006; accepted 15 November 2006
Received by M. Batzer
Available online 14 December 2006
Maximum likelihood phylogeny reconstruction methods are widely used in uncovering and assessing the evolutionary history and relationships
of natural systems. However, several simplifying assumptions commonly made in this analysis limit the explanatory power of the results obtained.
We present an algorithm that performs the phylogenetic analysis without making the common assumptions for sequence data from at least three
leaf nodes in a star phylogeny. In particular, the underlying nucleotide substitution model does not have to be reversible and may include neighbor-
dependent processes like the CpG methylation deamination process (CpG-effect). The base composition of the sequences at the external nodes and
the one of the ancestral sequence may be different from each other and they do not have to be stationary state distributions of the corresponding
substitution model. The algorithm is able to reconstruct the ancestral base composition and accurately estimate substitution frequencies in the
branches of the star phylogeny. Extensive tests on simulated data validate the very favorable performance of the algorithm. As an application we
present the analysis of aligned genomic sequences from human, mouse, and dog. Different substitution pattern can be observed in the three
© 2006 Elsevier B.V. All rights reserved.
Keywords: Phylogeny; Ancient DNA reconstruction; Nucleotide substitution; CpG-effect


Source: Arndt, Peter - Max-Planck-Institut für molekulare Genetik
Spang, Rainer - Computational Molecular Biology Group, Max-Planck-Institut für molekulare Genetik


Collections: Biology and Medicine; Biotechnology; Computer Technologies and Information Sciences; Physics