title: Genome phylogeny based on short-range correlations in DNA sequences.
abstract: The surprising fact that global statistical properties computed on a genomewide scale may reveal species information has first been observed in studies of dinucleotide frequencies. Here we will look at the same phenomenon with a totally different statistical approach. We show that patterns in the short-range statistical correlations in DNA sequences serve as evolutionary fingerprints of eukaryotes. All chromosomes of a species display the same characteristic pattern, markedly different from those of other species. The chromosomes of a species are sorted onto the same branch of a phylogenetic tree due to this correlation pattern. The average correlation between nucleotides at a distance k is quantified in two independent ways: (i) by estimating it from a higher-order Markov process and (ii) by computing the mutual information function at a distance k. We show how the quality of phylogenetic reconstruction depends on the range of correlation strengths and on the length of the underlying sequence segment. This concept of the correlation pattern as a phylogenetic signature of eukaryote species combines two rather distant domains of research, namely phylogenetic analysis based on molecular observation and the study of the correlation structure of DNA sequences.
authors.affiliation: Bioinformatics Group, Department of Biology, Darmstadt University of Technology, D-64287 Darmstadt, Germany.
authors.forename: Manuel
authors.initials: M
authors.lastname: Dehnert
authors.forename: Rainer
authors.initials: R
authors.lastname: Plaumann
authors.forename: Werner E
authors.initials: WE
authors.lastname: Helm
authors.forename: Marc-Th
authors.initials: MT
authors.lastname: Hütt
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods; D016678:Genome; D006801:Humans; D010802:Phylogeny; D010944:Plants / Q000235:genetics; D017422:Sequence Analysis, DNA / Q000379:methods