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Whole proteome prokaryote phylogeny without sequence alignment: a K-string composition approach.

Ji Qi1, Bin Wang, Bai-Iin Hao

  • 1The Institute of Theoretical Physics, Academia Sinica, Beijing 100080, China, qiji@itp.ac.cn

Journal of Molecular Evolution
|January 27, 2004
PubMed
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This study introduces a novel method to determine microbial evolutionary relatedness using oligopeptide frequencies. This approach offers a robust alternative to traditional gene-based phylogenetic analyses.

Area of Science:

  • Microbial evolutionary biology
  • Bioinformatics
  • Computational genomics

Background:

  • Traditional phylogenetic reconstruction relies on gene selection and sequence alignment, which can be complex and ambiguous.
  • Comparing microbial organisms often involves challenges due to varying gene content and sequence lengths.

Purpose of the Study:

  • To propose a systematic method for inferring evolutionary relatedness of microbial organisms.
  • To offer an alternative to gene-based phylogenetic reconstruction using proteome oligopeptide content.

Main Methods:

  • The method analyzes the frequency of amino acid K-strings (oligopeptides) within complete proteomes.
  • The length of the oligopeptides (K) acts as a tunable parameter to adjust the resolution power of the analysis.
  • Phylogenetic trees are constructed based on these oligopeptide frequencies.

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Main Results:

  • The proposed method circumvents ambiguities associated with gene selection and sequence alignment.
  • Increasing the oligopeptide length (K) leads to the convergence of tree topologies.
  • Application to 109 organisms (16 Archaea, 87 Bacteria, 6 Eukarya) produced an unrooted tree largely consistent with established phylogenetic relationships.

Conclusions:

  • Oligopeptide frequency analysis provides a viable and systematic approach to microbial phylogeny.
  • The method demonstrates strong agreement with SSU rRNA-based phylogenies, particularly in lower taxa.
  • This technique offers a robust alternative for reconstructing the microbial 'tree of life'.