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  • Key words: G + C content — Composition bias — Phylogenetic analysis — Mitochondrial genes  (1)
  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Journal of molecular evolution 48 (1999), S. 284-290 
    ISSN: 1432-1432
    Keywords: Key words: G + C content — Composition bias — Phylogenetic analysis — Mitochondrial genes
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract. It is now well-established that compositional bias in DNA sequences can adversely affect phylogenetic analysis based on those sequences. Phylogenetic analyses based on protein sequences are generally considered to be more reliable than those derived from the corresponding DNA sequences because it is believed that the use of encoded protein sequences circumvents the problems caused by nucleotide compositional biases in the DNA sequences. There exists, however, a correlation between AT/GC bias at the nucleotide level and content of AT- and GC-rich codons and their corresponding amino acids. Consequently, protein sequences can also be affected secondarily by nucleotide compositional bias. Here, we report that DNA bias not only may affect phylogenetic analysis based on DNA sequences, but also drives a protein bias which may affect analyses based on protein sequences. We present a striking example where common phylogenetic tools fail to recover the correct tree from complete animal mitochondrial protein-coding sequences. The data set is very extensive, containing several thousand sites per sequence, and the incorrect phylogenetic trees are statistically very well supported. Additionally, neither the use of the LogDet/paralinear transform nor removal of positions in the protein alignment with AT- or GC-rich codons allowed recovery of the correct tree. Two taxa with a large compositional bias continually group together in these analyses, despite a lack of close biological relatedness. We conclude that even protein-based phylogenetic trees may be misleading, and we advise caution in phylogenetic reconstruction using protein sequences, especially those that are compositionally biased.
    Type of Medium: Electronic Resource
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