Segmenting bacterial and viral DNA sequence alignments with a trans-dimensional phylogenetic factorial hidden Markov model

The traditional approach to phylogenetic inference assumes that a single phylogenetic tree can represent the relationships and divergence between the taxa. However, taxa sequences exhibit varying levels of conservation, e.g. because of regulatory elements and active binding sites. Also, certain bact...

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Veröffentlicht in:Applied statistics 2009-07, Vol.58 (3), p.307-327
Hauptverfasser: Lehrach, Wolfgang P., Husmeier, Dirk
Format: Artikel
Sprache:eng
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Zusammenfassung:The traditional approach to phylogenetic inference assumes that a single phylogenetic tree can represent the relationships and divergence between the taxa. However, taxa sequences exhibit varying levels of conservation, e.g. because of regulatory elements and active binding sites. Also, certain bacteria and viruses undergo interspecific recombination, where different strains exchange or transfer DNA subsequences, leading to a tree topology change. We propose a phylogenetic factorial hidden Markov model to detect recombination and rate variation simultaneously. This is applied to two DNA sequence alignments: one bacterial (Neisseria) and another of type 1 human immunodeficiency virus. Inference is carried out in the Bayesian framework, using reversible jump Markov chain Monte Carlo sampling.
ISSN:0035-9254
1467-9876
DOI:10.1111/j.1467-9876.2008.00648.x