Sliding MinPD: building evolutionary networks of serial samples via an automated recombination detection approach

Bioinformatics. 2007 Nov 15;23(22):2993-3000. doi: 10.1093/bioinformatics/btm413. Epub 2007 Aug 23.


Motivation: Traditional phylogenetic methods assume tree-like evolutionary models and are likely to perform poorly when provided with sequence data from fast-evolving, recombining viruses. Furthermore, these methods assume that all the sequence data are from contemporaneous taxa, which is not valid for serially-sampled data. A more general approach is proposed here, referred to as the Sliding MinPD method, that reconstructs evolutionary networks for serially-sampled sequences in the presence of recombination.

Results: Sliding MinPD combines distance-based phylogenetic methods with automated recombination detection based on the best-known sliding window approaches to reconstruct serial evolutionary networks. Its performance was evaluated through comprehensive simulation studies and was also applied to a set of serially-sampled HIV sequences from a single patient. The resulting network organizations reveal unique patterns of viral evolution and may help explain the emergence of disease-associated mutants and drug-resistant strains with implications for patient prognosis and treatment strategies.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Base Sequence
  • Chromosome Mapping / methods*
  • DNA Mutational Analysis / methods*
  • Evolution, Molecular*
  • Genome, Viral / genetics*
  • Molecular Sequence Data
  • Phylogeny
  • Recombination, Genetic / genetics*
  • Sequence Alignment / methods*
  • Sequence Analysis, DNA / methods*