title: Assessment of automated genotyping protocols as tools for surveillance of HIV-1 genetic diversity.
abstract: BACKGROUND
  The routine use of drug resistance testing provides an abundant source of HIV-1 sequence data. However, it is not clear how reliable standard genotyping of these sequences is for describing HIV-1 genetic variation and for detecting novel genetic variants and epidemiological trends.
  
  
  OBJECTIVE
  To compare assignment of HIV-1 resistance test sequences to reference strains across commonly used genotyping protocols.
  
  
  METHODS
  Subtype assignments were compared across three standard genotyping protocols for 10 537 resistance test sequences, representing approximately one-fifth of all reported infections in the United Kingdom. Sequences that were inconsistently genotyped across methods, or that were unassigned by at least one method, were examined for evidence of recombination using sliding-window-based approaches.
  
  
  RESULTS
  Although agreement across methods was high for subtypes B, C and H, it was generally much lower (< 50%) for other subtypes. Disagreement between methods typically involved closely related, but epidemiologically distinct, groups or involved a significant proportion ( approximately 12%) of divergent sequences in which analysis revealed widespread evidence of recombination and a remarkable diversity of unusual recombinant forms.
  
  
  CONCLUSIONS
  With frequent long-distance transfer of viral strains and widespread recombination between them, genetic and epidemiological relationships within HIV-1 are becoming increasingly complex. Current methods of subtype assignment vary in their ability to identify novel genetic variants and to distinguish epidemiologically distinct strains. Capturing meaningful epidemiological information from resistance test data will require a critical understanding of the methodologies used in order to appreciate the possible sources of error and misclassification.
authors.affiliation: Department of Infection, University College London, UK. r.gifford@ucl.ac.uk
authors.forename: Robert
authors.initials: R
authors.lastname: Gifford
authors.forename: Tulio
authors.initials: T
authors.lastname: de Oliveira
authors.forename: Andrew
authors.initials: A
authors.lastname: Rambaut
authors.forename: Richard E
authors.initials: RE
authors.lastname: Myers
authors.forename: Catherine V
authors.initials: CV
authors.lastname: Gale
authors.forename: David
authors.initials: D
authors.lastname: Dunn
authors.forename: Robert
authors.initials: R
authors.lastname: Shafer
authors.forename: Anne-Mieke
authors.initials: AM
authors.lastname: Vandamme
authors.forename: Paul
authors.initials: P
authors.lastname: Kellam
authors.forename: Deenan
authors.initials: D
authors.lastname: Pillay
mesh_terms: D030541:Databases, Genetic; D024882:Drug Resistance, Viral; D014644:Genetic Variation; D005838:Genotype; D015658:HIV Infections / Q000821:virology; D054303:HIV Reverse Transcriptase; D015497:HIV-1 / Q000145:classification / Q000187:drug effects / Q000235:genetics*; D006801:Humans; D010802:Phylogeny; D011995:Recombination, Genetic
chemical_list: D054303:HIV Reverse Transcriptase