Title: Assessment of automated genotyping protocols as tools for surveillance of HIV-1 genetic diversity
Authors: Gifford, Robert ×
de Oliveira, Tulio
Rambaut, Andrew
Myers, Richard E
Gale, Catherine V
Dunn, David
Shafer, Robert
Vandamme, Anne-Mieke
Kellam, Paul
Pillay, Deenan #
Issue Date: Jul-2006
Publisher: Gower Academic Journals
Series Title: AIDS vol:20 issue:11 pages:1521-1529
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. OBJECTIVES: 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.
ISSN: 0269-9370
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Laboratory of Clinical and Epidemiological Virology (Rega Institute)
× corresponding author
# (joint) last author

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