Comparative study of methods for detecting sequence compartmentalization in human immunodeficiency virus type 1

TitleComparative study of methods for detecting sequence compartmentalization in human immunodeficiency virus type 1
Publication TypeJournal Article
Year of Publication2007
AuthorsZarate, S, Pond, SLK, Shapshak, P, Frost, SD
JournalJournal of Virology
Date Published2007
KeywordsBrain, Central Nervous System, Databases, Evolution, External, Female, Genetic, Genetic Techniques, Genitalia, HIV Infections, HIV-1, Humans, Male, Models, Molecular, Phylogeny, Recombination, Statistical

Human immunodeficiency virus (HIV) infects different organs and tissues. During these infection events, subpopulations of HIV type 1 (HIV-1) develop and, if viral trafficking is restricted between subpopulations, the viruses can follow independent evolutionary histories, i.e., become compartmentalized. This phenomenon is usually detected via comparative sequence analysis and has been reported for viruses isolated from the central nervous system (CNS) and the genital tract. Several approaches have been proposed to study the compartmentalization of HIV sequences, but to date, no rigorous comparison of the most commonly employed methods has been made. In this study, we systematically compared inferences made by six different methods for detecting compartmentalization based on three data sets: (i) a sample of 45 patients with sequences gathered from the CNS, (ii) sequences from the female genital tract of 18 patients, and (iii) a set of simulated sequences. We found that different methods often reached contradictory conclusions. Methods based on the topology of a phylogenetic tree derived from clonal sequences were generally more sensitive in detecting compartmentalization than those that relied solely upon pairwise genetic distances between sequences. However, as the branching structure in a phylogenetic tree is often uncertain, especially for short, low-diversity, or recombinant sequences, tree-based approaches may need to be modified to take phylogenetic uncertainty into account. Given the frequently discordant predictions of different methods and the strengths and weaknesses of each particular methodology, we recommend that a suite of several approaches be used for reliable inference of compartmentalized population structure.