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An Evolutionary Model-Based Algorithm for Accurate Phylogenetic Breakpoint Mapping and Subtype Prediction in HIV-1

Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1) are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and d...

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Autores principales: Kosakovsky Pond, Sergei L., Posada, David, Stawiski, Eric, Chappey, Colombe, Poon, Art F.Y., Hughes, Gareth, Fearnhill, Esther, Gravenor, Mike B., Leigh Brown, Andrew J., Frost, Simon D.W.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2776870/
https://www.ncbi.nlm.nih.gov/pubmed/19956739
http://dx.doi.org/10.1371/journal.pcbi.1000581
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author Kosakovsky Pond, Sergei L.
Posada, David
Stawiski, Eric
Chappey, Colombe
Poon, Art F.Y.
Hughes, Gareth
Fearnhill, Esther
Gravenor, Mike B.
Leigh Brown, Andrew J.
Frost, Simon D.W.
author_facet Kosakovsky Pond, Sergei L.
Posada, David
Stawiski, Eric
Chappey, Colombe
Poon, Art F.Y.
Hughes, Gareth
Fearnhill, Esther
Gravenor, Mike B.
Leigh Brown, Andrew J.
Frost, Simon D.W.
author_sort Kosakovsky Pond, Sergei L.
collection PubMed
description Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1) are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial) sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL) procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol) sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (≈5%) fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance of accurate, robust and extensible subtyping procedures is clear.
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spelling pubmed-27768702009-12-03 An Evolutionary Model-Based Algorithm for Accurate Phylogenetic Breakpoint Mapping and Subtype Prediction in HIV-1 Kosakovsky Pond, Sergei L. Posada, David Stawiski, Eric Chappey, Colombe Poon, Art F.Y. Hughes, Gareth Fearnhill, Esther Gravenor, Mike B. Leigh Brown, Andrew J. Frost, Simon D.W. PLoS Comput Biol Research Article Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1) are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial) sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL) procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol) sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (≈5%) fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance of accurate, robust and extensible subtyping procedures is clear. Public Library of Science 2009-11-26 /pmc/articles/PMC2776870/ /pubmed/19956739 http://dx.doi.org/10.1371/journal.pcbi.1000581 Text en Kosakovsky Pond et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Kosakovsky Pond, Sergei L.
Posada, David
Stawiski, Eric
Chappey, Colombe
Poon, Art F.Y.
Hughes, Gareth
Fearnhill, Esther
Gravenor, Mike B.
Leigh Brown, Andrew J.
Frost, Simon D.W.
An Evolutionary Model-Based Algorithm for Accurate Phylogenetic Breakpoint Mapping and Subtype Prediction in HIV-1
title An Evolutionary Model-Based Algorithm for Accurate Phylogenetic Breakpoint Mapping and Subtype Prediction in HIV-1
title_full An Evolutionary Model-Based Algorithm for Accurate Phylogenetic Breakpoint Mapping and Subtype Prediction in HIV-1
title_fullStr An Evolutionary Model-Based Algorithm for Accurate Phylogenetic Breakpoint Mapping and Subtype Prediction in HIV-1
title_full_unstemmed An Evolutionary Model-Based Algorithm for Accurate Phylogenetic Breakpoint Mapping and Subtype Prediction in HIV-1
title_short An Evolutionary Model-Based Algorithm for Accurate Phylogenetic Breakpoint Mapping and Subtype Prediction in HIV-1
title_sort evolutionary model-based algorithm for accurate phylogenetic breakpoint mapping and subtype prediction in hiv-1
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2776870/
https://www.ncbi.nlm.nih.gov/pubmed/19956739
http://dx.doi.org/10.1371/journal.pcbi.1000581
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