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Cited by 223Evolution and Genetic DynamicsHIV Research and TreatmentGenomics and Phylogenetic Studies

Adaptation to different human populations by HIV-1 revealed by codon-based analyses

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Kosakovsky Pond, Sergei L, Frost, Simon D. W, Grossman, Zehava, Gravenor, Michael B, Richman, Douglas D, Brown, Andrew J. Leigh·2006·PLoS Computational Biology
DOI 10.1371/journal.pcbi.0020062PMC PMC1480537
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Abstract

Several codon-based methods are available for detecting adaptive evolution in protein-coding sequences, but to date none specifically identify sites that are selected differentially in two populations, although such comparisons between populations have been historically useful in identifying the action of natural selection. We have developed two fixed effects maximum likelihood methods: one for identifying codon positions showing selection patterns that persist in a population and another for detecting whether selection is operating differentially on individual codons of a gene sampled from two different populations. Applying these methods to two HIV populations infecting genetically distinct human hosts, we have found that few of the positively selected amino acid sites persist in the population; the other changes are detected only at the tips of the phylogenetic tree and appear deleterious in the long term. Additionally, we have identified seven amino acid sites in protease and reverse transcriptase that are selected differentially in the two samples, demonstrating specific population-level adaptation of HIV to human populations.

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  • Approaches estimating the number of sites under strong purifying selection in one region versus another and directly testing for differences in site-specific ! estimates are relevant primarily for comparing selective pressures across regions within a gene.

    “Relaxed selection across sites in a gene has also been explored by estimating the number of sites under strong purifying selection in one region versus another (Wertheim and Worobey 2009) and by directly testing for differences in sitespecific !estimates (Pond et al. 2006); however, such approaches are relevant primarily for comparing selective pressures across regions within a gene.”

    From RELAX: Detecting Relaxed Selection in a Phylogenetic Framework (2015) · cites this paper as Pond et al. 2006

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Authors
Kosakovsky Pond, S. L., Frost, S. D. W., Grossman, Z., Gravenor, M. B., Richman, D. D., & Brown, A. J. L.
Affiliations
  • University of California San Diego (US)
  • Israel Ministry of Health (IL)
  • University of Edinburgh (GB)
Corresponding author
Brown, Andrew J. Leigh
ORCID
Venue
PLoS Computational Biology
Publisher
Public Library of Science (PLoS)
Published
2006-06-23
Volume
2
Issue
6
Pages
e62
ISSN
  • 1553-734X (ISSN-L)
  • 1553-7358
DOI
10.1371/journal.pcbi.0020062
PMC
PMC1480537
OpenAlex
W1964475452
Cited by
223
References
1
Citations by year
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FWCI
5.61
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS Computational Biology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
  • TUScholarShare (Temple University) (submittedVersion, cc-by)
Funders
  • U.S. Department of Veterans Affairs
  • National Institutes of Health (AI-38858, AI 27670, AI47745, AI-36214, AI29164)
  • Center for AIDS Research, University of Washington
  • University of California, San Diego
  • National Institute of Allergy and Infectious Diseases (AI38858, R01AI057167, AI-47745, AI57167, R21AI047745, AI 43638, AI-29164, R56AI047745, AI-36214, R37AI029164, U01AI038858, R01AI047745, U01AI027670, U01AI043638, AI2-7670, P30AI036214)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
  • Life Sciences › Immunology and Microbiology › Virology › HIV Research and Treatment
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords
HIV-1, adaptive evolution, positive selection, HIV protease, HIV reverse transcriptase, amino acid sites, deleterious mutations
MeSH terms
Adaptation, Physiological, Codon, Biological Evolution, Genetics, Population, Humans, Selection, Genetic, Genetic Variation, HIV-1, HIV Infections, Sequence Analysis, DNA, Genetic Predisposition to Disease

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