Evidence map›Paper›PMID 23986591›Full record

ArticleJournal of virology2013

Quantifying selection against synonymous mutations in HIV-1 env evolution.

Fabio Zanini, Richard A Neher

Abstract read
In one paragraph

Article in Journal of virology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed.

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  16. Neutral Theory and Rapidly Evolving Viral Pathogens.Molecular biology and evolution · 2018
    Article
  17. The Puzzle of HIV Neutral and Selective Evolution.Molecular biology and evolution · 2018
    Article
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Fabio ZaniniEvolutionary Dynamics and Biophysics Group and Max Planck Institute for Developmental Biology, Tübingen, Germany.
Richard A Neher

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intrapatient evolution of human immunodeficiency virus type 1 (HIV-1) is driven by the adaptive immune system resulting in rapid change of HIV-1 proteins. When cytotoxic CD8(+) T cells or neutralizing antibodies target a new epitope, the virus often escapes via nonsynonymous mutations that impair recognition. Synonymous mutations do not affect this interplay and are often assumed to be neutral. We test this assumption by tracking synonymous mutations in longitudinal intrapatient data from the C2-V5 part of the env gene. We find that most synonymous variants are lost even though they often reach high frequencies in the viral population, suggesting a cost to the virus. Using published data from SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) assays, we find that synonymous mutations that disrupt base pairs in RNA stems flanking the variable loops of gp120 are more likely to be lost than other synonymous changes: these RNA hairpins might be important for HIV-1. Computational modeling indicates that, to be consistent with the data, a large fraction of synonymous mutations in this genomic region need to be deleterious with a cost on the order of 0.002 per day. This weak selection against synonymous substitutions does not result in a strong pattern of conservation in cross-sectional data but slows down the rate of evolution considerably. Our findings are consistent with the notion that large-scale patterns of RNA structure are functionally relevant, whereas the precise base pairing pattern is not.

Indexed as

Mutation, MissenseSelection, Geneticenv Gene Products, Human Immunodeficiency VirusEvolution, MolecularHIV-1HumansLongitudinal StudiesNucleic Acid ConformationRNA, Viralenv Gene Products, Human Immunodeficiency VirusRNA, Viral

Identifiers

PMID23986591
PMCPMC3807363

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.