Evidence map›Paper›PMID 18535013›Full record

ArticleMolecular biology and evolution2008

Compensatory evolution in RNA secondary structures increases substitution rate variation among sites.

Jennifer L Knies, Kristen K Dang, Todd J Vision, Noah G Hoffman, Ronald Swanstrom, Christina L Burch

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in Molecular biology and evolution, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
0.4field-weighted citation impact, top 35% of its field
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

16 citing papers in PubMed, 84 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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  6. Article
  7. RNA Secondary Structure Alteration Caused by Single Nucleotide Variants.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
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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

6 authors at 1 institution in 1 country.

Jennifer L KniesDepartment of Biology, University of North Carolina, Chapel Hill, USA. Jennifer_Knies@brown.edu
Kristen K Dang
Todd J Vision
Noah G Hoffman
Ronald Swanstrom
Christina L Burch
University of North Carolina at Chapel Hill · US

Funding

Training in Sexually Transmitted Infections and HIVT32AI007001 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SENA-SOBERANO, ARLENE C. · 1985 to 2025
$10.9M
Molecular Biology of Viral Diseases Predoctoral Training GrantT32AI007419 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Mark T Heise, CARY A MOODY · 1993 to 2026
$4.7M
Biological properties of HIV-1 V3 evolutionary variantsR37AI044667 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SWANSTROM, RONALD I · 2005 to 2014
$3.4M
BIOLOGICAL PROPERTIES OF HIV1 V3 EVOLUTIONARY VARIANTSR01AI044667 · NIAID · UNIVERSITY OF NORTH CAROLINA CHAPEL HILL · PI SWANSTROM, RONALD I · 1999 to 2002
$800k
Phylogenetic Analysis with Complex Genome Rearrangement EventsR01GM078991 · NIGMS · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI TANG, JIJUN · 2006 to 2009
$715k
Viral evolution:mutational effects and interactionsR01GM067940 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BURCH, CHRISTINA L. · 2003 to 2007
$711k
Biological Properties of HIV-1 V3 Evolutionary VariantsR56AI044667 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SWANSTROM, RONALD I · 2016 to 2016
$396k
NIAID NIH HHS AI44667NIAID NIH HHS R01 AI044667NIAID NIH HHS R37 AI044667NIAID NIH HHS R56 AI044667NIAID NIH HHS T32 AI007001NIAID NIH HHS T32 AI007419NIAID NIH HHS T32-AI007419NIAID NIH HHS T32-AI07001NIGMS NIH HHS GM067940NIGMS NIH HHS R01 GM067940NIGMS NIH HHS R01 GM078991
6 · The paper itself

Abstract

There is growing evidence that interactions between biological molecules (e.g., RNA-RNA, protein-protein, RNA-protein) place limits on the rate and trajectory of molecular evolution. Here, by extending Kimura's model of compensatory evolution at interacting sites, we show that the ratio of transition to transversion substitutions (kappa) at interacting sites should be equal to the square of the ratio at independent sites. Because transition mutations generally occur at a higher rate than transversions, the model predicts that kappa should be higher at interacting sites than at independent sites. We tested this prediction in 10 RNA secondary structures by comparing phylogenetically derived estimates of kappa in paired sites within stems (kappa(p)) and unpaired sites within loops (kappa(u)). Eight of the 10 structures showed an excellent match to the quantitative predictions of the model, and 9 of the 10 structures matched the qualitative prediction kappa(p) > kappa(u). Only the Rev response element from the human immunovirus (HIV) genome showed the reverse pattern, with kappa(p) < kappa(u). Although a variety of evolutionary forces could produce quantitative deviations from the model predictions, the reversal in magnitude of kappa(p) and kappa(u) could be achieved only by violating the model assumption that the underlying transition (or transversion) mutation rates were identical in paired and unpaired regions of the molecule. We explore the ability of the APOBEC3 enzymes, host defense mechanisms against retroviruses, which induce transition mutations preferentially in single-stranded regions of the HIV genome, to explain this exception to the rule. Taken as a whole, our findings suggest that kappa may have utility as a simple diagnostic to evaluate proposed secondary structures.

Indexed as

Evolution, MolecularModels, GeneticNucleic Acid ConformationPhylogenyAPOBEC DeaminasesBayes TheoremComputational BiologyCytidine DeaminaseCytosine DeaminaseGenes, envMutationRNASequence AlignmentAPOBEC3 proteins, humanAPOBEC DeaminasesCytidine DeaminaseCytosine DeaminaseRNA

Identifiers

PMID18535013
PMCPMC2734131
OpenAlexW2142847509

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.