Evidence map›Paper›PMID 24727706›Full record

ArticleGenomics

Ascertaining regions affected by GC-biased gene conversion through weak-to-strong mutational hotspots.

Valer Gotea, Laura Elnitski

Abstract read
In one paragraph

Article in Genomics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Valer GoteaNational Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA. Electronic address: vgotea@nih.gov.
Laura ElnitskiNational Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.

Funding

Regulatory and epigenetic landscapes reveal biological processes, disease mechanisms and diagnostic markersZIAHG200323 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI ELNITSKI, LAURA L · 2009 to 2025
$27.6M
Intramural NIH HHS Z99 HG999999
6 · The paper itself

Abstract

A major objective for evolutionary biology is to identify regions affected by positive selection. High dN/dS values for proteins and accelerated lineage-specific substitution rates for non-coding regions are considered classic signatures of positive selection. However, these could also be the result of non-adaptive phenomena, such as GC-biased gene conversion (gBGC), which favors the fixation of strong (C/G) over weak (A/T) nucleotides. Recent estimates indicate that gBGC affected up to 20% of regions with signatures of positive selection. Here we evaluate the impact of gBGC through its molecular signature of weak-to-strong mutational hotspots. We implemented specific modifications to the test proposed by Tang and Lewontin (1999) for identifying regions of differential variability and applied it to regions previously investigated for the influence of gBGC. While we found significant agreement with previous reports, our results suggest a smaller influence of gBGC than previously estimated, warranting further development of methods for its detection.

Indexed as

Gene ConversionMutation RateAlgorithmsAnimalsBase CompositionBase SequenceComputer SimulationConsensus SequenceDNA Mutational AnalysisGenome, HumanHumansModels, GeneticMolecular Sequence DataPituitary Adenylate Cyclase-Activating PolypeptideSequence AlignmentADCYAP1 protein, humanPituitary Adenylate Cyclase-Activating PolypeptideGC-biased gene conversion (gBGC)Modified Tang–Lewontin testMutation hotspotsPositive selectionWeak-to-strong mutation bias

Identifiers

PMID24727706
PMCPMC4527313

What OpenQuestion holds

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Registered trials

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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.