Evidence map›Paper›PMID 25926696›Full record

ArticleBiology letters2015

The effects of sex-biased gene expression and X-linkage on rates of adaptive protein sequence evolution in Drosophila.

Victoria Ávila, José L Campos, Brian Charlesworth

Abstract read
In one paragraph

Article in Biology letters, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
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  9. Estimating the parameters of background selection and selective sweeps inProceedings of the National Academy of Sciences of the United States of America · 2017
    Article
  10. 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

3 authors.

Victoria ÁvilaInstitute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, UK.
José L CamposInstitute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, UK.
Brian CharlesworthInstitute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, UK brian.charlesworth@ed.ac.uk.

Funding

Biotechnology and Biological Sciences Research Council BB/G003076/1Biotechnology and Biological Sciences Research Council BB/H006028/1
6 · The paper itself

Abstract

A faster rate of adaptive evolution of X-linked genes compared with autosomal genes may be caused by the fixation of new recessive or partially recessive advantageous mutations (the Faster-X effect). This effect is expected to be largest for mutations that affect only male fitness and absent for mutations that affect only female fitness. We tested these predictions in Drosophila melanogaster by using genes with different levels of sex-biased expression and by estimating the extent of adaptive evolution of non-synonymous mutations from polymorphism and divergence data. We detected both a Faster-X effect and an effect of male-biased gene expression. There was no evidence for a strong association between the two effects--modest levels of male-biased gene expression increased the rate of adaptive evolution on both the autosomes and the X chromosome, but a Faster-X effect occurred for both unbiased genes and female-biased genes. The rate of genetic recombination did not influence the magnitude of the Faster-X effect, ruling out the possibility that it reflects less Hill-Robertson interference for X-linked genes.

Indexed as

Genes, InsectGenes, X-LinkedPolymorphism, GeneticAdaptation, BiologicalAnimalsDrosophila melanogasterDrosophila ProteinsEvolution, MolecularFemaleGene ExpressionMaleSex FactorsDrosophila ProteinsDrosophilaFaster-X effectrecombinationsex-biased gene expressionsexual selection

Identifiers

PMID25926696
PMCPMC4424624

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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.