Evidence map›Paper›PMID 27661078›Full record

ArticlePLoS genetics2016

Experimental Evolution of Gene Expression and Plasticity in Alternative Selective Regimes.

Yuheng Huang, Aneil F Agrawal

Abstract read
In one paragraph

Article in PLoS genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

43 citing papers in PubMed.

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  14. How predictable is adaptation from standing genetic variation? Experimental evolution inPhilosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Review
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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

2 authors.

Yuheng HuangDepartment of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada.
Aneil F AgrawalDepartment of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Little is known of how gene expression and its plasticity evolves as populations adapt to different environmental regimes. Expression is expected to evolve adaptively in all populations but only those populations experiencing environmental heterogeneity are expected to show adaptive evolution of plasticity. We measured the transcriptome in a cadmium-enriched diet and a salt-enriched diet for experimental populations of Drosophila melanogaster that evolved for ~130 generations in one of four selective regimes: two constant regimes maintained in either cadmium or salt diets and two heterogeneous regimes that varied either temporally or spatially between the two diets. For populations evolving in constant regimes, we find a strong signature of counter-gradient evolution; the evolved expression differences between populations adapted to alternative diets is opposite to the plastic response of the ancestral population that is naïve to both diets. Based on expression patterns in the ancestral populations, we identify a set of genes for which we predict selection in heterogeneous regimes to result in increases in plasticity and we find the expected pattern. In contrast, a set of genes where we predicted reduced plasticity did not follow expectation. Nonetheless, both gene sets showed a pattern consistent with adaptive expression evolution in heterogeneous regimes, highlighting the difference between observing "optimal" plasticity and improvements in environment-specific expression. Looking across all genes, there is evidence in all regimes of differences in biased allele expression across environments ("allelic plasticity") and this is more common among genes with plasticity in total expression.

Identifiers

PMID27661078
PMCPMC5035091

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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.