Evidence map›Paper›PMID 41791251›Full record

ArticleEcotoxicology and environmental safety2026

Artificial selection for resistance to copper and off-target physiological and behavioral effects in Drosophila melanogaster.

Kazzrie A Arnold, Elizabeth R Everman

Abstract read
In one paragraph

Article in Ecotoxicology and environmental safety, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Kazzrie A ArnoldSchool of Biological Sciences, University of Oklahoma, 730 Van Vleet Oval, Norman, OK 73019, USA.
Elizabeth R EvermanSchool of Biological Sciences, University of Oklahoma, 730 Van Vleet Oval, Norman, OK 73019, USA. Electronic address: e.everman@ou.edu.

Funding

Linking genomic, physiological, and behavioral responses using a Drosophila model of heavy metal stressR00ES033257 · NIEHS · UNIVERSITY OF OKLAHOMA · PI EVERMAN, ELIZABETH · 2023 to 2025
$747k
NIEHS NIH HHS R00 ES033257
6 · The paper itself

Abstract

Pollution resulting from mining, industry, and agriculture has played an important role in shaping the evolution of diverse organisms. Heavy metal contamination is of particular concern due to the health effects for humans and cross-tolerance effects that may influence pesticide resistance. We used a replicated artificial selection approach to examine the response to copper selection in Drosophila melanogaster collected from a retired mine and active fruit orchard. We tracked shifts in resistance to the target trait, adult copper resistance, as well as off-target effects on cadmium and lead resistance, starvation resistance, lifespan, and feeding aversion to copper contaminated food. Selection for copper resistance increased the focal trait and slowed the loss of resistance to non-essential heavy metals. Starvation resistance increased in response to copper selection, but was not sufficient to explain the increase in copper resistance. We also found that lifespan responded to copper selection in flies collected from one of the two collection sites, suggesting that life history traits may be influenced by repeated heavy metal exposure. Future genomic analysis will help clarify the genetic control of the selection response. Together, our results underscore the complexity of adaptive shifts in polygenic traits and provide a basis for further exploration of costs and correlative change following copper selection.

Indexed as

CopperDrosophila melanogasterDrug ResistanceSelection, GeneticAnimalsBehavior, AnimalCadmiumFemaleLeadLongevityMaleCadmiumCopperLeadArtificial selectionCopperCross-toleranceHeavy metal resistance

Identifiers

PMID41791251
PMCPMC13010382

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.