Evidence map›Paper›PMID 41219154›Full record

ArticleG3 (Bethesda, Md.)2026

Pleiotropy and the evolutionary stability of plastic phenotypes: a geometric framework.

Charles Qiujie Wang, James G DuBose

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Charles Qiujie WangDepartment of Biology, Emory University, 1510 Clifton Rd NE #2006, Atlanta, GA 30322, United States.
James G DuBoseDepartment of Biology, Emory University, 1510 Clifton Rd NE #2006, Atlanta, GA 30322, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Phenotypic plasticity allows organisms to express different traits in response to different environmental or genetic conditions. Understanding the evolution of conditional phenotypes is challenging because they are not expressed by all members of a population, which allows for the accumulation of deleterious variation due to a reduced efficacy of purifying selection. Theory suggests pleiotropic effects help prevent the decay of conditional phenotypes by exposing the variation accrued in one context to the effects of purifying selection in an alternative context. However, existing frameworks for describing the evolutionary dynamics of conditional phenotypes are limited in their ability to flexibly model the complex pleiotropic architectures that often underlie conditional phenotypes. To help improve our understanding of the evolutionary stability of conditional phenotypes, here we describe a geometric model that allows for explicit modeling of different fitness optima for conditional and alternative phenotypes, as well as their underlying pleiotropic associations. Using stochastic simulations and mathematical analyses, we show that this model recapitulates and elaborates on existing predictions regarding the role of pleiotropy in maintaining conditional phenotypes. Specifically, we found that more pleiotropic conditional phenotypes experience decreased rates of decay in fitness over periods of inexpression, the effects of which are comparable for phenotypes that are spatially and temporally conditional. Furthermore, the functional form of the relationship between conditional phenotype expression pattern and decay rate is mediated by pleiotropic effect, which provides more explicit hypotheses of when pleiotropic constraint is expected to play a significant role in the evolutionary maintenance of conditional phenotypes. Finally, we found that when pleiotropic architectures evolve over periods of conditional phenotype inexpression, decoupling from other phenotypes readily evolves and facilitates decay in fitness.

Indexed as

Biological EvolutionEvolution, MolecularGenetic PleiotropyModels, GeneticPhenotypeComputer SimulationGenetic FitnessSelection, Geneticgeometric modelplasticitypleiotropy

Identifiers

PMID41219154
PMCPMC12774609

What Socratic holds

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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 Socratic graph.