MétaCan
Menu
Back to cohort
Record W4408316629 · doi:10.1093/evolut/qpaf050

Transgenerational epigenetic inheritance increases trait variation but is not adaptive

2025· article· en· W4408316629 on OpenAlexafffund
René S. Shahmohamadloo, John M. Fryxell, Seth M. Rudman

Bibliographic record

VenueEvolution · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsUniversity of GuelphUniversity of Victoria
FundersNational Institute of General Medical SciencesNational Institutes of HealthCanada First Research Excellence Fund
KeywordsBiologyEpigeneticsPhenotypic plasticityTransgenerational epigeneticsTraitInheritance (genetic algorithm)Evolutionary biologyMaternal effectGeneticsOffspringEcologyGene

Abstract

fetched live from OpenAlex

Understanding organismal responses to environmental change is a central goal of biology with profound implications for the conservation of biodiversity. Widespread evidence of epigenetic modifications in response to environmental stress, including those inherited across generations, has led to considerable speculation about their role in organismal responses to environmental change. Yet, the magnitude and fitness consequences of epigenetic marks carried beyond maternal inheritance are largely unknown. Here, we tested how transgenerational epigenetic inheritance (TEI) shapes the phenotypic response of Daphnia clones to the environmental stressor Microcystis. We split individuals from each of eight genotypes into exposure and control treatments (P0 generation) and tracked the fitness of their descendants to the F3 generation. We found transgenerational epigenetic exposure to Microcystis led to reduced survival and growth rates and no consistent effect on offspring production. TEI was associated with increases in trait variance, suggesting the potential for heritable bet hedging driven by TEI. Taken together, our results demonstrate that TEI causes substantial-but not adaptive-trait shifts, suggesting transgenerational adaptive plasticity may be rare.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.884
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.237
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueEvolutionSame topicEvolution and Genetic DynamicsFrench-language works237,207