Effect of a locally adapted genome on environmentally induced epigenetic variation
Bibliographic record
Abstract
Both genetic variation and environmentally induced epigenetic changes allow organisms to persist through the heterogeneity of their habitats.Selection on genetic variation can promote local adaptation of populations.However, in absence of genetic variation, clonal organisms mostly rely on epigenetics to respond to environmental heterogeneity.We used the potential of unisexual organisms in incorporating their host genome, to empirically assess whether the presence of a locally adapted genome affects environmentally induced epigenetic changes in clonal organisms.We addressed this problematic by using unisexual lineages of the kleptogen vertebrate Ambystoma laterale-jeffersonianum complex that can optionally incorporate genetic material from locally adapted sexual hosts through genomic exchanges.More specifically, we compared environmentally induced epigenetic changes between lineages strictly reproducing clonally vs. those incorporating a locally adapted genome.The results revealed that both lineage and sample site components, as well as their interaction, affected epigenetic variation.When lineages were analysed separately, differences among sample sites were only detected in lineages impervious to genomic exchanges.Sample sites had no significant effect on the epigenetic variation of lineages that performed genomic exchanges.These results suggest that environmentally induced epigenetic variation among sites depends more on the lack of locally adapted alleles than on the level of genetic variation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".