Raw and transformed methylation sensitive amplification polymorphism (MSAP) data for Ciona intestinalis, and daily average temperature data for the ten sample sites along the Atlantic coast of Nova Scotia, Canada
Bibliographic record
Abstract
Biological invasion provides a promising system for studying rapid environmental accommodation and adaptation in the wild. Mounting evidence indicates that epigenetic modifications such as DNA methylation play crucial roles in rapid local accommodation and adaptation. Thus, we hypothesize that different local environments can trigger methylation divergence among marine invasive populations at fine geographical scales. In this study, we examined population methylation patterns in the invasive ascidian, Ciona intestinalis, along the Atlantic coast of Nova Scotia, Canada, where significant temperature differences exist at defined locations along the coast. Using the methylation-sensitive amplification polymorphism (MSAP) technique, we observed a high level of intra- and inter-population diversity, as well as significant population methylation differentiation. We identified a correlation between local environments and methylation patterns, and further consistently recovered 14 temperature-related subepiloci by using multiple analyses. All these results demonstrate a substantial role of temperature in shaping population methylation patterns and an epigenetic response to environmental changes during range expansions. The complex fine-scale methylation structures among populations of C. intestinalis observed in this study suggest that multiple biotic and abiotic factors, as well as their interactions, should be further investigated to reveal epigenetic mechanisms of local accommodation and adaptation during biological invasions in marine ecosystems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".