Epigenetic patterns in Atlantic herring (<i>Clupea harengus</i>): Temperature and photoperiod as environmental stressors during larval development
Bibliographic record
Abstract
Understanding the molecular mechanisms underlying individual responses to environmental changes is crucial for species conservation and management. Pelagic fishes including Atlantic herring (Clupea harengus) are of particular interest because of their key ecological and economic roles and their susceptibility to a changing ocean from global warming. Temperature and photoperiod have been linked with spawning time and location in adult herring, but no study has thus far investigated the role of environmental factors on gene regulation during the vulnerable early developmental stages. Here, we examine DNA methylation patterns of larval herring bred under two temperatures (11°C and 13°C) and photoperiod (6 and 12 h) regimes in a 2 × 2 factorial design. We found consistently high levels of global methylation across all individuals and a decline in global methylation with increased developmental stage that was more pronounced at 13°C (p ≤ 0.007) than at 11°C (p ≥ 0.21). Most of the differentially methylated sites were in exon and promoter regions for genes linked to metabolism and development, some of which were hypermethylated at higher temperature. These results demonstrate the important role of DNA methylation during larval development and suggest that this molecular mechanism might be key in regulating early-stage responses to environmental stressors in Atlantic herring.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".