Data from: Similarities in temperature-dependent gene expression plasticity across time-scales in threespine stickleback (Gasterosteus aculeatus)
Bibliographic record
Abstract
Phenotypic plasticity occurs at a variety of time-scales, but little is known about the degree to which plastic responses at different time-scales are associated with similar underlying molecular processes, which is critical for assessing the effects of plasticity on evolutionary trajectories. To address this issue, we identified differential gene expression in response to developmental temperature in the muscle transcriptome of adult threespine stickleback (Gasterosteus aculeatus) exposed to 12, 18, and 24 °C until hatch and then held at 18 °C for nine months, and compared these results to differential gene expression in response to adult thermal acclimation in stickleback developed at 18 °C and then acclimated to 5 and 25 °C as adults. Adult thermal acclimation affected the expression of 7,940 and 7,015 genes in response to cold and warm acclimation, respectively, and 4,851 of these genes responded in both treatments. In contrast, the expression of only 33 and 29 genes were affected by cold and warm development, respectively. The majority of the genes affected by developmental temperature were also affected by adult acclimation temperature. Many genes that were differentially expressed as a result of adult acclimation were associated with previously identified temperature-dependent effects on DNA methylation patterns, suggesting a role of epigenetic mechanisms in regulating gene expression plasticity during acclimation. Taken together, these results demonstrate similarities between the persistent effects of developmental plasticity on gene expression and the effects of adult thermal acclimation, emphasizing the potential for mechanistic links between plasticity acting at these different life stages.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.049 | 0.015 |
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".