Parental thermal environment controls the offspring phenotype in Brook charr (<i>Salvelinus fontinalis</i>): insights from a transcriptomic study
Bibliographic record
Abstract
Brook charr is a cold-water species which is highly sensitive to increased water temperatures, such as those associated with climate change. Environmental variation can potentially induce phenotypic changes that are inherited across generations, for instance, via epigenetic mechanisms. Here, we tested whether parental thermal regimes (intergenerational plasticity) and offspring-rearing temperatures (within-generational plasticity) modify the brain transcriptome of Brook charr progeny (fry stage). Parents were exposed to either cold or warm temperatures during final gonad maturation and their progeny were reared at 5 or 8 °C during the first stages of development. Illumina Novaseq6000 was used to sequence the brain transcriptome at the yolk sac resorption stage. The number of differentially expressed genes was very low when comparing fry reared at different temperatures (79 differentially expressed genes). In contrast, 9,050 differentially expressed genes were significantly differentially expressed between fry issued from parents exposed to either cold or warm temperatures. There was a significant downregulation of processes related to neural and synaptic activity in fry originating from the warm parental group vs fry from the cold parental one. We also observed significant upregulation of DNA methylation genes and of the most salient processes associated with compensation to warming, such as metabolism, cellular response to stress, and adaptive immunity.
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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".