Genetic and environmental basis of transcriptional thermal plasticity of brook charr (<i>Salvelinus fontinalis</i>) fry
Bibliographic record
Abstract
Variation in transcriptomic responses is recognized as an underlying mechanism driving phenotypic responses to environmental variations. Whether this variation is adaptive or maladaptive can have significant implications for the evolutionary trajectory of populations. Understanding the inheritance of this transcriptional variation across generations, whether it is genetic, non-genetic, or both is limited. To address this knowledge gap, we assessed the expression of targeted genes in brook charr fry ( Salvelinus fontinalis) reared at two different temperatures (5 and 8 °C) and produced by breeders exposed to either cold or warm thermal regimes during final gonad maturation. Using a high-throughput OpenArray® chip, we measured the relative expression of 10 candidate genes associated with environmental stress. Parental temperature affected the expression of the SRY-box transcription factor 2, a gene associated with neurogenesis, and of Cholecystokinin and neuropeptide Y genes, both associated with appetite regulation, regardless of offspring-rearing temperature. Additive genetic, maternal, and paternal effects were low, with the absence of genotype × environmental interactions indicating that environmental factors may be more important in shaping gene expression.
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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".