Transcriptomic analyses of juvenile Striped Bass (Morone saxatilis) exposed to chronic and acute temperature change
Bibliographic record
Abstract
Striped Bass are economically important, migratory fishes, which occur across a wide range of latitudes. Given their wide-ranging nature, Striped Bass can cope with a broad range of environmental temperatures, yet the mechanisms underlying this ability have not been thoroughly described. Heat shock proteins (HSPs) are inducible molecular chaperones, which help mitigate protein damage resulting from increased temperatures. The importance of HSPs has been demonstrated in a number of fish species, but their role in Striped Bass is poorly understood. This study characterizes changes in gene expression in juvenile Striped Bass, following acute and chronic temperature change. Fish were acclimated to one of three temperatures (15, 25 or 30°C) and sampled at one of two treatments (control or after CTmax), following which we assessed differential gene expression and gene ontology in muscle. It is clear from our differential expression analyses that acclimation to warm temperatures elicits more robust changes to gene expression, compared to acute temperature increases. Our differential expression analyses also revealed induction of many different heat shock proteins, including hsp70, hsp90, hsp40 and other small HSPs, after both acute and chronic temperature increase in white muscle. Furthermore, the most consistent gene ontology pattern that emerged following both acclimation and CTmax was upregulation of transcripts involved in "protein folding", which also include heat shock proteins. Gene ontology analyses also suggest changes to other processes after acclimation, including decreased growth pathways and changes to DNA methylation. Overall, these data suggest that HSPs likely play a major role in the Striped Bass's ability to tolerate warm waters.
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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".