Salmonid gene expression biomarkers indicative of physiological responses to changes in salinity, temperature, but not dissolved oxygen
Bibliographic record
Abstract
An organism's ability to respond effectively to environmental change is critical to their survival. Yet, life stage and overall condition can dictate tolerance thresholds to heightened environmental stressors, such that stress may not be equally felt across individuals and at all times. Also, the transcriptional responses induced by environmental changes can reflect both generalized responses as well as others that are highly specific to the type of change being experienced. Thus, if transcriptional biomarkers specific to a stressor, even under multi-stressor conditions, can be identified, the biomarkers could then be applied in natural environments to determine when and where an individual experiences such a stressor. Here, we experimentally challenged juvenile Chinook salmon (Oncorhynchus tshawytscha) to validate candidate gill gene expression biomarkers. A sophisticated experimental design manipulated salinity (freshwater, brackish, and seawater), temperature (10, 14, and 18°C) and dissolved oxygen (normoxia and hypoxia) in all 18 possible combinations for six days using separate trials for three smolt statuses (pre-smolt, smolt, and de-smolt). In addition, changes in juvenile behaviour, plasma variables, gill Na+/K+-ATPase activity, body size, body morphology, and skin pigmentation supplemented the gene expression responses. We identified biomarkers specific to salinity and temperature that transcended the multiple stressors, smolt status, and mortality (live, dead, and moribund). Similar biomarkers for dissolved oxygen were not identified. This work demonstrates the unique power of gene expression biomarkers to identify a specific stressor even under multi-stressor conditions, and we discuss our next steps for hypoxia biomarkers using an RNA-seq study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".