Developing specific molecular biomarkers for thermal stress in salmonids
Bibliographic record
Abstract
BACKGROUND: Pacific salmon (Oncorhynchus spp.) serve as good biological indicators of the breadth of climate warming effects on fish because their anadromous life cycle exposes them to environmental challenges in both marine and freshwater environments. Our study sought to mine the extensive functional genomic studies in fishes to identify robust thermally-responsive biomarkers that could monitor molecular physiological signatures of chronic thermal stress in fish using non-lethal sampling of gill tissue. RESULTS: Candidate thermal stress biomarkers for gill tissue were identified using comparisons among microarray datasets produced in the Molecular Genetics Laboratory, Pacific Biological Station, Nanaimo, BC, six external, published microarray studies on chronic and acute temperature stress in salmon, and a comparison of significant genes across published studies in multiple fishes using deep literature mining. Eighty-two microarray features related to 39 unique gene IDs were selected as candidate chronic thermal stress biomarkers. Most of these genes were identified both in the meta-analysis of salmon microarray data and in the literature mining for thermal stress markers in salmonids and other fishes. Quantitative reverse transcription PCR (qRT-PCR) assays for 32 unique genes with good efficiencies across salmon species were developed, and their activity in response to thermally challenged sockeye salmon (O. nerka) and Chinook salmon (O. tshawytscha) (cool, 13-14 °C and warm temperatures 18-19 °C) over 5-7 days was assessed. Eight genes, including two transcripts of each SERPINH1 and HSP90AA1, FKBP10, MAP3K14, SFRS2, and EEF2 showed strong and robust chronic temperature stress response consistently in the discovery analysis and both sockeye and Chinook salmon validation studies. CONCLUSIONS: The results of both discovery analysis and gene expression showed that a panel of genes involved in chaperoning and protein rescue, oxidative stress, and protein biosynthesis were differentially activated in gill tissue of Pacific salmon in response to elevated temperatures. While individually, some of these biomarkers may also respond to other stressors or biological processes, when expressed in concert, we argue that a biomarker panel comprised of some or all of these genes could provide a reliable means to specifically detect thermal stress in field-caught salmon.
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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 | 0.001 | 0.001 |
| 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".