Gill and Liver Transcript Expression Changes Associated With Gill Damage in Atlantic Salmon (Salmo salar)
Bibliographic record
Abstract
Gill damage represents a significant challenge in the teleost fish aquaculture industry globally, due to the gill’s involvement in several vital functions and direct contact with the surrounding environment. To examine the local and systemic effects accompanying gill damage (which is likely to negatively affect gill function) of Atlantic salmon, we performed a field sampling to collect gill and liver tissue after several environmental insults (e.g., harmful algal blooms). Before sampling, gills were visually inspected and gill damage was scored; gill scores were assigned from pristine [gill score 0 (GS0)] to severely damaged gills (GS3). Using a 44K salmonid microarray platform, we aimed to compare the transcriptomes of pristine and moderately damaged (i.e., GS2) gill tissue. Rank Products analysis (5% percentage of false-positives) identified 254 and 34 upregulated and downregulated probes, respectively, in GS2 compared with GS0. Differentially expressed probes represented genes associated with functions including gill remodeling, wound healing, and stress and immune responses. We performed gill and liver qPCR for all four gill damage scores using microarray-identified and other damage-associated biomarker genes. Transcripts related to wound healing (e.g., neb and klhl41b ) were significantly upregulated in GS2 compared with GS0 in the gills. Also, transcripts associated with immune and stress-relevant pathways were dysregulated (e.g., downregulation of snaclec 1-like and upregulation of igkv3 ) in GS2 compared with GS0 gills. The livers of salmon with moderate gill damage (i.e., GS2) showed significant upregulation of transcripts related to wound healing (i.e., chtop ), apoptosis (e.g., bnip3l ), blood coagulation (e.g., f2 and serpind1b ), transcription regulation (i.e., pparg ), and stress-responses (e.g., cyp3a27 ) compared with livers of GS0 fish. We performed principal component analysis (PCA) using transcript levels for gill and liver separately. The gill PCA showed that PC1 significantly separated GS2 from all other gill scores. The genes contributing most to this separation were pgam2 , des , neb , tnnt2 , and myom1. The liver PCA showed that PC1 significantly separated GS2 from GS0; levels of hsp70 , cyp3a27 , pparg , chtop , and serpind1b were the highest contributors to this separation. Also, hepatic acute phase biomarkers (e.g., serpind1b and f2 ) were positively correlated to each other and to gill damage. Gill damage-responsive biomarker genes and associated qPCR assays arising from this study will be valuable in future research aimed at developing therapeutic diets to improve farmed salmon welfare.
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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".