Transcriptomic response of lumpfish (Cyclopterus lumpus) head kidney to viral mimic, with a focus on the interferon regulatory factor family
Bibliographic record
Abstract
The economic importance of lumpfish ( Cyclopterus lumpus ) is increasing, but several aspects of its immune responses are not well understood. To discover genes and mechanisms involved in the lumpfish antiviral response, fish were intraperitoneally injected with either the viral mimic polyinosinic:polycytidylic acid [poly(I:C)] or phosphate-buffered saline (PBS; vehicle control), and head kidneys were sampled 24 hours post-injection (hpi) for transcriptomic analyses. RNA sequencing (RNA-Seq) (adjusted p-value <0.05) identified 4,499 upregulated and 3,952 downregulated transcripts in the poly(I:C)-injected fish compared to the PBS-injected fish. Eighteen genes identified as differentially expressed by RNA-Seq were included in a qPCR study that confirmed the upregulation of genes encoding proteins with antiviral immune response functions (e.g., rsad2 ) and the downregulation of genes (e.g., jarid2b ) with potential cellular process functions. In addition, transcript expression levels of 12 members of the interferon regulatory factor (IRF) family [seven of which were identified as poly(I:C)-responsive in this RNA-Seq study] were analyzed using qPCR. Levels of irf1a , irf1b , irf2 , irf3 , irf4b , irf7 , irf8 , irf9 , and irf10 were significantly higher and levels of irf4a and irf5 were significantly lower in the poly(I:C)-injected fish compared to the PBS-injected fish. This research and associated new genomic resources enhance our understanding of the genes and molecular mechanisms underlying the lumpfish response to viral mimic stimulation and help identify possible therapeutic targets and biomarkers for viral infections in this species.
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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".