The circadian transcriptome of marine fish (Sparus aurata) larvae reveals highly synchronized biological processes at the whole organism level
Bibliographic record
Abstract
The regulation of circadian gene expression remains largely unknown in farmed fish larvae. In this study, a high-density oligonucleotide microarray was used to examine the daily expression of 13,939 unique genes in whole gilthead sea bream (Sparus aurata) larvae with fast growth potentiality. Up to 2,229 genes were differentially expressed, and the first two components of Principal Component Analysis explained more than 81% of the total variance. Clustering analysis of differentially expressed genes identified 4 major clusters that were triggered sequentially, with a maximum expression at 0 h, 3 h, 9-15 h and 18-21 h zeitgeber time. Various core clock genes (per1, per2, per3, bmal1, cry1, cry2, clock) were identified in clusters 1-3, and their expression was significantly correlated with several genes in each cluster. Functional analysis revealed a daily consecutive activation of canonical pathways related to phototransduction, intermediary metabolism, development, chromatin remodeling, and cell cycle regulation. This daily transcriptome of whole larvae resembles a cell cycle (G1/S, G2/M, and M/G1 transitions) in synchronization with multicellular processes, such as neuromuscular development. This study supports that the actively feeding fish larval transcriptome is temporally organized in a 24-h cycle, likely for maximizing growth and development.
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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) | 0.000 | 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".