Seasonal Freeze Resistance of Rainbow Smelt (<i>Osmerus mordax</i>) Is Generated by Differential Expression of Glycerol‐3‐Phosphate Dehydrogenase, Phosphoenolpyruvate Carboxykinase, and Antifreeze Protein Genes
Bibliographic record
Abstract
In winter, rainbow smelt (Osmerus mordax) accumulate glycerol and produce an antifreeze protein (AFP), which both contribute to freeze resistance. The role of differential gene expression in the seasonal pattern of these adaptations was investigated. First, cDNAs encoding smelt and Atlantic salmon (Salmo salar) phosphoenolpyruvate carboxykinase (PEPCK) and smelt glyceraldehyde-3-phosphate dehydrogenase (GAPDH) were cloned so that all sequences required for expression analysis would be available. Using quantitative PCR, expression of beta actin in rainbow smelt liver was compared with that of GAPDH in order to determine its validity as a reference gene. Then, levels of glycerol-3-phosphate dehydrogenase (GPDH), PEPCK, and AFP relative to beta actin were measured in smelt liver over a fall-winter-spring interval. Levels of GPDH mRNA increased in the fall just before plasma glycerol accumulation, implying a driving role in glycerol synthesis. GPDH mRNA levels then declined during winter, well in advance of serum glycerol, suggesting the possibility of GPDH enzyme or glycerol conservation in smelt during the winter months. PEPCK mRNA levels rose in parallel with serum glycerol in the fall, consistent with an increasing requirement for amino acids as metabolic precursors, remained elevated for much of the winter, and then declined in advance of the decline in plasma glycerol. AFP mRNA was elevated at the onset of fall sampling in October and remained elevated until April, implying separate regulation from GPDH and PEPCK. Thus, winter freezing point depression in smelt appears to result from a seasonal cycle of GPDH gene expression, with an ensuing increase in the expression of PEPCK, and a similar but independent cycle of AFP gene expression.
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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".