Heat shock response of killifish (<i>Fundulus heteroclitus</i>): candidate gene and heterologous microarray approaches
Bibliographic record
Abstract
Northern and southern subspecies of the Atlantic killifish, Fundulus heteroclitus, differ in maximal thermal tolerance. To determine whether these subspecies also differ in their heat shock response (HSR), we exposed 20°C acclimated killifish to a 2 h heat shock at 34°C and examined gene expression in fish from both subspecies during heat shock and recovery using real-time quantitative PCR and a heterologous cDNA microarray designed for salmonid fishes. The heat shock proteins Hsp70-1, hsp27, and hsp30 were upregulated to a greater extent in the high temperature-tolerant southern subspecies than in the less tolerant northern subspecies, whereas hsp70-2 (which showed the largest upregulation of all the heat shock proteins) in both gill and muscle and hsp90α in muscle was upregulated to a greater extent in northern than in southern fish. These data demonstrate that differences in the HSR between subspecies cannot be due to changes in a single global regulator but must occur via gene-specific mechanisms. They also suggest that the role, if any, of hsps in establishing thermal tolerance is complex and varies from gene to gene. Heterologous microarray hybridization provided interpretable gene expression signatures, detecting differential regulation of genes known to be involved in the heat shock response in other species. Under control conditions, a variety of genes were differentially expressed in muscle between subspecies that suggest differences in muscle fiber type and could relate to previously observed differences between subspecies in the thermal sensitivity of swimming performance and metabolism.
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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".