River‐Specific Gene Expression Patterns Associated with Habitat Selection for Key Hormone‐Coding Genes in Glass Eel‐Stage American Eels
Bibliographic record
Abstract
Abstract The glass eel stage of the American Eel Anguilla rostrata marks the onset of the catadromous migration into estuarine or freshwater habitats, and the endocrine mechanisms underlying this habitat selection are still not well understood. Using a candidate genes approach, the aim of this study was to test for different patterns of gene expression related to (1) salinity preferences and/or (2) capture site to predict physiological differences between migratory behaviors. We performed analyses revealing the expression of genes coding for key hormonal factors or their receptors on glass eel‐stage American Eels collected at the mouths of three rivers on the east coast of Canada (Grande‐Rivière‐Blanche, St. Lawrence estuary; Rivière‐Saint‐Jean, Gaspé Peninsula; and the Mersey River, Nova Scotia); eels from the three systems displayed different salinity preferences (brackish water/salt water/freshwater) under laboratory conditions. Transcripts from genes coding for prolactin (PRL), thyroid‐stimulating hormone β subunit, type‐2 iodothyronine deiodinase (DIO‐2), thyroid hormone receptors αa and αb (THRαa and THRαb), growth hormone (GH), insulin‐like growth factor 1 (IGF‐1), and their respective receptors (GH‐R1 and IGF‐1R) were all detected in glass eels. No differences in the expression patterns were detected pertaining to salinity preference, but strong differences were found among rivers. Rivière‐Saint‐Jean glass eels, which were the longest and the least pigmented among the three rivers, were characterized by the highest expression of PRL, DIO‐2, and THRαb. Those from Grande‐Rivière‐Blanche showed an increase in IGF‐1R. Glass eels captured from these two rivers also exhibited the highest expression of GH and GH‐R1. Overall, these results confirm gene × environment interactions at the gene expression level when glass eels settle into their continental habitat. As such, our results also support the concept of the presence of different ecotypes in the Atlantic Canadian coast and in the estuary and Gulf of St. Lawrence.
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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".