Transcription and Translation of the Salmon Gonadotropin-Releasing Hormone Genes in Brain and Gonads of Sexually Maturing Rainbow Trout (Oncorhynchus mykiss)1
Bibliographic record
Abstract
Rainbow trout sexually mature at the end of Year 3. The form of GnRH that controls gonadotropin release in trout is salmon GnRH (sGnRH). In the tetraploid rainbow trout, two genes encode an identical sGnRH peptide. The sGnRH gene-1 produces one mRNA, whereas sGnRH gene-2 can produce more than one. This study asks whether the transcripts and their protein products are expressed in the brain and gonads and whether the pattern correlates with sexual maturity over the final year leading to first spawning. Brain sGnRH mRNA and protein were continuously present throughout the third year. We show for the first time that the long sGnRH-2 mRNA transcript is expressed in neural tissue and not exclusively in gonadal tissue. Expression of the long sGnRH-2 mRNA in the brain coincides with high levels of sGnRH peptide in the brain during a time of increased gonadal growth. Thus, the long sGnRH-2 mRNA in the brain may act to regulate sGnRH production in a stage-specific rather than a tissue-specific manner. In gonads, local sGnRH is thought to play an autocrine/paracrine role in regulating gonadal maturation and spawning. In the maturing gonads, sGnRH gene-1 and -2 are expressed intermittently. Strikingly, sGnRH peptide was not detected in the gonads at any time during Year 3. These results suggest that either the sGnRH transcripts in the gonads are not translated into protein or, if translated, the protein is rapidly released, resulting in gonadal content below 1 fM per fish.
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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".