Identification of olfactory receptor genes in Atlantic salmon <i>Salmo salar</i>
Bibliographic record
Abstract
It has been hypothesized that salmonids use olfactory cues to return to their natal rivers and streams. The key components of the molecular pathways involved in imprinting and homing, however, are still unknown. Aquatic chemical cues are received through the nares and into the nasal cavity that contains a single olfactory organ, the olfactory rosette. The olfactory rosette contains sensory neurons, each of which is thought to express only one olfactory receptor. If odorants are involved in salmonid homing migration then olfactory receptors should play a critical role in the dissipation of information from the environment to the fish. Therefore, to understand the molecular basis for imprinting and homing in Atlantic salmon Salmo salar it is important to identify and characterize the repertoire of olfactory receptors in this species. The first public assembly of the S. salar genome was searched for genes encoding three of the superfamilies of fish olfactory receptors: V2R-like (olfc), V1R-like (ora) and main olfactory receptor (mor). A further six ora genes were added to ora1 and ora2, which had been described previously. In addition, 48 putative mors were identified, 24 of which appear to be functional based on their gene structures and predicted amino-acid sequences. Phylogenetic analyses were then used to compare these S. salar olfactory receptor genes with those of zebrafish Danio rerio, two pufferfish species Takifugu rubripes and Tetraodon nigroviridis, medaka Oryzias latipes and three-spined stickleback Gasterosteus aculeatus.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 0.001 |
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".