Olfactory receptor subgenome and expression in a highly olfactory procellariiform seabird
Bibliographic record
Abstract
Abstract Procellariiform seabirds are known for their well-developed olfactory capabilities, reflected by their large olfactory bulb to brain ratio and olfactory-mediated behaviors. Many species in this clade use olfactory cues for foraging and navigation, and some species can recognize individual-specific odors. Their genomes and transcriptomes may yield important clues about how the olfactory receptor (OR) subgenome was shaped by natural and sexual selection. In this study, we assembled a high-quality Leach’s storm petrel ( Oceanodroma leucorhoa ) genome to facilitate characterization of the OR repertoire. We also surveyed expressed OR genes through transcriptome analysis of the olfactory epithelium - to our knowledge, the first avian study to interrogate OR diversity in this way. We detected a large number (∼61) of intact OR genes, and identified OR genes under positive selection. In addition, we estimated that this species has the lowest proportion (∼60%) of pseudogenes compared to other waterbirds studied thus far. We show that the traditional annotation-based genome mining method underestimates OR gene number (214) as compared to copy number analysis using depth-of-coverage analysis, which estimated a total of 492 OR genes. By examining OR expression pattern in this species, we identified highly expressed OR genes, and OR genes that were differentially expressed between age groups, providing valuable insight into the development of olfactory capabilities in this and other avian species. Our genomic evidence is consistent with the Leach’s storm petrel’s well-developed olfactory sense, a key sensory foundation for its pelagic lifestyle and behavioral ecology.
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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 | 0.001 | 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) | 0.001 | 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".