Genetic diversity of canine olfactory receptors
Bibliographic record
Abstract
BACKGROUND: Evolution has resulted in large repertoires of olfactory receptor (OR) genes, forming the largest gene families in mammalian genomes. Knowledge of the genetic diversity of olfactory receptors is essential if we are to understand the differences in olfactory sensory capability between individuals. Canine breeds constitute an attractive model system for such investigations. RESULTS: We sequenced 109 OR genes considered representative of the whole OR canine repertoire, which consists of more than 800 genes, in a cohort of 48 dogs of six different breeds. SNP frequency showed the overall level of polymorphism to be high. However, the distribution of SNP was highly heterogeneous among OR genes. More than 50% of OR genes were found to harbour a large number of SNP, whereas the rest were devoid of SNP or only slightly polymorphic. Heterogeneity was also observed across breeds, with 25% of the SNP breed-specific. Linkage disequilibrium within OR genes and OR clusters suggested a gene conversion process, consistent with a mean level of polymorphism higher than that observed for introns and intergenic sequences. A large proportion (47%) of SNP induced amino-acid changes and the Ka/Ks ratio calculated for all alleles with a complete ORF indicated a low selective constraint with respect to the high level of redundancy of the olfactory combinatory code and an ongoing pseudogenisation process, which affects dog breeds differently. CONCLUSION: Our demonstration of a high overall level of polymorphism, likely to modify the ligand-binding capacity of receptors distributed differently within the six breeds tested, is the first step towards understanding why Labrador Retrievers and German Shepherd Dogs have a much greater potential for use as sniffer dogs than Pekingese dogs or Greyhounds. Furthermore, the heterogeneity in OR polymorphism observed raises questions as to why, in a context in which most OR genes are highly polymorphic, a subset of these genes is not? This phenomenon may be related to the nature of their ligands and their importance in everyday life.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".