Large‐scale prion protein genotyping in Canadian caribou populations and potential impact on chronic wasting disease susceptibility
Bibliographic record
Abstract
Polymorphisms within the prion protein gene (Prnp) are an intrinsic factor that can modulate chronic wasting disease (CWD) pathogenesis in cervids. Although wild European reindeer (Rangifer tarandus tarandus) were infected with CWD, as yet there have been no reports of the disease in North American caribou (R. tarandus spp.). Previous Prnp genotyping studies on approximately 200 caribou revealed single nucleotide polymorphisms (SNPs) at codons 2 (V/M), 129 (G/S), 138 (S/N), 146 (N/n) and 169 (V/M). The impact of these polymorphisms on CWD transmission is mostly unknown, except for codon 138. Reindeer carrying at least one allele encoding for asparagine (138NN or 138SN) are less susceptible to clinical CWD upon infection by natural routes, with the majority of prions limited to extraneural tissues. We sequenced the Prnp coding region of two caribou subspecies (n = 986) from British Columbia, Saskatchewan, Yukon, Nunavut and the Northwest Territories, to identify SNPs and their frequencies. Genotype frequencies at codon 138 differed significantly between barren-ground (R. t. groenlandicus) and woodland (R. t. caribou) caribou when we excluded the Chinchaga herd (p < .05). We also found new variants at codons 153 (Y/F) and 242 (P/L). Our findings show that the 138N allele is rare among caribou in areas with higher risk of contact with CWD-infected species. As both subspecies are classified as Threatened and play significant roles in North American Indigenous culture, history, food security and the economy, determining frequencies of Prnp genotypes associated with susceptibility to CWD is important for future wildlife management measures.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".