Frequent Missense and Insertion/Deletion Polymorphisms in the Ovine Shadoo Gene Parallel Species-Specific Variation in PrP
Bibliographic record
Abstract
BACKGROUND: The cellular prion protein PrP(C) is encoded by the Prnp gene. This protein is expressed in the central nervous system (CNS) and serves as a precursor to the misfolded PrP(Sc) isoform in prion diseases. The prototype prion disease is scrapie in sheep, and whereas Prnp exhibits common missense polymorphisms for V136A, R154H and Q171R in ovine populations, genetic variation in mouse Prnp is limited. Recently the CNS glycoprotein Shadoo (Sho) has been shown to resemble PrP(C) both in a central hydrophobic domain and in activity in a toxicity assay performed in cerebellar neurons. Sho protein levels are reduced in prion infections in rodents. Prompted by these properties of the Sho protein we investigated the extent of natural variation in SPRN. PRINCIPAL FINDINGS: Paralleling the case for ovine versus human and murine PRNP, we failed to detect significant coding polymorphisms that alter the mature Sho protein in a sample of neurologically normal humans, or in diverse strains of mice. However, ovine SPRN exhibited 4 missense mutations and expansion/contraction in a series of 5 tandem Ala/Gly-containing repeats R1-R5 encoding Sho's hydrophobic domain. A Val71Ala polymorphism and polymorphic expansion of wt 67(Ala)(3)Gly70 to 67(Ala)(5)Gly72 reached frequencies of 20%, with other alleles including Delta67-70 and a 67(Ala)(6)Gly73 expansion. Sheep V71, A71, Delta67-70 and 67(Ala)(6)Gly73 SPRN alleles encoded proteins with similar stability and posttranslational processing in transfected neuroblastoma cells. SIGNIFICANCE: Frequent coding polymorphisms are a hallmark of the sheep PRNP gene and our data indicate a similar situation applies to ovine SPRN. Whether a common selection pressure balances diversity at both loci remains to be established.
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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) | 0.002 | 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".