PSIV-2 Investigating candidate scur genes in Bos taurus breeds
Bibliographic record
Abstract
Abstract Scurs (loose horns) are inherited in a sex-influenced manner and are believed to appear in cattle when the animal is heterozygous (Pp) for the polled mutation. They are unwanted by beef producers, but are difficult to eradicate because scurs are epistatic to the polled mutation. With the development of a test for the 202 bp indel on BTA1 resulting in the polled phenotype in Celtic breeds, horned (pp) and polled (PP/Pp) animals can be genotyped at this locus. The aims of this study were: 1) to confirm the polled genotype in scurred families from a Canadian beef research herd (SCBRH), scurred cattle families from producers (SCFP), and polled and scurred feedlot steers using the Celtic poll test (PC), and 2) to identify new candidate genes between the recombinant genes of the postulated scur loci on BTA19. Through PCR amplification, the polled/horned genotype was confirmed in the SCBRH, SPCF, and 153 phenotyped feedlot steers with gel electrophoresis. One family from the SPCF, 26 scurred and 10 polled feedlot steers were genotyped as horned. Removing the SPCF horned animals from the scur loci mapping data changed the recombinant markers and created a new boundary, resulting in examination of five new candidate genes (CTDNEP1, FGF11, SOX15, SHBG, DHRS7C) based on function and position. To identify SNPs segregating with scurs, 16 animals were chosen from the PC genotyped feedlot steers, 8 Pp scurred steers and 8 Pp polled steers. Two SNP’s found in CTDNEP1 and DHRS7C were examined in the SCBRH with PCR-RFLP using BseRI and AciI, respectively, but did not segregate with scurs. In conclusion, careful phenotyping and genotyping for the polled/horned status of an animal should be confirmed for future studies to determine the genetic mutation resulting in scurs.
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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 | 0.001 |
| 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".