Molecular cloning, sequence characteristics, and polymorphism analyses of the tyrosinase-related protein 2 / DOPAchrome tautomerase gene of black-boned sheep (<i>Ovis aries</i>)
Bibliographic record
Abstract
Tyrosinase-related protein 2 (TYRP2) plays a pivotal role in the biosynthesis of eumelanin. Black-boned sheep have excessive melanin and eumelanin, resulting in dark (black) muscles and organs. This study was designed to investigate the effects of variants of the TYRP2 gene on black traits and coat colour of black-boned sheep. Melanin traits were measured in three populations of sheep (Nanping black-boned, Nanping normal, and Romney Marsh) and compared in this study. From the TYRP2 cDNA, all 8 exons and their flanking regions were amplified and characterized. Fifteen single nucleotide polymorphisms (SNPs) were identified in the exons and their flanking regions. Five exonic polymorphic sites, including two synonymous (c.93T>G and c.1140C>T) and three non-synonymous mutations (c.163C>T (p.R55W), c.605G>A (p.R202H), and c.1141A>G (p.T381A)), were retrieved. PCR-RFLP analysis of c.605G>A showed that the frequencies of allele G in the Nanping black-boned, Nanping normal, and Romney Marsh sheep were 0.632, 0.603, and 0.886, respectively. Sheep with the GG genotype had significantly (P < 0.05) lower tyrosinase activity, alkali-soluble melanin content, and ratio of eumelanin : total melanin than sheep with GA and AA genotypes when measured across all investigated samples but not when samples within each population of sheep were compared. However, there was no association of TYRP2 genotype at a single SNP position with coat colour across populations. Nonetheless, the two breeds with higher overall tyrosinase activity did produce darker and more varied coat colours than the breed with lower tyrosinase activity.
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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) | 0.000 | 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 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".