Genetic variants in melanogenesis proteins <i>TYRP1</i> and <i>TYR</i> are associated with the golden rhesus macaque phenotype
Bibliographic record
Abstract
Nonhuman primates (NHPs) are vital translational research models due to their high genetic, physiological, and anatomical homology with humans. The "golden" rhesus macaque (Macaca mulatta) phenotype is a naturally occurring, inherited trait with a visually distinct pigmentation pattern resulting in light blonde colored fur. Retinal imaging also reveals consistent hypopigmentation and occasional foveal hypoplasia. Here, we describe the use of genome-wide association in 2 distinct NHP populations to identify candidate variants in genes linked to the golden phenotype. Two missense variants were identified in the Tyrosinase-related protein 1 gene (Asp343Gly and Leu415Pro) that segregate with the phenotype. An additional and distinct association was also found with a Tyrosinase variant (His256Gln), indicating the light-colored fur phenotype can result from multiple genetic mechanisms. The implicated genes are related through their contribution to the melanogenesis pathway. Variants in these 2 genes are known to cause pigmentation phenotypes in other species and to be associated with oculocutaneous albinism in humans. The novel associations presented in this study will permit further investigations into the role these proteins and variants play in the melanogenesis pathway and model the effects of genetic hypopigmentation and altered melanogenesis in a naturally occurring nonhuman primate model.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".