Single-nucleotide polymorphisms in calpastatin gene and the association with growth traits in Tibetan sheep (<i>Ovis aries</i>)
Bibliographic record
Abstract
The calpastatin gene has been extensively studied as a candidate gene because of its regulatory function within muscle development of animals. However, little is known about the association between variation of the calpastatin gene and growth traits in Tibetan sheep. Using DNA sequencing, four single-nucleotide polymorphisms g.3844A>G, g.88874T>C, g.89126C>T, and g.89157A>C were identified in this study. An association analysis indicates that the g.3844A>G and g.89126C>T polymorphisms affected body weight ( P < 0.05). The g.89157A>C polymorphism was significantly correlated with body weight and chest circumference ( P < 0.05). The quantitative real-time polymerase chain reaction analysis revealed that the expression of calpastatin gene presented an increasing trend with an increase in age. Remarkably lower mRNA expression was detected at the fetal stage compared with adult ewes ( P < 0.05). These findings indicated that the calpastatin gene polymorphisms were involved in growth-related traits in Tibetan sheep, which can be considered as genetic markers for improving the growth traits of Chinese Tibetan sheep.
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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) | 0.001 | 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".