Haplotype combination of polymorphisms in the <i>ADIPOQ</i> gene promoter is associated with growth traits in Qinchuan cattle
Bibliographic record
Abstract
Adiponectin modulates lipid and glucose metabolism in adipose tissues and is also related to bone metabolism. Polymorphisms in the ADIPOQ gene likely have an impact on growth traits in cattle. In this study, we examined the relationship between ADIPOQ polymorphisms and body measurement parameters in Chinese beef cattle. First, we sequenced ADIPOQ and 1.2 kb of DNA upstream of its promoter, and we found 14 polymorphisms. With the luciferase reporter assay, we showed that the two polymorphisms SNP PR_-135 A>G and PR_-68 G>C, which are located in the core region of promoter, influence promoter activity of ADIPOQ. Second, we identified three haplotypes involved in these two polymorphic sites: A (A-135/C-68), B (A-135/G-68), and C (G-135/G-68). Haplotypes B and C are major haplotypes in five Chinese populations of cattle (Qinchuan, Nanyang, Jiaxian, Hazakh, and Chinese Holstein). We studied the effects of these three haplotypes on body measurements, gene expression, and promoter activity, and we found that the genotypes are associated with body measurement parameters in Qinchuan cattle. Individuals with genotype BC (AG/GG) had significantly higher body height and heart girth than others, and this result may be interpreted by the following two observations. The promoter activity with haplotype B (A/G) is significantly higher than those with A (A/C) and C (G/G) in driving reporter gene transcription; the ADIPOQ mRNA level in cattle with genotype BC (AG/GG) is relatively lower than that in cattle with genotype BB (AA/GG).
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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 | 0.001 | 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".