Mapping of quantitative trait loci for cholesterol, LDL, HDL, and triglyceride serum concentrations in pigs
Why this work is in the frame
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Bibliographic record
Abstract
The fine mapping of polymorphisms influencing cholesterol (CT), triglyceride (TG), and lipoprotein serum levels in human and mouse has provided a wealth of knowledge about the complex genetic architecture of these traits. The extension of these genetic analyses to pigs would be of utmost importance since they constitute a valuable biological and clinical model for the study of coronary artery disease and myocardial infarction. In the present work, we performed a whole genome scan for serum lipid traits in a half-sib Duroc pig population of 350 individuals. Phenotypic registers included total CT, TG, and low (LDL)- and high (HDL)-density lipoprotein serum concentrations at 45 and 190 days of age. This approach allowed us to identify two genomewide significant quantitative trait loci (QTL) for HDL-to-LDL ratio at 45 days (SSC6, 84 cM) and for TG at 190 days (SSC4, 23 cM) as well as a number of chromosomewide significant QTL. The comparison of QTL locations at 45 and 190 days revealed a notable lack of concordance at these two time points, suggesting that the effects of these QTL are age specific. Moreover, we have observed a considerable level of correspondence among the locations of the most significant porcine lipid QTL and those identified in humans. This finding might suggest that, in mammals, diverse polymorphisms located in a common set of genes are involved in the genetic variation of serum lipid levels.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it