Identification of single nucleotide polymorphisms in the bovine interleukin-12 and interleukin-23 receptor genes and their associations with health and production traits in Holstein cows
Bibliographic record
Abstract
Interleukin-12 (IL-12) and interleukin-23 (IL-23) are proinflammatory cytokines produced by macrophages and dendritic cells in response to infection with intracellular pathogens. The IL-12 receptor (IL-12R) is a heterodimer composed of 2 subunits, β1 and β2. The IL-23 receptor (IL-23R) is a heterodimer composed of the IL-12Rβ1 subunit and a unique IL-23R subunit. Given the importance of IL-12 and IL-23 for modulating inflammation and the host immune response, the IL-12 and IL-23 receptor genes may be suitable candidate genes for studying disease resistance in dairy cattle. We hypothesize that single nucleotide polymorphisms (SNP) exist within these genes and that they contribute to variation in health and production traits in dairy cattle. To investigate this, a selective DNA pool was constructed using bull semen based on the estimated breeding values for somatic cell score (SCS), an indicator trait used to achieve genetic improvement for resistance to mastitis. Gene segments were amplified from this pool by PCR and the amplicons were sequenced to reveal SNP. A total of 10 SNP, including 2 in IL-12Rβ1, 5 in IL-12Rβ2, and 3 in IL-23R were identified. The SNP (n=5) were found in the 5' untranslated region (UTR) putative promoter regions of the genes, and SNP IL-23R c.1714A>C was a nonsynonymous SNP. Canadian Holstein bulls (n=492) were genotyped using Sequenom MassARRAY (Sequenom Inc., San Diego, CA). No association was found with SCS based on bull deregressed estimated breeding values for SCS; however, associations of SNP in the IL-12Rβ2 gene (c.-511A>G, c.87A>G, c.2957A>C) were found with milk and protein yield. Further investigation will be required to elucidate the biological and practical relevance of these SNP.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".