Genetic parameters of adaptive immune response traits in Canadian Holsteins
Bibliographic record
Abstract
The objectives of this study were to estimate genetic parameters of cell-mediated (CMIR) and antibody-mediated (AMIR) immune response (IR) traits of Holstein cattle on a national scale and to associate estimated breeding values of CMIR, AMIR, and overall IR with routinely evaluated traits in Canada. In collaboration with the Canadian Bovine Mastitis Research Network, 445 Holstein cows from 42 herds across Canada were immunized to measure delayed-type hypersensitivity as an indicator of CMIR and serum antibody for AMIR to putative type 1 and type 2 test antigens, respectively. Primary (d 14) and secondary (d 21) AMIR were measured for both IgG1 and IgG2. A series of uni- and bivariate linear animal models were used to estimate genetic parameters and breeding values for CMIR and the 4 AMIR traits. The models included the fixed effects of parity and stage of lactation and the random effects of herd-technician, animal, and residual. Heritability of CMIR was 0.19 (SE=0.10) and for AMIR traits ranged from 0.16 to 0.41 (SE=0.09-0.11) depending on time and antibody isotype. The genetic correlations between CMIR and AMIR were negative and ranged from -0.13 to -0.45 (SE=0.32-0.46). The results indicate adaptive immune response traits are moderately heritable and provide a potential for genetic selection. The negative genetic correlations between CMIR and AMIR indicate the importance of considering both traits in breeding for overall disease resistance. Significant beneficial associations between the reproductive traits number of services and first service to conception were found, which may indicate these reproductive traits would improve with genetic selection for enhanced immune response.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".