Genetic Parameters, Linear Associations, and Genome-Wide Association Study for Endotoxin-Induced Cortisol Response in Holstein heifers
Bibliographic record
Abstract
Lipopolysaccharide (LPS) endotoxin is a well-characterized microbe-associated molecular pattern (MAMP) that forms the outer membrane of both pathogenic and commensal Gram-negative bacteria. It plays a crucial role in triggering inflammatory disorders such as mastitis, acidosis, and septicemia. In heifers, an LPS challenge induces a dynamic stress response, marked by elevated cortisol levels, increased body temperature, and altered immune function. Research indicates that LPS administration leads to a significant rise in cortisol post-challenge. Building on this understanding, the present study aimed to estimate genetic parameters for serum cortisol response to LPS challenge in Holstein heifers and its linear associations with production, health, reproduction, and conformation traits. Additionally, a genome-wide association study (GWAS) was conducted to identify genetic regions associated with cortisol response. A total of 252 animals were evaluated for cortisol response, with correlations estimated between cortisol levels and 55 genomic breeding values for key traits. Genetic parameters and heritability for cortisol response were estimated using Residual Maximum Likelihood (REML) in the Blupf90+ v 2.57 software. Single-Step GWAS (ssGWAS) employing a 10-SNP window approach and 42,123 SNP markers was performed to identify genomic regions that explained at least 0.5% of additive genetic variance. Finally, candidate genes and QTLs located 50 kb up and downstream of those windows were identified. The cortisol response showed significant but weak linear associations with cystic ovaries, body maintenance requirements, lactation persistency, milk yield, and protein yield (p-value ≤ 0.05) and showed suggestive weak linear associations with udder texture, clinical ketosis, heel horn erosion, and milking speed (p-value ≤ 0.15). Cortisol response showed significant additive genetic variance, along with moderate heritability of 0.26 (±0.19). A total of 34 windows explained at least 0.5% of additive genetic variance, and 75 QTLs and 11 candidate genes, comprising the genes CCL20, DAW1, CSMD2, HMGB4, B3GAT2, PARD3, bta-mir-2285aw, CFH, CDH2, ENSBTAG00000052242, and ENSBTAG00000050498, were identified. The functional enrichment analysis allowed us to infer two instances where these gene products could interfere with cortisol production: the first instance is related to the complement system, and the second one is related to the EMT (Epithelium–Mesenchymal Transition) and pituitary gland formation. Among the QTLs, 13 were enriched in the dataset, corresponding to traits related to milk (potassium content), the exterior (udder traits, teat placement, foot angle, rear leg placement, and feet and leg conformation), production (length of productive life, net merit, and type), and reproduction (stillbirth and calving ease). In summary, the cortisol response to LPS challenge in Holstein heifers seems to be moderately heritable and has weak but significant linear associations with important production and health traits. Several candidate genes identified could perform important roles, in at least two ways, for cortisol production, and QTLs were identified close to regions of the genome that explained a significant amount of additive genetic variance for cortisol response. Therefore, further investigations are warranted to validate these findings with a larger dataset.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".