Genome-wide association study and functional analyses for clinical and subclinical ketosis in Holstein cattle
Bibliographic record
Abstract
Ketosis is one of the most frequent metabolic diseases in high-yielding dairy cows and is characterized by high concentrations of ketone bodies in blood, urine, and milk, causing high economic losses. The search for polymorphic genes, whose alleles have different effects on resistance to developing the disease, is of extreme importance to help select less susceptible animals. The aims of this study were to identify genomic regions associated with clinical and subclinical ketosis (β-hydroxybutyrate concentration) in North American Holstein dairy cattle and to investigate these regions to identify candidate genes and metabolic pathways associated with these traits. To achieve this, a GWAS was performed for 4 traits: clinical ketosis lactation 1, clinical ketosis lactation 2 to 5, subclinical ketosis lactation 1, and subclinical ketosis lactation 2 to 5. The estimated breeding values from 77,277 cows and 7,704 bulls were deregressed and used as pseudophenotypes in the GWAS. The top-20 genomic regions explaining the largest proportion of the genetic variance were investigated for putative genes associated with the traits through functional analyses. Regions of interest were identified on chromosomes 2, 5, and 6 for clinical ketosis lactation 1; 3, 6, and 7 for clinical ketosis lactation 2 to 5; 1, 2, and 12 for subclinical ketosis lactation 1; and 20, 11, and 25 for subclinical ketosis lactation 2 to 5. The highlighted genes potentially related to clinical and subclinical ketosis included ACAT2 and IGF1. Enrichment analysis of the list of candidate genes for clinical and subclinical ketosis showed molecular functions and biological processes involved in fatty acid metabolism, lipid metabolism, and inflammatory response in dairy cattle. Several genomic regions and SNPs related to susceptibility to ketosis in dairy cattle that were previously described in other studies were confirmed. The novel genomic regions identified in this study aid to characterize the most important genes and pathways that explain the susceptibility to clinical and subclinical ketosis in dairy cattle.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".