0486 Development of a genetic marker panel for ketosis in dairy cattle
Bibliographic record
Abstract
During the transition period high-yielding dairy cattle are susceptible to ketosis, a metabolic disease which has negative impacts on the health, fertility and milk production of the cow. Genetic selection of animals resistant to developing ketosis is a potential solution to the economic losses faced by producers, as well as the reduced herd health and welfare associated with this disease. Genetic evaluations for ketosis, a health trait with low heritability, would benefit from the additional information provided by genetic markers. The objective of this study is to identify novel single nucleotide polymorphisms (SNP) within candidate genes for ketosis to be incorporated into a custom marker panel. Investigating candidate genes provides the opportunity to discover SNP with a functional role that are not currently included on commercially-available marker panels. A list of 123 candidate genes, selected based on biological relevance, were selected for in silico investigation; this includes genes which encode key enzymes and regulatory factors involved in metabolic pathways, genes that have been shown to be differentially expressed in ketotic animals, and genes that have been proposed by genome-wide association studies (GWAS). A preliminary GWAS from our group identified 462 SNP from high-density genotypes that are associated with de-regressed estimated breeding values for ketosis. These SNP were mapped to genes involved in pathways that were expected to be involved in ketosis (i.e., PPAR signaling pathway, CoA biosynthesis), as well as unexpected (i.e., T and B cell receptor signaling, apoptosis). Within the candidate genes, putative SNP were identified by aligning sequence data from online cDNA libraries with the gene reference sequence. The variant calling program, Sequencher 4.9, was used to identify SNP and their corresponding amino acid substitutions. SNP were prioritized for inclusion in the panel based on their Sorting Intolerant From Tolerant prediction score, to select polymorphisms which would most likely alter the function of the encoded protein. A set of 1081 SNP were incorporated onto a custom low-density panel. To our knowledge, this is the first custom panel composed of markers found in candidate genes that are specific to ketosis. The second phase of this project will use this panel to genotype several thousand cows from herds originating from Quebec, Canada; these data to be collected spring 2016.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".