PSXI-1 Identifying genomic regions linked to novel reproductive traits in Holstein cattle.
Bibliographic record
Abstract
Abstract Estrus behavior is an important driver of reproductive success in dairy cows, with direct impacts on fertility and herd productivity. Recent studies highlight the genetic variability in estrus behavior, however regions in the bovine genome underlying this variability need to be determined. Genome-wide association studies can be a powerful approach to discover those genomic regions and potentially enable improved selection strategies for reproductive efficiency. Single-step genome wide association study will be used to investigate the genetic architecture of estrus behavior in Holstein cows by integrating pedigree and genomic data. Three estrus-related traits derived from activity-monitoring collars (CowScout; GEA, Düsseldorf, Germany) will be analyzed: Calving to first estrus activity with 3,569 records on 2,465 cows, maximum intensity of estrus behavior with 9,078 records on 2,465 cows, and estrus duration with 9,078 records on 2,465 cows. In total, 1,434 phenotyped cows and 797 animals in the pedigree were genotyped. The proportion of genetic variance explained by 10-single nucleotide polymorphism (SNP) sliding windows across the genome will be estimated using the BLUPF90 suite. Genomic windows explaining ≥ 0.5% of the additive genetic variance will be mapped for candidate genes and quantitative trait loci using GALLO R package for the three reproductive traits. A functional enrichment analysis will be conducted to explore the biological relevance of the identified genes. Descriptive analysis revealed considerable variability among these traits, with calving to first estrus activity averaging 54.1 days (SD = 39.6, CV = 73.2%), maximum intensity of estrus behavior at 30.6 (SD = 16.1, CV = 52.7%), and estrus duration at 10.8 hours (SD = 3.6, CV = 33.8%). The findings from this study will contribute to a deeper understanding of the underlying genetic mechanisms of estrus behavior in Holsteins. The new insights could unravel new potentials to improve fertility and reproductive traits in dairy cattle breeding programs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.003 | 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".