Novel approaches for the Genetic Improvement of Fertility and Reproduction in Dairy Cattle
Bibliographic record
Abstract
For decades, animal breeding programs have allowed the dairy industry to select highly productive cows, however, at the same time, reproductive performance has declined. The challenge of selecting fertility-related traits is their low heritability and selection accuracy. Traits that are closer to the biology of the animal, combined with a better understanding of the biological mechanisms and genetic architecture of fertility, could enhance the efficiency of genetic selection. \nIn the first study of this thesis, a recently developed indicator of pregnancy rate, called size and position score of the reproductive tract, was investigated as a potential novel trait for genetic selection to improve fertility. For this aim, genetic parameters were estimated to determine the potential of the score as a novel trait and how it genetically correlates with other economically important traits evaluated in Canada. \nMore than just the conception ability of females, the reproductive outcome is also defined by the gametic compatibility of the mating pair. Little is known about pair compatibility in livestock and investigating its genetic background provides insights into its possible application to optimize mate allocation. In the second study of this thesis, transmission ratio distortion (TRD), a deviation from Mendelian inheritance expectations, was used to identify genomic regions associated with gametic incompatibility. Functional analyses of these regions were used to identify potential biological mechanisms involved, which is the first step towards developing applications for improved mate allocations. \nThe TRD regions identified in the second study were observed to overlap with copy number variant (CNV) regions associated with stillbirth. These CNV are structural variants that can influence gene expression and structure, impacting phenotypic variance. As a result, CNV could be the origin of TRD signals. Considering causes of stillbirth are still largely unknown, functional analyses of these overlapping regions were carried out in the third study to provide insights into the mechanisms, which may be underlying stillbirth in dairy cows. Results pinpointed calving difficulty and, more interestingly, an abnormal uterine inflammation process as potential causes of stillbirth.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".