31 Gametic Incompatibility: Improving the Success of Mate Allocation in Dairy Cattle
Bibliographic record
Abstract
Abstract In the dairy industry, mate allocation is mainly based on the parents’ breeding values and inbreeding coefficients aiming to achieve the producer’s breeding goal. With artificial insemination, the portfolio of sires to choose from is large and the quality of the semen doses is standardized. However, not all sire-dam matings are equally likely to produce a successful pregnancy. Among other reproduction issues, the success of a mating could vary due to the incompatibility of gametes coming from the sire and the dam and could influence the fertilization’s success, additionally to the reproductive capacity of the parents. Considering the gametic incompatibility of the potential parents could be a novel option to improve mating plans. Under the hypothesis that gametic incompatibility has a significant effect on reproduction and reduces the odds of fertilization and pregnancy, this study aimed to determine the genetic background of gametic incompatibility. Transmission ratio distortion (TRD), which detects deviations from Mendelian inheritance expectations, is commonly used to identify deleterious mutations. We adapted the TRD model by including an interaction effect between the gametes leading to the offspring genotype to detect regions with TRD effects and gametic incompatibility. Our dataset contained 436,651 genotyped (50K SNP) Canadian Holstein cattle from 283,817 parents-offspring trios. A total of 482 regions with TRD containing 671 positional genes were found. The functional analysis detected biological pathways associated with uterus development, embryonic skeletal system development, and nervous system development. Additionally, gene ontology terms from the topology-based pathway enrichment analysis were mostly related to the steroid hormones signalling pathway. Although difficult, genes specific to gametic incompatibility could be differentiated from genes underlying other reproduction processes by refining the genetic regions with TRD. With further investigation, we will provide new information to improve mate allocation for the dairy cattle industry.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".