Whole-genome DNA methylation analysis of the sperm in relation to bull fertility
Bibliographic record
Abstract
In brief: Bull fertility is an important economic trait, this study identified some DNA methylation biomarkers that are associated with bull fertility. Abstract: Subfertile bulls may cause huge economic losses in dairy production since their semen could be used to inseminate thousands of cows by artificial insemination. This study adopted whole-genome enzymatic methyl sequencing and aimed to identify candidate DNA methylation markers in bovine sperm that correlate with bull fertility. Twelve bulls were selected (high bull fertility = 6; low bull fertility = 6) based on the industry's internally used Bull Fertility Index. After sequencing, a total of 450 CpG had a DNA methylation difference higher than 20% (q < 0.01) had been screened. The 16 most significant differentially methylated regions (DMRs) were identified using a 10% methylation difference cut-off (q < 5.88 × 10-16). Interestingly, most of the differentially methylated cytosines (DMCs) and DMRs were distributed on the X and Y chromosomes, demonstrating that the sex chromosomes play essential roles in bull fertility. Additionally, the functional classification showed that the beta-defensin family, zinc finger protein family, and olfactory and taste receptors could be clustered. Moreover, the enriched G protein-coupled receptors such as neurotransmitter receptors, taste receptors, olfactory receptors, and ion channels indicated that the acrosome reaction and capacitation processes are pivotal for bull fertility. In conclusion, this study identified the sperm-derived bull fertility-associated DMRs and DMCs at the whole genome level, which could complement and integrate into the existing genetic evaluation methods, increasing our decisive capacity to select good bulls and explain bull fertility better in the future.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".