Cytogenetic screening of a Canadian swine breeding nucleus using a newly developed karyotyping method named oligo-banding
Bibliographic record
Abstract
BACKGROUND: The frequency of chromosomal rearrangements in Canadian breeding boars has been estimated at 0.91 to 1.64%. These abnormalities are widely recognized as a potential cause of subfertility in livestock production. Since artificial insemination is practiced in almost all intensive pig production systems, the use of elite boars carrying cytogenetic defects that have an impact on fertility can lead to major economic losses. To avoid keeping subfertile boars in artificial insemination centres and spreading chromosomal defects within populations, cytogenetic screening of boars is crucial. Different techniques are used for this purpose, but several issues are frequently encountered, i.e. environmental factors can influence the quality of results, the lack of genomic information outputted by these techniques, and the need for prior cytogenetic skills. The aim of this study was to develop a new pig karyotyping method based on fluorescent banding patterns. RESULTS: The use of 207,847 specific oligonucleotides generated 96 fluorescent bands that are distributed across the 18 autosomes and the sex chromosomes. Tested alongside conventional G-banding, this oligo-banding method allowed us to identify four chromosomal translocations and a rare unbalanced chromosomal rearrangement that was not detected by conventional banding. In addition, this method allowed us to investigate chromosomal imbalance in spermatozoa. CONCLUSIONS: The use of oligo-banding was found to be appropriate for detecting chromosomal aberrations in a Canadian pig nucleus and its convenient design and use make it an interesting tool for livestock karyotyping and cytogenetic studies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".