Non-Random Distribution of Reciprocal Translocation Breakpoints in the Pig Genome
Bibliographic record
Abstract
Balanced chromosome rearrangements are one of the main etiological factors contributing to hypoprolificacy in the domestic pig. Amongst domestic animals, the pig is considered to have the highest prevalence of chromosome rearrangements. To date over 200 unique chromosome rearrangements have been identified. The factors predisposing pigs to chromosome rearrangements, however, remain poorly understood. Nevertheless, here we provide empirical evidence which sustains the notion that there is a non-random distribution of chromosomal rearrangement breakpoints in the pig genome. We sought to establish if there are structural chromosome factors near which rearrangement breakpoints preferentially occur. The distribution of rearrangement breakpoints was analyzed across three level, chromosomes, chromosome arms, and cytogenetic GTG-bands (G-banding using trypsin and giemsa). The frequency of illegitimate exchanges (e.g., reciprocal translocations) between individual chromosomes and chromosome arms appeared to be independent of chromosome length and centromere position. Meanwhile chromosome breakpoints were overrepresented on some specific G-bands, defining chromosome hotspots for ectopic exchanges. Cytogenetic band level factors, such as the length of bands, chromatin density, and presence of fragile sites, were associated with the presence of translocation breakpoints. The characteristics of these bands were largely similar to that of hotspots in the human genome. Therefore, those hotspots are proposed as a starting point for future molecular analyses into the genomic landscape of porcine chromosome rearrangements.
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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) | 0.001 | 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".