Somatic Mosaicism in Bulls Estimated from Genome-Wide CNV Array and <b><i>TSPY</i></b> Gene Copy Numbers
Bibliographic record
Abstract
Somatic mosaicism has become a focus in human research due to the implications of individual genetic variability in disease. Here, we assessed somatic copy number variations (CNVs) in Holstein bulls in 2 respects. We estimated genome-wide CNVs and assayed CNVs of the TSPY gene, the most variable bovine gene from the Y chromosome. Somatic tissues (blood, lung, heart, muscle, testis, and brain) of 4 bulls were arrayed on the Illumina Bovine SNP50k chip and qPCR tested for TSPY copy numbers. Our results showed extensive copy number divergence in tissues within the same animal as well as significant copy number alterations of TSPY. We detected a mean of 31 CNVs per animal among which 14 were of germline origin, as they were constantly present in all investigated tissues of the animal, while 18 were specific to 1 tissue. Thus, 57% of the total number of detected CNVs was the result of de novo somatic events. Further, TSPY copy number was found to vary significantly among tissues as well as among the same tissue type from different animals in a wide range from 7 to 224% of the calibrator. Our study shows significant autosomal and Y-chromosomal de novo somatic CNV in bulls.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".