Identification and characterisation of de novo germline structural variants in two commercial pig lines using trio-based whole genome sequencing
Bibliographic record
Abstract
BACKGROUND: De novo mutations arising in the germline are a source of genetic variation and their discovery broadens our understanding of genetic disorders and evolutionary patterns. Although the number of de novo single nucleotide variants (dnSNVs) has been studied in a number of species, relatively little is known about the occurrence of de novo structural variants (dnSVs). In this study, we investigated 37 deeply sequenced pig trios from two commercial lines to identify dnSVs present in the offspring. The identified dnSVs were characterised by identifying their parent of origin, their functional annotations and characterizing sequence homology at the breakpoints. RESULTS: We identified four swine germline dnSVs, all located in intronic regions of protein-coding genes. Our conservative, first estimate of the swine germline dnSV rate is 0.108 (95% CI 0.038-0.255) per generation (one dnSV per nine offspring), detected using short-read sequencing. Two detected dnSVs are clusters of mutations. Mutation cluster 1 contains a de novo duplication, a dnSNV and a de novo deletion. Mutation cluster 2 contains a de novo deletion and three de novo duplications, of which one is inverted. Mutation cluster 2 is 25 kb in size, whereas mutation cluster 1 (197 bp) and the other two individual dnSVs (64 and 573 bp) are smaller. Only mutation cluster 2 could be phased and is located on the paternal haplotype. Mutation cluster 2 originates from both micro-homology as well as non-homology mutation mechanisms, where mutation cluster 1 and the other two dnSVs are caused by mutation mechanisms lacking sequence homology. The 64 bp deletion and mutation cluster 1 were validated through PCR. Lastly, the 64 bp deletion and the 573 bp duplication were validated in sequenced offspring of probands with three generations of sequence data. CONCLUSIONS: Our estimate of 0.108 dnSVs per generation in the swine germline is conservative, due to our small sample size and restricted possibilities of dnSV detection from short-read sequencing. The current study highlights the complexity of dnSVs and shows the potential of breeding programs for pigs and livestock species in general, to provide a suitable population structure for identification and characterisation of dnSVs.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".