The genomic pool of standing structural variation outnumbers single nucleotide polymorphism by threefold in the marine teleost <i>Chrysophrys auratus</i>
Bibliographic record
Abstract
Recent studies have highlighted an important role of structural variation (SV) in ecological and evolutionary processes, but few have studied nonmodel species in the wild. As part of our long-term research programme on the nonmodel teleost fish Australasian snapper (Chrysophrys auratus), we aim to build one of the first catalogues of genomic variants (SNPs and indels, and deletions, duplications and inversions) in fishes and evaluate overlap of genomic variants with regions under putative selection (Tajima's D and π), and coding sequences (genes). For this, we analysed six males and six females from three locations in New Zealand and generated a high-resolution genomic variation catalogue. We characterized 20,385 SVs and found they intersected with almost a third of all annotated genes. Together with small indels, SVs account for three times more variation in the genome in terms of bases affected compared to SNPs. We found that a sizeable portion of detected SVs was in the upper and lower genomic regions of Tajima's D and π, indicating that some of these have an effect on the phenotype. Together, these results shed light on the often neglected genomic variation that is produced by SVs and highlights the need to go beyond the mere measure of SNPs when investigating evolutionary processes, such as species diversification and adaptation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".