Nucleotide and structural polymorphisms of the eastern oyster genome paint a mosaic of divergence, selection, and human impacts
Bibliographic record
Abstract
Abstract The eastern oyster, Crassostrea virginica , is a valuable fishery and aquaculture species that provides critical services as an ecosystem engineer. Oysters have a life-history that promotes high genetic diversity and gene flow while also occupying a wide range of habitats in variable coastal environments from the southern Gulf of Mexico to the southern waters of Atlantic Canada. To understand the interplay of genetic diversity, gene flow, and intense environmental selection, we used whole genome re-sequencing data from 90 individuals across the eastern United States and Gulf of Mexico, plus 5 selectively bred lines. Our data confirmed a large phylogeographic break between oyster populations in the Gulf of Mexico and the Atlantic coast of the USA. We also demonstrated that domestication has artificially admixed genetic material between the two ocean basins, and selected lines with admixed ancestry continue to maintain heterozygosity at these sites through several generations post admixture, possibly indicating relevance to desirable aquaculture traits. We found that genetic and structural variation are high in both wild and selected populations, but we also demonstrated that, when controlling for domestication admixture across ocean basins, wild populations do have significantly higher levels of nucleotide diversity and copy number variation than selected lines. Within the Atlantic coast, we detected subtle but distinct population structure, introgression of selected lines within wild individuals, an interaction between structural variation and putatively adaptive population structure, and evidence of candidate genes responding to selection from salinity. Our study highlights the potential for applying whole genome sequencing to highly polymorphic species and provides a road map for future work examining the genome variation of eastern oyster populations.
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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 | 0.000 | 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".