Whole‐genome sequencing reveals fine‐scale environment‐associated divergence near the range limits of a temperate reef fish
Bibliographic record
Abstract
Abstract Environmental variation is increasingly recognized as an important driver of diversity in marine species despite the lack of physical barriers to dispersal and the presence of pelagic stages in many taxa. A robust understanding of the genomic and ecological processes involved in structuring populations is lacking for most marine species, often hindering management and conservation action. Cunner (Tautogolabrus adspersus) is a temperate reef fish with both pelagic early life‐history stages and strong site‐associated homing as adults; the species is also of interest for use as a cleaner fish in salmonid aquaculture in Atlantic Canada. We aimed to characterize genomic and geographic differentiation of cunner in the Northwest Atlantic. To achieve this, a chromosome‐level genome assembly for cunner was produced and used to characterize spatial population structure throughout Atlantic Canada using whole‐genome sequencing. The genome assembly spanned 0.72 Gbp and 24 chromosomes; whole‐genome sequencing of 803 individuals from 20 locations from Newfoundland to New Jersey identified approximately 11 million genetic variants. Principal component analysis revealed four regional Atlantic Canadian groups. Pairwise FST and selection scans revealed signals of differentiation and selection at discrete genomic regions, including adjacent peaks on chromosome 10 across multiple pairwise comparisons (i.e. FST 0.5–0.75). Redundancy analysis suggested association of environmental variables related to benthic temperature and oxygen range with genomic structure. Results suggest regional scale diversity in this temperate reef fish and can directly inform the collection and translocation of cunner for aquaculture applications and the conservation of wild populations throughout the Northwest Atlantic.
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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 | 0.001 | 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".