Genome-wide analysis of the harbour porpoise (Phocoena phocoena) indicates isolation-by-distance across the North Atlantic and potential local adaptation in adjacent waters
Bibliographic record
Abstract
Abstract The harbour porpoise ( Phocoena phocoena ), a highly mobile cetacean species of the Northern Hemisphere, inhabits basins that vary broadly in salinity, temperature, and food availability; such variation can drive divergent adaptation among local populations. To shed light on range-wide population structure and local adaptation, we generated ddRAD sequencing data spanning the entire North Atlantic and the Baltic Sea, as well as the Black Sea as an outgroup, and mapped this data to the high-quality draft genome of the species. We identified 11,978 genome-wide SNPs from 150 individuals, which we used for population genetic inferences. Our results support genetic differentiation between North Atlantic and Baltic Sea populations, with Kattegat as a transition zone. Across the North Atlantic the population differentiation is subtle from west to east, congruent with an isolation-by-distance pattern, but indicates a separation of southern North Sea harbour porpoises. We identified genomic outlier regions, i.e., scaffold regions where SNPs with high F ST across North Atlantic populations co-occur. Together with the draft genome annotation, these regions could point towards candidate genes for differential local adaptation processes among populations. Furthermore, they enable the development of a SNP panel for routine population assignment which will be useful in a conservation and management context. We identified six outlier loci putatively under positive selection, based on the population structure inferred from the complete SNP set. Our study highlights the value of genome resources in conservation and management and provides a crucial additional resource for the study of harbour porpoise evolution and phylogeny.
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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 | 0.000 | 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".