Population genomics of parallel phenotypic evolution in stickleback across stream–lake ecological transitions
Bibliographic record
Abstract
Understanding the genetics of adaptation is a central focus in evolutionary biology. Here, we use a population genomics approach to examine striking parallel morphological divergences of parapatric stream-lake ecotypes of threespine stickleback fish in three watersheds on the Haida Gwaii archipelago, western Canada. Genome-wide variation at greater than 1000 single nucleotide polymorphism loci indicate separate origin of giant lake and small-bodied stream fish within each watershed (mean F(ST) between watersheds = 0.244 and within = 0.114). Genome scans within watersheds identified a total of 21 genomic regions that are highly differentiated between ecotypes and are probably subject to directional selection. Most outliers were watershed-specific, but genomic regions undergoing parallel genetic changes in multiple watersheds were also identified. Interestingly, several of the stream-lake outlier regions match those previously identified in marine-freshwater and benthic-limnetic genome scans, indicating reuse of the same genetic loci in different adaptive scenarios. We also identified multiple new outlier loci, which may contribute to unique aspects of differentiation in stream-lake environments. Overall, our data emphasize the important role of ecological boundaries in driving both local and broadly occurring parallel genetic changes during 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 | 0.001 |
| 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".