Partially repeatable genetic basis of benthic adaptation in threespine sticklebacks
Bibliographic record
Abstract
The extent to which convergent adaptation to similar ecological niches occurs by a predictable genetic basis remains a fundamental question in biology. Threespine stickleback fish have undergone an adaptive radiation in which ancestral oceanic populations repeatedly colonized and adapted to freshwater habitats. In multiple lakes in British Columbia, two different freshwater ecotypes have evolved: a deep-bodied benthic form adapted to forage near the lake substrate, and a narrow-bodied limnetic form adapted to forage in open water. Here, we use genome-wide linkage mapping in marine × benthic F2 genetic crosses to test the extent of shared genomic regions underlying benthic adaptation in three benthic populations. We identify at least 100 Quantitative Trait Loci (QTL) harboring genes influencing skeletal morphology. The majority of QTL (57%) are unique to one cross. However, four genomic regions affecting eight craniofacial and armor phenotypes are found in all three benthic populations. We find that QTL are clustered in the genome and overlapping QTL regions are enriched for genomic signatures of natural selection. These findings suggest that benthic adaptation has occurred via both parallel and nonparallel genetic changes.
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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 | 0.000 |
| 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) | 0.001 | 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".