Genetic evidence for environment-dependent hybrid incompatibilities in threespine stickleback
Bibliographic record
Abstract
Hybrid incompatibilities occur when interactions between opposite-ancestry alleles at different loci reduce the fitness of hybrids. Most work on incompatibilities has focused on those that are ‘intrinsic’, meaning they affect viability and sterility in the laboratory. Theory predicts that ecological selection can also underlie hybrid incompatibilities, but tests of this hypothesis are scarce. In this article, we compiled genetic data for F 2 hybrid crosses between divergent populations of threespine stickleback fish ( Gasterosteus aculeatus L.) that were born and raised in either the field (semi-natural experimental ponds) or the laboratory (aquaria). We tested for differences in excess heterozygosity between these two environments at ancestry informative loci—a genetic signature of selection against incompatibilities. We found that excess ancestry heterozygosity was elevated by approximately 3% in crosses raised in ponds compared to those raised in aquaria. Previous results from F1 hybrids in the field suggest that pond-specific (single-locus) heterosis is unlikely to explain this finding. Our study suggests that, in stickleback, a coarse signal of environment-dependent hybrid incompatibilities is reliably detectable and that extrinsic incompatibilities have evolved before intrinsic incompatibilities.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".