Searching for intralocus sexual conflicts in the three-spined stickleback ( <i>Gasterosteus aculeatus</i> ) genome
Bibliographic record
Abstract
Differences between sexes in trait fitness optima can generate intralocus sexual conflicts that have the potential to maintain genetic diversity through balancing selection. However, these differences are unlikely to be associated with strong selective coefficients and are challenging to detect. Additionally, recent studies have highlighted that duplications on sexual chromosomes can create artifactual signals of intralocus sexual conflicts. Thus, testing the relationship between intralocus sexual conflicts and balancing selection requires stringent filtering of duplicated regions, and dedicated methods to detect loci with low levels of intersex differentiation. In this study, we investigated intralocus sexual conflicts in the three-spined stickleback using whole-genome sequencing (mean coverage = 12×) of 50 females and 49 males from an anadromous population in the St. Lawrence River, Québec, Canada. After stringent filtering of duplications from the sex chromosomes, we compared three methods to detect intralocus sexual conflicts. We found only two genomic regions under potential intralocus sexual conflict that also showed signals of balancing selection. Overall, our results suggest that most intralocus sexual conflicts do not drive long-term balancing selection and are most likely transient.
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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".