Evolutionary potential for genomic islands of sexual divergence on recombining sex chromosomes
Bibliographic record
Abstract
Differentiated sex chromosomes are thought to develop through the accumulation of polymorphisms at loci subject to opposing selection between males and females, and/or between haploids and diploids. As sex chromosomes differentiate, reduced recombination becomes favored between selected loci and the sex-determining region, strengthening genetic associations between alleles favored in a sex and the corresponding sex chromosome. Here a model is analyzed to explore whether polymorphism at one sexually or ploidally antagonistic locus facilitates the spread of rare alleles at other loci experiencing antagonistic selection, promoting further differentiation of the sex chromosomes. It is found that antagonistic polymorphisms can spread and capture other such loci, building 'genomic islands' of differentiation on sex chromosomes, but the conditions are very restrictive, requiring the loci to be strongly selected, tightly linked and distant from the sex-determining region. Epistatic interactions can facilitate the promotion of polymorphism among selected loci, but only if preferentially favoring heterozygotes. Although these results apply to any taxa, plants provide a fertile ground for testing these and related theories given the recurrent evolutionary transitions to dioecy, which provide multiple opportunities to track the early evolution of sex chromosomes.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".