Ancestral and neo-sex chromosomes contribute to population divergence in a dioecious plant
Bibliographic record
Abstract
ABSTRACT Empirical evidence from several animal groups suggests that sex chromosomes may disproportionately contribute to reproductive isolation. This occurs particularly when sex chromosomes are associated with turnover of sex determination systems resulting from structural rearrangements to the sex chromosomes. We investigated these predictions in the dioecious plant Rumex hastatulus , which is comprised of populations of two sex chromosome cytotypes. Using population genomic analyses, we investigated the demographic history of R. hastatulus and explored the contributions of ancestral and neo-sex chromosomes to population genetic divergence. Our study revealed that the cytotypes represented genetically divergent populations with evidence for historical but not contemporary gene flow between them. In agreement with classical predictions, we found that the ancestral X chromosome was disproportionately divergent compared with the rest of the genome. Excess differentiation was also observed on the Y chromosome, even when using measures of differentiation that control for differences in effective population size. Our estimates of the timing of the origin of the neo-sex chromosomes in R. hastatulus are coincident with cessation of gene flow, suggesting that the chromosomal fusion event that gave rise to the origin of the XYY cytotype may have also been a key driver of reproductive isolation.
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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 | 0.000 | 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".