Genomic Patterns of Adaptive Divergence between Chromosomally Differentiated Sunflower Species
Bibliographic record
Abstract
Understanding the genetic mechanisms of speciation and basis of species differences is among the most important challenges in evolutionary biology. Two questions of particular interest are what roles divergent selection and chromosomal differentiation play in these processes. A number of recently proposed theories argue that chromosomal rearrangements can facilitate the development and maintenance of reproductive isolation and species differences by suppressing recombination within rearranged regions. Reduced recombination permits the accumulation of alleles contributing to isolation and adaptive differentiation and protects existing differences from the homogenizing effects of introgression between incipient species. Here, we examine patterns of genetic diversity and divergence in rearranged versus collinear regions in two widespread, extensively hybridizing sunflower species, Helianthus annuus and Helianthus petiolaris, using sequence data from 77 loci distributed throughout the genomes of the two species. We find weak evidence for increased genetic divergence near chromosomal break points but not within rearranged regions overall. We find no evidence for increased rates of adaptive divergence on rearranged chromosomes; in fact, collinear chromosomes show a far greater excess of fixed amino acid differences between the two species. A comparison with a third sunflower species indicates that much of the nonsynonymous divergence between H. annuus and H. petiolaris probably occurred during or soon after their formation. Our results suggest a limited role for chromosomal rearrangements in genetic divergence, but they do document substantial adaptive divergence and provide further evidence of how species integrity and genetic identity can be maintained at many loci in the face of extensive hybridization and gene flow.
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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 | 0.001 | 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".