MOLECULAR DEMOGRAPHIC HISTORY OF THE ANNUAL SUNFLOWERS<i>HELIANTHUS ANNUUS</i>AND<i>H. PETIOLARIS</i>-LARGE EFFECTIVE POPULATION SIZES AND RATES OF LONG-TERM GENE FLOW
Bibliographic record
Abstract
Hybridization between distinct species may lead to introgression of genes across species boundaries, and this pattern can potentially persist for extended periods as long as selection at some loci or genomic regions prevents thorough mixing of gene pools. However, very few reliable estimates of long-term levels of effective migration are available between hybridizing species throughout their history. Accurate estimates of divergence dates and levels of gene flow require data from multiple unlinked loci as well as an analytical framework that can distinguish between lineage sorting and gene flow and incorporate the effects of demographic changes within each species. Here we use sequence data from 18 anonymous nuclear loci in two broadly sympatric sunflower species, Helianthus annuus and H. petiolaris, analyzed within an "isolation with migration" framework to make genome-wide estimates of the ages of these two species, long-term rates of gene flow between them, and effective population sizes and historical patterns of population growth. Our results indicate that H. annuus and H. petiolaris are approximately one million years old and have exchanged genes at a surprisingly high rate (long-term N(ef)m estimates of approximately 0.5 in each direction), with somewhat higher rates of introgression from H. annuus into H. petiolaris than vice versa. In addition, each species has undergone dramatic population expansion since divergence, and both species have among the highest levels of genetic diversity reported for flowering plants. Our results provide the most comprehensive estimate to date of long-term patterns of gene flow and historical demography in a nonmodel plant system, and they indicate that species integrity can be maintained even in the face of extensive gene flow over a prolonged period.
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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) | 0.000 | 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".