Genome‐wide genotyping‐by‐sequencing data provide a high‐resolution view of wild <i>Helianthus</i> diversity, genetic structure, and interspecies gene flow
Bibliographic record
Abstract
PREMISE: Wild sunflowers harbor considerable genetic diversity and are a major resource for improvement of the cultivated sunflower, Helianthus annuus. The Helianthus genus is also well known for its propensity for gene flow between taxa. METHODS: We surveyed genomic diversity of 292 samples of wild Helianthus from 22 taxa that are cross-compatible with the cultivar using genotyping by sequencing. With these data, we derived a high-resolution phylogeny of the taxa, interrogated genome-wide levels of diversity, explored H. annuus population structure, and identified localized gene flow between H. annuus and its close relatives. KEY RESULTS: Our phylogenomic analyses confirmed a number of previously established interspecific relationships and indicated for the first time that a newly described annual sunflower, H. winteri, is nested within H. annuus. Principal component analyses showed that H. annuus has geographic population structure with most notable subpopulations occurring in California and Texas. While gene flow was identified between H. annuus and H. bolanderi in California and between H. annuus and H. argophyllus in Texas, this genetic exchange does not appear to drive observed patterns of H. annuus population structure. CONCLUSIONS: Wild H. annuus remains an excellent resource for cultivated sunflower breeding effort because of its diversity and the ease with which it can be crossed with cultivated H. annuus. Cases of interspecific gene flow such as those documented here also indicate wild H. annuus can act as a bridge to capture alleles from other wild taxa; continued breeding efforts with it may therefore reap the largest rewards.
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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".