Genome scans reveal candidate domestication and improvement genes in cultivated sunflower, as well as post‐domestication introgression with wild relatives
Bibliographic record
Abstract
The development of modern crops typically involves both selection and hybridization, but to date most studies have focused on the former. In the present study, we explore how both processes, and their interactions, have molded the genome of the cultivated sunflower (Helianthus annuus), a globally important oilseed. To identify genes targeted by selection during the domestication and improvement of sunflower, and to detect post-domestication hybridization with wild species, we analyzed transcriptome sequences of 80 genotypes, including wild, landrace, and modern lines of H. annuus, as well as two cross-compatible wild relatives, Helianthus argophyllus and Helianthus petiolaris. Outlier analyses identified 122 and 15 candidate genes associated with domestication and improvement, respectively. As in several previous studies, genes putatively involved in oil biosynthesis were the most extreme outliers. Additionally, several promising associations were observed with previously mapped quantitative trait loci (QTLs), such as branching. Admixture analyses revealed that all the modern cultivar genomes we examined contained one or more introgressions from wild populations, with every chromosome having evidence of introgression in at least one modern line. Cumulatively, introgressions cover c. 10% of the cultivated sunflower genome. Surprisingly, introgressions do not avoid candidate domestication genes, probably because of the reintroduction of branching.
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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".