Genetic Architecture of Leaf Ecophysiological Traits in Helianthus
Bibliographic record
Abstract
We investigated quantitative trait loci (QTLs) for several leaf chemistry traits in early-generation hybrids between Helianthus annuus and Helianthus petiolaris, the parental species of the ancient diploid hybrid sunflower species Helianthus anomalus, Helianthus deserticola, and Helianthus paradoxus. We grew individuals of a second-generation backcross (BC(2)) toward H. petiolaris under optimum conditions in a glass house experiment. Trait values were measured once for each individual. In addition, genotypic data previously determined for each individual were employed for composite interval mapping of QTLs. We detected QTLs for leaf carbon concentration, leaf nitrogen concentration, leaf nitrogen per unit area, and photosynthetic nitrogen use efficiency. Leaf carbon isotope discrimination (delta(13)C) and leaf nitrogen isotopic composition (delta(15)N) were analyzed, but no significant QTLs were found for these traits. Interestingly, two neighboring loci explained a relatively large percentage of the variation in leaf nitrogen per unit area. This was notable because leaf nitrogen has been shown to strongly affect the fitness of early-generation sunflower hybrids in the H. anomalus habitat, and QTLs of large effect are expected to respond relatively quickly to selection. We speculate that the genetic architecture underlying leaf nitrogen may have facilitated the colonization of active desert sand dunes by H. anomalus.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".