Species- and genome-wide dissection of the shoot ionome in Brassica napus and its relationship to seedling development
Bibliographic record
Abstract
Knowing the genetic basis of the plant ionome is essential for understanding the control of nutrient transport and accumulation. The aim of this research was to (i) study mineral nutrient concentrations in a large and diverse set of Brassica napus, (ii) describe the relationships between the shoot ionome and seedling development, and (iii) identify genetic regions associated with variation of the shoot ionome. The plant material under study was a germplasm set consisting of 509 inbred lines that was genotyped by a 6K single nucleotide polymorphism (SNP) array and phenotyped by analyzing the concentrations of eleven mineral nutrients in the shoots of 30 days old seedlings. Among mineral concentrations, positive correlations were found, whereas mineral concentrations were mainly negatively correlated with seedling development traits from earlier studies. In a genome-wide association mapping approach, altogether 29 significantly associated loci were identified across seven traits after correcting for multiple testing. The associations included a locus with effects on the concentrations of Cu, Mn, and Zn on chromosome C3, and a genetic region with multiple associations for Na concentration on chromosome A9. This region was situated within an association hotspot close to SOS1, a key gene for Na tolerance in plants.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".