QTLs for resistance to the false brome rust<i>Puccinia brachypodii</i>in the model grass<i>Brachypodium distachyon</i>L.
Bibliographic record
Abstract
The potential of the model grass Brachypodium distachyon L. (Brachypodium) for studying grass-pathogen interactions is still underexploited. We aimed to identify genomic regions in Brachypodium associated with quantitative resistance to the false brome rust fungus Puccinia brachypodii . The inbred lines Bd3-1 and Bd1-1, differing in their level of resistance to P. brachypodii, were crossed to develop an F(2) population. This was evaluated for reaction to a virulent isolate of P. brachypodii at both the seedling and advanced growth stages. To validate the results obtained on the F(2), resistance was quantified in F(2)-derived F(3) families in two experiments. Disease evaluations showed quantitative and transgressive segregation for resistance. A new AFLP-based Brachypodium linkage map consisting of 203 loci and spanning 812 cM was developed and anchored to the genome sequence with SSR and SNP markers. Three false brome rust resistance QTLs were identified on chromosomes 2, 3, and 4, and they were detected across experiments. This study is the first quantitative trait analysis in Brachypodium. Resistance to P. brachypodii was governed by a few QTLs: two acting at the seedling stage and one acting at both seedling and advanced growth stages. The results obtained offer perspectives to elucidate the molecular basis of quantitative resistance to rust fungi.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".