Biosynthesis of sakuranetin regulated by <scp>O</scp>s<scp>MPK</scp>6‐<scp>O</scp>s<scp>WRKY</scp>67‐<scp>O</scp>s<scp>NOMT</scp> cascade enhances resistance to false smut disease
Bibliographic record
Abstract
Rice false smut disease, caused by the fungal pathogen Ustilaginoidea virens, significantly restricts both the production and quality of rice grains. However, the molecular mechanism underlying rice resistance against U. virens remain largely elusive. Transcriptome analysis of rice panicles infected with U. virens revealing the crucial role of genes involved in sakuranetin biosynthesis in conferring resistance to the pathogen. In vitro assays demonstrated that sakuranetin was most effective at inhibiting mycelial growth, spore germination, and host infection by U. virens. The expression of OsNOMT, the key enzyme in sakuranetin biosynthesis, is directly regulated by the transcription factor OsWRKY67. Furthermore, OsMPK6, a mitogen-activated protein kinase, interacts with and phosphorylates OsWRKY67, thereby modulating sakuranetin biosynthesis and resistance to U. virens. Moreover, the exogenous application of synthetic sakuranetin significantly reduces U. virens infection. Our findings reveal that the OsMPK6-OsWRKY67-OsNOMT signaling cascade plays a pivotal role in rice resistance to U. virens by regulating sakuranetin biosynthesis.
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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 | 0.000 | 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) | 0.001 | 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".