Identification and functional analysis of mitogen-activated protein kinase kinase kinase (MAPKKK) genes in canola (Brassica napus L.)
Bibliographic record
Abstract
Mitogen-activated protein kinase (MAPK) signalling cascades, consisting of three types of reversibly phosphorylated kinases (MAPKKK, MAPKK, and MAPK), are involved in important processes including plant immunity and hormone responses. The MAPKKKs comprise the largest family in the MAPK cascades, yet only a few of these genes have been associated with physiological functions, even in the model plant Arabidopsis thaliana. Canola (Brassica napus L.) is one of the most important oilseed crops in China and worldwide. To explore MAPKKK functions in biotic and abiotic stress responses in canola, 66 MAPKKK genes were identified and 28 of them were cloned. Phylogenetic analysis of these canola MAPKKKs with homologous genes from representative species classified them into three groups (A-C), comprising four MAPKKKs, seven ZIKs, and 17 Raf genes. A further 15 interaction pairs between these MAPKKKs and the downstream BnaMKKs were identified through a yeast two-hybrid assay. The interactions were further validated through bimolecular fluorescence complementation (BiFC) analysis. In addition, by quantitative real-time reverse transcription-PCR, it was further observed that some of these BnaMAPKKK genes were regulated by different hormone stimuli, abiotic stresses, or fungal pathogen treatments. Interestingly, two novel BnaMAPKKK genes, BnaMAPKKK18 and BnaMAPKKK19, which could elicit hypersensitive response (HR)-like cell death when transiently expressed in Nicotiana benthamiana leaves, were successfully identified. Moreover, it was found that BnaMAPKKK19 probably mediated cell death through BnaMKK9. Overall, the present work has laid the foundation for further characterization of this important MAPKKK gene family in canola.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".