A MAP kinase cascade broadly regulates development and virulence of <i>Sclerotinia sclerotiorum</i> and can be targeted by HIGS for disease control
Bibliographic record
Abstract
Abstract Sclerotinia sclerotiorum causes white mold or stem rot in a broad range of economically important plants, bringing significant yield losses worldwide. Host-induced gene silencing (HIGS) has been showing promising effects in controlling many fungal pathogens, including S. sclerotiorum . However, molecular genetic understanding of signaling pathways involved in its development and pathogenicity is needed to provide effective host-induced gene silencing (HIGS) targets for disease control. Here, by employing a forward genetic screen, we characterized an evolutionarily conserved mitogen-activated protein kinase (MAPK) cascade in S. sclerotiorum , consisting of SsSte50-SsSte11-SsSte7-Smk1, controlling mycelial growth, sclerotia development, compound appressoria formation, virulence, and hyphal fusion. Moreover, disruption of the putative downstream transcription factor SsSte12 led to normal sclerotia but aberrant appressoria formation and host penetration defects, suggestive of diverged regulation downstream of the MAPK cascade. Most importantly, targeting of SsSte50 using host-expressed HIGS double stranded RNA resulted in largely reduced virulence of S. sclerotiorum on Nicotiana benthamiana leaves. Therefore, this MAPK signaling cascade is generally needed for its growth, development, and pathogenesis, and is an ideal HIGS target for mitigating economic damages caused by S. sclerotiorum infection.
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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".