GhSTZ-Mediated Suppression of Metabolic–Immune Coordination Compromises Cotton Defense Against Verticillium Wilt
Bibliographic record
Abstract
Verticillium wilt (VW), caused by Verticillium dahliae, poses a significant threat to global cotton production. Through analysis of public transcriptome databases, this study identified GhSTZ, a C2H2 zinc finger protein transcription factor gene, which was significantly induced by V. dahliae. Suppressing GhSTZ expression via virus-induced gene silencing significantly enhanced cotton resistance to VW. This resistance manifested as a 1.2-fold increase in lignin deposition, optimized ROS (reactive oxygen species) homeostasis, and a 1.3-fold elevation in glucose levels. Transcriptome analysis revealed 338 differentially expressed genes in GhSTZ-silenced plants, with 97 upregulated and 241 downregulated. Key downregulated genes included PME (pectin methylesterase) and PG1-pec (polygalacturonase) in the pentose phosphate pathway, while the key upregulated genes comprised C4H (cinnamate 4-hydroxylase) and C3H (p-coumarate 3-hydroxylase) in the phenylpropanoid biosynthesis pathway. Notably, in the plant–pathogen interaction signaling pathway, approximately half of the genes exhibited upregulated expression while the other half showed downregulation. Protein–protein interaction network analysis further revealed cooperative interaction between PME and the secoisolariciresinol dehydrogenase SIRD. This study is the first to elucidate GhSTZ as a negative regulator that compromises cotton disease resistance through a tripartite mechanism. These findings offer a novel approach to enhancing crop disease resistance by targeting the negative regulatory genes.
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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 | 0.000 | 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) | 0.000 | 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".