Gene expression profiling and silencing reveal that monolignol biosynthesis plays a critical role in penetration defence in wheat against powdery mildew invasion
Bibliographic record
Abstract
Cell wall apposition (CWA) formation is one of the first lines of defence used by plants to halt invading fungi such as powdery mildew. Lignin is a complex polymer of hydroxylated and methoxylated phenylpropane units (monolignols) and lignification renders the cell wall more resistant to pathogen attack. The role of monolignol biosynthesis in CWA-mediated defence against powdery mildew penetration into cereals is demonstrated here using RNA interference (RNAi)-mediated gene silencing and enzyme-specific inhibitors. Thirteen cDNAs representing eight genes involved in monolignol biosynthesis were cloned from an expression sequence tag (EST) library derived from the epidermis of diploid wheat (Triticum monococcum) infected with Blumeria graminis f. sp. tritici (Bgt). Differential expression patterns were found for these genes in susceptible and resistant plants after infection. Transcripts of phenylalanine ammonia lyase (PAL), caffeic acid O-methyltransferase (CAOMT), ferulic acid hydroxylase (FAH), caffeoyl-CoA O-methyltransferase (CCoAMT), and cinnamyl alcohol dehydrogenase (CAD) were accumulated, particularly in the epidermis. RNAi-mediated transient gene silencing in the epidermis led to a higher penetration efficiency of Bgt than in the controls. Gene silencing also compromised penetration resistance to varying degrees with different genes against an inappropriate pathogen, B. graminis f. sp. hordei (Bgh). Co-silencing led to greater penetration of Bgt or Bgh than when the genes were silenced separately. Fluorescence emission spectra analyses revealed that gene silencing hampered host autofluorescence response at fungal contact sites. These results illustrate that monolignol biosynthesis is critically important for host defence against both appropriate and inappropriate pathogen invasion in wheat.
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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".