Endogenous silencing of <i><scp>P</scp>uccinia triticina</i> pathogenicity genes through <i>in planta</i>‐expressed sequences leads to the suppression of rust diseases on wheat
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Rust fungi are destructive plant pathogens. The draft genomes of several wheat-infecting species have been released and potential pathogenicity genes identified through comparative analyses to fungal pathogens that are amenable to genetic manipulation. Functional gene analysis tools are needed to understand the infection process of these obligate parasites and to confirm whether predicted pathogenicity genes could become targets for disease control. We have modified an Agrobacterium tumefaciens-mediated in planta-induced transient gene silencing (PITGS) assay for use in Triticum spp. (wheat), and used this assay to target predicted wheat leaf rust fungus, Puccinia triticina (Pt) pathogenicity genes, a MAP kinase (PtMAPK1), a cyclophilin (PtCYC1) and calcineurin B (PtCNB), to analyze their roles in disease. Agroinfiltration effectively delivered hairpin silencing constructs in wheat, leading to the generation of fungal gene-specific siRNA molecules in infiltrated leaves, and resulting in up to 70% reduction in transcription of the endogenous target genes in superinfected Pt. In vivo silencing caused severe disease suppression, compromising fungal growth and sporulation, as viewed by confocal microscopy and measured by reductions in fungal biomass and emergence of uredinia. Interestingly, using the same gene constructs, suppression of infection by Puccinia graminis and Puccinia striiformis was also achieved. Our results show that A. tumefaciens-mediated PITGS can be used as a reverse-genetics tool to discover gene function in rust fungi. This proof-of-concept study indicates that the targeted fungal transcripts might be important in pathogenesis, and could potentially be used as promising targets for developing RNA interference-based resistance against rust fungi.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 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 it