The ORF2 protein of Fusarium graminearum virus 1 suppresses the transcription of <i>FgDICER2</i> and <i>FgAGO1</i> to limit host antiviral defences
Bibliographic record
Abstract
The filamentous fungus Fusarium graminearum possesses an RNA-interference (RNAi) pathway that acts as a defence response against virus infections and exogenous double-stranded (ds) RNA. Fusarium graminearum virus 1 (FgV1), which infects F. graminearum, confers hypovirulence-associated traits such as reduced mycelial growth, increased pigmentation and reduced pathogenicity. In this study, we found that FgV1 can suppress RNA silencing by interfering with the induction of FgDICER2 and FgAGO1, which are involved in RNAi antiviral defence and the hairpin RNA/RNAi pathway in F. graminearum. In an FgAGO1- or FgDICER2-promoter/GFP-reporter expression assay the green fluorescent protein (GFP) transcript levels were reduced in FgV1-infected transformed mutant strains. By comparing transcription levels of FgDICER2 and FgAGO1 in fungal transformed mutants expressing each open reading frame (ORF) of FgV1 with or without a hairpin RNA construct, we determined that reduction of FgDICER2 and FgAGO1 transcript levels requires only the FgV1 ORF2-encoded protein (pORF2). Moreover, we confirmed that the pORF2 binds to the upstream region of FgDICERs and FgAGOs in vitro. These combined results indicate that the pORF2 of FgV1 counteracts the RNAi defence response of F. graminearum by interfering with the induction of FgDICER2 and FgAGO1 in a promoter-dependent manner.
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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".