<i>Botrytis cinerea</i> small RNAs are associated with tomato AGO1 and silence tomato defense-related target genes supporting cross-kingdom RNAi
Bibliographic record
Abstract
Abstract Cross-kingdom or cross-species RNA interference (RNAi) is broadly present in many interacting systems between microbes/parasites and their plant and animal hosts. A recent study by Qin et al . (2022) performed correlation analysis using global sRNA- and mRNA-deep sequencing data of cultured B. cinerea and B. cinerea -infected tomato leaves and claimed that cross-kingdom RNAi may not occur in B. cinerea –tomato interaction (Qin et al ., 2022). Here, we use experimental evidence and additional bioinformatics analysis of the datasets produced by Qin et al . (2022) to identify the key reasons why a discrepancy between the conclusion of Qin et al. 2022 and previously published findings occurred. We also provided additional experimental evidence to support the presence of cross-kingdom RNAi between tomato and B. cinerea . We believe it is important to clarify the basic concept and mechanism of cross-kingdom/cross-species sRNA trafficking and illustrate proper bioinformatics analyses in this regard for all the scientists and researchers in this field.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".