RNA N6-adenine methylation dynamics impact <i>Hyaloperonospora arabidopsidis</i> resistance in <i>Arabidopsis</i>
Bibliographic record
Abstract
Abstract In plants, epitranscriptomic mark N6-adenine methylation (m6A) is dynamically regulated by (a)biotic stressors. However, there is limited knowledge on m6A dynamics at single nucleotide resolution on specific RNA molecule under stresses, and their role in environmental adaptation. By using Oxford Nanopore Technology direct RNA sequencing (ONT-DRS) and a neural network model, here we show transcript-specific dynamics of m6A modification at single nucleotide resolution by biotic stress during Hyaloperonospera arabidopsidis ( Hpa ) infection in Arabidopsis . In wild-type seedlings, pathogen infection causes significant reduction of global m6A ratios, which correlates with activation of m6A-modified transcripts. Defect of m6A deposition in the m6A mutant hakai-1 mimics m6A reduction from Hpa infection at ∼70% of sites, resulting in constitutive overexpression of basal defence genes and enhanced resistance against the pathogen. Our results demonstrate that m6A dynamics impact defence response against pathogen, providing a promising target for future crop improvement strategies.
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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".