Genome-Wide Identification and Characterization of RNA/DNA Differences Associated with Fusarium graminearum Infection in Wheat
Bibliographic record
Abstract
RNA/DNA difference (RDD) is a post-transcriptional modification playing a crucial role in regulating diverse biological processes in eukaryotes. Although it has been extensively studied in plant chloroplast and mitochondria genomes, RDDs in plant nuclear genomes are not well studied at present. Here, we investigated the RDDs associated with fusarium head blight (FHB) through a novel method by comparing the RNA-seq data between Fusarium-infected and control samples of four wheat genotypes. A total of 187 high-confidence unique RDDs in 36 genes were identified, representing the first landscape of the FHB-responsive RDD in wheat. The majority (26) of these 36 RDD genes were correlated either positively or negatively with FHB levels. Effects of these RDDs on RNA and protein sequences have been identified, their editing frequency and the expression level of the corresponding genes provided, and the prediction of the effect on the minimum folding free energy of mRNA, miRNA binding, and colocation of RDDs with conserved domains presented. RDDs were predicted to induce modifications in the mRNA and protein structures of the corresponding genes. In two genes, TraesCS1B02G294300 and TraesCS3A02G263900, editing was predicted to enhance their affinity with tae-miR9661-5p and tae-miR9664-3p, respectively. To our knowledge, this study is the first report of the association between RDD and FHB in wheat; this will contribute to a better understanding of the molecular basis underlying FHB resistance, and potentially lead to novel strategies to improve wheat FHB resistance through epigenetic methods.
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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 | 0.001 | 0.001 |
| 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".