Dynamic Coordination of Alternative Splicing and Subgenome Expression Bias Underlies Rusty Root Symptom Response in Panax ginseng
Bibliographic record
Abstract
. While transcriptomic analyses have demonstrated extensive remodeling of stress signaling networks, the post-transcriptional defense circuitry remains obscure. We profiled alternative splicing (AS) in three phloem tissues, the healthy phloem (AG), the non-reddened phloem neighboring lesions (BG), and the reddened lesion core (CG), to delineate AS reprogramming during GRS progression. The frequency of AS was sharply elevated in CG, with intron retention predominating. Extensive gains and losses of splice events indicate large-scale rewiring of the splice network. Overlapping differentially alternative spliced genes (DAGs) identified in both CG vs AG and CG vs BG contrasts were significantly enriched for RNA-spliceosome assembly and stress-response pathways, revealing a conserved post-transcriptional response associated with lesion formation. Integrative analysis of differentially expressed genes uncovered 671 loci under dual regulation; functional classification categorized these genes in receptor-like kinase signaling and chromatin-remodeling modules, underscoring the synergy between AS and transcriptional control. Moreover, the B subgenome disproportionately contributed stress-responsive transcripts in diseased tissue, suggesting an adaptive, subgenome-biased strategy. These findings demonstrate that dynamic AS remodeling and subgenome expression bias jointly orchestrate ginseng defense against GRS and provide a framework for breeding disease-resilient crops.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".