Wheat transcriptome profiling reveals abscisic and gibberellic acid treatments regulate early-stage phytohormone defense signaling, cell wall fortification, and metabolic switches following <i>Fusarium graminearum</i> -challenge
Bibliographic record
Abstract
ABSTRACT Background Application of the wheat phytohormones abscisic acid (ABA) or gibberellic acid (GA) affect Fusarium head blight (FHB) disease severity; however, the molecular underpinnings of the elicited phenotypes remain unclear. Herein, the transcriptomic responses of an FHB-susceptible wheat cultivar ‘Fielder’ were characterized upon treatment with ABA, an ABA receptor antagonist (AS6), or GA in the presence or absence of Fusarium graminearum ( Fg ) challenge. Results A total of 30,876 differentially expressed genes (DEGs) where identified in ‘Fielder’ (26,004) and Fg (4,872). Fg challenge alone resulted in the most substantial wheat DEGs contributing to 57.2% of the total transcriptomic variation. Using a combination of topology overlap and correlation analyses, 9,689 Fg -related wheat DEGs were defined. Further enrichment analysis of the top 1% networked wheat DEGs identified critical expression changes within defense responses, cell structural metabolism, molecular transport, and membrane/lipid metabolism. Fg -challenged conditions also included the expression of a putative Fg ABA-biosynthetic cytochrome P450 and repression of wheat FUS3 for dysregulating ABA and GA crosstalk. ABA treatment alone elicited 4536 (32%) wheat DEGs common to those of the Fg -challenge, and Fg +ABA further enhanced 888 (12.5%) of them. These ABA elicited DEGs are involved in defense through both classical and non-classical phytohormone signaling and regulating cell wall structures including polyphenolic metabolism. Conversely, Fg +GA opposed 2239 (33%) Fg -elicited wheat DEGs, including modulating primary and secondary metabolism, defense responses, and flowering genes. ABA and jointly ABA⍰ Fg ⍰[ Fg +ABA] treatments repressed, while Fg +GA induced an over-representation of wheat DEGs mapping to chromosome 6BL. Finally, compared to Fg +ABA, co-application of Fg +AS6 did not antagonize ABA biosynthesis or signal but rather elicited antagonistic Fg (557) and wheat (11) DEGs responses directly tied to stress responses, phytohormone transport, and FHB. Conclusions Comparative transcriptomics highlight the effects of wheat phytohormones on individual pathway and global metabolism simultaneously. Application of ABA may reduce FHB severity through misregulating defense mechanisms and cell wall fortification pathways. GA application may alter primary and secondary metabolism, creating a metabolic shift to ultimately reduce FHB severity. By comparing these findings to those previously reported for four additional plant genotypes, an additive model of the wheat- Fg interaction is proposed.
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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".