Comparative transcriptomic analysis of wheat cultivars differing in their resistance to Fusarium head blight infection during grain-filling stages reveals unique defense mechanisms at play
Bibliographic record
Abstract
Fusarium head blight (FHB) is a devastating fungal disease that poses a significant threat to wheat production, causing substantial yield losses. Understanding the molecular mechanisms of wheat resistance to FHB is crucial for developing effective disease management strategies. This study aimed to investigate the mechanisms of FHB resistance and the patterns of toxin accumulation in three wheat cultivars, Annong8455, Annong1589, and Sumai3, with different levels of resistance, ranging from low to high respectively, under natural field conditions. Samples were taken at three different grain-filling stages (5, 10, and 15 DPA) for gene expression analysis and phenotypic observation. Results found that toxin concentration was inversely correlated with varietal resistance but not correlated with disease phenotypes, indicating that toxin analysis is a more accurate measure of disease status in wheat ears and grains. Transcriptomic data showed that Sumai3 exhibited a stronger immune response during all stages of grain filling by upregulating genes involved in the active destruction of pathogens and removal of toxins. In contrast, Annong1589 showed a passive prevention of the spread of toxins into cells by the upregulation of genes involved in tyramine biosynthesis at the early stage (5 DPA), which may be involved in cell wall strengthening. Our study demonstrates the complexity of FHB resistance in wheat, with cultivars exhibiting unique and overlapping defense mechanisms, and highlights the importance of considering the temporal and spatial dynamics of gene expression in breeding programs for developing more resistant wheat cultivars.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".