Transcriptional Profiling and Genetic Mapping of Barley Responses to Bacterial Flagellin
Bibliographic record
Abstract
Diverse plant species detect bacterial flagellin using leucine-rich repeat receptor-like kinases to activate defense responses and promote resistance against bacterial invasion. In barley, the impact of flagellin on inducible defense responses has not been fully described. Here, we report that the flagellin-derived flg22 peptide induces callose, reactive oxygen species (ROS) bursts, and differential expression of 2,603 genes in barley. Cultivated barley genotypes produce different amplitudes of flg22-induced ROS bursts, indicating genetic variation for microbe-associated molecular pattern responses. Association mapping revealed a region on chromosome 7 underlying variation in flg22-induced ROS bursts, which contains 12 flg22-induced genes. Genotypes with higher flg22 responses had higher induced resistance to Xanthomonas translucens pv. translucens ( Xtt), the causal organism of bacterial leaf streak. The flg22 region of Xtt flagellin evades detection in both barley and Arabidopsis, and a single amino acid change can restore immunogenicity of the peptide. Together, this work underlines the effectiveness of the flagellin-triggered defenses in promoting barley resistance to Xtt, which evades recognition of the flg22 region in its host. [Formula: see text]Copyright © 2025 His Majesty the King in Right of Canada, as represented by the Minister of Agriculture and Agri-Food Canada. This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
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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".