Integrated Metabolo-Transcriptomics Reveals Fusarium Head Blight Candidate Resistance Genes in Wheat QTL-Fhb2
Bibliographic record
Abstract
BACKGROUND: Fusarium head blight (FHB) caused by Fusarium graminearum not only causes severe losses in yield, but also reduces quality of wheat grain by accumulating mycotoxins. Breeding for host plant resistance is considered as the best strategy to manage FHB. Resistance in wheat to FHB is quantitative in nature, involving cumulative effects of many genes governing resistance. The poor understanding of genetics and lack of precise phenotyping has hindered the development of FHB resistant cultivars. Though more than 100 QTLs imparting FHB resistance have been reported, none discovered the specific genes localized within the QTL region, nor the underlying mechanisms of resistance. FINDINGS: In our study recombinant inbred lines (RILs) carrying resistant (R-RIL) and susceptible (S-RIL) alleles of QTL-Fhb2 were subjected to metabolome and transcriptome profiling to discover the candidate genes. Metabolome profiling detected a higher abundance of metabolites belonging to phenylpropanoid, lignin, glycerophospholipid, flavonoid, fatty acid, and terpenoid biosynthetic pathways in R-RIL than in S-RIL. Transcriptome analysis revealed up-regulation of several receptor kinases, transcription factors, signaling, mycotoxin detoxification and resistance related genes. The dissection of QTL-Fhb2 using flanking marker sequences, integrating metabolomic and transcriptomic datasets, identified 4-Coumarate: CoA ligase (4CL), callose synthase (CS), basic Helix Loop Helix (bHLH041) transcription factor, glutathione S-transferase (GST), ABC transporter-4 (ABC4) and cinnamyl alcohol dehydrogenase (CAD) as putative resistance genes localized within the QTL-Fhb2 region. CONCLUSION: Some of the identified genes within the QTL region are associated with structural resistance through cell wall reinforcement, reducing the spread of pathogen through rachis within a spike and few other genes that detoxify DON, the virulence factor, thus eventually reducing disease severity. In conclusion, we report that the wheat resistance QTL-Fhb2 is associated with high rachis resistance through additive resistance effects of genes, based on cell wall enforcement and detoxification of DON. Following further functional characterization and validation, these resistance genes can be used to replace the genes in susceptible commercial cultivars, if nonfunctional, based on genome editing to improve FHB resistance.
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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 | 0.001 |
| 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) | 0.000 | 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".