Metabolic profiling to discriminate wheat near isogenic lines, with quantitative trait loci at chromosome 2DL, varying in resistance to fusarium head blight
Bibliographic record
Abstract
The resistance in wheat to fusarium head blight (FHB) is controlled by several quantitative trait loci (QTLs), which are mainly expressed as two different types of resistance. The objective of this study was to assess the potential of a metabolomics approach to identify resistance-related metabolites associated with a QTL that confers resistance to FHB. Two near isogenic lines (NIL), with alternate alleles for the FHB resistance/susceptibility QTL on chromosome 2DL, were grown under greenhouse conditions and spikelets were inoculated with F. graminearum. Metabolites were extracted from the rachis and spikelets using a mixture of methanol-water and chloroform, and subsequently analyzed using GC/MS. Compound identification and quantification were achieved using AMDIS, GMD and NIST libraries, and MET-IDEA as the software platform. A total of 182 components were detected. A t-test of the quantities of these metabolites identified 27 resistance-related (RR) metabolites, including 22 constitutive (RRC) and 8 induced (RRI), with three common metabolites. Canonical discriminant analysis was used to classify treatments and to identify the associated metabolic functions. The putative metabolic pathways linking the RR-metabolites identified here are discussed. Key words: Functional genomics, metabolomics, fusarium head blight, Triticum aestivum, Fusarium graminearum
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".