Genetically-linked simultaneous overexpression of multiple herbicide-metabolizing genes for broad-spectrum resistance in an agricultural weed <i>Echinochloa phyllopogon</i>
Bibliographic record
Abstract
Summary Previous research unveiled that the overexpression of catalytically promiscuous CYP81A cytochrome P450s underlies the multiple-herbicide resistance (MHR) in a Californian population of Echinochloa phyllopogon . However, it does not fully accommodate the resistance to diverse herbicides in MHR E. phyllopogon although the genetic inheritance of MHR was suggested as under a single gene control. We investigated the high-level resistance to diclofop-methyl in MHR E. phyllopogon . Detailed diclofop-methyl metabolism was analyzed, followed by gene expression study and functional characterization of P450 genes. The generality of the MHR mechanism was investigated using another MHR line. The MHR line rapidly produced two distinct hydroxylated-diclofop-acid, only one of which was the major metabolite produced by CYP81A12/21. Gene expression study identified the genetically linked overexpression of a novel gene CYP709C69 with CYP81A12/21 in the MHR line. The gene conferred diclofop-methyl resistance in plants and produced another hydroxylated-diclofop-acid in yeast. The activity was observed in some CYP709C in plants. Unlike the broad substrate-specificity in CYP81As, CYP709C69 showed narrow substrate-specificity. The overexpression of the CYP81A and CYP709C69 was also observed in another MHR line. The present findings establish a novel concept that genetically-linked simultaneous overexpression of herbicide-metabolizing genes enhances and broadens the profile of metabolic resistance in weeds.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".