The Transcription Factor MYB59 Regulates K<sup>+</sup>/NO<sub>3</sub><sup>−</sup> Translocation in the Arabidopsis Response to Low K<sup>+</sup> Stress
Bibliographic record
Abstract
Potassium and nitrogen are essential nutrients for plant growth and development.Plants can sense potassium nitrate (K + /NO 3 -) levels in soils, and accordingly they adjust root-to-shoot K + /NO 3 -transport to balance the distribution of these ions between roots and shoots.In this study, we show that the transcription factorMYB59 maintains this balance by regulating the transcription of the Arabidopsis (Arabidopsis thaliana) Nitrate Transporter1.5 (NRT1.5)/Nitrate Transporter/Peptide Transporter Family7.3 (NPF7.3) in response to low K + (LK) stress.The myb59 mutant showed a yellow-shoot sensitive phenotype when grown on LK medium.Both the transcript and protein levels of NPF7.3 were remarkably reduced in the myb59 mutant.LK stress repressed transcript levels of both MYB59 and NPF7.3.The npf7.3 and myb59 mutants, as well as the npf7.3myb59 double mutant, showed similar LK-sensitive phenotypes.Ion content analyses indicated that root-to-shoot K + /NO 3 -transport was significantly reduced in these mutants under LK conditions.Moreover, chromatin immunoprecipitation and electrophoresis mobility shift assay assays confirmed that MYB59 bound directly to the NPF7.3 promoter.Expression of NPF7.3 in root vasculature driven by the PHOSPHATE 1 promoter rescued the sensitive phenotype of both npf7.3 and myb59 mutants.Together, these data demonstrate that MYB59 responds to LK stress and directs root-to-shoot K + /NO 3 -transport by regulating the expression of NPF7.3 in Arabidopsis roots.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".