Asymmetric distribution of cytokinins determines root hydrotropism in Arabidopsis thaliana
Bibliographic record
Abstract
The phenomenon of plant root tips sensing moisture gradient in soil and growing towards higher water potential is designated as root hydrotropism, which is critical for plants to survive when water is a limited factor. Molecular mechanisms regulating such a fundamental process, however, are largely unknown. Here we report our identification that cytokinins are key signaling molecules directing root growth orientation in a hydrostimulation (moisture gradient) condition. Lower water potential side of the root tip shows more cytokinin response relative to the higher water potential side. Consequently, two cytokinin downstream type-A response regulators, ARR16 and ARR17, were found to be up-regulated at the lower water potential side, causing increased cell division in the meristem zone, which allows the root to bend towards higher water potential side. Genetic analyses indicated that various cytokinin biosynthesis and signaling mutants, including the arr16 arr17 double mutant, are significantly less responsive to hydrostimulation. Consistently, treatments with chemical inhibitors interfering with either cytokinin biosynthesis or cell division completely abolished root hydrotropic response. Asymmetrically induced expression of ARR16 or ARR17 effectively led to root bending in both wild-type and miz1, a previously known hydrotropism-defective mutant. These data demonstrate that asymmetric cytokinin distribution is a primary determinant governing root hydrotropism.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".