Auxin response cell-autonomously controls ground tissue initiation in the early <i>Arabidopsis</i> embryo
Bibliographic record
Abstract
). In contrast, it is completely unknown how ground tissue identity is first specified from totipotent precursor cells in the embryo. The plant signaling molecule auxin, acting through AUXIN RESPONSE FACTOR (ARF) transcription factors, is critical for embryo patterning. The auxin effector ARF5/MONOPTEROS (MP) acts both cell-autonomously and noncell-autonomously to control embryonic vascular tissue formation and root initiation, respectively. Here we show that auxin response and ARF activity cell-autonomously control the asymmetric division of the first ground tissue cells. By identifying embryonic target genes, we show that MP transcriptionally initiates the ground tissue lineage and acts upstream of the regulatory network that controls ground tissue patterning and maintenance. Strikingly, whereas the SHR network depends on MP, this MP function is, at least in part, SHR independent. Our study therefore identifies auxin response as a regulator of ground tissue specification in the embryonic root, and reveals that ground tissue initiation and maintenance use different regulators and mechanisms. Moreover, our data provide a framework for the simultaneous formation of multiple cell types by the same transcriptional regulator.
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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) | 0.002 | 0.001 |
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".