Arabidopsis Transient Expression Analysis Reveals that Activation of GLABRA2 May Require Concurrent Binding of GLABRA1 and GLABRA3 to the Promoter of GLABRA2
Bibliographic record
Abstract
Transcription factors regulate gene expression by directly binding the cis-acting regulatory elements of target genes via their DNA-binding domains or by interacting with other transcription factors. Trichome cell fate determination in Arabidopsis utilizes a lateral inhibition mechanism that relies on the interplay of transcription factors. GLABRA1 (GL1), an R2R3 MYB transcription factor, GLABRA3 (GL3), a basic helix-loop-helix (bHLH) transcription factor, and TRANSPARENT TESTA GLABRA1 (TTG1), a WD40 protein, are believed to form a transcriptional activator complex to control the transcription of GLABRA2 (GL2), which in turn induces trichome formation in shoots. However, the molecular mechanism of the regulation of GL2 expression by this activator complex is still poorly understood. Here we report that GL1 and GL3 control GL2 expression by a previously unrecognized mechanism in which in addition to the protein-protein interaction between GL1 and GL3, concurrent binding of GL1 and GL3 to the promoter of GL2 via their own DNA-binding domains is probably required to activate GL2. We demonstrate that disruption or deletion of the DNA-binding domains in either GL1 or GL3 completely abolishes the transcriptional activity of the GL1-GL3 complex in activating GL2. These results provide new insight into the interplay of GL1 and GL3 transcription factors in the activation of GL2.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".