miR156/SPL10 Modulates Lateral Root Development, Branching and Leaf Morphology in Arabidopsis by Silencing AGAMOUS-LIKE 79
Bibliographic record
Abstract
The developmental functions of miR156-SPL regulatory network have been extensively studied in Arabidopsis, but the downstream genes regulated by each SPL have not been well characterized. In this study, Next Generation Sequencing-based transcriptome analysis was performed on roots of wild type (WT) and miR156 overexpression (miR156OE) plants. One of the SPL genes, SPL10, which represses lateral root growth in Arabidopsis, was significantly downregulated in miR156OE plants. A transcription factor, AGAMOUS-like MADS box protein 79 (AGL79), was also significantly downregulated in the miR156OE plants, but was upregulated in the SPL10 overexpression (SPL10OE) Arabidopsis plants. In addition, SPL10 was found to bind to the core consensus SPL binding sequences in AGL79 gene. Moreover, analyses of complementation lines revealed a linear relationship between SPL10 and AGL79 in regulating Arabidopsis plant development. In addition, it was observed that plant phenotypes are AGL79 dose-dependent, with higher expression causing narrow leaf shape, less number of leaves and early flowering time, whereas relatively lower AGL79 overexpression produce plants with more rosette leaves and more lateral branches. Our findings revealed direct binding of SPL10 to AGL79 promoter, which further suggests a role for miR156/SPL10 module in plant lateral root growth by directly regulating AGL79.
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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".