Aluminum Stress Response Is Regulated Through a miR156/SPL13 Module in Medicago sativa
Bibliographic record
Abstract
BACKGROUND: (alfalfa) production on acidic soils, resulting in major yield losses worldwide. The highly conserved miRNA156 (miR156) functions by downregulating at least 11 SQUAMOSA promoter-binding protein-like (SPL) transcription factors in alfalfa, including SPL13, but its role in Al stress remains unclear. This study aimed to investigate the miR156/SPL regulatory network's function in alfalfa under Al stress. METHODS: Gene expression analyses, histochemical staining, nutrient profiling, phenotypic assays, transcriptome profiling, and ChIP-seq were conducted on alfalfa plants with altered miR156 and SPL13 expression to assess their roles in the Al stress response. RESULTS: Al stress induced SPL13 expression while repressing miR156 in the roots. Elevated miR156 intensified Al accumulation, lipid peroxidation, and plasma membrane damage, accompanied by reduced leaf nitrogen, magnesium, sulfur, and phosphorus content. Phenotypically, increased SPL13 enhanced the root length and Al tolerance, whereas SPL13 silencing reduced tolerance. Transcriptome profiling of SPL13-silenced plants identified differentially expressed genes involved in the Al response, including aluminum-activated malate transporters and various transcription factors (GRAS, Myb-related, bHLH041, NAC, WRKY53, bZIP, and MADS-box). ChIP-seq revealed that SPL13 directly regulates genes encoding a protein kinase, cytochrome P450, and fasciclin-like arabinogalactan proteins. CONCLUSIONS: The MsmiR156/MsSPL13 network plays a crucial regulatory role in alfalfa's response to Al toxicity. These findings provide novel genetic targets and foundational knowledge to advance molecular breeding for enhanced Al tolerance in alfalfa.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".