A soybean β‐expansin gene<i>GmEXPB2</i>intrinsically involved in root system architecture responses to abiotic stresses
Bibliographic record
Abstract
Root system architecture responds plastically to some abiotic stresses, including phosphorus (P), iron (Fe) and water deficiency, but its response mechanism is still unclear. We cloned and characterized a vegetative β-expansin gene, GmEXPB2, from a Pi starvation-induced soybean cDNA library. Transient expression of 35S::GmEXPB2-GFP in onion epidermal cells verified that GmEXPB2 is a secretory protein located on the cell wall. GmEXPB2 was found to be primarily expressed in roots, and was highly induced by Pi starvation, and the induction pattern was confirmed by GUS staining in transgenic soybean hairy roots. Results from intact soybean composite plants either over-expressing GmEXPB2 or containing knockdown constructs, showed that GmEXPB2 is involved in hairy root elongation, and subsequently affects plant growth and P uptake, especially at low P levels. The results from a heterogeneous transformation system indicated that over-expressing GmEXPB2 in Arabidopsis increased root cell division and elongation, and enhanced plant growth and P uptake at both low and high P levels. Furthermore, we found that, in addition to Pi starvation, GmEXPB2 was also induced by Fe and mild water deficiencies. Taken together, our results suggest that GmEXPB2 is a critical root β-expansin gene that is intrinsically involved in root system architecture responses to some abiotic stresses, including P, Fe and water deficiency. In the case of Pi starvation responses, GmEXPB2 may enhance both P efficiency and P responsiveness by regulating adaptive changes of the root system architecture. This finding has great agricultural potential for improving crop P uptake on both low-P and P-fertilized soils.
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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 | 0.001 |
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".