Overexpression of Rice Phosphate Transporter Gene OsPT2 Enhances Tolerance to Low Phosphorus Stress in Soybean
Bibliographic record
Abstract
Low phosphorous (P) availability in soils limits production of soybean [ Glycine max (L.) Merr.] around the world. This study was conducted to determine whether exogenous expression of the rice ( Oryza sativa L.) phosphates transporter gene OsPT2 would increase inorganic phosphates (Pi) acquisition and improve yield in transgenic soybean. Cotyledonary-node explants of the soybean were inoculated with the Agrobacterium tumefaciens strain EHA105 harboring the vector pCAMBIA3301-OsPT2 , which contained OsPT2 , gus and bar genes. Ten fertile T 0 transgenic plants were obtained and semiquantitative RT-PCR of progenies demonstrated that OsPT2 gene was overexpressing in the T 2 generation. Three T 2 transgenic lines overexpressing OsPT2 were selected and subjected to testing for tolerance to low concentrations of Pi (low-Pi; 20 µM Pi) by hydroponic culture using modified Hoagland’s nutrient solution. The total P contents in the leaves, stems, roots, and seeds of the transgenic plants significantly increased under the concentrations of low-Pi and 1,000 µM Pi of standard Hoagland’s nutrient solution. Under low-Pi stress, the yields of the transgenic lines were significantly higher than those of the wild type. Taken together, our data suggest that the overexpression of OsPT2 in transgenic soybean lines improves Pi acquisition and seed yield, and OsPT2 may serve as one of the promising target genes that can be manipulated in crop improvement for minor use of Pi fertilizers.
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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".