<scp>OsPT4</scp> Facilitates Selenomethionine Transport and Biosynthesis to Enhance Seed Accumulation in Rice: Molecular Mechanisms and Biotechnological Potential
Bibliographic record
Abstract
Selenium (Se) is a vital micronutrient for humans, with important functions for health and anti-cancer properties. Organic Se shows higher antioxidant activity and much lower toxicity compared to inorganic Se, making it safer for use. Selenomethionine (SeMet) is one of the primary forms of organic Se. OsPT4, the high-affinity phosphate (Pi) transporter (PHT) of rice, has been investigated for its role in the transport of the different forms of Se, and its effects on the accumulation of SeMet in this study. The OsPT4 mutant and overexpression lines were used as research materials. Phenotypic analyses revealed that OsPT4 confers improved Se tolerance in shoots upon selenite exposure. Heterologous expression assays in Xenopus laevis oocytes and yeast systems and translocation assays in different transgenic lines of rice confirmed OsPT4-mediated selenite and SeMet transport activity, establishing its responsibility for root-to-shoot Se translocation. Transcriptomic profiling, amino acid quantification and qRT-PCR analyses further indicated that OsPT4 up-regulates methionine (Met) biosynthesis, the direct precursor of SeMet. Notably, OsPT4 significantly increased SeMet accumulation and promoted the formation of Se-rich micron-sized spherical particles in seeds under Se supplementation. These findings provide mechanistic insights into OsPT4-mediated SeMet trafficking and metabolism, advancing strategies for developing Se-biofortified rice cultivars with enhanced nutritional and therapeutic value.
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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) | 0.002 | 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".