Altered Expression of OsNLA1 Modulates Pi Accumulation in Rice (Oryza sativa L.) Plants
Bibliographic record
Abstract
Current agricultural practices rely on heavy use of fertilizers for increased crop productivity. However, the problems associated with heavy fertilizer use, such as high cost and environmental pollution, require the development of crop species with increased nutrient use efficiency. In this study, by using transgenic approaches, we have revealed the critical role of OsNLA1 in phosphate (Pi) accumulation of rice plants. When grown under sufficient Pi and nitrate levels, OsNLA1 knockdown (Osnla1-1, Osnla1-2 and Osnla1-3) lines accumulated higher Pi content in their shoot tissues compared to wild-type, whereas, over-expression lines (OsNLA1-OE1, OsNLA1-OE2 and OsNLA1-OE3) lines accumulated the least levels of Pi. However, under high Pi levels, knockdown lines knockdown lines accumulated much higher Pi content compared to wild-type and exhibited Pi toxicity symptoms in the leaves. In contrast, the over-expression lines had 50- 60% of the Pi content of wild-type and did not show such symptoms. When grown under limiting nitrate levels, OsNLA1 transgenic lines also displayed a similar pattern in Pi accumulation and Pi toxicity symptoms compared to wild-type suggesting an existence of cross-talk between nitrogen (N) and phosphorous (P), which is regulated by OsNLA1. The greater Pi accumulation in knockdown lines was a result of enhanced Pi uptake/permeability of roots compared to the wild-type. The cross-talk between N and P was found to be nitrate specific since the knockdown lines failed to over-accumulate Pi under low (sub-optimal) ammonium level. Moreover, OsNLA1 was also found to interact with OsPHO2, a known regulator of Pi homeostasis, in a Yeast Two-Hybrid (Y2H) assay. Taken together, these results show that OsNLA1 is involved in Pi homeostasis regulating Pi uptake and accumulation in rice and may provide an opportunity to enhance P use efficiency by manipulating nitrate supply in the soil.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".