High-temperature adaptation of an <i>OsNRT2.3</i> allele is thermoregulated by small RNAs
Bibliographic record
Abstract
Climate change negatively affects crop yield, which hinders efforts to reach agricultural sustainability and food security. Here, we show that a previously unidentified allele of the nitrate transporter gene OsNRT2.3 is required to maintain high yield and high nitrogen use efficiency under high temperatures. We demonstrate that this tolerance to high temperatures in rice accessions harboring the HTNE-2 (high temperature resistant and nitrogen efficient-2) alleles from enhanced translation of the OsNRT2.3b mRNA isoform and the decreased abundance of a unique small RNA (sNRT2.3-1) derived from the 5′ untranslated region of OsNRT2.3 . sNRT2.3-1 binds to the OsNRT2.3a mRNA in a temperature-dependent manner. Our findings reveal that allelic variation in the 5′ untranslated region of OsNRT2.3 leads to an increase in OsNRT2.3b protein levels and higher yield during high-temperature stress. Our results also provide a breeding strategy to produce rice varieties with higher grain yield and lower N fertilizer input suitable for a sustainable agriculture that is resilient against climate change.
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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 | 0.001 |
| 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".