Increased nitrogen‐use efficiency in transgenic rice plants over‐expressing a nitrogen‐responsive early nodulin gene identified from rice expression profiling
Why this work is in the frame
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Bibliographic record
Abstract
Development of genetic varieties with improved nitrogen-use efficiency (NUE) is essential for sustainable agriculture. In this study, we developed a growth system for rice wherein N was the growth-limiting factor, and identified N-responsive genes by a whole genome transcriptional profiling approach. Some genes were selected to test their functionality in NUE by a transgenic approach. One such example with positive effects on NUE is an early nodulin gene OsENOD93-1. This OsENOD93-1 gene responded significantly to both N induction and N reduction. Transgenic rice plants over-expressing the OsENOD93-1 gene had increased shoot dry biomass and seed yield. This OsENOD93-1 gene was expressed at high levels in roots of wild-type (WT) plants, and its protein product was localized in mitochondria. Transgenic plants accumulated higher concentrations of total amino acids and total N in roots. A higher concentration of amino acids in xylem sap was detected in transgenic plants, especially under N stress. In situ hybridization revealed that OsENOD93-1 is expressed in vascular bundles, as well as in epidermis and endodermis. This work demonstrates that transcriptional profiling, coupled with a transgenic validation approach, is an effective strategy for gene discovery. The knowledge gained from this study could be applied to other important crops.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it