The Arabidopsis Halophytic Relative<i>Thellungiella halophila</i>Tolerates Nitrogen-Limiting Conditions by Maintaining Growth, Nitrogen Uptake, and Assimilation
Bibliographic record
Abstract
A comprehensive knowledge of mechanisms regulating nitrogen (N) use efficiency is required to reduce excessive input of N fertilizers while maintaining acceptable crop yields under limited N supply. Studying plant species that are naturally adapted to low N conditions could facilitate the identification of novel regulatory genes conferring better N use efficiency. Here, we show that Thellungiella halophila, a halophytic relative of Arabidopsis (Arabidopsis thaliana), grows better than Arabidopsis under moderate (1 mm nitrate) and severe (0.4 mm nitrate) N-limiting conditions. Thellungiella exhibited a lower carbon to N ratio than Arabidopsis under N limitation, which was due to Thellungiella plants possessing higher N content, total amino acids, total soluble protein, and lower starch content compared with Arabidopsis. Furthermore, Thellungiella had higher amounts of several metabolites, such as soluble sugars and organic acids, under N-sufficient conditions (4 mm nitrate). Nitrate reductase activity and NR2 gene expression in Thellungiella displayed less of a reduction in response to N limitation than in Arabidopsis. Thellungiella shoot GS1 expression was more induced by low N than in Arabidopsis, while in roots, Thellungiella GS2 expression was maintained under N limitation but was decreased in Arabidopsis. Up-regulation of NRT2.1 and NRT3.1 expression was higher and repression of NRT1.1 was lower in Thellungiella roots under N-limiting conditions compared with Arabidopsis. Differential transporter gene expression was correlated with higher nitrate influx in Thellungiella at low (15)NO(3)(-) supply. Taken together, our results suggest that Thellungiella is tolerant to N-limited conditions and could act as a model system to unravel the mechanisms for low N tolerance.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".