Adaption of Roots to Nitrogen Deficiency Revealed by 3D Quantification and Proteomic Analysis
Bibliographic record
Abstract
Rapeseed (Brassica napus) is an important oil crop worldwide. However, severe inhibition of rapeseed production often occurs in the field due to nitrogen (N) deficiency. The root system is the main organ to acquire N for plant growth, but little is known about the mechanisms underlying rapeseed root adaptions to N deficiency. Here, dynamic changes in root architectural traits of N-deficient rapeseed plants were evaluated by 3D in situ quantification. Root proteome responses to N deficiency were analyzed by the tandem mass tag-based proteomics method, and related proteins were characterized further. Under N deficiency, rapeseed roots become longer, with denser cells in the meristematic zone and larger cells in the elongation zone of root tips, and also become softer with reduced solidity. A total of 171 and 755 differentially expressed proteins were identified in short- and long-term N-deficient roots, respectively. The abundance of proteins involved in cell wall organization or biogenesis was highly enhanced, but most identified peroxidases were reduced in the N-deficient roots. Notably, peroxidase activities also were decreased, which might promote root elongation while lowering the solidity of N-deficient roots. These results were consistent with the cell wall components measured in the N-deficient roots. Further functional analysis using transgenic Arabidopsis (Arabidopsis thaliana) plants demonstrated that the two root-related differentially expressed proteins contribute to the enhanced root growth under N deficiency conditions. These results provide insights into the global changes of rapeseed root responses to N deficiency and may facilitate the development of rapeseed cultivars with high N use efficiency through root-based genetic improvements.
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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 | 0.000 | 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 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".