Single-cell nuclear transcriptomics reveal root tip adaptations to nitrogen scarcity in wheat
Why this work is in the frame
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Bibliographic record
Abstract
Roots play a critical role in acquisition and utilization of nitrogen in wheat, influencing nitrogen use efficiency (NUE), and ultimately determining yield. However, the detailed responses of root tips to fluctuations in nitrogen availability and the underlying regulatory mechanisms enabling adaptation to nitrogen-limited conditions, remain elusive. In this study, we used single-cell nuclear transcriptomics of the high-nitrogen utilization variety (HNV) Zhengmai 1860 (ZM1860) to construct a comprehensive map of root tip cells under both controlled and nitrogen starvation (N-starv) conditions. Identification of various cell types and their associated genes highlighted the diversity of cellular processes. Using single-nucleus consensus weighted gene co-expression network analysis (hdWGCNA), we identified key modules central to nitrogen metabolism. These identified the prominent role of epidermal cells (EC). The gene TaGS1.2 , which is involved in glutamine synthesis, exhibited increased expression under nitrogen-deficient conditions, validating its functional significance in nutrient acquisition. Serving as a key functional gene that adapts to nitrogen-deficient conditions this gene also positively regulated root development. Analysis of the transcriptional regulatory network in EC further revealed the pivotal role of TaGS1.2 in the nitrogen metabolism network. We also uncovered mechanisms that enhance cell-to-cell communication in nitrogen-deficient environments by identifying specific receptors. Single-cell nuclear transcriptome mapping offers valuable insights into the complex responses of root tip cells to nitrogen scarcity and guides future breeding strategies aimed at developing more nitrogen-efficient wheat varieties.
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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