Morphological and Transcriptomic Analyses Provide New Insights into Linseed (Linum usitatissimum L.) Seedling Roots Response to Nitrogen Stress
Bibliographic record
Abstract
Nitrogen (N) is the most important macro-nutrient for plant growth and development, which not only results in the highest cost in crop production but may also lead to environmental pollution. Hence, there is a need to develop N and use efficient genotypes, a prerequisite for which is a better understanding of N stress adaptation. Here, responses of two contrasting linseed accessions at the seedling stage were assessed for N stress-induced changes in twelve phenotypic traits and for gene expression profiling in the roots. The results showed that nine out of twelve phenotypic traits were affected under N stress conditions, and include total root length (TRL), root tips (RT), shoot dry weight (SDW), root dry weight (RDW), root-to-shoot ratio (R/S), plant nitrogen content (PNC), shoot nitrogen content (SNC), root nitrogen content (RNC), and nitrogen use efficiency (NUE). For example, under N stress, the TRL, RDW, SDW, PNC, SNC, and RNC showed reductions of 7.1, 7.6, 16.0, 43.7, 43.3, and 38.7%, respectively. The N-efficient (NE) genotype outperformed the N-inefficient (NI) genotype for all root and shoot traits and NUE under N stress and N normal conditions. Transcriptome analysis identified 1034 differentially expressed genes (DEGs) under the contrasting N conditions and uncovered the opposite responses of the two linseed genotypes to N starvation at the gene expression level. DEGs included 153 transcription factors distributed in 27 families, among which ERF, MYB, NAC, and WRKY were the most represented. In addition, DEGs involved in N absorption and transport, root development, amino acid transport, and antioxidant activity were found to be differentially expressed. The candidate genes identified in the current study are purported for their roles in N metabolism in other crops and might also play a pivotal role in N stress adaptation in linseed, and therefore could be useful for further detailed research on N stress response in linseed, paving the way toward developing N-efficient linseed cultivars with improved root system architecture.
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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".