Genome-Wide Identification, Characterization, and Expression Analysis of NRT Gene Family in Suaeda glauca
Bibliographic record
Abstract
Nitrogen (N) is crucial for plant growth and stress resistance and is primarily absorbed and transported by nitrate transporters (NRT). Suaeda glauca, known for its strong salt-alkali stress resistance, and SgNRT genes have rarely been reported. This study aims to identify and analyze the SgNRT gene family to understand its composition, evolutionary patterns, and roles in salt stress responses. We identified 212 SgNRTs, which were categorized into three branches, with SgNRT1/SgNPF and SgNRT2 as the major families. Structural analysis, conserved domains, chromosomal localization, and collinearity were also examined. Spatiotemporal expression characteristics of SgNRT genes were analyzed, revealing specific expression across 13 organs or tissues and dynamic responses to salt treatment over 48 h. Notably, SgNRT1.185, SgNRT2.25, and SgNRT2.2 exhibited rapid salt induction in leaves (activated within 0.5 h, peaking at 2 h), with SgNRT1.185 showing relatively high upregulation. SgNRT1.185 and SgNRT2.35 were induced by high salt concentrations (200 mM) in both roots and leaves. SgNRT2.35 exhibited higher basal and stress-induced levels than the other genes. Bioinformatics analysis suggests spatially specific expression of SgNRT genes, potentially involved in nitrogen absorption and transport across various developmental stages and organs/tissues of Suaeda glauca. These findings offer a theoretical basis for understanding the adaptive strategies of Suaeda glauca under saline-alkali stress and provide insights into the functional evolution of plant NRT genes, aiding in the development of stress-resistant crops.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".