Transcriptome Study of Rice Roots Status under High Alkaline Stress at Seedling Stage
Bibliographic record
Abstract
Alkaline stress is harmful to plant growth and development, it would induce endogenic ionic concentration and osmotic pressure, trigger relevant genes expression with transcription factor binding, signal transduction and hormone synthesis. In this study, we selected “Dongdao-4”, a salt-alkali stress tolerance rice cultivar, which was subjected to extreme high pH (pH = 11.5) alkaline stress at the trefoil stage for 7 days. Using the RNA-seq technology, we analyzed variations in genes expressed between the fourth and the seventh day of treatment. The number of differentially expressed genes (DEGs) was 3804, 2534, 207 and 3276 for fourth day-stress vs. fourth day-control, seventh day-stress vs. seventh day-control, seventh day-control vs. fourth day-control and seventh day-stress vs. fourth day-stress, respectively. Gene ontology (GO) results revealed that DEGs were mainly enriched in apoptotic process, electron carrier activity, receptor activity, molecular transducer activity. The Kyoto Encyclopedia of Genes and Genomes (KEGG) results implied that DEGs were mainly enriched in metabolic pathways, biosynthesis of secondary metabolites. In particular, DEGs were distributed in genes related to the transcription factor, leucine rich repeats (LRRs) and hormones. We also report here for the first-time identification of 125 genes specifically expressed during the alkaline stress. Our results provided important information assisting with the exploration of the molecular mechanisms of rice plants subjected to high pH condition and can facilitate rice abiotic tolerance breeding.
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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 | 0.000 | 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) | 0.001 | 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".