Transcriptome analysis of Tamarix ramosissima leaves in response to NaCl stress
Bibliographic record
Abstract
Halophyte Tamarix ramosissima. Lcdcb (T. ramosissima) are known as the representative of Tamarix plants that are widely planted in salinized soil. However, molecular mechanisms towards salt tolerance and adaptation are largely rare. In this study, we carried out RNA-sequence and transcriptome analysis of T. ramosissima in response to NaCl stress, screened differentially expressed genes (DEGs) and further verified by qRT-PCR. Results showed that 105702 unigenes were spliced from the raw data of transcriptome sequencing, where 54238 unigenes were retrieved from KEGG, KOG, NR, and SwissProt. After 48 hours of NaCl treatment, the expression levels of 6374 genes were increased, and 5380 genes were decreased in leaves. After 168 hours, the expression levels of 3837 genes were up-regulated and 7808 genes were down-regulated. In particular, 8 transcription factors annotated to the KEGG Pathway were obtained, involving the WRKY and bZIP transcription family. In addition, KEGG pathway annotation showed that expression of 39 genes involved in ROS scavenging mechanisms were significantly changed, in which 21 genes were up-regulated and 18 genes were down-regulated after 48 hours as well as 15 genes were up-regulated and 24 genes were down-regulated after 168h. Simultaneously, the enzyme activities of SOD and POD were significantly enhanced under NaCl treatment, but the enzyme activity of CAT was not significantly enhanced. Moreover, WRKY, MYB and bZIP may participate in the process of salt resistance in T. ramosissima. This study provides gene resources and a theoretical basis for further molecular mechanisms of salt tolerance in T. ramosissima.
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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".