Effects of drought and salt-stresses on gene expression in Caragana korshinskii seedlings revealed by RNA-seq
Bibliographic record
Abstract
BACKGROUND: Drought and soil salinity are major abiotic stresses. The mechanisms of stress tolerance have been studied extensively in model plants. Caragana korshinskii is characterized by high drought and salt tolerance in northwestern China; unique patterns of gene expression allow it to tolerate the stress imposed by dehydration and semi-desert saline soil. There have, however, been no reports on the differences between C. korshinskii and model plants in the mechanisms underlying their drought and salt tolerance and regulation of gene expression. RESULTS: Three sequencing libraries from drought and salt-treated whole-seedling- plants and the control were sequenced to investigate changes in the C. korshinskii transcriptome in response to drought and salt stresses. Of the 129,451 contigs, 70,662 (54.12 %) were annotated with gene descriptions, gene ontology (GO) terms, and metabolic pathways, with a cut-off E-value of 10(-5). These annotations included 56 GO terms, 148 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and 25 Clusters of Orthologous Groups (COG). On comparison of the transcriptomes of the control, drought- and salt-treated plants, 1630 and 1521 contigs showed significant differences in transcript abundance under drought and salt stresses. Compared to the differentially expressed genes (DEGs) in drought- or salt-treated Arabidopsis in the database, 542 DEGs in drought-treated C. korshinskii and 529 DEGs in salt-treated samples were presumably unique to C. korshinskii. The transcription profiles revealed that genes related to transcription factors, protein kinases, and antioxidant enzymes are relevant to the tolerance of drought and salt stress in this species. The expression patterns of 38 randomly selected DEGs were confirmed by quantitative real-time PCR and were essentially consistent with the changes in transcript abundance identified by RNA-seq. CONCLUSIONS: The present study identified potential genes involved in drought and salt tolerance in C. korshinskii, as well as many DEGs uniquely expressed in drought- or salt-treated C. korshinskii samples compared to Arabidopsis. To our knowledge, this study is the first exploration of the C. korshinskii transcriptome under drought and salt conditions, and these results will facilitate the discovery of specific stress-resistance-related genes in C. korshinskii, possibly leading to the development of novel plant cultivars through genetic engineering.
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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".