Energy deprivation affects nitrogen assimilation and fatty acid biosynthesis leading to leaf chlorosis under waterlogging stress in the endangered <i>Abies koreana</i>
Bibliographic record
Abstract
Energy deprivation triggers various physiological, biochemical and molecular changes in plants under abiotic stress. We investigated the oxidative damages in the high altitude grown conifer Korean fir (Abies koreana) exposed to waterlogging stress. Our experimental results showed that waterlogging stress led to leaf chlorosis, 35 days after treatment. A significant decrease in leaf fresh weight, chlorophyll and sugar content supported this phenotypic change. Biochemical analysis showed a significant increase in leaf proline, lipid peroxidase and 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical content of waterlogged plants. To elucidate the molecular mechanisms, we conducted RNA-sequencing (RNA-seq) and de novo assembly. Using RNA-seq analysis approach and filtering (P < 0.05 and false discovery rate <0.001), we obtained 134 unigenes upregulated and 574 unigenes downregulated. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis placed the obtained differentially expressed unigenes in α-linoleic pathway, fatty acid degradation, glycosis, glycolipid metabolism and oligosaccharide biosynthesis process. Mapping of unigenes with Arabidopsis using basic local alignment search tool for nucleotides showed several critical genes in photosynthesis and carbon metabolism downregulated. Following this, we found the repression of multiple nitrogen (N) assimilation and nucleotide biosynthesis genes including purine metabolism. In addition, waterlogging stress reduced the levels of polyunsaturated fatty acids with a concomitant increase only in myristic acid. Together, our results indicate that the prolonged snowmelt may cause inability of A. koreana seedlings to lead the photosynthesis normally due to the lack of root intercellular oxygen and emphasizes a detrimental effect on the N metabolic pathway, compromising this endangered tree's ability to be fully functional under waterlogging stress.
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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".