ELF18-INDUCED LONG NONCODING RNA 25 positively regulates the pathogen defense-related CYP82C2 expression in Arabidopsis
Bibliographic record
Abstract
Abstract Long noncoding RNAs (lncRNAs) are emerging as important regulators of gene expression during plant immune responses. In this study, we identified a novel lncRNA, ELF18-INDUCED LONG NONCODING RNA 25 ( ELENA25 ), located in the intergenic region between AT4G31960 and CYTOCHROME P450, family 82, subfamily C, polypeptide 2 ( CYP82C2 ) in Arabidopsis. ELENA25 was initially identified through custom lncRNA microarray data. Here, its full-length sequence (810 bp) was determined using primer walking and confirmed by sequencing. ELENA25 expression was preferentially induced by flg22, a bacterial pathogen-associated molecular pattern (PAMP), in a late-phase and FLS2 receptor-dependent manner. Neighboring genes AT4G31960 and CYP82C2 were also flg22-inducible, with expression abolished in the fls2 mutant background. To assess whether ELENA25 regulates the expression of nearby genes, we generated ELENA25 -overexpressing (OX) and knockout (KO) plants. In ELENA25 OX lines, CYP82C2 expression was significantly upregulated under normal and flg22-treated conditions, while AT4G31960 expression remained unchanged. Conversely, in the elena25 mutants (KO), CYP82C2 expression was significantly reduced, indicating that ELENA25 positively regulates CYP82C2 transcription. Expression levels of other nearby cytochrome P450 genes, including CYP82C3 and CYP82C4 , and other indole glucosinolate-related CYP genes were not affected by ELENA25 expression changes. Collectively, our results demonstrate that ELENA25 is a flg22-inducible lncRNA that specifically enhances CYP82C2 expression in a FLS2-dependent manner. This study provides new insights into the role of lncRNAs in plant innate immunity, highlighting ELENA25 as a positive regulator of defense-related gene expression.
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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".