The senescence regulator S40 family members from <i>Caragana intermedia</i> and <i>Arabidopsis thaliana</i> inhibit leaf senescence via promoting cytokinins synthesis
Bibliographic record
Abstract
Abstract Leaf senescence is regulated by both endogenous hormones and environmental stimuli in a programmed and concerted way. The members of the S40 family have been reported to play roles in leaf senescence. Here we report that overexpression of an S40 family member from Caragana intermedia, CiS40-11 , delayed the leaf senescence. Phylogenetic analysis revealed that the CiS40-11 protein had the highest identity with AtS40-5 and AtS40-6 of A. thaliana. CiS40-11 was highly expressed in leaves and was down-regulated after dark treatment. The subcellular localization analysis showed that CiS40-11 was a cytoplasm-nucleus dual-localized protein. Leaf senescence was delayed in CiS40-11 transgenic A. thaliana or by its transient expression in C. intermedia . Transcriptomic analysis and endogenous hormones assay revealed that CiS40-11 inhibited leaf senescence via promoting the biosynthesis of cytokinins, through blocking AtMYB2 expression in CiS40-11 overexpression lines. Furthermore, in the ats40-5a and ats40-6a mutants, AtMYB2 expression was increased and their leaves exhibited a premature senescence phenotype. Our results show that CiS40-11 (and its orthologs, AtS40-5 and AtS40-6) promoted cytokinin synthesis by inhibiting the expression of MYB2 and releasing its negative regulation on the expression of IPTs to inhabit leaf senescence. Highlight The senescence regulator S40 family members CiS40-11, AtS40-5 and AtS40-6 are induced by light and inhibition leaf senescence by promoting cytokinin synthesis.
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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 | 0.001 |
| 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".