Genome-wide identification, characterization, and transcriptional analysis of the metacaspase gene family in cucumber (<i>Cucumis sativus</i>)
Bibliographic record
Abstract
Metacaspase (MC), a family of caspase-like proteins, plays vital roles in regulating programmed cell death (PCD) during development and in response to stresses in plants. In this study, five MC genes (designated as CsMC1 to CsMC5) were identified in the cucumber (Cucumis sativus) genome. Sequence analysis revealed that CsMC1-CsMC3 belong to type I MC proteins, while CsMC4 and CsMC5 are type II MC proteins. Phylogenetic tree and conserved motif analysis of MC proteins indicated that these proteins can be classified into two groups, which are correlated with the types of these MC proteins. Gene structure analysis demonstrated that type I CsMC genes contain 4-7 introns, while all type II CsMC genes harbor one intron. In addition, many hormone-, stress-, and development-related cis-elements were identified in the promoter regions of CsMC genes. Expression analysis using RNA-seq data revealed that CsMC genes have distinct expression patterns in various tissues and developmental stages. qRT-PCR results showed that the transcript levels of CsMC genes could be regulated by various abiotic stresses such as NaCl, PEG, and cold. These results demonstrate that the cucumber MC gene family may function in tissue development and plant stress responses.
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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 | 0.001 | 0.001 |
| 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".