Genome-wide systematic characterization and its regulatory expression reprogramming process of the bZIP transcription factors during trauma response in <i>Camellia sinensis</i>
Bibliographic record
Abstract
Basic leucine zipper (bZIP) transcription factor (TF) genes regulate numerous biological processes, as well as biotic and abiotic responses. Although the genome of the tea tree (Camellia sinensis (L.) Kuntze) has been released, knowledge regarding the bZIP TF family in C. sinensis, e.g., phylogenetic relationship and transcriptional gene expression profiles, remains limited. In this study, we characterized 77 bZIP genes in C. sinensis based on transcriptomic and genomic data and divided them into 11 groups according to their phylogenetic relationship with those in Arabidopsis, which allowed us to identify 14 pairs of orthologous proteins shared by Arabidopsis and C. sinensis and 19 pairs of paralogous proteins in C. sinensis. Conserved motif analysis of CsbZIP proteins showed high group specificity. Our classification was supported by the predicted specificities based on DNA-binding domains, as well as the dimerization property based on characteristic features in the basic and hinge regions and the leucine zipper. Specifically, they indicated that some highly conserved amino acid residues exist across each major group in the tree of land plant life. Expression profiling analyses indicate that the CsbZIP genes are likely involved in response to trauma, and a model was established to display the unique expression of each group during different time intervals after wounding. This work provides useful clues for further functional characterization of the CsbZIP TFs.
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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 | 0.000 |
| 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 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".