Transcriptomic and physiological analysis identifies a gene network module highly associated with brassinosteroid regulation in hybrid sweetgum tissues differing in the capability of somatic embryogenesis
Bibliographic record
Abstract
Somatic embryogenesis is a preferred method for large-scale production of forest trees due to its high propagation efficiency. In this study, hybrid sweetgum leaves with phase changes from mature to embryogenic state were selected as experimental material to study somatic embryo initiation. Embryogenicity ranged from high to low, i.e. from 45%, 25%, and 12.5% to 0, with the samples of embryogenic callus (EC), whiten leaf edge (WLI), whiten leaf (WLII), and green leaf (GL) respectively. High correlations existed between embryogenicity and endogenous brassinosteroids (BRs) (r = 0.95, p < 0.05). Similarly, concentrations of endogenous BRs of the sample set correlated positively (r = 0.93, 0.99, 0.87, 0.99, 0.96 respectively, P < 0.05) to expression of somatic embryo (SE)-related genes, i.e. BBM, LEC2, ABI3, PLT2, and WOX2. Hierarchical cluster and weighted gene coexpression network analysis identified modules of coexpressed genes and network in 4820 differentially expressed genes (DEGs) from All-BR-Regulated Genes (ABRG). Moreover, exogenously-supplemented epiBR, together with 2,4-D and 6-BA, increased embryogenicity of GL-sourced callus, and expression of SE- and auxin-related genes, while brassinazole (BRZ), a BR biosynthesis inhibitor, reduced embryogenicity. Evidences obtained in this study revealed that BRs involved in phase change of leaf explants and may function in regulating gene expression and enhancing auxin effects. This study successfully established protocols for inducing somatic embryogenesis from leaf explants in hybrid sweetgum, which could facilitate the propagation process greatly, and provide theoretical basis for manipulating SE competence of explants in ornamental woody plants.
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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".