Functional Study of Key Genes in <i>Eucalyptus</i> Asexual Reproduction
Bibliographic record
Abstract
Transcriptome analysis revealed significant differences in gene expression between differentiated and dedifferentiated tissues in Eucalyptus species with varying embryogenetic potentials. Specifically, 9 229 and 8 989 differentially expressed genes (DEGs) were identified in E. camaldulensis and E. grandis x urophylla , respectively. Key genes involved in somatic embryogenesis, such as somatic embryogenesis receptor kinase, ethylene, auxin, and transcription factors, were differentially regulated. Functional studies using Eucalyptus hairy roots demonstrated the utility of these genes in secondary cell wall biosynthesis and wood formation. Overexpression of FLOWERING LOCUS T (FT) induced early flowering, facilitating rapid breeding cycles. The identified genes and their functional roles offer valuable insights for improving vegetative propagation and breeding programs. The findings also highlight the potential of using genetic and transcriptomic tools to accelerate the development of Eucalyptus species with desirable traits. This study aimed to identify and functionally characterize key genes involved in the asexual reproduction of Eucalyptus , focusing on somatic embryogenesis and dedifferentiation processes and enhance the understanding of molecular mechanisms underlying these processes to improve vegetative propagation techniques for commercial and breeding purposes.
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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".