Profiling of the gene expression and alternative splicing landscapes of <i>Eucalyptus grandis</i>
Bibliographic record
Abstract
Eucalyptus is a widely planted hardwood tree species due to its fast growth, superior wood properties and adaptability. However, the post-transcriptional regulatory mechanisms controlling tissue development and stress responses in Eucalyptus remain poorly understood. In this study, we performed a comprehensive analysis of the gene expression profile and the alternative splicing (AS) landscape of E. grandis using strand-specific RNA-Seq, which encompassed 201 libraries including different organs, developmental stages, and environmental stresses. We identified 10 416 genes (33.49%) that underwent AS, and numerous differentially expressed and/or differential AS genes involved in critical biological processes, such as primary-to-secondary growth transition of stems, adventitious root formation, aging and responses to phosphorus- or boron-deficiency. Co-expression analysis of AS events and gene expression patterns highlighted the potential upstream regulatory role of AS events in multiple processes. Additionally, we highlighted the lignin biosynthetic pathway to showcase the potential regulatory functions of AS events in the KNAT3 and IRL3 genes within this pathway. Our high-quality expression atlas and AS landscape serve as valuable resources for unravelling the genetic control of woody plant development, long-term adaptation, and understanding transcriptional diversity in Eucalyptus. Researchers can conveniently access these resources through the interactive ePlant browser (https://bar.utoronto.ca/eplant_eucalyptus).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".