Transcriptome and metabolome profiling provide insights into molecular mechanism of pseudostem elongation in banana
Bibliographic record
Abstract
BACKGROUND: Banana plant height is an important trait for horticultural practices and semi-dwarf cultivars show better resistance to damages by wind and rain. However, the molecular mechanisms controlling the pseudostem height remain poorly understood. Herein, we studied the molecular changes in the pseudostem of a semi-dwarf banana mutant Aifen No. 1 (Musa spp. Pisang Awak sub-group ABB) as compared to its wild-type dwarf cultivar using a combined transcriptome and metabolome approach. RESULTS: A total of 127 differentially expressed genes and 48 differentially accumulated metabolites were detected between the mutant and its wild type. Metabolites belonging to amino acid and its derivatives, flavonoids, lignans, coumarins, organic acids, and phenolic acids were up-regulated in the mutant. The transcriptome analysis showed the differential regulation of genes related to the gibberellin pathway, auxin transport, cell elongation, and cell wall modification. Based on the regulation of gibberellin and associated pathway-related genes, we discussed the involvement of gibberellins in pseudostem elongation in the mutant banana. Genes and metabolites associated with cell wall were explored and their involvement in cell extension is discussed. CONCLUSIONS: The results suggest that gibberellins and associated pathways are possibly developing the observed semi-dwarf pseudostem phenotype together with cell elongation and cell wall modification. The findings increase the understanding of the mechanisms underlying banana stem height and provide new clues for further dissection of specific gene functions.
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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".