Kinase CIPK9 integrates glucose and abscisic acid signaling to regulate seed oil metabolism in rapeseed
Bibliographic record
Abstract
Rapeseed (Brassica napus), an important oil crop worldwide, provides large amounts of lipids for human requirements. Calcineurin B-like (CBL)-interacting protein kinase 9 (CIPK9) was reported to regulate seed oil content in the plant. Here, we generated gene-silenced lines through RNA interference biotechnology and loss-of-function mutant bnacipk9 using CRISPR/Cas9 to further study BnaCIPK9 functions in the seed oil metabolism of rapeseeds. We discovered that compared with wild-type (WT) lines, gene-silenced and bnacipk9 lines had substantially different oil contents and fatty acid compositions: seed oil content was improved by 3%-5% and 1%-6% in bnacipk9 lines and gene-silenced lines, respectively; both lines were with increased levels of monounsaturated fatty acids and decreased levels of polyunsaturated fatty acids. Additionally, hormone and glucose content analyses revealed that compared with WT lines the bnacipk9 lines showed significant differences: in bnacipk9 seeds, indoleacetic acid and abscisic acid (ABA) levels were higher; glucose and sucrose contents were higher with a higher hexose-to-sucrose ratio in bnacipk9 mid-to-late maturation development seeds. Furthermore, the bnacipk9 was less sensitive to glucose and ABA than the WT according to stomatal aperture regulation assays and the expression levels of genes involved in glucose and ABA regulating pathways in rapeseeds. Notably, in Arabidopsis (Arabidopsis thaliana), exogenous ABA and glucose imposed on developing seeds revealed the effects of ABA and glucose signaling on seed oil accumulation. Altogether, our results strongly suggest a role of CIPK9 in mediating the interaction between glucose flux and ABA hormone signaling to regulate seed oil metabolism in rapeseed.
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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 | 0.001 |
| 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".