Identification and characterization of CBL and CIPK gene families in canola (Brassica napus L.)
Bibliographic record
Abstract
BACKGROUND: Canola (Brassica napus L.) is one of the most important oil-producing crops in China and worldwide. The yield and quality of canola is frequently threatened by environmental stresses including drought, cold and high salinity. Calcium is a ubiquitous intracellular secondary messenger in plants. Calcineurin B-like proteins (CBLs) are Ca2+ sensors and regulate a group of Ser/Thr protein kinases called CBL-interacting protein kinases (CIPKs). Although the CBL-CIPK network has been demonstrated to play crucial roles in plant development and responses to various environmental stresses in Arabidopsis, little is known about their function in canola. RESULTS: In the present study, we identified seven CBL and 23 CIPK genes from canola by database mining and cloning of cDNA sequences of six CBLs and 17 CIPKs. Phylogenetic analysis of CBL and CIPK gene families across a variety of species suggested genome duplication and diversification. The subcellular localization of three BnaCBLs and two BnaCIPKs were determined using green fluorescence protein (GFP) as the reporter. We also demonstrated interactions between six BnaCBLs and 17 BnaCIPKs using yeast two-hybrid assay, and a subset of interactions were further confirmed by bimolecular fluorescence complementation (BiFC). Furthermore, the expression levels of six selected BnaCBL and 12 BnaCIPK genes in response to salt, drought, cold, heat, ABA, methyl viologen (MV) and low potassium were examined by quantitative RT-PCR and these CBL or CIPK genes were found to respond to multiple stimuli, suggesting that the canola CBL-CIPK network may be a point of convergence for several different signaling pathways. We also performed a comparison of interaction patterns and expression profiles of CBL and CIPK in Arabidospsis, canola and rice, to examine the differences between orthologs, highlighting the importance of studying CBL-CIPK in canola as a prerequisite for improvement of this crop. CONCLUSIONS: Our findings indicate that CBL and CIPK family members may form a dynamic complex to respond to different abiotic or hormone signaling. Our comparative analyses of the CBL-CIPK network between canola, Arabidopsis and rice highlight functional differences and the necessity to study CBL-CIPK gene functions in canola. Our data constitute a valuable resource for CBL and CPK genomics.
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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 | 0.002 | 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) | 0.001 | 0.001 |
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".