Targeted Editing of SlMAPK6 Using CRISPR/Cas9 Technology to Promote the Development of Axillary Buds in Tomato Plants
Bibliographic record
Abstract
The mitogen-activated protein kinase (MAPK) cascade signaling system has been relatively conserved throughout the evolution of eukaryotes and is involved in the regulation of growth and development and metabolism. In this study, dwarf tomato plants were used as the research material. First, the tissue-specific expression of SlMAPK6 was measured in wild-type plants by quantitative RT-PCR. The results showed that SlMAPK6 was highly expressed in the tissues of the stems, leaves and flowers but was expressed at low levels in the tissues of the roots, sepals and fruits. Second, SlMAPK6-knockout lines CRISPR-3 and CRISPR-7 were obtained by CRISPR-Cas9 technology and Agrobacterium-mediated transformation. Compared with wild-type, the mutant lines CRISPR-3 and CRISPR-7 showed significant phenotypic characteristics, such as increased numbers of axillary buds and true leaves, thickened stems, and longer leaflets. In addition, to explore the molecular mechanism by which MAPK regulates axillary bud growth, we also showed that SlMAPK6 positively regulates the strigolactone synthesis genes SlCCD7 and SlCCD8 and the gibberellin (GA) synthesis genes GA20ox3 and GA3ox1 and negatively regulates the axillary bud development-related genes Ls, BL and BRC1b/TCP8 and the GA synthesis inhibitory gene GAI. Therefore, SlMAPK6 appears to regulate the synthesis of strigolactone and GA to induce the growth and development of tomato axillary buds.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".