Evaluation of Factors Affecting <i>In Planta</i> Gene Editing Efficiency in Wheat (<i>Triticum aestivum</i> L.)
Why this work is in the frame
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Bibliographic record
Abstract
Gene editing in polyploid crops still suffers from low efficiency, and further improvement is needed for its routine implementation in the modern breeding practice. Here we examined factors that affect the CRISPR/Cas9-mediated gene editing efficiency in allohexaploid wheat plants. We selected three guide RNAs (gRNAs) and evaluated the potential of using heat shock at the seedlings stage to increase editing efficiency in transgenic plants. Only one out of three gRNAs demonstrated significantly increased editing efficiency following heat shock treatment. We also examined the expression of DNA repair and replication gene orthologues in response to heat shock in wheat leaves. Misregulation of the chromatin remodelers following the heat shock treatment could potentially be involved in the increase of editing efficiency in wheat. Overall, the editing efficiency of gRNAs observed in our study correlated with predictive scores from the gRNA design tools. The editing rate of the top-ranked gRNAs could potentially be increased using heat treatment of the transgenic plants.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 it