Optimized methods for random and targeted mutagenesis in field pea (Pisum sativum L.)
Bibliographic record
Abstract
Field pea is an important pulse crop for its dense nutritional profile and contribution to sustainable agricultural practices. Recently, it has received extensive attention as a potential leading source of plant-based proteins. However, the adoption of peas as a mainstream source of proteins is affected by a relatively moderate protein content, anti-nutritional factors and high levels of off-flavor components that reduce protein quality. Availability of genetic variation for desirable seed quality traits is the foundation for the sustainable development of pea varieties with improved protein content and quality. Mutagenesis has been an important tool in gene functional characterization studies and creating genetic variability for crop breeding. Large-scale mutagenesis of a crop using physical and chemical agents requires diligent selection of the mutagen and optimization of its dose to increase the frequency of mutations. In this study, we present detailed optimized protocols for physical and chemical mutagenesis of pea using gamma irradiation and ethyl methanesulfonate (EMS), respectively. Gamma radiation and EMS titration kill curves were established to identify optimal doses of the two mutagenic agents. Based on germination, survival rate and growth phenotypes, a gamma radiation dose of 225 Gy and EMS concentration of 5 mm were selected as optimal dosages for mutagenesis in field pea. The presented protocol has been modified from previously established mutagenesis protocols in other crop plants. Our results indicate that the optimal mutagen dosage is genotype dependent. CRISPR/Cas-based gene editing provides a precise and rapid method for targeted genetic manipulation in plants. With the recent success of gene editing in pea using CRISPR/Cas, this innovative technology is expected to become an integral component of the gene discovery and crop improvement toolkit in pea. Here, we describe an optimized methods for targeted mutagenesis of pea protoplasts, including mesophyll protoplast extraction, PEG-mediated transformation and gene editing of a LOX gene using CRISPR/Cas system. The general strategies and methods of mutagenesis described here provide an essential resource for mutation breeding and functional genomics studies in pea. These methods also provide a foundation for similar studies in other crops.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".