Mutation of MsSPL8 Alleles via CRISPR/Cas9-Mediated Genome Editing Leads to Superior Abiotic Stress Resiliency and Distinct Morphological Alterations in Alfalfa
Bibliographic record
Abstract
Increase in demand for meat, milk and their products is expected to escalate considerably in coming years due to our ever-expanding population. While increases in forage crop production will therefore be a necessity to meet demand, our ability to attain high levels of forage crop productivity is likely to be constrained by typical environmental pressures such as drought and salinity due to climate change. Alfalfa (Medicago sativa L.) is one of the world’s most widely grown forage species, with a cropping area of over 30 million hectares worldwide. As such, there is a critical need to exploit advanced molecular breeding technologies in this species with the aim of rapidly developing alfalfa cultivars with improved biomass, as well as resiliency to various types of abiotic stress. It has been shown previously that the RNAi-mediated down-regulation of the miRNA156 target gene, SQUAMOSA PROMOTER BINDING PROTEIN-LIKE8 (MsSPL8), enhances biomass production, as well as drought and salinity tolerance, in alfalfa. However, due to negative public perception and regulatory constraints surrounding the use of transgenic crops, it remains a challenge to implement such a crop in growers’ fields. CRISPR/Cas9-based genome editing provides an alternative breeding tool that yields germplasm bearing a mutation that is fundamentally identical to those achieved using conventional breeding approaches such as chemical mutagenesis, and the resulting plants can be made transgene-free in a straightforward manner. In this study, we successfully targeted MsSPL8 alleles using this technology in alfalfa, and isolated genotypes with mutations in approximately 25%, 50% and 75% of MsSPL8 alleles, respectively, in this tetraploid species. Furthermore, enhanced drought and salinity resistance, along with distinct morphological alterations including early flowering and reductions in internode length, were noted in the first generation of edited genotypes, which suggests that CRISPR/Cas9 can provide an effective breeding tool in alfalfa.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".