The CRISPR/Cas9-Mediated Modulation of SQUAMOSA PROMOTER-BINDING PROTEIN-LIKE 8 in Alfalfa Leads to Distinct Phenotypic Outcomes
Bibliographic record
Abstract
Alfalfa ( Medicago sativa L.) is the most widely grown perennial leguminous forage and is an essential component of the livestock industry. Previously, the RNAi-mediated down-regulation of alfalfa SQUAMOSA PROMOTER-BINDING PROTEIN-LIKE 8 ( MsSPL8 ) was found to lead to increased branching, regrowth and biomass, as well as enhanced drought tolerance. In this study, we aimed to further characterize the function of MsSPL8 in alfalfa using CRISPR/Cas9-induced mutations in this gene. We successfully generated alfalfa genotypes with small insertions/deletions (indels) at the target site in up to three of four MsSPL8 alleles in the first generation. The efficiency of editing appeared to be tightly linked to the particular gRNA used. The resulting genotypes displayed consistent morphological alterations, even with the presence of up to two wild-type MsSPL8 alleles, including reduced leaf size and early flowering. Other phenotypic effects appeared to be dependent upon mutational dosage, with those plants with the highest number of mutated MsSPL8 alleles also exhibiting significant decreases in internode length, plant height, shoot and root biomass, and root length. Furthermore, MsSPL8 mutants displayed improvements in their ability to withstand water-deficit compared to empty vector control genotypes. Taken together, our findings suggest that allelic mutational dosage can elicit phenotypic gradients in alfalfa, and discrepancies may exist in terms of MsSPL8 function between alfalfa genotypes, growth conditions, or specific alleles. In addition, our results provide the foundation for further research exploring drought tolerance mechanisms in a forage crop.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".