Ectopic expression of miR156 represses nodulation and causes morphological and developmental changes in Lotus japonicus
Bibliographic record
Abstract
The effects of microRNA156 overexpression on general plant architecture, branching, flowering time and nodulation were investigated in the model legume, Lotus japonicus. We cloned an miR156 homolog, LjmiR156a, from L. japonicus, and investigated its SQUAMOSA PROMOTER BINDING PROTEIN LIKE (SPL) genes and its biological function at enhancing vegetative biomass yield, extending flowering time, and its impact on nodulation. Thirteen potential targets for LjmiR156 were identified in vitro and their expression profiles were determined in aerial and underground parts of mature plants, including genes coding for eight SPLs, one WD-40, one RNA-directed DNA polymerase, two transport proteins, and one histidine-phosphotransfer protein. Two SPL and one WD-40 cleavage targets for LjmiR156-TC70253, AU089191, and TC57859-were identified. Transgenic plants with ectopic expression of LjmiR156a showed enhanced branching, dramatically delayed flowering, underdeveloped roots, and reduced nodulation. We also examined the transcript levels of key genes involved in nodule organogenesis and infection thread formation to determine the role of miR156 in regulating symbiosis. Overexpression of LjmiR156a led to repression of several nodulation genes during the early stages of root development such as three ENOD genes, SymPK, POLLUX, CYCLOPS, Cerberus, and Nsp1, and the stimulation of NFR1. Our results show that miR156 regulates vegetative biomass yield, flowering time and nodulation by silencing downstream target SPLs and other genes, suggesting that the miR156 regulatory network could be modified in forage legumes (such as alfalfa and trefoils) and in leafy vegetables (like lettuce and spinach) to positively impact economically valuable crop species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".