The soybean (<i>Glycine max</i>) nodulation‐suppressive <scp>CLE</scp> peptide, Gm<scp>RIC</scp>1, functions interspecifically in common white bean (<i>Phaseolus vulgaris</i>), but not in a supernodulating line mutated in the receptor Pv<scp>NARK</scp>
Bibliographic record
Abstract
Legume plants regulate the number of nitrogen-fixing root nodules they form via a process called the Autoregulation of Nodulation (AON). Despite being one of the most economically important and abundantly consumed legumes, little is known about the AON pathway of common bean (Phaseolus vulgaris). We used comparative- and functional-genomic approaches to identify central components in the AON pathway of common bean. This includes identifying PvNARK, which encodes a LRR receptor kinase that acts to regulate root nodule numbers. A novel, truncated version of the gene was identified directly upstream of PvNARK, similar to Medicago truncatula, but not seen in Lotus japonicus or soybean. Two mutant alleles of PvNARK were identified that cause a classic shoot-controlled and nitrate-tolerant supernodulation phenotype. Homeologous over-expression of the nodulation-suppressive CLE peptide-encoding soybean gene, GmRIC1, abolished nodulation in wild-type bean, but had no discernible effect on PvNARK-mutant plants. This demonstrates that soybean GmRIC1 can function interspecifically in bean, acting in a PvNARK-dependent manner. Identification of bean PvRIC1, PvRIC2 and PvNIC1, orthologues of the soybean nodulation-suppressive CLE peptides, revealed a high degree of conservation, particularly in the CLE domain. Overall, our work identified four new components of bean nodulation control and a truncated copy of PvNARK, discovered the mutation responsible for two supernodulating bean mutants and demonstrated that soybean GmRIC1 can function in the AON pathway of bean.
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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 | 0.000 |
| 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".