Widespread variation in<i>NSP1</i>, a gene involved in rhizobium nodulation, across species of<i>Acmispon</i>(Fabaceae) from diverse habitats
Bibliographic record
Abstract
GRAS proteins comprise a large family of genes that play important roles in regulating gene expression throughout all stages of plant development. The physiological and phylogenetic breadth of GRAS proteins known among model species suggests that they may be useful as molecular genetic markers in non-model species. For example, GRAS genes involved in regulating legume–rhizobium symbioses may reveal ecological and evolutionary variation in these relationships. In this study, we collected sequences from Nodulation Signaling Protein 1 (NSP1), a gene involved in the development of an infection thread through which rhizobia enter roots, in five species of Acmispon Raf. to quantify genetic variation within and between closely related species and to compare sequence divergence in NSP1 from Acmispon with other legumes. We found a high degree of similarity of NSP1 from Acmispon with homologues in other angiosperms. Thirty-two unique alleles were identified within Acmispon, and much of this variation reflects spatial and geographic variation of sampled populations. There was no evidence of selection at the molecular level. Given the strong genetic structure found among Acmispon species, especially in a microsatellite region of the N-terminus, and the existence of homologues, NSP1 could be a useful phylogenetic marker across angiosperms.
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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 | 0.001 | 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) | 0.001 | 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".