Investigation of variations in NBS motifs in alfalfa (<i>Medicago sativa</i>), <i>M. edgeworthii</i>, and <i>M. ruthenica</i>
Bibliographic record
Abstract
Medicago edgeworthii Sirjaev and M. ruthenica (L.) Ledebour are allogamous, diploid (2n = 2x = 16) perennials from Asia, which have a remarkable ability to survive stress , but are genetically distant from cultivated alfalfa (M. sativa L., 2n = 4x = 32). In lieu of hybridization, potentially important genes from the Asian species could be transferred to alfalfa using transgenic techniques. Many plant disease resistance genes (R-genes) belong to the nucleotide binding site-leucine rich repeats (NBS-LRR) superfamily and have several highly conserved NBS region motifs, which can be used to identify them. Thus, genomic DNA of alfalfa and the two Asian species was primed with a degenerate forward P-loop primer paired with degenerate reverse primers designed for GLPLA, RNBS-C, or RNBS-D-non-Toll/Interleukin (RNBS-D-non-TIR) motifs. The P-Loop/GLPLA primer combination yielded the largest number of sequences without stop codons, and alfalfa had the greatest variation within the kinase and RNBS-C domains; however several kinase and RNBS-C sequences were unique to M. edgeworthii or M. ruthenica. Priming with the P-loop/RNBS-C primer pair resulted in some open reading frames, which apparently did not belong to the NBS-LRR superfamily. The only open reading frames for the P-loop/RNBS-D-non-TIR primer combination were for M. ruthenica. These non-TIR-type clones, and the only non-TIR-type clone from the P-loop/GLPLA PCR (alfalfa), had sequences that were markedly different from the TIR-type sequences. The RNBS-C region may be useful in identifying non-TIRtype R-gene analogs in future studies. Screening for unique R-gene analogs in genetically distant Medicago species may be a very effective way of isolating potential new R-genes for transfer to alfalfa. Key words: Alfalfa, disease resistance, kinase, Medicago edgeworthii, Medicago ruthenica, NBS-LRR, R-gene analog
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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) | 0.000 | 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 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".