Isolation and characterization of resistance gene analogues from <i>Psilanthus</i> species that represent wild relatives of cultivated coffee endemic to India
Bibliographic record
Abstract
Biotic or abiotic stress can cause considerable damage to crop plants that can be managed by building disease resistance in the cultivated gene pool through breeding for disease resistance genes (R-genes). R-genes, conferring resistance to diverse pathogens or pests share a high level of similarity at the DNA and protein levels in different plant species. This property of R-genes has been successfully employed to isolate putative resistance gene analogues (RGAs) using a PCR-based approach from new plant sources. Using a similar approach, in the present study, we have successfully amplified putative RGAs having nucleotide-binding-site leucine-rich repeats (NBS-LRR-type RGAs) from seven different sources: two cultivated coffee species (Coffea arabica L. and Coffea canephora Pierre ex. A. Froehner), four related taxa endemic to India (wild tree coffee species: Psilanthus bengalensis (Roem. & Schuttles) J.-F. Leroy, Psilanthus khasiana , Psilanthus travencorensis (Wight & Arn.) J.-F. Leroy, Psilanthus weightiana (Wall. ex Wight & Arn.) J.-F. Leroy), and a cDNA pool originally prepared from light- and drought-stressed Coffea arabica L. leaves. The total PCR amplicons obtained using NBS-LRR-specific primers from each source were cloned and transformed to construct seven independent libraries, from which 434 randomly picked clones were sequenced. In silico analysis of the sequenced clones revealed 27 sequences that contained characteristic RGA motifs, of which 24 had complete uninterrupted open reading frames. Comparisons of these with published RGAs showed several of these to be novel RGA sequences. Interestingly, most of such novel RGAs belonged to the related wild Psilanthus species. The data thus suggest the potential of the secondary gene pool as possible untapped donors of resistance genes to the present day cultivated species of coffee.
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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 | 0.000 |
| 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 | 0.001 |
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".