Divergent diversity patterns of NBS and LRR domains of resistance gene analogs in wild emmer wheat populations
Bibliographic record
Abstract
Disease resistance (R) genes are intriguing in their evolution and diversity patterns because of their constant interactions with evolving pathogens. In this study, we demonstrate the use of resistance gene analog (RGA) markers to estimate genetic diversity among 13 populations (118 genotypes) of Triticum dicoccoides collected along a natural aridity gradient in Israel. The diversity patterns of 204 markers derived from two R-gene domains, nucleotide binding site (NBS) and leucine-rich repeat (LRR), were compared and contrasted. Diversity patterns of NBS domain markers differed significantly from those of the LRR domain. NBS markers showed higher between-population diversity (Fst=0.58), while LRR markers showed higher within-population diversity (Fst=0.35). Gene diversity (He) values were twofold higher in the LRR domain than in the NBS domain (0.144 vs. 0.067). LRR He values were correlated with precipitation in the spring (r=0.8, p=0.01), while NBS He values showed no correlation with any ecogeographical variable. The evolutionary and applicative inferences of these findings are discussed. The current study demonstrates that RGA profiling is an excellent tool for studying diversity of R genes in natural plant populations.
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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) | 0.000 | 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".