Conditional neutrality at two adjacent NBS‐LRR disease resistance loci in natural populations of <i>Arabidopsis lyrata</i>
Bibliographic record
Abstract
We examined patterns of nucleotide diversity at a genomic region containing two linked candidate disease resistance (NBS-LRR) genes in seven populations of the outcrossing plant Arabidopsis lyrata. In comparison with two adjacent control genes and neutral reference genes across the genome, the NBS-LRR genes exhibited elevated nonsynonymous variation and a large number of major-effect polymorphisms causing early stop codons and/or frameshift mutations. In contrast, analysis of synonymous diversity provided no evidence that the region was subject to long-term balancing selection or recent selective sweeps in any of the seven populations surveyed. Also in contrast with earlier surveys of one of these R genes, there was no evidence that the resistance genes or the major-effect mutations were subject to elevated differentiation between populations. We suggest that conditional neutrality in the absence of the corresponding pathogen, rather than long-term balancing selection or local adaptation, may in some circumstances be a significant cause of elevated functional polymorphism at R genes. In contrast with the R genes, analysis of diversity and differentiation at the flanking FERONIA locus showed high population divergence, suggesting local adaptation on this locus controlling male-female signalling during fertilization.
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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 | 0.001 |
| 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 | 0.001 |
| 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".