Population-based resequencing analysis of wild and cultivated barley revealed weak domestication signal of selection and bottleneck in the<i>Rrs2</i>scald resistance gene region
Bibliographic record
Abstract
Many plant disease resistance (R) genes have been cloned, but the potential of utilizing these plant R-gene genomic resources for genetic inferences of plant domestication history remains unexplored. A population-based resequencing analysis of the genomic region near the Rrs2 scald resistance gene was made in 51 accessions of wild and cultivated barley from 41 countries. Fifteen primer pairs were designed to sample the genomic region with a total length of 10 406 bp. More nucleotide diversity was found in wild (π = 0.01846) than cultivated (π = 0.01507) barley samples. Three distinct groups of 29 haplotypes were detected for all 51 samples, and they were well mixed with wild and cultivated barley samples from different countries and regions. The neutrality tests by Tajima's D were not significant, but a significant (P < 0.05) case by Fu and Li's D* and F* was found in the barley cultivar samples. The estimate of selection intensity by K(a)/K(s) was 0.691 in wild barley and 0.580 in cultivated barley. The estimate of the minimum recombination events was 16 in wild barley and 19 in cultivated barley. A coalescence simulation revealed a bottleneck intensity of 1.5 to 2 since barley domestication. Together, the domestication signal in the genomic region was weak both in human selection and domestication bottleneck.
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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 | 0.000 | 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) | 0.001 | 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".