Striking convergent selection history of wheat and barley and its potential for breeding
Bibliographic record
Abstract
Over the past 10,000 years, the development of civilization has been enabled by the domestication of plants and animals tailored to human needs. The Triticeae tribe, including barley and wheat, has emerged as one of the most important sources of staple foods worldwide. Here, comparing genomes of wheat and barley genotypes from around the world, we unveiled genomic footprints of convergent selection affecting genes involved in crop adaptation and productivity, as well as a lack of parallel selection for diverse genes delivering genetic diversity specific to particular geographic and associated environmental conditions. We demonstrate that studying convergent selection between crops can help to identify genes crucial for adaptation and sources of diversity for improving cultivated species—forming the basis of the proposed concept of inter-crop translational research for breeding. Convergent selection between crops can help to identify genetic variants with important roles in adaptation as a source of diversity for the improvement of cultivated species through the concept of inter-crop translational research for breeding.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".