Elevated Mutation Burdens in Canadian Oat and Wheat Cultivars Released over the Past Century
Bibliographic record
Abstract
Modern high-yielding crop cultivars are known to have narrow genetic bases, making them vulnerable to biotic and abiotic stresses. However, little is known about the extent of deleterious genetic variants (or mutation burden) present in these cultivars. An attempt was made using RNA-Seq to screen genome-wide deleterious genetic variants in 141 oat and 142 wheat cultivars released through Canadian breeding programs over the past century. The screening identified 5726 and 3022 deleterious genetic variants across all 21 chromosomes of both the oat and wheat genomes, respectively. These deleterious variants were largely harbored in a few cultivars and were involved with diverse biological processes, cellular components, and molecular functions. More highly deleterious variants were predicted in oat, than in wheat, cultivars, and different gene expression profiles at the early seedling stage were observed between oat and wheat cultivars, illustrating different genetic impacts of the oat and wheat breeding programs. Estimating mutation burdens for each cultivar revealed large variations among both the oat and wheat cultivars. These mutation burdens were found to increase from early to recent oat and wheat cultivars and were associated with higher cultivar yields. Genetic analyses also revealed genetic shifts and expansions from early to recent oat and wheat cultivars. These findings provide the first empirical evidence of elevated mutation burdens in Canadian oat and wheat cultivars and are useful for advancing plant breeding programs to minimize genetic risk.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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".