Genome‐Wide Reduction of Genetic Diversity in Wheat Breeding
Bibliographic record
Abstract
ABSTRACT Public concerns about crop uniformity introduced by modern plant breeding and genetic vulnerability to biotic and abiotic stresses have been one of the major forces driving long‐term efforts in plant germplasm conservation for future food security. However, such concerns have gained little empirical support, as recent molecular diversity analyses of improved crop gene pools did not reveal much reduction from early to recent breeding efforts. We conducted a genome‐wide examination of 75 Canadian hard red spring wheat (Triticum aestivum L.) cultivars released from 1845 to 2004 using 370 simple sequence repeat (or SSR) markers that were widely distributed over all 21 wheat chromosomes. A total of 2280 SSR alleles were detected. Allelic reduction occurred in every part of the wheat genome and a majority of the reduced alleles resided in only a few early cultivars. Significant allelic reduction started in the 1930s. Considering 2010 SSR alleles detected in the 20 earliest cultivars, 38% of them were retained, 18% were new, and 44% were lost in the 20 most recent cultivars. The net reduction of the total SSR variation in 20 recent cultivars was 17%. This clear‐cut evidence not only supports the contention that modern plant breeding reduces the genetic diversity of Canadian wheat, but also underlies the need for conserving wheat germplasm and introducing genetic diversity into wheat breeding.
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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 | 0.001 |
| 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".