Detecting<i>de Novo</i>Homoeologous Recombination Events in Cultivated<i>Brassica napus</i>Using a Genome-Wide SNP Array
Bibliographic record
Abstract
Abstract The heavy selection pressure due to intensive breeding of Brassica napus has created a narrow gene pool, limiting the ability to produce improved varieties through crosses between B. napus cultivars. One mechanism that has contributed to the adaptation of important agronomic traits in the allotetraploid B. napus has been chromosomal rearrangements resulting from homoeologous recombination between the constituent A and C diploid genomes. Determining the rate and distribution of such events in natural B. napus will assist efforts to understand and potentially manipulate this phenomenon. The Brassica high-density 60K SNP array, which provides genome-wide coverage for assessment of recombination events, was used to assay 254 individuals derived from 11 diverse cultivated spring type B. napus. These analyses identified reciprocal allele gain and loss between the A and C genomes and allowed visualization of de novo homoeologous recombination events across the B. napus genome. The events ranged from loss/gain of 0.09 Mb to entire chromosomes, with almost 5% aneuploidy observed across all gametes. There was a bias toward sub-telomeric exchanges leading to genome homogenization at chromosome termini. The A genome replaced the C genome in 66% of events, and also featured more dominantly in gain of whole chromosomes. These analyses indicate de novo homoeologous recombination is a continuous source of variation in established Brassica napus and the rate of observed events appears to vary with genetic background. The Brassica 60K SNP array will be a useful tool in further study and manipulation of this phenomenon.
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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 | 0.000 |
| 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 | 0.000 |
| 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".