Untangling structural factors and evolutionary drivers in nascent polyploids
Bibliographic record
Abstract
SUMMARY Allopolyploids have globally higher fitness than their diploid progenitors however, by comparison, most resynthesized allopolyploids have poor fertility and highly unstable genome. Elucidating the evolutionary processes promoting genome stabilization and fertility is thus essential to comprehend allopolyploid success. Using the Brassica model, we mimicked the speciation process of a nascent allopolyploid species by resynthesizing allotetraploid B. napus and systematically selecting for euploid individuals over eight generations in four independent allopolyploidization events with contrasted genetic backgrounds, cytoplasmic donors and polyploid formation type. We evaluated the evolution of meiotic behavior, fertility and identified rearrangements in S1 to S9 lineages, to explore the positive consequences of euploid selection on B. napus genome stability. Recurrent selection of euploid plants for eight generations drastically reduced the percentage of aneuploid progenies as early as the fourth generation, concomitantly with a quasi disappearance of newly fixed homoeologous rearrangements. The consequences of homoeologous rearrangements on meiotic behavior and seed number strongly depended on the genetic background and cytoplasm donor. The combined use of both self-fertilisation and outcrossing as well as recurrent euploid selection, allowed identification of genomic regions associated with fertility and meiotic behavior, providing complementary evidence to explain B. napus speciation success.
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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 | 0.000 | 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".