The <i>BOY NAMED SUE</i> Quantitative Trait Locus Confers Increased Meiotic Stability to an Adapted Natural Allopolyploid of <i>Arabidopsis</i>
Bibliographic record
Abstract
Whole-genome duplication resulting from polyploidy is ubiquitous in the evolutionary history of plant species. Yet, polyploids must overcome the meiotic challenge of pairing, recombining, and segregating more than two sets of chromosomes. Using genomic sequencing of synthetic and natural allopolyploids of Arabidopsis thaliana and Arabidopsis arenosa, we determined that dosage variation and chromosomal translocations consistent with homoeologous pairing were more frequent in the synthetic allopolyploids. To test the role of structural chromosomal differentiation versus genetic regulation of meiotic pairing, we performed sequenced-based, high-density genetic mapping in F2 hybrids between synthetic and natural lines. This F2 population displayed frequent dosage variation and deleterious homoeologous recombination. The genetic map derived from this population provided no indication of structural evolution of the genome of the natural allopolyploid Arabidopsis suecica, compared with its predicted parents. The F2 population displayed variation in meiotic regularity and pollen viability that correlated with a single quantitative trait locus, which we named BOY NAMED SUE, and whose beneficial allele was contributed by A. suecica. This demonstrates that an additive, gain-of-function allele contributes to meiotic stability and fertility in a recently established allopolyploid and provides an Arabidopsis system to decipher evolutionary and molecular mechanisms of meiotic regularity in polyploids.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".