Linkage maps for Arabidopsis lyrata subsp. lyrata and<i>Arabidopsis lyrata</i>subsp. petraea combining anonymous and Arabidopsis thaliana–derived markers
Bibliographic record
Abstract
Arabidopsis lyrata, a close relative of the model plant Arabidopsis thaliana, is 1 of a few plant species for which the genome is to be entirely sequenced, which promises to yield important insights into genome evolution. Only 2 sparse linkage maps have been published, and these were based solely on markers derived from the A. thaliana genome. Because the genome of A. lyrata is practically twice as large as that of A. thaliana, the extent of map coverage of the A. lyrata genome remains uncertain. In this study, a 2-way pseudo-testcross strategy was used to construct genetic linkage maps of A. lyrata subsp. petraea and A. lyrata subsp. lyrata, using simple sequence repeat (SSR) and cleaved amplified polymorphic sequence (CAPS) markers from the A. thaliana genome, and anonymous amplified fragment length polymorphism (AFLP) markers that could potentially uncover regions unique to the A. lyrata genome. The SSR and CAPS markers largely confirmed the relationships between linkage groups in A. lyrata and A. thaliana. AFLP markers slightly increased the coverage of the A. lyrata maps, but mostly increased marker density on the linkage groups. We noted a much lower level of polymorphism and a greater segregation distortion in A. lyrata subsp. lyrata markers. The implications of these findings for the sequencing of the A. lyrata genome are discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".