A binary vector-based large insert library for<i>Brassica napus</i>and identification of clones linked to a fertility restorer locus for<i>Ogura</i>cytoplasmic male sterility (CMS)
Bibliographic record
Abstract
We constructed and characterized a large DNA insert library for Brassica napus that would facilitate genome-related research and map-based cloning efforts in Brassica species. This library, consisting of 92,160 clones arrayed in 384-well microtiter dishes, was based on a conventional plant transformation vector (binary vector), and was constructed using a single ligation with transformation efficiency of over 5000 recombinants per microliter of ligation mixture. Every clone in this library contains an insert in the size range of 30-190 kb, facilitating both chromosome walking and plant transformation. Screening this library with three DNA markers (C2, F10, and CabR) that are linked to a fertility restorer locus for Ogura cytoplasmic male sterility (CMS) identified at least 17 positive clones for each probe. Among the 17 positive clones identified by C2, nine are linked to the restorer locus. Marker F10 identified 21 clones, of which only two are linked to the restorer locus. None of 68 clones identified by CabR is linked to the restorer locus. A stability test using two clones identified by the C2 marker indicated that large DNA inserts are stable in this conventional vector in both Escherichia coli and Agrobacterium.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".