Painting the rye genome with genome-specific sequences
Bibliographic record
Abstract
We used rye-specific repetitive DNA sequences in fluorescence in situ hybridization (FISH) to paint the rye genome and to identify rye DNA in a wheat background. A 592 bp fragment from the rye-specific dispersed repetitive family R173 (named UCM600) was cloned and used as a FISH probe. UCM600 is dispersed over the seven rye chromosomes, being absent from the pericentromeric and subtelomeric regions. A similar pattern of distribution was also observed on the rye B chromosomes, but with weaker signals. The FISH hybridization patterns using UCM600 as probe were comparable with those obtained with the genomic in situ hybridization (GISH) procedure. There were, however, sharper signals and less background with FISH. UCM600 was combined with the rye-specific sequences Bilby and pSc200 to obtain a more complete painting. With these probes, the rye chromosomes were labeled with distinctive patterns; thus, allowing the rye cultivar 'Imperial' to be karyotyped. It was also possible to distinguish rye chromosomes in triticale and alien rye chromatin in wheat-rye addition and translocation lines. The distribution of UCM600 was similar in cultivated rye and in the wild Secale species Secale vavilovii Grossh., Secale sylvestre Host, and Secale africanum Stapf. Thus, UCM600 can be used to detect Secale DNA introgressed from wild species in a wheat background.
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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 | 0.001 |
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".