Bacterial artificial chromosome–based physical map of<i>Gibberella zeae</i>(<i>Fusarium graminearum</i>)
Bibliographic record
Abstract
Fusarium graminearum is the primary causal pathogen of Fusarium head blight of wheat and barley. To accelerate genomic analysis of F. graminearum, we developed a bacterial artificial chromosome (BAC)-based physical map and integrated it with the genome sequence and genetic map. One BAC library, developed in the HindIII restriction enzyme site, consists of 4608 clones with an insert size of approximately 107 kb and covers about 13.5 genome equivalents. The other library, developed in the BamHI restriction enzyme site, consists of 3072 clones with an insert size of approximately 95 kb and covers about 8.0 genome equivalents. We fingerprinted 2688 clones from the HindIII library and 1536 clones from the BamHI library and developed a physical map of F. graminearum consisting of 26 contigs covering 39.2 Mb. Comparison of our map with the F. graminearum genome sequence showed that the size of our physical map is equivalent to the 36.1 Mb of the genome sequence. We used 31 sequence-based genetic markers, randomly spaced throughout the genome, to integrate the physical map with the genetic map. We also end-sequenced 17 BamHI BAC clones and identified 4 clones that spanned gaps in the genome sequence. Our new integrated map is highly reliable and useful for a variety of genomics studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".