The strategy and current status of Brassica rapa genome project
Bibliographic record
Abstract
Brassica rapa is considered an ideal candidate to act as a reference species for Brassica genomic studies. Among the three basic Brassica species, B. rapa (AA genome) has the smallest genome (529 Mbp), compared to B. nigra (BB genome, 632 Mbp) and B. oleracea (CC genome, 696 Mbp). There is also a large collection of available cultivars of B. rapa, as well as a broad array of B. rapa genomic resources available. Under international consensus, various genomic studies on B. rapa have been conducted, including the construction of a physical map based on 22.5X genome coverage, end sequencing of 146,000 BACs, sequencing of >150,000 expressed sequence tags, and successful phase 2 shotgun sequencing of 589 euchromatic region-tiling BACs based on comparative positioning with the Arabidopsis genome. These sequenced BACs mapped onto the B. rapa genome provide beginning points for genome sequencing of each chromosome. Applying this strategy, all of the 10 chromosomes of B. rapa have been assigned to the sequencing centers in seven countries, Korea, UK, China, India, Canada, Australia, and Japan. The two longest chromosomes, A3 and A9, have been sequenced except for several gaps, by NAAS in Korea. Meanwhile a China group, including IVF and BGI, performed whole genome sequencing with Illumina system. These Sanger and NGS sequence data will be integrated to assemble a draft sequence of B. rapa. The imminent B. rapa genome sequence offers novel insights into the organization and evolution of the Brassica genome. In parallel, the transfer of knowledge from B. rapa to other Brassica crops would be expected.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".