A plant-transformation-competent BIBAC/BAC-based map of rice for functional analysis and genetic engineering of its genomic sequence
Bibliographic record
Abstract
Sequencing of the rice genome has provided a platform for functional genomics research of rice and other cereal species. However, multiple approaches are needed to determine the functions of its genes and sequences and to use the genome sequencing results for genetic improvement of cereal crops. Here, we report a plant-transformation-competent, binary bacterial artificial chromosome (BIBAC) and bacterial artificial chromosome (BAC) based map of rice to facilitate these studies. The map was constructed from 20 835 BIBAC and BAC clones, and consisted of 579 overlapping BIBAC/BAC contigs. To facilitate functional analysis of chromosome 8 genomic sequence and cloning of the genes and QTLs mapped to the chromosome, we anchored the chromosomal contigs to the existing rice genetic maps. The chromosomal map consists of 11 contigs, 59 genetic markers, and 36 sequence tagged sites, spanning a total of ca. 38 Mb in physical length. Comparative analysis between the genetic and physical maps of chromosome 8 showed that there are 3 "hot" and 2 "cold" spots of genetic recombination along the chromosomal arms in addition to the "cold spot" in the centromeric region, suggesting that the sequence component contents of a chromosome may affect its local genetic recombination frequencies. Because of its plant transformability, the BIBAC/BAC map could provide a platform for functional analysis of the rice genome sequence and effective use of the sequencing results for gene and QTL cloning and molecular breeding.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 0.000 |
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 teacher head, 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".