Expression, mapping, and genetic variability of<i>Brassica napus</i>disease resistance gene analogues
Bibliographic record
Abstract
Numerous sequences analogous to resistance (R) genes exist in plant genomes and could be involved in resistance traits. The aim of this study was to identify a large number of Brassica napus sequences related to R genes and also to test the adequacy of specific PCR-based tools for studying them. Different consensus primers were compared for their efficiency in amplifying resistance-gene analogues (RGAs) related to the nucleotide-binding-site subgroup of R genes. Specific primers were subsequently designed to fine-study the different RGAs and we tested their efficiency in three species related to B. napus: Brassica oleracea, Brassica rapa, and Arabidopsis thaliana. Forty-four B. napus RGAs were identified. Among 29 examined, at least one-third were expressed. Eighteen RGAs were mapped on 10 of the 19 B. napus linkage groups. The high variability within these sequences permitted discrimination of each genotype within a B. napus collection. The RGA-specific primers amplified RGAs in the B. oleracea and B. rapa genomes, but the sequences appear to be poorly conserved in A. thaliana. Specific RGA primers are a precise tool for studying known-sequence RGAs. These sequences represent interesting markers that could be correlated with resistance traits in B. napus or related Brassica genomes.
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) | 0.000 | 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 | 0.000 |
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 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".