Fine mapping of Brassica napus blackleg resistance gene Rlm1 through bulked segregant RNA sequencing
Bibliographic record
Abstract
Abstract The fungal pathogen Leptosphaeria maculans causes blackleg disease on canola and rapeseed (Brassica napus) in many parts of the world. A B. napus cultivar, ‘Quinta’, has been widely used for the classification of L. maculans into pathogenicity groups. In this study, we confirmed the presence of Rlm1 in a DH line (DH24288) derived from B. napus cultivar ‘Quinta’. Rlm1 was located on chromosome A07, between 13.07 to 22.11 Mb, using a BC1 population made from crosses of F1 plants of DH16516 (a susceptible line) x DH24288 with bulked segregant RNA Sequencing (BSR-Seq). Rlm1 was further fine mapped in a 100 kb region from 19.92 to 20.03 Mb in the BC1 population consisting of 1247 plants and a F2 population consisting of 3000 plants using SNP markers identified from BSR-Seq through Kompetitive Allele-Specific PCR (KASP). A potential resistance gene, BnA07G27460D, was identified in this Rlm1 region. BnA07G27460D encodes a serine/threonine dual specificity protein kinase, catalytic domain and is homologous to STN7 in predicted genes of B. rapa and B. oleracea, and A. thaliana. Robust SNP markers associated with Rlm1 were developed, which can assist in introgression of Rlm1 and confirm the presence of Rlm1 gene in canola breeding programs.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".