Exploring Cloned Disease Resistance Gene Homologues and Resistance Gene Analogues in Brassica nigra, Sinapis arvensis, and Sinapis alba: Identification, Characterisation, Distribution, and Evolution
Bibliographic record
Abstract
This study identifies and classifies resistance gene analogues (RGAs) in the genomes of Brassica nigra, Sinapis arvensis and Sinapis alba using the RGAugury pipeline. RGAs were categorised into four main classes: receptor-like kinases (RLKs), receptor-like proteins (RLPs), nucleotide-binding leucine-rich repeat (NLR) proteins and transmembrane-coiled-coil (TM-CC) genes. A total of 4499 candidate RGAs were detected, with species-specific proportions. RLKs were the most abundant across all genomes, followed by TM-CCs and RLPs. The sub-classification of RLKs and RLPs identified LRR-RLKs, LRR-RLPs, LysM-RLKs, and LysM-RLPs. Atypical NLRs were more frequent than typical ones in all species. Atypical NLRs were more frequent than typical ones in all species. We explored the relationship between chromosome size and RGA count using regression analysis. In B. nigra and S. arvensis, larger chromosomes generally harboured more RGAs, while S. alba displayed the opposite trend. Exceptions were observed in all species, where some larger chromosomes contained fewer RGAs in B. nigra and S. arvensis, or more RGAs in S. alba. The distribution and density of RGAs across chromosomes were examined. RGA distribution was skewed towards chromosomal ends, with patterns differing across RGA types. Sequence hierarchical pairwise similarity analysis revealed distinct gene clusters, suggesting evolutionary relationships. The study also identified homologous genes among RGAs and non-RGAs in each species, providing insights into disease resistance mechanisms. Finally, RLKs and RLPs were co-localised with reported disease resistance loci in Brassica, indicating significant associations. Phylogenetic analysis of cloned RGAs and QTL-mapped RLKs and RLPs identified distinct clusters, enhancing our understanding of their evolutionary trajectories. These findings provide a comprehensive view of RGA diversity and genomics in these Brassicaceae species, providing valuable insights for future research in plant disease resistance and crop improvement.
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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 | 0.001 |
| 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".