Identification of candidate genes associated with resistance against race 0 of Colletotrichum lentis in Lens ervoides
Bibliographic record
Abstract
Resistance to anthracnose caused by the fungal pathogen Colletotrichum lentis was explored through transcriptome sequencing over a period of 24 to 96 h post-inoculation (hpi) of the partially resistant recombinant inbred lines (RIL) LR-66-528 and susceptible LR-66-524 of the crop wild relative Lens ervoides population LR-66. The development of infection vesicles and primary hyphae by C. lentis were significantly higher on susceptible RIL LR-66-524 compared to partially resistant LR-66-528 at 24 and 48 hpi, but exponential trends in fungal growth were observed between 24 to 96 hpi in both RILs. Comparison of inoculated with mock-inoculated samples revealed 3091 disease responsive genes, among which 477 were differentially expressed between the two RILs. These were clustered into six expression clusters with genes that had either high or low expression in one of the RILs. Differentially expressed genes (DEGs) were functionally annotated and included genes coding LRR and NB-ARC domain disease resistance proteins, protein detoxification, LRR receptor-like kinase family proteins, and wall-associated Ser/Thr Kinases. DEGs were compared to genes in previously published anthracnose resistance QTLs mapped in LR-66 and revealed 22 DEGs located in 3 QTLs. Expression of 21 DEGs was validated using RT-qPCR confirming expression trends in RNA-seq.
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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".