QTL mapping reveals genetic determinants of fungal disease resistance in the wild lentil species Lens ervoides
Bibliographic record
Abstract
Abstract Lens ervoides, a wild relative of lentil is an important source of allelic diversity for enhancing the genetic resistance of the cultivated species against economically important fungal diseases, such as anthracnose and Stemphylium blight caused by Colletotrichum lentis and Stemphylium botryosum, respectively. To unravel the genetic control underlying resistance to these fungal diseases, a recombinant inbred line (RIL) population (n = 94, F9) originating from a cross between two L. ervoides accessions, L01-827A and IG 72815, was genotyped on the Illumina HiSeq 2500 platform. A total of 289.07 million 100 bp paired-end reads were generated, giving an average 7.53-fold genomic coverage to the RILs and identifying 2,180 high-quality SNPs that assembled in 543 unique haplotypes. Seven linkage groups were resolved among haplotypes, equal to the haploid chromosome number in L. ervoides. The genetic map spanned a cumulative distance of 740.94 cM. Composite interval mapping revealed five QTLs with a significant association with resistance to C. lentis race 0, six QTLs for C. lentis race 1 resistance, and three QTLs for S. botryosum resistance. Taken together, the data obtained in the study reveal that the expression of resistance to fungal diseases in L. ervoides is a result of rearrangement of resistant alleles contributed by both parental accessions.
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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 | 0.001 | 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 | 0.000 |
| 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".