Nucleotide-binding site (NBS) profiling of genetic diversity in durum wheat
Bibliographic record
Abstract
Molecular markers are effective tools to investigate genetic diversity for resistance to pathogens. NBS (nucleotide-binding site) profiling is a PCR (polymerase chain reaction)-based approach to studying genetic variability that specifically targets chromosome regions containing R-genes and R-gene analogues. We used NBS profiling to measure genetic diversity among 58 accessions of durum wheat. Mean polymorphism rates detected using MseI and AluI as restriction enzymes were 34% and 22%, respectively. Mean number of polymorphisms per enzyme-primer combination was equal to 23.8 +/- 5.9, ranging from 13 to 31 polymorphic bands. In total, 96 markers over 190 indicated a good capacity to discriminate between accessions (the polymorphic index content ranging from 0.30 to 0.50). The results obtained with NBS profiling were compared with simple sequence repeat (SSR) and amplified fragment length polymorphism (AFLP) data of the same set of accessions. The genetic distances computed with 190 NBS profiling markers were in close agreement with those obtained with AFLP and SSR markers (r = 0.73 and 0.76, respectively). Our results indicate that NBS profiling provides an effective means to investigate genetic diversity in durum wheat.
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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 | 0.001 |
| 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 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".