Genotyping single nucleotide polymorphisms in barley by tetra-primer ARMS–PCR
Bibliographic record
Abstract
Single nucleotide polymorphisms (SNPs) are the most abundant form of DNA polymorphism. These polymorphisms can be used in plants as simple genetic markers for many breeding applications, for population studies, and for germplasm fingerprinting. The great increase in the available DNA sequences in the databases has made it possible to identify SNPs by "database mining", and the single most important factor preventing their widespread use appears to be the genotyping cost. Many genotyping platforms rely on the use of sophisticated, automated equipment coupled to costly chemistry and detection systems. A simple and economical method involving a single PCR is reported here for barley SNP genotyping. Using the tetra-primer ARMS-PCR procedure, we have been able to assay unambiguously five SNPs in a set of 132 varieties of cultivated barley. The results show the reliability of this technique and its potential for use in low- to moderate-throughput situations; the association of agronomically important traits is discussed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".