EST-SSR markers derived from an elite barley cultivar (<i>Hordeum vulgare</i>L. ‘Morex’): polymorphism and genetic marker potential
Bibliographic record
Abstract
Microsatellites or simple sequence repeats have become the markers of choice for marker-assisted selection because of their low template DNA requirement, high reproducibility, and high level of polymorphism. This study investigated a new set of barley (Hordeum vulgare L.) EST-derived SSR markers designed to target gene sequences expressed during grain development, as they are more likely to be important in determining grain quality. The EST sequences (HVSMEh and HVSMEi) were derived from cDNA libraries of the elite six-rowed cultivar Morex, made from spikes harvested at 5 to 45 days after pollination. Approximately half of the 110 SSR markers derived from the ESTs were polymorphic in a panel of 8 diverse barley genotypes, with PIC values between 0.19 and 0.79. Twenty of the new markers were mapped to chromosomal locations using 2 doubled haploid populations. To demonstrate marker potential, quantitative trait locus (QTL) analyses were carried out with phenotypic data on wort beta-glucan content and beta-glucanase activity, two traits with a long history of genetic studies. Most of the EST-SSR markers mapped to within 10 cM of the cellulose synthase (HvCesA) and cellulose synthase-like (HvCslF) genes, which provides highly informative functional markers for tracking these genes in breeding programs. It was also observed that on any given chromosome, the QTL for beta-glucan content and beta-glucanase activity were rarely coincident but tended to occur in adjacent intervals along chromosomal regions, which agreed with their independent genetic basis; the adjacent localization may be important for coordination of cell wall degradation during germination and malting.
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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 | 0.001 |
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".