Development and mapping of EST-derived simple sequence repeat markers for hexaploid wheat
Bibliographic record
Abstract
Expressed sequence tags (ESTs) are a valuable source of molecular markers. To enhance the resolution of an existing linkage map and to identify putative functional polymorphic gene loci in hexaploid wheat (Triticum aestivum L.), over 260,000 ESTs from 5 different grass species were analyzed and 5418 SSR-containing sequences were identified. Using sequence similarity analysis, 156 cross-species superclusters and 138 singletons were used to develop primer pairs, which were then tested on the genomic DNA of barley (Hordeum vulgare), maize (Zea mays), rice (Oryza sativa), and wheat. Three-hundred sixty-eight primer pairs produced PCR amplicons from at least one species and 227 primer pairs amplified DNA from two or more species. EST-SSR sequences containing dinucleotide motifs were significantly more polymorphic (74%) than those containing trinucleotides (56%), and polymorphism was similar for markers in both coding and 5' untranslated (UTR) regions. Out of 112 EST-SSR markers, 90 identified 149 loci that were integrated into a reference wheat genetic map. These loci were distributed on 19 of the 21 wheat chromosomes and were clustered in the distal chromosomal regions. Multiple-loci were detected by 39% of the primer pairs. Of the 90 mapped ESTs, putative functions for 22 were identified using BLASTX queries. In addition, 80 EST-SSR markers (104 loci) were located to chromosomes using nullisomic-tetrasomic lines. The enhanced map from this study provides a basis for comparative mapping using orthologous and PCR-based markers and for identification of expressed genes possibly affecting important traits in 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) | 0.001 | 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".