Isolation and characterization of SSR sequences from the genome and TAC clones of common wheat using the PCR technique
Bibliographic record
Abstract
We have developed the 2-step PCR method, a kind of suppression PCR procedure, to isolate simple sequence repeats (SSRs) from common wheat (Triticum aestivum L.) in a more convenient manner. This system requires neither genomic library screening nor the SSR-enrichment procedure. As a result, we designed 131 primer pairs based on isolated SSRs from not only genomic DNA, but also transformation-competent artificial chromosome (TAC) clones. It has been demonstrated that 34 of the 131 SSR markers developed were polymorphic among 8 wheat lines. Four of 34 polymorphic SSR markers were derived from TAC clones, indicating that this method could be applied to the targeted development of unique SSR markers in large genomic DNA libraries such as those composed of bacterial artificial chromosomes (BACs). A considerable number of isolated SSR clones had similarities with part of several long terminal repeats of retrotransposons (LTR-RTs) identified in various Triticeae genome sequences. Most of those SSRs showed smear amplification profiles, suggesting that a considerable number of dysfunctional SSRs originating from repetitive DNA components, especially LTR-RTs, might exist in the common wheat genome.
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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 | 0.001 |
| 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 | 0.001 |
| 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".