High-Efficiency Thermal Asymmetric InterLaced (HE-TAIL) PCR for Amplification of Ds Transposon Insertion Sites in Barley
Bibliographic record
Abstract
Thermal Asymmetric Interlaced PCR (TAIL PCR) has been used in many different species to isolate flanking sequences adjacent to known sequences. This method has always been a challenge in large genome species, therefore alternative methods have been employed to obtain the flanking sequences. However, these methods are expensive and laborious. Here, we have devised a new and improved method to obtain flanking sequences from barley genome. The proposed method is named as the High-efficiency Thermal Asymmetric Interlaced PCR (HE-TAIL PCR). We have introduced a new 15-mer sequence from the green fluorescent protein (GFP). The new primers efficiently generated transposon flanking sequences in the newly generated barley Ds insertion lines as compared to previously reported hiTAIL PCR by Liu and Chen (2007). Using TAIL PCR, minimal manipulation of genomic DNA is required and large number of samples can be performed at the same time, increasing the efficiency of PCR based amplification of flanking sequences. This HE-TAIL PCR method has effectively introduced the many benefits of TAIL PCR into large genome cereals research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".