Optimal conditions to use Pfu exo- DNA polymerase for highly efficient ligation-mediated polymerase chain reaction protocols
Bibliographic record
Abstract
Ligation-Mediated Polymerase Chain Reaction (LMPCR) is the most sensitive sequencing technique available to map single-stranded DNA breaks at the nucleotide level of resolution using genomic DNA. LMPCR has been adapted to map DNA damage and reveal DNA-protein interactions inside living cells. However, the sequence context (GC content), the global break frequency and the current combination of DNA polymerases used in LMPCR affect the quality of the results. In this study, we developed and optimized an LMPCR protocol adapted for Pyrococcus furiosus exo(-) DNA polymerase (Pfu exo(-)). The relative efficiency of Pfu exo(-) was compared to T7-modified DNA polymerase (Sequenase 2.0) at the primer extension step and to Thermus aquaticus DNA polymerase (Taq) at the PCR amplification step of LMPCR. At all break frequencies tested, Pfu exo(-) proved to be more efficient than Sequenase 2.0. During both primer extension and PCR amplification steps, the ratio of DNA molecules per unit of DNA polymerase was the main determinant of the efficiency of Pfu exo(-), while the efficiency of Taq was less affected by this ratio. Substitution of NaCl for KCl in the PCR reaction buffer of Taq strikingly improved the efficiency of the DNA polymerase. Pfu exo(-) was clearly more efficient than Taq to specifically amplify extremely GC-rich genomic DNA sequences. Our results show that a combination of Pfu exo(-) at the primer extension step and Taq at the PCR amplification step is ideal for in vivo DNA analysis and DNA damage mapping using LMPCR.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.018 |
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".