Improving the performance of true single molecule sequencing for ancient DNA
Bibliographic record
Abstract
BACKGROUND: Second-generation sequencing technologies have revolutionized our ability to recover genetic information from the past, allowing the characterization of the first complete genomes from past individuals and extinct species. Recently, third generation Helicos sequencing platforms, which perform true Single-Molecule DNA Sequencing (tSMS), have shown great potential for sequencing DNA molecules from Pleistocene fossils. Here, we aim at improving even further the performance of tSMS for ancient DNA by testing two novel tSMS template preparation methods for Pleistocene bone fossils, namely oligonucleotide spiking and treatment with DNA phosphatase. RESULTS: We found that a significantly larger fraction of the horse genome could be covered following oligonucleotide spiking however not reproducibly and at the cost of extra post-sequencing filtering procedures and skewed %GC content. In contrast, we showed that treating ancient DNA extracts with DNA phosphatase improved the amount of endogenous sequence information recovered per sequencing channel by up to 3.3-fold, while still providing molecular signatures of endogenous ancient DNA damage, including cytosine deamination and fragmentation by depurination. Additionally, we confirmed the existence of molecular preservation niches in large bone crystals from which DNA could be preferentially extracted. CONCLUSIONS: We propose DNA phosphatase treatment as a mechanism to increase sequence coverage of ancient genomes when using Helicos tSMS as a sequencing platform. Together with mild denaturation temperatures that favor access to endogenous ancient templates over modern DNA contaminants, this simple preparation procedure can improve overall Helicos tSMS performance when damaged DNA templates are targeted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 0.000 |
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 teacher head, 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".