Palindromic Sequence Artifacts Generated during Next Generation Sequencing Library Preparation from Historic and Ancient DNA
Bibliographic record
Abstract
Degradation-specific processes and variation in laboratory protocols can bias the DNA sequence composition from samples of ancient or historic origin. Here, we identify a novel artifact in sequences from historic samples of Atlantic cod (Gadus morhua), which forms interrupted palindromes consisting of reverse complementary sequence at the 5' and 3'-ends of sequencing reads. The palindromic sequences themselves have specific properties - the bases at the 5'-end align well to the reference genome, whereas extensive misalignments exists among the bases at the terminal 3'-end. The terminal 3' bases are artificial extensions likely caused by the occurrence of hairpin loops in single stranded DNA (ssDNA), which can be ligated and amplified in particular library creation protocols. We propose that such hairpin loops allow the inclusion of erroneous nucleotides, specifically at the 3'-end of DNA strands, with the 5'-end of the same strand providing the template. We also find these palindromes in previously published ancient DNA (aDNA) datasets, albeit at varying and substantially lower frequencies. This artifact can negatively affect the yield of endogenous DNA in these types of samples and introduces sequence bias.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".