New insights from old bones: DNA preservation and degradation in permafrost preserved mammoth remains
Bibliographic record
Abstract
Despite being plagued by heavily degraded DNA in palaeontological remains, most studies addressing the state of DNA degradation have been limited to types of damage which do not pose a hindrance to Taq polymerase during PCR. Application of serial qPCR to the two fractions obtained during extraction (demineralization and protein digest) from six permafrost mammoth bones and one partially degraded modern elephant bone has enabled further insight into the changes which endogenous DNA is subjected to during diagenesis. We show here that both fractions exhibit individual qualities in terms of the prevailing type of DNA (i.e. mitochondrial versus nuclear DNA) as well as the extent of damage, and in addition observed a highly variable ratio of mitochondrial to nuclear DNA among the six mammoth samples. While there is evidence suggesting that mitochondrial DNA is better preserved than nuclear DNA in ancient permafrost samples, we find the initial DNA concentration in the bone tissue to be as relevant for the total accessible mitochondrial DNA as the extent of DNA degradation post-mortem. We also evaluate the general applicability of indirect measures of preservation such as amino-acid racemization, bone crystallinity index and thermal age to these exceptionally well-preserved samples.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".