Defeating<i>numts</i>: Semi-pure mitochondrial DNA from eggs and simple purification methods for field-collected wildlife tissues
Bibliographic record
Abstract
Mitochondrial DNA (mtDNA) continues to play a pivotal role in phylogeographic, phylogenetic, and population genetic studies. PCR amplification with mitochondrial primers often yields ambiguous sequences, in part because of the co-amplification of nuclear copies of mitochondrial genes (numts) and true mitochondrial heteroplasmy arising from mutations, hybridization with paternal leakage, gene duplications, and recombination. Failing to detect numts or to distinguish the origin of such homologous sequences results in the incorrect interpretation of data. However, few studies obtain purified mtDNA to confirm the mitochondrial origin of the first reference sequences for a species. Here, we demonstrate the importance and ease of obtaining semi-pure mtDNA from wildlife tissues, preserved under various typical field conditions, and investigate the success of 3 commercial extraction kits, cesium-chloride gradient mtDNA purification, long-template PCR amplification, cloning, and more species-specific degenerate primers. Using more detailed avian examples, we illustrate that unfertilized or undeveloped eggs provide the purest sources of mtDNA; that kits provide an alternative to cesium-chloride gradient methods; and that long-template PCR, cloning, and degenerate primers cannot be used to produce reliable mitochondrial reference sequences, but can be powerful tools when used in conjunction with purified mtDNA stocks to distinguish numts from true heteroplasmy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".