Interrogating 1000 Insect Genomes for NUMTs: A Risk Assessment for Species Scans
Bibliographic record
Abstract
The nuclear genomes of most animal species include segments of the mitogenome, but the count of these NUMTs varies greatly. This study examines the incidence of NUMTs derived from a 658 bp region of the cytochrome c oxidase I (COI) gene as a proxy for other coding regions of the mitochondrial genome. Analysis focuses on the most diverse group of terrestrial organisms, insects, because COI-based identification systems play a key role in clarifying their diversity, an essential antecedent to genome sequencing. Nearly 10,000 COI NUMTs ≥ 100 bp were detected in the genomes of 1,002 insect species with a range from 0–443. NUMT counts were similar among congeners, but differences among genera in a family were often large with genome size explaining 56% of the mitogenome-wide variation in counts. While many of these NUMTs possessed an indel or premature stop codon allowing their exclusion, the others could complicate species diagnosis as they averaged 10.1% divergence from their mitochondrial homologue. The count of NUMTs varies widely among insect lineages, peaking in groups that employ direct development or incomplete metamorphosis. They can raise the apparent species count by up to 22% when the 658 bp barcode region is examined while shorter targets (300 bp, 150 bp) elevate exposure (58–111%) to “ghost” species. As a result, NUMTs represent a particular complication for protocols (e.g., eDNA, metabarcoding) which employ short amplicons for biodiversity assessments.
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 | 0.021 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".