Haplodiploidy accelerates mitogenome evolution in insects
Bibliographic record
Abstract
Rates of mitogenome evolution differ among animal lineages, and this variation has been linked to life history, ecological traits, and— potentially—to sex-determination system. Insects are a strong model for examining the latter factor because haplodiploidy (HD) has evolved on multiple occasions from a diplodiploid (DD) ancestral state. We tested for rate differences between DD and HD taxa by examining sequence change in a sentinel segment of the mitogenome, the 658 bp barcode region of the cytochrome c oxidase I (COI) gene. Specifically, we investigated if amino acid substitutions and indels are more frequent in HD than DD lineages by inspecting COI sequences from over 86,000 BINs (a species proxy) representing 783 insect families and 26 orders. Among them, ten lineages, varying in rank from tribe to order, are HD. Our analysis, which accounts for phylogeny, indicates that HD lineages have higher rates (1.7×) of amino acid substitution, higher Ka/Ks (3.5×), and far more indels than DD taxa. While our results demonstrate that HD accelerates mitogenome evolution, future work needs to clarify its mechanistic basis. We hypothesize that HD facilitates positive selection for mitochondrial mutations which encode proteins that interact with nuclear gene products. Such coevolutionary interactions should be facilitated because recessive mutations in the nuclear genome are fully exposed to selection in males of HD but not DD lineages.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".