Molecular evolution under increasing transposable element burden in Drosophila: A speed limit on the evolutionary arms race
Bibliographic record
Abstract
BACKGROUND: Genome architecture is profoundly influenced by transposable elements (TEs), and natural selection against their harmful effects is a critical factor limiting their spread. Genome defense by the piRNA silencing pathway also plays a crucial role in limiting TE proliferation. How these two forces jointly determine TE abundance is not well understood. To shed light on the nature of factors that predict TE success, we test three distinct hypotheses in the Drosophila genus. First, we determine whether TE abundance and relaxed genome-wide purifying selection on protein sequences are positively correlated. This serves to test the hypothesis that variation in TE abundance in the Drosophila genus can be explained by the strength of natural selection, relative to drift, acting in parallel against mildly deleterious non-synonymous mutations. Second, we test whether increasing TE abundance is correlated with an increased rate of amino-acid evolution in genes encoding the piRNA machinery, as might be predicted by an evolutionary arms race model. Third, we test whether increasing TE abundance is correlated with greater codon bias in genes of the piRNA machinery. This is predicted if increasing TE abundance selects for increased efficiency in the machinery of genome defense. RESULTS: Surprisingly, we find neither of the first two hypotheses to be true. Specifically, we found that genome-wide levels of purifying selection, measured by the ratio of non-synonymous to synonymous substitution rates (ω), were greater in species with greater TE abundance. In addition, species with greater TE abundance have greater levels of purifying selection in the piRNA machinery. In contrast, it appears that increasing TE abundance has primarily driven adaptation in the piRNA machinery by increasing codon bias. CONCLUSIONS: These results indicate that within the Drosophila genus, a historically reduced strength of selection relative to drift is unlikely to explain patterns of increased TE success across species. Other factors, such as ecological exposure, are likely to contribute to variation in TE abundances within species. Furthermore, constraints on the piRNA machinery may temper the evolutionary arms race that would drive increasing rates of evolution at the amino acid level. In the face of these constraints, selection may act primarily by improving the translational efficiency of the machinery of genome defense through efficient codon usage.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".