Rapid Increase in frequency of gene copy-number variants during experimental evolution in Caenorhabditis elegans
Bibliographic record
Abstract
BACKGROUND: Gene copy-number variation (CNVs), which provides the raw material for the evolution of novel genes, is widespread in natural populations. We investigated whether CNVs constitute a common mechanism of genetic change during adaptation in experimental Caenorhabditis elegans populations. Outcrossing C. elegans populations with low fitness were evolved for >200 generations. The frequencies of CNVs in these populations were analyzed by oligonucleotide array comparative genome hybridization, quantitative PCR, PCR, DNA sequencing across breakpoints, and single-worm PCR. RESULTS: Multiple duplications and deletions rose to intermediate or high frequencies in independent populations. Several lines of evidence suggest that these changes were adaptive: (i) copy-number changes reached high frequency or were fixed in a short time, (ii) many independent populations harbored CNVs spanning the same genes, and (iii) larger average size of CNVs in adapting populations relative to spontaneous CNVs. The latter is expected if larger CNVs are more likely to encompass genes under selection for a change in gene dosage. Several convergent CNVs originated in populations descended from different low fitness ancestors as well as high fitness controls. CONCLUSIONS: We show that gene copy-number changes are a common class of adaptive genetic change. Due to the high rates of origin of spontaneous duplications and deletions, copy-number changes containing the same genes arose readily in independent populations. Duplications that reached high frequencies in these adapting populations were significantly larger in span. Many convergent CNVs may be general adaptations to laboratory conditions. These results demonstrate the great potential borne by CNVs for evolutionary adaptation.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".