Widespread Recurrent Evolution of Genomic Features
Bibliographic record
Abstract
The recent explosion of genome sequences from all major phylogenetic groups has unveiled an unexpected wealth of cases of recurrent evolution of strikingly similar genomic features in different lineages. Here, we review the diverse known types of recurrent evolution in eukaryotic genomes, with a special focus on metazoans, ranging from reductive genome evolution to origins of splice-leader trans-splicing, from tandem exon duplications to gene family expansions. We first propose a general classification scheme for evolutionary recurrence at the genomic level, based on the type of driving force-mutation or selection-and the environmental and genomic circumstances underlying these forces. We then discuss various cases of recurrent genomic evolution under this scheme. Finally, we provide a broader context for repeated genomic evolution, including the unique relationship of genomic recurrence with the genotype-phenotype map, and the ways in which the study of recurrent genomic evolution can be used to understand fundamental evolutionary processes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".