De Novo Gene Evolution of Antifreeze Glycoproteins in Codfishes Revealed by Whole Genome Sequence Data
Bibliographic record
Abstract
New genes can arise through duplication of a pre-existing gene or de novo from non-coding DNA, providing raw material for evolution of new functions in response to a changing environment. A prime example is the independent evolution of antifreeze glycoprotein genes (afgps) in the Arctic codfishes and Antarctic notothenioids to prevent freezing. However, the highly repetitive nature of these genes complicates studies of their organization. In notothenioids, afgps evolved from an extant gene, yet the evolutionary origin of afgps in codfishes is unknown. Here, we demonstrate that afgps in codfishes have evolved de novo from non-coding DNA 13-18 Ma, coinciding with the cooling of the Northern Hemisphere. Using whole-genome sequence data from several codfishes and notothenioids, we find higher copy number of afgp in species exposed to more severe freezing suggesting a gene dosage effect. Notably, antifreeze function is lost in one lineage of codfishes analogous to the afgp losses in non-Antarctic notothenioids. This indicates that selection can eliminate the antifreeze function when freezing is no longer imminent. In addition, we show that evolution of afgp-assisting antifreeze potentiating protein genes (afpps) in notothenioids coincides with origin and lineage-specific losses of afgp. The origin of afgps in codfishes is one of the first examples of an essential gene born from non-coding DNA in a non-model species. Our study underlines the power of comparative genomics to uncover past molecular signatures of genome evolution, and further highlights the impact of de novo gene origin in response to a changing selection regime.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".