Temperature and Pressure Shaped the Evolution of Antifreeze Proteins in Polar and Deep Sea Zoarcoid Fishes
Bibliographic record
Abstract
Antifreeze proteins (AFPs) have enabled teleost fishes to repeatedly colonize polar seas. Four AFP types have convergently evolved in several fish lineages. AFPs inhibit ice crystal growth and lower tissue freezing point. In lineages with AFPs, species inhabiting colder environments may possess more AFP copies. Elucidating how differences in AFP copy number evolve is challenging due to the genes' tandem array structure and consequently poor resolution of these repetitive regions. Here, we explore the evolution of type III AFPs (AFP III) in the globally distributed suborder Zoarcoidei, leveraging six new long-read genome assemblies. Zoarcoidei has fewer genomic resources relative to other polar fish clades while it is one of the few groups of fishes adapted to both the Arctic and Southern Oceans. Combining these new assemblies with additional long-read genomes available for Zoarcoidei, we conducted a comprehensive phylogenetic test of AFP III evolution and modeled the effects of thermal habitat and depth on AFP III gene family evolution. We confirm a single origin of AFP III via neofunctionalization of the enzyme sialic acid synthase B. We also show that AFP copy number increased under low temperature but decreased with depth, potentially because pressure lowers freezing point. Associations between the environment and AFP III copy number were driven by duplications of paralogs that were translocated out of the ancestral locus at which AFP III arose. Our results reveal novel environmental effects on AFP evolution and demonstrate the value of high-quality genomic resources for studying how structural genomic variation shapes convergent 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".