Origin of an antifreeze protein gene in response to Cenozoic climate change
Bibliographic record
Abstract
Antifreeze proteins (AFPs) inhibit ice growth within fish and protect them from freezing in icy seawater. Alanine-rich, alpha-helical AFPs (type I) have independently (convergently) evolved in four branches of fishes, one of which is a subsection of the righteye flounders. The origin of this gene family has been elucidated by sequencing two loci from a starry flounder, Platichthys stellatus, collected off Vancouver Island, British Columbia. The first locus had two alleles that demonstrated the plasticity of the AFP gene family, one encoding 33 AFPs and the other allele only four. In the closely related Pacific halibut, this locus encodes multiple Gig2 (antiviral) proteins, but in the starry flounder, the Gig2 genes were found at a second locus due to a lineage-specific duplication event. An ancestral Gig2 gave rise to a 3-kDa "skin" AFP isoform, encoding three Ala-rich 11-a.a. repeats, that is expressed in skin and other peripheral tissues. Subsequent gene duplications, followed by internal duplications of the 11 a.a. repeat and the gain of a signal sequence, gave rise to circulating AFP isoforms. One of these, the "hyperactive" 32-kDa Maxi likely underwent a contraction to a shorter 3.3-kDa "liver" isoform. Present day starry flounders found in Pacific Rim coastal waters from California to Alaska show a positive correlation between latitude and AFP gene dosage, with the shorter allele being more prevalent at lower latitudes. This study conclusively demonstrates that the flounder AFP arose from the Gig2 gene, so it is evolutionarily unrelated to the three other classes of type I AFPs from non-flounders. Additionally, this gene arose and underwent amplification coincident with the onset of ocean cooling during the Cenozoic ice ages.
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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 | 0.000 |
| 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 | 0.000 |
| 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".