Novel regulators of growth identified in the evolution of fin proportion in flying fish
Bibliographic record
Abstract
Abstract Identifying the genetic foundations of trait variation and evolution is challenging as it is often difficult to parse meaningful signals from confounding signatures such as drift and epistasis. However, identification of the genetic loci underlying morphological and physiological traits can be honed through the use of comparative and complementary genetic approaches, whereby shared sets of genes that are repeatedly implicated across large evolutionary time periods as under selection can illuminate important pathways and epistatic relationships that function as novel regulators of trait development. Here we intersect comparative genomic analyses with unbiased mutagenesis screens in distantly related species to define the control of proportional growth, as changes in the size and relative proportions of tissues underlie a large degree of the variant forms seen in nature. Through a phylogenomic analysis of genome-wide variation in 35 species of flying fishes and relatives, we identify genetic signatures in both coding and regulatory regions underlying the convergent evolution of increased paired fin size and aerial gliding behaviors, key innovations for flying fishes and flying halfbeaks. To refine our analysis, we intersected convergent phylogenomic signatures with mutants identified in distantly related zebrafish with altered fin size. Through these paired approaches, we identify a surprising role for an L-type amino acid transporter, lat4a , and the potassium channel, kcnh2a , in the regulation of fin proportion. We show that specific epistatic interaction between these genetic loci in zebrafish closely phenocopies the observed fin proportions of flying fishes. The congruence of experimental and phylogenomic findings point to a conserved, non-canonical signaling interaction that integrates bioelectric cues and amino acid transport in the establishment of relative size in development and evolution.
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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 | 0.001 | 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 | 0.000 |
| 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".