Parallel Evolution of Auditory Genes for Echolocation in Bats and Toothed Whales
Bibliographic record
Abstract
The ability of bats and toothed whales to echolocate is a remarkable case of convergent evolution. Previous genetic studies have documented parallel evolution of nucleotide sequences in Prestin and KCNQ4, both of which are associated with voltage motility during the cochlear amplification of signals. Echolocation involves complex mechanisms. The most important factors include cochlear amplification, nerve transmission, and signal re-coding. Herein, we screen three genes that play different roles in this auditory system. Cadherin 23 (Cdh23) and its ligand, protocadherin 15 (Pcdh15), are essential for bundling motility in the sensory hair. Otoferlin (Otof) responds to nerve signal transmission in the auditory inner hair cell. Signals of parallel evolution occur in all three genes in the three groups of echolocators--two groups of bats (Yangochiroptera and Rhinolophoidea) plus the dolphin. Significant signals of positive selection also occur in Cdh23 in the Rhinolophoidea and dolphin, and Pcdh15 in Yangochiroptera. In addition, adult echolocating bats have higher levels of Otof expression in the auditory cortex than do their embryos and non-echolocation bats. Cdh23 and Pcdh15 encode the upper and lower parts of tip-links, and both genes show signals of convergent evolution and positive selection in echolocators, implying that they may co-evolve to optimize cochlear amplification. Convergent evolution and expression patterns of Otof suggest the potential role of nerve and brain in echolocation. Our synthesis of gene sequence and gene expression analyses reveals that positive selection, parallel evolution, and perhaps co-evolution and gene expression affect multiple hearing genes that play different roles in audition, including voltage and bundle motility in cochlear amplification, nerve transmission, and brain function.
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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 | 0.000 |
| 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".