Comparative genomic analyses illuminate the distinct evolution of megabats within Chiroptera
Bibliographic record
Abstract
The revision of the sub-order Microchiroptera is one of the most intriguing outcomes in recent mammalian molecular phylogeny. The unexpected sister-taxon relationship between rhinolophoid microbats and megabats, with the exclusion of other microbats, suggests that megabats arose in a relatively short period of time from a microbat-like ancestor. In order to understand the genetic mechanism underlying adaptive evolution in megabats, we determined the whole-genome sequences of two rousette megabats, Leschenault's rousette (Rousettus leschenaultia) and the Egyptian fruit bat (R. aegyptiacus). The sequences were compared with those of 22 other mammals, including nine bats, available in the database. We identified that megabat genomes are distinct in that they have extremely low activity of SINE retrotranspositions, expansion of two chemosensory gene families, including the trace amine receptor (TAAR) and olfactory receptor (OR), and elevation of the dN/dS ratio in genes for immunity and protein catabolism. The adaptive signatures discovered in the genomes of megabats may provide crucial insight into their distinct evolution, including key processes such as virus resistance, loss of echolocation, and frugivorous feeding.
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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 | 0.001 |
| 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) | 0.002 | 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".