Evolutionary and Functional Novelty of Pancreatic Ribonuclease: a Study of Musteloidea (order Carnivora)
Bibliographic record
Abstract
Pancreatic ribonuclease (RNASE1) is a digestive enzyme that has been one of the key models in studies of evolutionary innovation and functional diversification. It has been believed that the RNASE1 gene duplications are correlated with the plant-feeding adaptation of foregut-fermenting herbivores. Here, we characterized RNASE1 genes from Caniformia, which has a simple digestive system and lacks microbial digestion typical of herbivores, in an unprecedented scope based on both gene sequence and tissue expression analyses. Remarkably, the results yielded new hypotheses regarding the evolution and the function of Caniformia RNASE1 genes. Four independent gene duplication events in the families of superfamily Musteloidea, including Procyonidae, Ailuridae, Mephitidae and Mustelidae, were recovered, rejecting previous Mustelidae-specific duplication hypothesis, but supporting Musteloidea duplication hypothesis. Moreover, our analyses revealed pronounced differences among the RNASE1 gene copies regarding their selection pressures, pI values and tissue expression patterns, suggesting the differences in their physiological functions. Notably, the expression analyses detected the transcription of a RNASE1 pseudogene in several tissues, raising the possibility that pseudogenes are also a potential source during the RNase functional diversification. In sum, the present work demonstrated a far more complex and intriguing evolutionary pattern and functional diversity of mammalian ribonuclease than previously thought.
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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) | 0.001 | 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".