Unveiling the functional and evolutionary landscape of RNA editing in chicken using genomics and transcriptomics
Bibliographic record
Abstract
The evolutionary and functional features of RNA editing are well studied in mammals, cephalopods, and insects, but not in birds. Here, we integrated transcriptomic and whole-genomic analyses to exhaustively characterize the expansive repertoire of adenosine-to-inosine (A-to-I) RNA editing sites (RESs) in the chicken. In addition, we investigated the evolutionary status of the chicken editome as a potential mechanism of domestication. We detected the lowest editing level in the liver of chickens, compared to muscles in humans, and found higher editing activity and specificity in the brain than in non-neural tissues, consistent with the brain’s functional complexity. To a certain extent, specific editing activity may account for the specific functions of tissues. Our results also revealed that sequences critical to RES secondary structures remained conserved within avian evolution. Furthermore, the RNA editome was shaped by purifying selection during chicken domestication and most RESs may have served as a selection pool for a few functional RESs involved in chicken domestication, including evolution of nervous and immune systems. Regulation of RNA editing in chickens by adenosine deaminase acting on RNA (ADAR) enzymes may be affected by non-ADAR factors whose expression levels changed widely after <i>ADAR</i> knockdown. Collectively, we provide comprehensive lists of candidate RESs and non-ADAR-editing regulators in the chicken, thus contributing to our current understanding of the functions and evolution of RNA editing in animals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".