Cloning, expression, and bioinformatics analysis of a putative pigeon retinoid acid-inducible gene-I
Bibliographic record
Abstract
Retinoid acid-inducible gene-I (RIG-I) is a major cytoplasmic RNA sensor, playing an essential role in detecting viral RNA and triggering antiviral innate immune responses. The objective of the present study was to characterize the structure and expression of the RIG-I gene in pigeons. The pigeon RIG-I (piRIG-I) was cloned from splenic lymphocytes of pigeons using reverse transcription polymerase chain reaction (RT-PCR) and rapid amplification of cDNA ends. The cDNA of piRIG-I contains a 147 bp 5′-untranslated regions (UTRs), a 2787 bp open reading frame, and 2962 bp 3′-UTRs. Based on this sequence, the encoded piRIG-I protein is predicted to consist of 928 amino acids, and it has conserved domains typical of RIG-I-like receptors (RLRs) including two tandem arranged N-terminal caspase recruitment domains, a domain with the signature of DExD/H box helicase (helicase domain), and a C-terminal repression domain similar to finch RIG-I, duck RIG-I, goose RIG-I, human RIG-I, and mouse RIG-I. The piRIG-I shows 82.1%, 78.6%, and 78.2% amino acid sequence identity with previously described finch RIG-I, duck RIG-I, and goose RIG-I, respectively, and 49.7%–53.8% sequence identity with mammalian homologs. Quantitative RT-PCR (qRT-PCR) analysis indicated that the piRIG-I mRNA is scarcely detected in healthy tissues, and it is strongly expressed in the thymus gland, kidney, spleen, and bursa of Fabricius. These findings lay the foundation for further research on the function and mechanism of avian RIG-I in innate immune response related to vaccinations and infectious diseases in the pigeon.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".