RNA Polyadenylation Sites on the Genomes of Microorganisms, Animals, and Plants
Bibliographic record
Abstract
Pre-messenger RNA (mRNA) 3'-end cleavage and subsequent polyadenylation strongly regulate gene expression. In comparison with the upstream or downstream motifs, relatively little is known about the feature differences of polyadenylation [poly(A)] sites among major kingdoms. We suspect that the precise poly(A) sites are very selective, and we therefore mapped mRNA poly(A) sites on complete and nearly complete genomes using mRNA sequences available in the National Center for Biotechnology Information (NCBI) Nucleotide database. In this paper, we describe the mRNA nucleotide [i.e., the poly(A) tail attachment position] that is directly in attachment with the poly(A) tail and the pre-mRNA nucleotide [i.e., the poly(A) tail starting position] that corresponds to the first adenosine of the poly(A) tail in the 29 most-mapped species (2 fungi, 2 protists, 18 animals, and 7 plants). The most representative pre-mRNA dinucleotides covering these two positions were UA, CA, and GA in 17, 10, and 2 of the species, respectively. The pre-mRNA nucleotide at the poly(A) tail starting position was typically an adenosine [i.e., A-type poly(A) sites], sometimes a uridine, and occasionally a cytidine or guanosine. The order was U>C>G at the attachment position but A>>U>C≥G at the starting position. However, in comparison with the mRNA nucleotide composition (base composition), the poly(A) tail attachment position selected C over U in plants and both C and G over U in animals, in both A-type and non-A-type poly(A) sites. Animals, dicot plants, and monocot plants had clear differences in C/G ratios at the poly(A) tail attachment position of the non-A-type poly(A) sites. This study of poly(A) site evolution indicated that the two positions within poly(A) sites had distinct nucleotide compositions and were different among kingdoms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".