Naturally occurring variations in sequence length creates microRNA isoforms that differ in argonaute effector complex specificity
Bibliographic record
Abstract
BACKGROUND: Micro(mi)RNAs are short RNA sequences, ranging from 16 to 35 nucleotides (miRBase; http://www.mirbase.org). The majority of the identified sequences are 21 or 22 nucleotides in length. Despite the range of sequence lengths for different miRNAs, individual miRNAs were thought to have a specific sequence of a particular length. A recent report describing a longer variant of a previously identified miRNA in Arabidopsis thaliana prompted this investigation for variations in the length of other miRNAs. RESULTS: In this paper, we demonstrate that a fifth of annotated A. thaliana miRNAs recorded in miRBase V.14 have stable miRNA isoforms that are one or two nucleotides longer than their respective recorded miRNA. Further, we demonstrate that miRNA isoforms are co-expressed and often show differential argonaute complex association. We postulate that these extensions are caused by differential cleavage of the parent precursor miRNA. CONCLUSIONS: Our systematic analysis of A. thaliana miRNAs reveals that miRNA length isoforms are relatively common. This finding not only has implications for miRBase and miRNA annotation, but also extends to miRNA validation experiments and miRNA localization studies. Further, we predict that miRNA isoforms are present in other plant species also.
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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 | 0.000 | 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) | 0.001 | 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".