A deeper view into the significance of simple sequence repeats in pre-miRNAs provides clues for its possible roles in determining the function of microRNAs
Bibliographic record
Abstract
BACKGROUND: The central tenet of 'genome content' has been that the 'non-coding' parts are highly enriched with 'microsatellites' or 'Simple Sequence Repeats' (SSRs). We presume that the presence and change in number of repeat unit (n) of SSRs in different genomic locations may or may not become beneficial, depending on the position of SSRs in a gene. Very few studies have looked into the existence of SSRs in the hair-pin precursors of miRNAs (pre-miRNAs). The interplay between SSRs and miRNAs is not yet clearly understood. RESULTS: Considering the potential significance of SSRs in pre-miRNAs, we analysed the miRNA hair-pin precursors of 171 organisms, which revealed a noticeable (29.8%) existence of SSRs in their pre-miRNAs. The maintenance of SSRs in pre-miRNAs even in the complex, highly evolved phyla like Chordata and Magnoliophyta shed light upon its diverse functions. Putative effects of SSRs in either regulating the biogenesis or function of miRNAs were more underlined based on computational and experimental analysis. A preliminary computational analysis to explore the relevance of such SSRs maintained in pre-miRNA sequences led to the detection of splicing regulatory elements (SREs) either in or near to the SSRs. The absence of SSRs correspondingly decreased the detection of SREs. CONCLUSION: The present study is the first implication for the possible involvement of SSRs in shaping the SREs to undergo Alternative Splicing events to produce miRNA isoforms in accordance with different stress environments. This part of work well demonstrates the importance of studying such consistently maintained SSRs residing in pre-miRNAs and can enhance more and more research towards deciphering the exact function of SSRs in the near future.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".