Abstract
RNA secondary structures are key regulators of long-range pre-messenger RNA (mRNA) alternative splicing, yet the rules governing these structures and their effects on splice site selection are not well understood. We uncover a direct role for microRNAs in controlling alternative splicing by remodeling splice-relevant stem-loop structures in pre-mRNAs, a mechanism we term MicroRNA-mediated Obstruction of Stem-loop Alternative Splicing (MIMOSAS). Using a curated set of Drosophila genes containing conserved complementary regions ("boxes"), we developed a bioinformatic pipeline that integrates genome-wide structural prediction with energetic modeling to identify microRNAs that disrupt long-range stem-loop structures associated with alternative donor/acceptor usage or putative polyadenylation sites. We experimentally validated these predictions in vivo in Drosophila and in mammalian cell lines incorporating several split fluorescent protein-based splicing reporters. Our data show that microRNAs bidirectionally modulate splice isoform ratios by engaging structured pre-mRNA regions in an AGO1-dependent process. MIMOSAS-active microRNAs often use noncanonical pairing and optimize local folding energies rather than strict seed matches, underscoring the importance of RNA secondary structure in functional specificity. These findings broaden microRNA function beyond canonical silencing or translation repression and reveal a structurally grounded, potentially widespread layer of alternative splicing regulation with implications for RNA-based therapies.
| Original language | English |
|---|---|
| Article number | gkag356 |
| Journal | Nucleic Acids Research |
| Volume | 54 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 24 Apr 2026 |
Funding
We thank German Farinas Perez and Miroslav Kubat for their input in the early stage of the project, and Zoraida Diaz-Perez for technical assistance. We also thank Dr John Dezek for critically reading the manuscript.Author contributions: Rong Grace Zhai (Conceptualization [lead], Funding acquisition [lead], Investigation [equal], Methodology [equal], Project administration [lead], Supervision [lead], Writing – original draft [equal], Writing – review & editing [equal]), Kai Ruan (Formal analysis [lead], Investigation [lead], Methodology [lead], Writing – original draft [equal], Writing – review & editing [equal]), Jiaqi Liu (Formal analysis [equal], Investigation [equal], Methodology [equal]), Melanie Xia (Formal analysis [equal], Investigation [equal], Methodology [equal]), Federica Bertolotti (Investigation [supporting], Methodology [supporting]), Ivo L. Hofacker (Investigation [equal], Methodology [equal]), and Stefan Wuchty (Conceptualization [supporting], Funding acquisition [supporting], Investigation [equal], Methodology [equal], Project administration [supporting], Supervision [supporting], Writing – original draft [equal], Writing – review & editing [equal]) This work was supported by National Institutes of Health grants R61/R33AT010408 to R.G.Z. Funding to pay the Open Access publication charges for this article was provided by R61/R33AT010408. This work was supported by National Institutes of Health grants R61/R33AT010408 to R.G.Z. Funding to pay the Open Access publication charges for this article was provided by R61/R33AT010408.
| Funders | Funder number |
|---|---|
| National Institutes of Health (NIH) | R61/R33AT010408 |
Austrian Fields of Science 2012
- 106005 Bioinformatics
- 106002 Biochemistry
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