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Updated: Jan 6, 2026

mirMachine: A One-Stop Shop for Plant miRNA Annotation
Published on: May 1, 2021
A robust model for quantitative prediction of the silencing efficacy of wild-type and A-to-I edited miRNAs
Shen Tian1, Goro Terai2, Yoshiaki Kobayashi1
1Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, Japan.
Abstract:
MicroRNAs (miRNAs) are small non-coding RNAs that play essential roles in the regulation of gene function by a mechanism known as RNA silencing. In a previous study, we revealed that miRNA-mediated silencing efficacy is correlated with the combinatorial thermodynamic properties of the miRNA seed-target mRNA duplex and the 5´-terminus of the miRNA duplex, which can be predicted using 'miScore'. In this study, a robust refined-miScore was developed by integrating the thermodynamic properties of various miRNA secondary structures and the latest thermodynamic parameters of wobble base-pairing, including newly established parameters for I:C base pairing. Through repeated random sampling and machine learning, refined-miScore models calculated with either melting temperature (Tm) or free energy change (ΔG) values were successfully built and validated in both wild-type and adenosine-to-inosine edited miRNAs. In addition to the previously reported contribution of the seed-target duplex and 5´-terminus region, the refined-miScore suggests that the central and 3´-terminus regions of the miRNA duplex also play a role in the thermodynamic regulation of miRNA-mediated silencing efficacy.
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