Relative Contribution of Sequence and Structure Features to the MRNA Binding of Argonaute/EIF2C-miRNA Complexes and the Degradation of MiRNA Targets
Overview
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How miRNAs recognize their target sites is a puzzle that many experimental and computational studies aimed to solve. Several features, such as perfect pairing of the miRNA seed, additional pairing in the 3' region of the miRNA, relative position in the 3' UTR, and the A/U content of the environment of the putative site, have been found to be relevant. Here we have used a large number of previously published data sets to assess the power that various sequence and structure features have in distinguishing between putative sites that do and those that do not appear to be functional. We found that although different data sets give widely different answers when it comes to ranking the relative importance of these features, the sites inferred from most transcriptomics experiments, as well as from comparative genomics, appear similar at this level. This suggests that miRNA target sites have been selected in evolution on their ability to trigger mRNA degradation. To understand at what step in the miRNA-induced response individual features play a role, we transfected human HEK293 cells with miRNAs and analyzed the association of Argonaute/EIF2C-miRNA complexes with target mRNAs and the degradation of these messages. We found that structural features of the target site are only important for Argonaute/EIF2C binding, while sequence features such as the A/U content of the 3' UTR are important for mRNA degradation.
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Determinants of Functional MicroRNA Targeting.
Hwang H, Chang H, Baek D Mol Cells. 2023; 46(1):21-32.
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Prediction of the miRNA interactome - Established methods and upcoming perspectives.
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