microRNAs (miRNAs) are important post-transcriptional regulators that activate silencing mechanisms by annealing to mRNA transcripts. While plant miRNAs match their targets with nearly-full complementarity leading to mRNA cleavage, miRNAs in most animals require only a short sequence called 'seed' to inhibit target translation. Recent findings showed that miRNAs in cnidarians, early-branching metazoans, act similarly to plant miRNAs, by exhibiting full complementarity and target cleavage; however, it remained unknown if seed-based regulation was possible in cnidarians. Here, we investigate the miRNA-target complementarity requirements for miRNA activity in the cnidarian Nematostella vectensis. We show that bilaterian-like complementarity of seed-only or seed and supplementary 3' matches are insufficient for miRNA-mediated knockdown. Furthermore, miRNA-target mismatches in the cleavage site decrease knockdown efficiency. Finally, miRNA silencing of a target with three seed binding sites in the 3' untranslated region that mimics typical miRNA targeting was repressed in zebrafish but not in Nematostella and another cnidarian, Hydractinia symbiolongicarpus. Altogether, these results unravel striking similarities between plant and cnidarian miRNAs supporting a possible common evolutionary origin of miRNAs in plants and animals.
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http://dx.doi.org/10.1038/s44319-024-00350-z | DOI Listing |
EMBO Rep
January 2025
Department of Ecology, Evolution and Behavior, Alexander Silberman Institute of Life Sciences, Faculty of Science, Hebrew University of Jerusalem, Jerusalem, 9190401, Israel.
microRNAs (miRNAs) are important post-transcriptional regulators that activate silencing mechanisms by annealing to mRNA transcripts. While plant miRNAs match their targets with nearly-full complementarity leading to mRNA cleavage, miRNAs in most animals require only a short sequence called 'seed' to inhibit target translation. Recent findings showed that miRNAs in cnidarians, early-branching metazoans, act similarly to plant miRNAs, by exhibiting full complementarity and target cleavage; however, it remained unknown if seed-based regulation was possible in cnidarians.
View Article and Find Full Text PDFFront Plant Sci
September 2024
Department of Biotechnology, Deen Dayal Upadhyaya Gorakhpur University, Gorakhpur, Uttar Pradesh, India.
Plant Cell Physiol
June 2023
Division of Plant Science, Research School of Biology, The Australian National University, Canberra, ACT 2601, Australia.
In plants, microRNA (miRNA)-target interactions (MTIs) require high complementarity, a feature from which bioinformatic programs have predicted numerous and diverse targets for any given miRNA, promoting the idea of complex miRNA networks. Opposing this is a hypothesis of constrained miRNA specificity, in which functional MTIs are restricted to the few targets whose required expression output is compatible with the expression of the miRNA. To explore these opposing views, the bioinformatic pipeline Targets Ranked Using Experimental Evidence was applied to strongly conserved miRNAs to identity their high-evidence (HE) targets across species.
View Article and Find Full Text PDFComput Biol Chem
October 2022
Inter-institutional Grad Program in Bioinformatics, University of Sao Paulo, Sao Paulo, SP, Brazil; School of Arts, Sciences and Humanities, University of Sao Paulo, Sao Paulo, SP, Brazil.
MicroRNAs (miRNAs) are non-coding RNAs containing 19-26 nucleotides, and they directly regulate the translation of mRNAs by binding to them. MiRNAs participate in various physiological processes and are associated with the development of diseases, such as cancer. Therefore, understanding miRNAs regulation on targets is crucial for understanding the mechanisms of diseases and for obtaining a more suitable treatment.
View Article and Find Full Text PDFPlant J
June 2022
Division of Plant Science, Research School of Biology, The Australian National University, Canberra, ACT, 2601, Australia.
Central to plant microRNA (miRNA) biology is the identification of functional miRNA-target interactions (MTIs). However, the complementarity basis of bioinformatic target prediction results in mostly false positives, and the degree of complementarity does not equate with regulation. Here, we develop a bioinformatic workflow named TRUEE (Targets Ranked Using Experimental Evidence) that ranks MTIs on the extent to which they are subjected to miRNA-mediated cleavage.
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