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Rapid Generation of MicroRNA Sponges for MicroRNA Inhibition

Overview of attention for article published in PLOS ONE, January 2012
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Title
Rapid Generation of MicroRNA Sponges for MicroRNA Inhibition
Published in
PLOS ONE, January 2012
DOI 10.1371/journal.pone.0029275
Pubmed ID
Authors

Joost Kluiver, Johan H. Gibcus, Chris Hettinga, Annelies Adema, Mareike K. S. Richter, Nancy Halsema, Izabella Slezak-Prochazka, Ye Ding, Bart-Jan Kroesen, Anke van den Berg

Abstract

MicroRNA (miRNA) sponges are transcripts with repeated miRNA antisense sequences that can sequester miRNAs from endogenous targets. MiRNA sponges are valuable tools for miRNA loss-of-function studies both in vitro and in vivo. We developed a fast and flexible method to generate miRNA sponges and tested their efficiency in various assays. Using a single directional ligation reaction we generated sponges with 10 or more miRNA binding sites. Luciferase and AGO2-immuno precipitation (IP) assays confirmed effective binding of the miRNAs to the sponges. Using a GFP competition assay we showed that miR-19 sponges with central mismatches in the miRNA binding sites are efficient miRNA inhibitors while sponges with perfect antisense binding sites are not. Quantification of miRNA sponge levels suggests that this is at least in part due to degradation of the perfect antisense sponge transcripts. Finally, we provide evidence that combined inhibition of miRNAs of the miR-17∼92 cluster results in a more effective growth inhibition as compared to inhibition of individual miRNAs. In conclusion, we describe and validate a method to rapidly generate miRNA sponges for miRNA loss-of-function studies.

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Mendeley readers

The data shown below were compiled from readership statistics for 241 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 <1%
United States 2 <1%
Netherlands 1 <1%
France 1 <1%
Finland 1 <1%
Italy 1 <1%
Egypt 1 <1%
United Kingdom 1 <1%
Unknown 231 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 69 29%
Researcher 50 21%
Student > Bachelor 25 10%
Student > Master 21 9%
Student > Doctoral Student 19 8%
Other 37 15%
Unknown 20 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 115 48%
Biochemistry, Genetics and Molecular Biology 46 19%
Medicine and Dentistry 17 7%
Neuroscience 9 4%
Engineering 6 2%
Other 18 7%
Unknown 30 12%