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RISC RNA Sequencing for Context-specific Identification of in Vivo MicroRNA Targets

Overview
Journal Circ Res
Date 2010 Oct 30
PMID 21030712
Citations 64
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Abstract

Rationale: MicroRNAs (miRs) are expanding our understanding of cardiac disease and have the potential to transform cardiovascular therapeutics. One miR can target hundreds of individual mRNAs, but existing methodologies are not sufficient to accurately and comprehensively identify these mRNA targets in vivo.

Objective: To develop methods permitting identification of in vivo miR targets in an unbiased manner, using massively parallel sequencing of mouse cardiac transcriptomes in combination with sequencing of mRNA associated with mouse cardiac RNA-induced silencing complexes (RISCs).

Methods And Results: We optimized techniques for expression profiling small amounts of RNA without introducing amplification bias and applied this to anti-Argonaute 2 immunoprecipitated RISCs (RISC-Seq) from mouse hearts. By comparing RNA-sequencing results of cardiac RISC and transcriptome from the same individual hearts, we defined 1645 mRNAs consistently targeted to mouse cardiac RISCs. We used this approach in hearts overexpressing miRs from Myh6 promoter-driven precursors (programmed RISC-Seq) to identify 209 in vivo targets of miR-133a and 81 in vivo targets of miR-499. Consistent with the fact that miR-133a and miR-499 have widely differing "seed" sequences and belong to different miR families, only 6 targets were common to miR-133a- and miR-499-programmed hearts.

Conclusions: RISC-sequencing is a highly sensitive method for general RISC profiling and individual miR target identification in biological context and is applicable to any tissue and any disease state.

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References
1.
Van Rooij E, Quiat D, Johnson B, Sutherland L, Qi X, Richardson J . A family of microRNAs encoded by myosin genes governs myosin expression and muscle performance. Dev Cell. 2009; 17(5):662-73. PMC: 2796371. DOI: 10.1016/j.devcel.2009.10.013. View

2.
Van Rooij E, Olson E . MicroRNAs: powerful new regulators of heart disease and provocative therapeutic targets. J Clin Invest. 2007; 117(9):2369-76. PMC: 1952642. DOI: 10.1172/JCI33099. View

3.
Friedman R, Farh K, Burge C, Bartel D . Most mammalian mRNAs are conserved targets of microRNAs. Genome Res. 2008; 19(1):92-105. PMC: 2612969. DOI: 10.1101/gr.082701.108. View

4.
Chi S, Zang J, Mele A, Darnell R . Argonaute HITS-CLIP decodes microRNA-mRNA interaction maps. Nature. 2009; 460(7254):479-86. PMC: 2733940. DOI: 10.1038/nature08170. View

5.
Matkovich S, Zhang Y, Van Booven D, Dorn 2nd G . Deep mRNA sequencing for in vivo functional analysis of cardiac transcriptional regulators: application to Galphaq. Circ Res. 2010; 106(9):1459-67. PMC: 2891025. DOI: 10.1161/CIRCRESAHA.110.217513. View