Literature DB >> 23748604

RNA secondary structure prediction using high-throughput SHAPE.

Sabrina Lusvarghi1, Joanna Sztuba-Solinska, Katarzyna J Purzycka, Jason W Rausch, Stuart F J Le Grice.   

Abstract

Understanding the function of RNA involved in biological processes requires a thorough knowledge of RNA structure. Toward this end, the methodology dubbed "high-throughput selective 2' hydroxyl acylation analyzed by primer extension", or SHAPE, allows prediction of RNA secondary structure with single nucleotide resolution. This approach utilizes chemical probing agents that preferentially acylate single stranded or flexible regions of RNA in aqueous solution. Sites of chemical modification are detected by reverse transcription of the modified RNA, and the products of this reaction are fractionated by automated capillary electrophoresis (CE). Since reverse transcriptase pauses at those RNA nucleotides modified by the SHAPE reagents, the resulting cDNA library indirectly maps those ribonucleotides that are single stranded in the context of the folded RNA. Using ShapeFinder software, the electropherograms produced by automated CE are processed and converted into nucleotide reactivity tables that are themselves converted into pseudo-energy constraints used in the RNAStructure (v5.3) prediction algorithm. The two-dimensional RNA structures obtained by combining SHAPE probing with in silico RNA secondary structure prediction have been found to be far more accurate than structures obtained using either method alone.

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Year:  2013        PMID: 23748604      PMCID: PMC3727345          DOI: 10.3791/50243

Source DB:  PubMed          Journal:  J Vis Exp        ISSN: 1940-087X            Impact factor:   1.355


  28 in total

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4.  Multiplexed RNA structure characterization with selective 2'-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq).

Authors:  Julius B Lucks; Stefanie A Mortimer; Cole Trapnell; Shujun Luo; Sharon Aviran; Gary P Schroth; Lior Pachter; Jennifer A Doudna; Adam P Arkin
Journal:  Proc Natl Acad Sci U S A       Date:  2011-06-03       Impact factor: 11.205

5.  Modeling and automation of sequencing-based characterization of RNA structure.

Authors:  Sharon Aviran; Cole Trapnell; Julius B Lucks; Stefanie A Mortimer; Shujun Luo; Gary P Schroth; Jennifer A Doudna; Adam P Arkin; Lior Pachter
Journal:  Proc Natl Acad Sci U S A       Date:  2011-06-03       Impact factor: 11.205

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9.  Simplified RNA secondary structure mapping by automation of SHAPE data analysis.

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Journal:  Nucleic Acids Res       Date:  2011-09-30       Impact factor: 16.971

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  8 in total

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Review 3.  Progress and outlook in structural biology of large viral RNAs.

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Journal:  Virus Res       Date:  2014-06-21       Impact factor: 3.303

4.  Capturing RNA Folding Free Energy with Coarse-Grained Molecular Dynamics Simulations.

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Journal:  Sci Rep       Date:  2017-04-10       Impact factor: 4.379

5.  APOL1 risk allele RNA contributes to renal toxicity by activating protein kinase R.

Authors:  Koji Okamoto; Jason W Rausch; Hidefumi Wakashin; Yulong Fu; Joon-Yong Chung; Patrick D Dummer; Myung K Shin; Preeti Chandra; Kosuke Suzuki; Shashi Shrivastav; Avi Z Rosenberg; Stephen M Hewitt; Patricio E Ray; Eisei Noiri; Stuart F J Le Grice; Maarten Hoek; Zhe Han; Cheryl A Winkler; Jeffrey B Kopp
Journal:  Commun Biol       Date:  2018-11-07

Review 6.  Probing the Structures of Viral RNA Regulatory Elements with SHAPE and Related Methodologies.

Authors:  Jason W Rausch; Joanna Sztuba-Solinska; Stuart F J Le Grice
Journal:  Front Microbiol       Date:  2018-01-09       Impact factor: 5.640

7.  Major satellite repeat RNA stabilize heterochromatin retention of Suv39h enzymes by RNA-nucleosome association and RNA:DNA hybrid formation.

Authors:  Oscar Velazquez Camacho; Carmen Galan; Kalina Swist-Rosowska; Reagan Ching; Michael Gamalinda; Fethullah Karabiber; Inti De La Rosa-Velazquez; Bettina Engist; Birgit Koschorz; Nicholas Shukeir; Megumi Onishi-Seebacher; Suzanne van de Nobelen; Thomas Jenuwein
Journal:  Elife       Date:  2017-08-01       Impact factor: 8.140

8.  Maturation of the 90S pre-ribosome requires Mrd1 dependent U3 snoRNA and 35S pre-rRNA structural rearrangements.

Authors:  Fredrik Lackmann; Sergey Belikov; Elena Burlacu; Sander Granneman; Lars Wieslander
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  8 in total

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