S. Lusvarghi, J. Sztuba-Solinska, K.J. Purzycka, J.W. Rausch and S.F.J. Le Grice are supported by the Intramural Research Program of the National Cancer Institute, National Institutes of Health, USA.

<ol>
	<li>Scott, W. G., Martick, M., Chi, Y. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structure+and+function+of+regulatory+RNA+elements:+ribozymes+that+regulate+gene+expression.">Structure and function of regulatory RNA elements: ribozymes that regulate gene expression.</a> Biochim. Biophys. Acta. 1789, 634-641 (2009).</li><li>Moore, P. B., Steitz, T. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+roles+of+RNA+in+the+synthesis+of+protein.">The roles of RNA in the synthesis of protein.</a> Cold Spring Harb. Perspect. Biol. 3, a003780 (2011).</li><li>Wilkinson, K. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+SHAPE+analysis+reveals+structures+in+HIV-1+genomic+RNA+strongly+conserved+across+distinct+biological+states.">High-throughput SHAPE analysis reveals structures in HIV-1 genomic RNA strongly conserved across distinct biological states.</a> Plos Biol. 6, 883-899 (2008).</li><li>Merino, E. J., Wilkinson, K. A., Coughlan, J. L., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNA+structure+analysis+at+single+nucleotide+resolution+by+selective+2+'-hydroxyl+acylation+and+primer+extension+(SHAPE).">RNA structure analysis at single nucleotide resolution by selective 2 '-hydroxyl acylation and primer extension (SHAPE).</a> J. Am. Chem. Soc. 127, 4223-4231 (2005).</li><li>Watts, J. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Architecture+and+secondary+structure+of+an+entire+HIV-1+RNA+genome.">Architecture and secondary structure of an entire HIV-1 RNA genome.</a> Nature. 460, 711-716 (2009).</li><li>Xu, W., Bolduc, F., Hong, N., Perreault, J. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+use+of+a+combination+of+computer-assisted+structure+prediction+and+SHAPE+probing+to+elucidate+the+secondary+structures+of+five+viroids.">The use of a combination of computer-assisted structure prediction and SHAPE probing to elucidate the secondary structures of five viroids.</a> Mol. Plant Pathol. , (2012).</li><li>Novikova, I. V., Hennelly, S. P., Sanbonmatsu, K. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structural+architecture+of+the+human+long+non-coding+RNA,+steroid+receptor+RNA+activator.">Structural architecture of the human long non-coding RNA, steroid receptor RNA activator.</a> Nucleic Acids Res. 40, 5034-5051 (2012).</li><li>Leshin, J. A., Heselpoth, R., Belew, A. T., Dinman, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+structural+analysis+of+yeast+ribosomes+using+hSHAPE.">High-throughput structural analysis of yeast ribosomes using hSHAPE.</a> RNA Biol. 8, 478-487 (2011).</li><li>Souliere, M. F., Haller, A., Rieder, R., Micura, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+powerful+approach+for+the+selection+of+2-aminopurine+substitution+sites+to+investigate+RNA+folding.">A powerful approach for the selection of 2-aminopurine substitution sites to investigate RNA folding.</a> J. Am. Chem. Soc. 133, 16161-16167 (2011).</li><li>Wilkinson, K. A., Merino, E. J., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selective+2+'-hydroxyl+acylation+analyzed+by+primer+extension+(SHAPE):+quantitative+RNA+structure+analysis+at+single+nucleotide+resolution.">Selective 2 '-hydroxyl acylation analyzed by primer extension (SHAPE): quantitative RNA structure analysis at single nucleotide resolution.</a> Nat. Protoc. 1, 1610-1616 (2006).</li><li>McGinnis, J. L., Duncan, C. D. S., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-Throughput+Shape+and+Hydroxyl+Radical+Analysis+of+Rna+Structure+and+Ribonucleoprotein+Assembly.">High-Throughput Shape and Hydroxyl Radical Analysis of Rna Structure and Ribonucleoprotein Assembly.</a> Method Enzymol. 468, 67-89 (2009).</li><li>Low, J. T., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=SHAPE-directed+RNA+secondary+structure+prediction.">SHAPE-directed RNA secondary structure prediction.</a> Methods. 52, 150-158 (2010).</li><li>Das, R., Laederach, A., Pearlman, S. M., Herschlag, D., Altman, R. B. S. A. F. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Semi-automated+footprinting+analysis+software+for+high-throughput+quantification+of+nucleic+acid+footprinting+experiments.">Semi-automated footprinting analysis software for high-throughput quantification of nucleic acid footprinting experiments.</a> Rna-a Publication of the Rna Society. 11, 344-354 (2005).</li><li>Kertesz, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+measurement+of+RNA+secondary+structure+in+yeast.">Genome-wide measurement of RNA secondary structure in yeast.</a> Nature. 467, 103-107 (2010).</li><li>Underwood, J. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=FragSeq:+transcriptome-wide+RNA+structure+probing+using+high-throughput+sequencing.">FragSeq: transcriptome-wide RNA structure probing using high-throughput sequencing.</a> Nat. Methods. 7, 995-1001 (2010).</li><li>Mauger, D. M., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Toward+global+RNA+structure+analysis.">Toward global RNA structure analysis.</a> Nat. Biotechnol. 28, 1178-1179 (2010).</li><li>Lucks, J. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiplexed+RNA+structure+characterization+with+selective+2'-hydroxyl+acylation+analyzed+by+primer+extension+sequencing+(SHAPE-Seq).">Multiplexed RNA structure characterization with selective 2'-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq).</a> Proc. Natl. Acad. Sci. USA. 108, 11063-11068 (2011).</li><li>Vasa, S. M., Guex, N., Wilkinson, K. A., Weeks, K. M., Giddings, M. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ShapeFinder:+a+software+system+for+high-throughput+quantitative+analysis+of+nucleic+acid+reactivity+information+resolved+by+capillary+electrophoresis.">ShapeFinder: a software system for high-throughput quantitative analysis of nucleic acid reactivity information resolved by capillary electrophoresis.</a> RNA. 14, 1979-1990 (2008).</li><li>Reuter, J. S., Mathews, D. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNAstructure:+software+for+RNA+secondary+structure+prediction+and+analysis.">RNAstructure: software for RNA secondary structure prediction and analysis.</a> BMC Bioinformatics. 11, 129 (2010).</li><li>Pang, P. S., Elazar, M., Pham, E. A., Glenn, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Simplified+RNA+secondary+structure+mapping+by+automation+of+SHAPE+data+analysis.">Simplified RNA secondary structure mapping by automation of SHAPE data analysis.</a> Nucleic Acids Res. 39, e151 (2011).</li><li>Deigan, K. E., Li, T. W., Mathews, D. H., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Accurate+SHAPE-directed+RNA+structure+determination.">Accurate SHAPE-directed RNA structure determination.</a> Proc. Natl. Acad. Sci. USA. 106, 97-102 (2009).</li><li>Darty, K., Denise, A., Ponty, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=VARNA:+Interactive+drawing+and+editing+of+the+RNA+secondary+structure.">VARNA: Interactive drawing and editing of the RNA secondary structure.</a> Bioinformatics. 25, 1974-1975 (2009).</li><li>Byun, Y., Han, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=PseudoViewer:+web+application+and+web+service+for+visualizing+RNA+pseudoknots+and+secondary+structures.">PseudoViewer: web application and web service for visualizing RNA pseudoknots and secondary structures.</a> Nucleic Acids Res. 34, 416-422 (2006).</li><li>Brown, T., Brown, D. J. S., Eckstein, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Oligonucleotides and Analogues - A Practical Approach. , 20 (1990).</li><li>Legiewicz, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+RNA+Transport+Element+of+the+Murine+musD+Retrotransposon+Requires+Long-range+Intramolecular+Interactions+for+Function.">The RNA Transport Element of the Murine musD Retrotransposon Requires Long-range Intramolecular Interactions for Function.</a> J. Biol. Chem. 285, 42097-42104 (2010).</li><li>Steen, K., Siegfried, N. A., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Syntheis+of+1-methyl-8-nitroisatoic+anhydride+(1M7).">Syntheis of 1-methyl-8-nitroisatoic anhydride (1M7).</a> Protocol Exchange. , (2011).</li><li>Mortimer, S. A., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+fast-acting+reagent+for+accurate+analysis+of+RNA+secondary+and+tertiary+structure+by+SHAPE+chemistry.">A fast-acting reagent for accurate analysis of RNA secondary and tertiary structure by SHAPE chemistry.</a> J. Am. Chem. Soc. 129, 4144-4145 (2007).</li><li>Mitra, S., Shcherbakova, I. V., Altman, R. B., Brenowitz, M., Laederach, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+single-nucleotide+structural+mapping+by+capillary+automated+footprinting+analysis.">High-throughput single-nucleotide structural mapping by capillary automated footprinting analysis.</a> Nucleic Acids Res. 36, e63 (2008).</li><li>Giddings, M. C., Severin, J., Westphall, M., Wu, J., Smith, L. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+software+system+for+data+analysis+in+automated+DNA+sequencing.">A software system for data analysis in automated DNA sequencing.</a> Genome Res. 8, 644-665 (1998).</li><li>Aviran, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modeling+and+automation+of+sequencing-based+characterization+of+RNA+structure.">Modeling and automation of sequencing-based characterization of RNA structure.</a> Proc. Natl. Acad. Sci. USA. 108, 11069-11074 (2011).</li></ol>

No conflicts of interest declared.

We present here a detailed protocol for high-throughput SHAPE, a technique that allows secondary structure determination to single-nucleotide resolution for RNAs of any size. Moreover, coupling experimental SHAPE data with secondary structure prediction algorithms facilitates generation of RNA 2D models with a higher degree of accuracy than is possible with either method alone. The combination of fluorescently-labeled primers and automated CE provides significant advantages over the traditional gel-based SHAPE, facilitat...

To understand the functions of catalytic and non-coding RNAs involved in regulation of splicing, translation, virus replication and cancer, a detailed knowledge of RNA structure is required1,2. Unfortunately, accurate prediction of RNA folding presents a formidable challenge. Classical probing agents suffer from many disadvantages such as toxicity, incomplete nucleotide coverage and/or throughput limited to 100-150 nucleotides per experiment. Unaided secondary structure prediction algorithms are similarly disadvantageous, owing to inaccuracies resulting from their inability to effectively distinguish among energetically similar structures. Large RNAs in particular are also often refractory to methods of 3D structure determination such as X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy, due to their conformational flexibility and large quantities of highly pure samples required for these techniques.
High-throughput SHAPE solves many of these problems by providing an effective, simple approach to probing the structures of large RNAs at single-nucleotide resolution. Moreover, the reagents used for SHAPE are safe, easy to handle and, in contrast to most other chemical probing reagents, react with all four ribonucleotides. These reagents can also penetrate cellular membranes, making it possible to probe RNAs in their in vivo context(s)3. Originally developed in the Weeks laboratory4, SHAPE has been used to analyze a wide variety of RNAs, the most notable example being determination of the complete secondary structure of the ~9 kb HIV-1 RNA genome5. Other notable achievements using SHAPE include elucidation of the structures of infectious viroids6, human long non-coding RNAs7, yeast ribosomes8, and riboswitches9 as well as to identify protein binding sites in virion-associated HIV-1 RNA3. While the original and high-throughput variations of the SHAPE protocol have been published elsewhere10-12, the present work provides a detailed description of RNA secondary structure determination by high-throughput SHAPE using fluorescent oligonucleotides, the Beckman Coulter CEQ 8000 Genetic Analyzer, and SHAPEfinder and RNAStructure (v5.3) software. Previously unpublished technical details and troubleshooting advice are also included.
Variations of SHAPE
The essence of SHAPE and its variations is exposure of RNA in aqueous solution to electrophilic anhydrides that selectively acylate 2'-hydroxyl (2'-OH) ribose groups, producing bulky adducts at the sites of modification. This chemical reaction serves as a means of interrogating local RNA structural dynamics, as single-stranded nucleotides are more prone to adopt conformations conducive to electrophilic attack by these reagents, while base paired or architecturally constrained nucleotides are less or unreactive10. Sites of adduct formation are detected by reverse transcription initiating from fluorescently or radiolabeled primers hybridized to a specific site on the modified RNA (the "(+)" primer extension reaction). When reverse transcriptase (RT) fails to traverse the acylated ribonucleotides, a pool of cDNA products is produced whose lengths coincide with sites of modification. A control, "(-)" primer extension reaction utilizing RNA that has not been exposed to reagent is also performed so that premature termination of DNA synthesis (i.e. "stops") due to RNA structure, nonspecific RNA strand breakage, etc., may be distinguished from pausing produced by chemical modification. Finally, two dideoxy-sequencing reactions initiating from the same primers are used as markers to correlate reactive nucleotides with the RNA primary sequence following electrophoresis.
In the original application of SHAPE, the same 32P-end-labeled primer is utilized for the (+), (-), and two sequencing reactions. Products of these reactions are loaded into adjacent wells in a 5-8% polyacrylamide slab gel, and fractionated by denaturing polyacrylamide gel electrophoresis (PAGE; Figure 1). Quantitative analysis of the gel images produced by conventional SHAPE can be performed using SAFA, a semi-automated footprinting analysis software13.
In contrast, high-throughput SHAPE employs fluorescently labeled primers and automated capillary electrophoresis. Specifically, for each region of RNA under investigation, a set of four DNA primers having a common sequence but different 5' fluorescent labels must be synthesized or purchased. These differently-labeled oligonucleotides serve to prime two SHAPE reactions and two sequencing reactions, the products of which are pooled and fractionated/detected by automated capillary electrophoresis (CE). Whereas the reactivity profile of 100-150 nt of RNA can be obtained from a set of four reactions using the original approach, high-throughput SHAPE allows resolution of 300-600 nt from a single pooled sample3. Up to 8 sets of reactions may be fractionated simultaneously, while as many as 96 samples can prepared for fractionation over the course of 12 consecutive CE runs (Figure 2). Moreover, the SHAPEfinder software, developed to process and analyze data emerging from the CEQ and other genetic analyzers, is more automated and require much less user intervention than SAFA13 or other gel-analysis packages.
More advanced high-throughput methodologies have recently emerged such as PARS (parallel analysis of RNA structure)14 and Frag-Seq (fragment-sequencing)15, which use structure-specific enzymes rather than alkylation reagents in conjunction with next generation sequencing techniques to obtain information about RNA structure. Despite the attractiveness of these techniques, the many limitations inherent to nuclease probing still remain16. These problems can be circumvented in the SHAPE sequencing (SHAPE-Seq)17 protocol, where next generation sequencing is preceded by chemical modification and reverse transcription of RNAs in a manner similar to that performed in conventional SHAPE. While these methods may represent the future of RNA structure determination, it is important to remember that next generation sequencing is very expensive, and remains unavailable to many laboratories.
SHAPE Data Analysis
Data produced in the genetic analyzer is presented in the form of an electropherogram, wherein the fluorescence intensity of the sample(s) flowing through the capillary detector is plotted against an index of migration time. This plot takes the form of overlapping traces corresponding to the four fluorescence channels used to detect the different fluorophores, and where each trace is comprised of peaks corresponding to individual cDNA or sequencing products. Electropherogram data is exported from the genetic analyzer as a tab-delimited text file and imported into ShapeFinder transformation and analysis software18.
ShapeFinder is initially used to perform a series of mathematical transformations on the data to ensure that migration times and peak volumes accurately reflect the identities and quantities of the reaction products, respectively. Peaks are then aligned and integrated, and the results tabulated together with the primary RNA sequence. A "reactivity profile" for the pertinent segment of RNA is obtained by subtracting control values from the (+) values associated with each RNA nucleotide, and normalizing the data as described below. This profile is imported into RNAstructure (v5.3) software19,20 , which converts the normalized reactivity values into pseudo-energy constraints that are incorporated into the RNA secondary structure folding algorithm. Combining chemical probing and folding algorithms in this way significantly improves the accuracy of structure prediction compared to either method alone12,21. The output of RNAstructure (v5.3) includes images of the lowest energy RNA secondary structures color-coded with the SHAPE reactivity profile(s), as well as the same structures in textual dot-bracket notation. The latter may subsequently be exported to software dedicated to the graphical display of RNA secondary structure such as Varna22 and PseudoViewer23.
<img alt="Figure 1" fo:content-width="4.8in" fo:src="/files/ftp_upload/50243/50243fig1highres.jpg" src="/files/ftp_upload/50243/50243fig1.jpg" /> 
Figure 1. Flowchart of RNA structure determination via SHAPE4,10. (A) RNA may be obtained from biological samples or by in vitro transcription. (B) Depending on the source, RNA is folded or otherwise processed and modified with SHAPE reagent. (C) Reverse transcription using fluorescently or radioactively labeled primers. (D) cDNA products are fractionated via either capillary or slab gel-based electrophoresis. (E) Fragment analysis. (F) RNA structure prediction. <a href="http://www.jove.com/files/ftp_upload/50243/50243fig1large.jpg" target="_blank">Click here to view larger figure.</a>
<img alt="Figure 2" fo:content-width="6in" fo:src="/files/ftp_upload/50243/50243fig2highres.jpg" src="/files/ftp_upload/50243/50243fig2.jpg" /> 
Figure 2. The high-throughput character of CE-based SHAPE allows rapid analysis of multiple RNAs, and/or multiple segments of the same RNA. (A) Represents how an RNA may be divided into 300-600 nt sections (color coded in green, blue and red) (B) Sections of the RNA are probed independently using different sets of fluorescent primers (black arrows) (C) Sets of reactions are pooled and loaded into wells A1, B1, C1, etc, respectively, providing complete coverage for the ~3 kb RNA1. Reaction products from RNAs 2, 3, 4, etc. may be similarly prepared for fractionation in consecutive electrophoretic runs. <a href="http://www.jove.com/files/ftp_upload/50243/50243fig2large.jpg" target="_blank">Click here to view larger figure.</a>

<table border="1">
	<tbody>
		<tr>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>REAGENTS</td>
		</tr>
		<tr>
			<td>N-methylisatoic anhydride (NMIA)</td>
			<td>Life technologies</td>
			<td>M25</td>
			<td>Dissolve in anhydrous DMSO</td>
		</tr>
		<tr>
			<td>1-methyl-t-nitroisatoic anhydride (1M7)</td>
			<td>see ref. 22</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Superscript III Reverse Transcriptase</td>
			<td>Life technologies</td>
			<td>18080044</td>
			<td>10,000 units</td>
		</tr>
		<tr>
			<td>Thermo sequenase cycle sequencing kit</td>
			<td>Affymetrix</td>
			<td>78500</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>Materials provided by the user</td>
		</tr>
		<tr>
			<td>RNA of interest</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>6 pmol per reaction (the limit of detection will be determined by the instrument)</td>
		</tr>
		<tr>
			<td>Sets of four 5' labeled primers (Cy5, Cy5.5, WellRed D2 and WellRed D1/Licor IR800)</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>Primers are complementary to the RNA and are used in reverse transcription and sequencing reactions. The listed fluorophores are optimal for the Beckman Coulter 8000 CEQ. Primers may be purchased or synthesized in house.</td>
		</tr>
		<tr>
			<td>DNA template</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>DNA is used for sequencing reactions, and must contain the sequence of the RNA being studied - including any 3'terminal extension, if present. Where applicable, it is often convenient to use the RNA transcription template.</td>
		</tr>
		<tr>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>Buffers</td>
		</tr>
		<tr>
			<td>10x RNA renaturation buffer</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>100 mM Tris-HCl pH 8.0, 1 M KCl, 1 mM EDTA</td>
		</tr>
		<tr>
			<td>5X RNA folding buffer</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>200 mM Tris-HCl pH 8.0, 25 mM MgCl2, 2.5 mM EDTA, 650 mM KCl. (This buffer might be changed depending on the case (e.g. pH, EDTA, Mg, RNase inhibitor)</td>
		</tr>
		<tr>
			<td>2.5X RT mix</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>4 &mu;l 5X buffer, 1 &mu;l 100 mM DTT, 1.5 &mu;l water,1 &mu;l 10 mM dNTPs, 0.5 &mu;l SuperScript III. Note that the 5X buffer and 100 mM DTT are provided with purchase of SuperScript III (Invitrogen).</td>
		</tr>
		<tr>
			<td>GenomeLab Sample Loading Solution (Beckman Coulter)</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>Attention: Avoid multiple freeze-thaw cycles</td>
		</tr>
		<tr>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>EQUIPMENT</td>
		</tr>
		<tr>
			<td>Capillary electrophoresis</td>
			<td>Beckman</td>
			<td>CEQ8000</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Thermocycler</td>
			<td>varies</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
		</tr>
	</tbody>
</table>

rna secondary structure prediction using high-throughput shape

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.

RNA containing the HIV-1 rev response element (RRE) and a 3' terminal structure cassette4 was prepared from a linearized plasmid by in vitro transcription, after which it was folded by heating, cooling, and incubation at 37 &deg;C in the presence of MgCl2. RNA was exposed to NMIA and then reverse transcribed from a 5'-end-labeled DNA primer hybridized to the 3' terminal structure cassette. The resulting SHAPE cDNA library, together with control and sequencing reactions, was then fractionate...

Watch this Scientific Journal Video about RNA Secondary Structure Prediction Using High-throughput SHAPE at JoVE.com

RNA Secondary Structure Prediction Using High-throughput SHAPE

High-throughput selective 2' hydroxyl acylation analyzed by primer extension (SHAPE) utilizes a novel chemical probing technology, reverse transcription, capillary electrophoresis and secondary structure prediction software to determine the structures of RNAs from several hundred to several thousand nucleotides at single nucleotide resolution.

Understanding the function of RNA involved in biological processes requires a thorough knowledge of RNA structure. Toward this end, the methodology dubbed ...

rna-secondary-structure-prediction-using-high-throughput-shape

Research

Education

JoVE Journal

JoVE Core

Molecular Biology

Biology

Unit 1

Transcription: DNA to RNA

SCIENTISTS IN ACTION

31.3K vistas.  Frederick National Laboratory for Cancer Research. De alto rendimiento selectiva 2 'acilación hidroxilo analizados por extensión del cebador (FORMA) utiliza un software de predicción de estructura secundaria de producto químico nuevo sondeo de la tecnología, la transcripción inversa, electroforesis capilar y para determinar las estructuras de ARN de varios cientos a varios miles de nucleótidos en una sola resolución de nucleótidos.

Video: RNA Secondary Structure Prediction Using High-throughput SHAPE

High-throughput Yeast Plasmid Overexpression Screen

The budding yeast, Saccharomyces cerevisiae, is a powerful model system for defining fundamental mechanisms of many important cellular processes, including those with direct relevance to human disease. Because of its short generation time and well-characterized genome, a major experimental advantage of the yeast model system is the ability to perform genetic screens to identify genes and pathways that are involved in a given process. Over the last thirty years such genetic screens have been used to elucidate the cell cycle, secretory pathway, and many more highly conserved aspects of eukaryotic cell biology 1-5. In the last few years, several genomewide libraries of yeast strains and plasmids have been generated 6-10. These collections now allow for the systematic interrogation of gene function using gain- and loss-of-function approaches 11-16. Here we provide a detailed protocol for the use of a high-throughput yeast transformation protocol with a liquid handling robot to perform a plasmid overexpression screen, using an arrayed library of 5,500 yeast plasmids. We have been using these screens to identify genetic modifiers of toxicity associated with the accumulation of aggregation-prone human neurodegenerative disease proteins. The methods presented here are readily adaptable to the study of other cellular phenotypes of interest.

Here we describe a plasmid overexpression screen in Saccharomyces cerevisiae, using an arrayed plasmid library and a high-throughput yeast transformation protocol with a liquid handling robot.

The budding yeast, Saccharomyces cerevisiae, is a powerful model system for defining fundamental mechanisms of many important cellular processes, ...

A Protocol for Computer-Based Protein Structure and Function Prediction

Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the understanding of their biological role. Although experimental methods can provide detailed information for a small fraction of these proteins, computational modeling is needed for the majority of protein molecules which are experimentally uncharacterized. The I-TASSER server is an on-line workbench for high-resolution modeling of protein structure and function. Given a protein sequence, a typical output from the I-TASSER server includes secondary structure prediction, predicted solvent accessibility of each residue, homologous template proteins detected by threading and structure alignments, up to five full-length tertiary structural models, and structure-based functional annotations for enzyme classification, Gene Ontology terms and protein-ligand binding sites. All the predictions are tagged with a confidence score which tells how accurate the predictions are without knowing the experimental data. To facilitate the special requests of end users, the server provides channels to accept user-specified inter-residue distance and contact maps to interactively change the I-TASSER modeling; it also allows users to specify any proteins as template, or to exclude any template proteins during the structure assembly simulations. The structural information could be collected by the users based on experimental evidences or biological insights with the purpose of improving the quality of I-TASSER predictions. The server was evaluated as the best programs for protein structure and function predictions in the recent community-wide CASP experiments. There are currently &gt;20,000 registered scientists from over 100 countries who are using the on-line I-TASSER server.

Guidelines for computer based structural and functional characterization of protein using the I-TASSER pipeline is described. Starting from query protein sequence, 3D models are generated using multiple threading alignments and iterative structural assembly simulations. Functional inferences are thereafter drawn based on matches to proteins with known structure and functions.

Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the ...

High-throughput Crystallization of Membrane Proteins Using the Lipidic Bicelle Method

Membrane proteins (MPs) play a critical role in many physiological processes such as pumping specific molecules across the otherwise impermeable membrane bilayer that surrounds all cells and organelles. Alterations in the function of MPs result in many human diseases and disorders; thus, an intricate understanding of their structures remains a critical objective for biological research. However, structure determination of MPs remains a significant challenge often stemming from their hydrophobicity. 
MPs have substantial hydrophobic regions embedded within the bilayer. Detergents are frequently used to solubilize these proteins from the bilayer generating a protein-detergent micelle that can then be manipulated in a similar manner as soluble proteins. Traditionally, crystallization trials proceed using a protein-detergent mixture, but they often resist crystallization or produce crystals of poor quality. These problems arise due to the detergent&prime;s inability to adequately mimic the bilayer resulting in poor stability and heterogeneity. In addition, the detergent shields the hydrophobic surface of the MP reducing the surface area available for crystal contacts. To circumvent these drawbacks MPs can be crystallized in lipidic media, which more closely simulates their endogenous environment, and has recently become a de novo technique for MP crystallization.
Lipidic cubic phase (LCP) is a three-dimensional lipid bilayer penetrated by an interconnected system of aqueous channels1. Although monoolein is the lipid of choice, related lipids such as monopalmitolein and monovaccenin have also been used to make LCP2. MPs are incorporated into the LCP where they diffuse in three dimensions and feed crystal nuclei. A great advantage of the LCP is that the protein remains in a more native environment, but the method has a number of technical disadvantages including high viscosity (requiring specialized apparatuses) and difficulties in crystal visualization and manipulation3,4. Because of these technical difficulties, we utilized another lipidic medium for crystallization-bicelles5,6 (Figure 1). Bicelles are lipid/amphiphile mixtures formed by blending a phosphatidylcholine lipid (DMPC) with an amphiphile (CHAPSO) or a short-chain lipid (DHPC). Within each bicelle disc, the lipid molecules generate a bilayer while the amphiphile molecules line the apolar edges providing beneficial properties of both bilayers and detergents. Importantly, below their transition temperature, protein-bicelle mixtures have a reduced viscosity and are manipulated in a similar manner as detergent-solubilized MPs, making bicelles compatible with crystallization robots. 
Bicelles have been successfully used to crystallize several membrane proteins5,7-11 (Table 1). This growing collection of proteins demonstrates the versatility of bicelles for crystallizing both alpha helical and beta sheet MPs from prokaryotic and eukaryotic sources. Because of these successes and the simplicity of high-throughput implementation, bicelles should be part of every membrane protein crystallographer&prime;s arsenal. In this video, we describe the bicelle methodology and provide a step-by-step protocol for setting up high-throughput crystallization trials of purified MPs using standard robotics.

Bicelles are lipid/amphiphile mixtures that maintain membrane proteins (MPs) within a lipid bilayer but have unique phase behavior that facilitates high-throughput screening by crystallization robots. This technique has successfully produced a number of high-resolution structures from both prokaryotic and eukaryotic sources. This video describes protocols for generating the lipidic bicelle mixture, incorporating MPs into the bicelle mixture, setting up crystallizations trials (manually as well as robotically) and harvesting crystals from the medium.

Membrane proteins (MPs) play a critical role in many physiological processes such as pumping specific molecules across the otherwise impermeable membrane ...

High-throughput Physical Mapping of Chromosomes using Automated in situ Hybridization

Projects to obtain whole-genome sequences for 10,000 vertebrate species1 and for 5,000 insect and related arthropod species2 are expected to take place over the next 5 years. For example, the sequencing of the genomes for 15 malaria mosquitospecies is currently being done using an Illumina platform3,4. This Anopheles species cluster includes both vectors and non-vectors of malaria. When the genome assemblies become available, researchers will have the unique opportunity to perform comparative analysis for inferring evolutionary changes relevant to vector ability. However, it has proven difficult to use next-generation sequencing reads to generate high-quality de novo genome assemblies5. Moreover, the existing genome assemblies for Anopheles gambiae, although obtained using the Sanger method, are gapped or fragmented4,6.
Success of comparative genomic analyses will be limited if researchers deal with numerous sequencing contigs, rather than with chromosome-based genome assemblies. Fragmented, unmapped sequences create problems for genomic analyses because: (i) unidentified gaps cause incorrect or incomplete annotation of genomic sequences; (ii) unmapped sequences lead to confusion between paralogous genes and genes from different haplotypes; and (iii) the lack of chromosome assignment and orientation of the sequencing contigs does not allow for reconstructing rearrangement phylogeny and studying chromosome evolution. Developing high-resolution physical maps for species with newly sequenced genomes is a timely and cost-effective investment that will facilitate genome annotation, evolutionary analysis, and re-sequencing of individual genomes from natural populations7,8.
Here, we present innovative approaches to chromosome preparation, fluorescent in situ hybridization (FISH), and imaging that facilitate rapid development of physical maps. Using An. gambiae as an example, we demonstrate that the development of physical chromosome maps can potentially improve genome assemblies and, thus, the quality of genomic analyses. First, we use a high-pressure method to prepare polytene chromosome spreads. This method, originally developed for Drosophila9, allows the user to visualize more details on chromosomes than the regular squashing technique10. Second, a fully automated, front-end system for FISH is used for high-throughput physical genome mapping. The automated slide staining system runs multiple assays simultaneously and dramatically reduces hands-on time11. Third, an automatic fluorescent imaging system, which includes a motorized slide stage, automatically scans and photographs labeled chromosomes after FISH12. This system is especially useful for identifying and visualizing multiple chromosomal plates on the same slide. In addition, the scanning process captures a more uniform FISH result. Overall, the automated high-throughput physical mapping protocol is more efficient than a standard manual protocol.

High-throughput Physical Mapping of Chromosomes using Automated in situ Hybridization

Genome assemblies based on massively parallel DNA sequencing technologies are usually highly fragmented. The development of physical chromosome maps can potentially improve genome assemblies. Here, we demonstrate innovative approaches to chromosome preparation, fluorescent in situ hybridization, and imaging that significantly increase throughput of the physical map development.

Projects to obtain whole-genome sequences for 10,000 vertebrate species1 and for 5,000 insect and related arthropod species2 are expected to take place ...

High-throughput Functional Screening using a Homemade Dual-glow Luciferase Assay

We present a rapid and inexpensive high-throughput screening protocol to identify transcriptional regulators of alpha-synuclein, a gene associated with Parkinson&#39;s disease. 293T cells are transiently transfected with plasmids from an arrayed ORF expression library, together with luciferase reporter plasmids, in a one-gene-per-well microplate format. Firefly luciferase activity is assayed after 48 hr to determine the effects of each library gene upon alpha-synuclein transcription, normalized to expression from an internal control construct (a hCMV promoter directing Renilla luciferase). This protocol is facilitated by a bench-top robot enclosed in a biosafety cabinet, which performs aseptic liquid handling in 96-well format. Our automated transfection protocol is readily adaptable to high-throughput lentiviral library production or other functional screening protocols requiring triple-transfections of large numbers of unique library plasmids in conjunction with a common set of helper plasmids. We also present an inexpensive and validated alternative to commercially-available, dual luciferase reagents which employs PTC124, EDTA, and pyrophosphate to suppress firefly luciferase activity prior to measurement of Renilla luciferase. Using these methods, we screened 7,670 human genes and identified 68 regulators of alpha-synuclein. This protocol is easily modifiable to target other genes of interest.

We present a rapid and inexpensive screening method for identifying transcriptional regulators using high-throughput robotic transfections and a homemade dual-glow luciferase assay. This protocol rapidly generates direct side-by-side functional data for thousands of genes and is easily modifiable to target any gene of interest.

We present a rapid and inexpensive high-throughput screening protocol to identify transcriptional regulators of alpha-synuclein, a gene associated with ...

A Manual Small Molecule Screen Approaching High-throughput Using Zebrafish Embryos

Zebrafish have become a widely used model organism to investigate the mechanisms that underlie developmental biology and to study human disease pathology due to their considerable degree of genetic conservation with humans. Chemical genetics entails testing the effect that small molecules have on a biological process and is becoming a popular translational research method to identify therapeutic compounds. Zebrafish are specifically appealing to use for chemical genetics because of their ability to produce large clutches of transparent embryos, which are externally fertilized. Furthermore, zebrafish embryos can be easily drug treated by the simple addition of a compound to the embryo media. Using whole-mount in situ hybridization (WISH), mRNA expression can be clearly visualized within zebrafish embryos. Together, using chemical genetics and WISH, the zebrafish becomes a potent whole organism context in which to determine the cellular and physiological effects of small molecules. Innovative advances have been made in technologies that utilize machine-based screening procedures, however for many labs such options are not accessible or remain cost-prohibitive. The protocol described here explains how to execute a manual high-throughput chemical genetic screen that requires basic resources and can be accomplished by a single individual or small team in an efficient period of time. Thus, this protocol provides a feasible strategy that can be implemented by research groups to perform chemical genetics in zebrafish, which can be useful for gaining fundamental insights into developmental processes, disease mechanisms, and to identify novel compounds and signaling pathways that have medically relevant applications.

The zebrafish is an excellent experimental organism to study vertebrate developmental processes and model human disease. Here, we describe a protocol on how to perform a manual high-throughput chemical screen in zebrafish embryos with a whole-mount in situ hybridization (WISH) read-out.

Zebrafish have become a widely used model organism to investigate the mechanisms that underlie developmental biology and to study human disease pathology ...

Highly Efficient Ligation of Small RNA Molecules for MicroRNA Quantitation by High-Throughput Sequencing

MiRNA cloning and high-throughput sequencing, termed miR-Seq, stands alone as a transcriptome-wide approach to quantify miRNAs with single nucleotide resolution. This technique captures miRNAs by attaching 3&#8217; and 5&#8217; oligonucleotide adapters to miRNA molecules and allows de novo miRNA discovery. Coupling with powerful next-generation sequencing platforms, miR-Seq has been instrumental in the study of miRNA biology. However, significant biases introduced by oligonucleotide ligation steps have prevented miR-Seq from being employed as an accurate quantitation tool. Previous studies demonstrate that biases in current miR-Seq methods often lead to inaccurate miRNA quantification with errors up to 1,000-fold for some miRNAs1,2. To resolve these biases imparted by RNA ligation, we have developed a small RNA ligation method that results in ligation efficiencies of over 95% for both 3&#8217; and 5&#8242; ligation steps. Benchmarking this improved library construction method using equimolar or differentially mixed synthetic miRNAs, consistently yields reads numbers with less than two-fold deviation from the expected value. Furthermore, this high-efficiency miR-Seq method permits accurate genome-wide miRNA profiling from in vivo total RNA samples2.

MicroRNAs (miRNAs) are a widely conserved class of regulatory molecules. Here we describe a miRNA cloning method that relies upon two potent ligation steps followed by high-throughput sequencing. Our method permits accurate genome-wide quantitation of miRNAs.

MiRNA cloning and high-throughput sequencing, termed miR-Seq, stands alone as a transcriptome-wide approach to quantify miRNAs with single nucleotide ...

High-throughput Screening for Chemical Modulators of Post-transcriptionally Regulated Genes

Both transcriptional and post-transcriptional regulation have a profound impact on genes expression. However, commonly adopted cell-based screening assays focus on transcriptional regulation, being essentially aimed at the identification of promoter-targeting molecules. As a result, post-transcriptional mechanisms are largely uncovered by gene expression targeted drug development. Here we describe a cell-based assay aimed at investigating the role of the 3&#39; untranslated region (3&#8217; UTR) in the modulation of the fate of its mRNA, and at identifying compounds able to modify it. The assay is based on the use of a luciferase reporter construct containing the 3&#8217; UTR of a gene of interest stably integrated into a disease-relevant cell line. The protocol is divided into two parts, with the initial focus on the primary screening aimed at the identification of molecules affecting luciferase activity after 24 hr of treatment. The second part of the protocol describes the counter-screening necessary to discriminate compounds modulating luciferase activity specifically through the 3&#8217; UTR. In addition to the detailed protocol and representative results, we provide important considerations about the assay development and the validation of the hit(s) on the endogenous target. The described cell-based reporter gene assay will allow scientists to identify molecules modulating protein levels via post-transcriptional mechanisms dependent on a 3&#8217; UTR.

Here we describe a cell-based reporter gene assay as a valuable tool to screen chemical libraries for compounds modulating post-transcriptional control mechanisms exerted through 3&#8217; UTR.

Both transcriptional and post-transcriptional regulation have a profound impact on genes expression. However, commonly adopted cell-based screening assays ...

Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay

Luminescent Identification of Functional Elements in 3&#8217;UTRs (3&#8217;LIFE) allows the rapid identification of targets of specific miRNAs within an array of hundreds of queried 3&#8217;UTRs. Target identification is based on the dual-luciferase assay, which detects binding at the mRNA level by measuring translational output, giving a functional readout of miRNA targeting. 3&#8217;LIFE uses non-proprietary buffers and reagents, and publically available reporter libraries, making genome-wide screens feasible and cost-effective. 3&#8217;LIFE can be performed either in a standard lab setting or scaled up using liquid handling robots and other high-throughput instrumentation. We illustrate the approach using a dataset of human 3&#8217;UTRs cloned in 96-well plates, and two test miRNAs, let-7c and miR-10b. We demonstrate how to perform DNA preparation, transfection, cell culture and luciferase assays in 96-well format, and provide tools for data analysis. In conclusion 3&#39;LIFE is highly reproducible, rapid, systematic, and identifies high confidence targets.

Detection of miRNA Targets in High-throughput Using the 3&#039;LIFE Assay

Luminescent identification of functional elements in 3&#8217; untranslated regions (3&#8217;UTRs) (3&#8217;LIFE) is a technique to identify functional regulation in 3&#8217;UTRs by miRNAs or other regulatory factors. This protocol utilizes high-throughput methodology such as 96-well transfection and luciferase assays to screen hundreds of putative interactions for functional repression.

Luminescent Identification of Functional Elements in 3&#8217;UTRs (3&#8217;LIFE) allows the rapid identification of targets of specific miRNAs within an ...

Identification of Kinase-substrate Pairs Using High Throughput Screening

We have developed a screening platform to identify dedicated human protein kinases for phosphorylated substrates which can be used to elucidate novel signal transduction pathways. Our approach features the use of a library of purified GST-tagged human protein kinases and a recombinant protein substrate of interest. We have used this technology to identify MAP/microtubule affinity-regulating kinase 2 (MARK2) as the kinase for a glucose-regulated site on CREB-Regulated Transcriptional Coactivator 2 (CRTC2), a protein required for beta cell proliferation, as well as the Axl family of tyrosine kinases as regulators of cell metastasis by phosphorylation of the adaptor protein ELMO. We describe this technology and discuss how it can help to establish a comprehensive map of how cells respond to environmental stimuli.

Protein phosphorylation is a central feature of how cells interpret and respond to information in their extracellular milieu. Here, we present a high throughput screening protocol using kinases purified from mammalian cells to rapidly identify kinases that phosphorylate a substrate(s) of interest.


We have developed a screening platform to identify dedicated human protein kinases for phosphorylated substrates which can be used to elucidate novel ...