RNA secondary structure modeling at consistent high accuracy using differential SHAPE

Rice, Greggory M.; Leonard, Christopher W.; Weeks, Kevin M.

doi:10.1261/rna.043323.113

Cited by 87 publications

(134 citation statements)

References 36 publications

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“…The global minimum free-energy secondary structures generated with and without experimental data shared only 73% of predicted base pairs. This level of dissimilarity leads to substantial, nontrivial differences in modeled structures (35). Only 7 of the 15 regions with mutually conserved structures were present in some form in the structures predicted without use of SHAPE data (Fig.…”

Section: Resultsmentioning

confidence: 99%

Functionally conserved architecture of hepatitis C virus RNA genomes

Mauger¹,

Golden

Yamane

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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119

190

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Hepatitis C virus (HCV) infects over 170 million people worldwide and is a leading cause of liver disease and cancer. The virus has a 9,650-nt, single-stranded, messenger-sense RNA genome that is infectious as an independent entity. The RNA genome has evolved in response to complex selection pressures, including the need to maintain structures that facilitate replication and to avoid clearance by cell-intrinsic immune processes. Here we used highthroughput, single-nucleotide resolution information to generate and functionally test data-driven structural models for three diverse HCV RNA genomes. We identified, de novo, multiple regions of conserved RNA structure, including all previously characterized cisacting regulatory elements and also multiple novel structures required for optimal viral fitness. Well-defined RNA structures in the central regions of HCV genomes appear to facilitate persistent infection by masking the genome from RNase L and double-stranded RNA-induced innate immune sensors. This work shows how structure-first comparative analysis of entire genomes of a pathogenic RNA virus enables comprehensive and concise identification of regulatory elements and emphasizes the extensive interrelationships among RNA genome structure, viral biology, and innate immune responses.RNA structure | evolution | motif discovery | functional validation H epatitis C virus (HCV) currently infects over 170 million people. There is no vaccine, and therapy, generally involving treatment with IFN and ribavirin, is often ineffective (1). Efficacious anti-HCV therapeutics are becoming available (2), but the extent to which they will mitigate the hepatitis C disease burden remains to be seen. Roughly 70% of acutely infected individuals fail to clear the virus and become lifelong HCV carriers, at risk for progressive hepatic fibrosis, cirrhosis, and hepatocellular carcinoma (3).HCV genomes are single-stranded, ∼9,650-nt, messengersense RNA molecules (4). The naked RNA initiates autonomous replication when transfected into cells and establishes chronic HCV infection in chimpanzees (5, 6). The HCV genomic RNA carries genetic information at two levels: a single large ORF encodes viral proteins and complex RNA structural elements regulate the viral replication cycle (4). Viral replication begins when conserved RNA elements in the 5′ UTR bind the 40S ribosome subunit and recruit essential translation factors (7). Translation produces a viral polyprotein that is cleaved by cellular and viral proteases to generate 10 viral proteins (4). The HCV genome is replicated through a negative-strand RNA intermediate by a viral RNA-dependent RNA polymerase (NS5B) in a process controlled by conserved RNA elements (8-17).The HCV genomic RNA is physically compact (18) and highly structured (19). These features likely facilitate persistent HCV infections in humans by protecting the genome from degradation by innate antiviral defenses (20,21). Two elements of this defense are RNase L, which cleaves in single-stranded regions (22), and diverse double...

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Section: Resultsmentioning

confidence: 99%

Functionally conserved architecture of hepatitis C virus RNA genomes

Mauger¹,

Golden

Yamane

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

119

190

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“…In some cases, the resulting models have disagreed with accepted structures (Quarrier et al 2010;Kladwang et al 2011c;Hajdin et al 2013;Sükösd et al 2013;Rice et al 2014), motivating efforts to estimate uncertainty (Kladwang et al 2011c;Ramachandran et al 2013), to incorporate alternative mapping strategies (Cordero et al 2012a;Kwok et al 2013), and to integrate mapping with systematic mutagenesis (mutate-and-map [M 2 ]) (Kladwang and Das 2010;Kladwang et al 2011a,b;Cordero et al 2014). Even these improvements do not provide routes to validation through independent experiments, and structure inferences remain under question (Wenger et al 2011).…”

Section: Introductionmentioning

confidence: 99%

High-throughput mutate-map-rescue evaluates SHAPE-directed RNA structure and uncovers excited states

Tian

Cordero

Kladwang

et al. 2014

RNA

101

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The three-dimensional conformations of noncoding RNAs underpin their biochemical functions but have largely eluded experimental characterization. Here, we report that integrating a classic mutation/rescue strategy with high-throughput chemical mapping enables rapid RNA structure inference with unusually strong validation. We revisit a 16S rRNA domain for which SHAPE (selective 2 ′ -hydroxyl acylation with primer extension) and limited mutational analysis suggested a conformational change between apo-and holo-ribosome conformations. Computational support estimates, data from alternative chemical probes, and mutate-and-map (M 2 ) experiments highlight issues of prior methodology and instead give a nearcrystallographic secondary structure. Systematic interrogation of single base pairs via a high-throughput mutation/rescue approach then permits incisive validation and refinement of the M 2 -based secondary structure. The data further uncover the functional conformation as an excited state (20 ± 10% population) accessible via a single-nucleotide register shift. These results correct an erroneous SHAPE inference of a ribosomal conformational change, expose critical limitations of conventional structure mapping methods, and illustrate practical steps for more incisively dissecting RNA dynamic structure landscapes.

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“…There have been promising results on several model RNAs of known structure, including large molecules such as the 1542-nucleotide Escherichia coli 16S ribosomal RNA (Deigan et al 2009;Hajdin et al 2013;Rice et al 2014). However, the general level of accuracy of these techniques for new RNAs has been questioned (Kladwang et al 2011c;Sukosd et al 2013;Tian et al 2014).…”

Section: Prelude: 1d Rna Chemical Mappingmentioning

confidence: 99%

“…For example, reanalysis of a model based on selective 2´-OH acylation by primer extension (SHAPE) of the 9173-nucleotide HIV-1 RNA genome (Watts et al 2009) suggested that more than half of the presented helices were not well-determined (Kladwang et al 2011c), and subsequent work, including both experimental and computational improvements, have significantly revised these uncertain regions (Pollom et al 2013;Siegfried et al 2014;Sukosd et al 2015). The debate over whether these methods produce acceptable structure accuracies continues (Deigan et al 2009;Eddy, 2014;Kladwang et al 2011c;Leonard et al 2013;Rice et al 2014;Sukosd et al 2013;Tian et al 2014) and will not be reviewed in detail here. There is general agreement, however, on some points.…”

Section: Prelude: 1d Rna Chemical Mappingmentioning

confidence: 99%

RNA structure through multidimensional chemical mapping

Tian

Das

2016

Quart. Rev. Biophys.

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Abstract. The discoveries of myriad non-coding RNA molecules, each transiting through multiple flexible states in cells or virions, present major challenges for structure determination. Advances in high-throughput chemical mapping give new routes for characterizing entire transcriptomes in vivo, but the resulting one-dimensional data generally remain too information-poor to allow accurate de novo structure determination. Multidimensional chemical mapping (MCM) methods seek to address this challenge. Mutate-and-map (M 2 ), RNA interaction groups by mutational profiling (RING-MaP and MaP-2D analysis) and multiplexed •OH cleavage analysis (MOHCA) measure how the chemical reactivities of every nucleotide in an RNA molecule change in response to modifications at every other nucleotide. A growing body of in vitro blind tests and compensatory mutation/rescue experiments indicate that MCM methods give consistently accurate secondary structures and global tertiary structures for ribozymes, ribosomal domains and ligand-bound riboswitch aptamers up to 200 nucleotides in length. Importantly, MCM analyses provide detailed information on structurally heterogeneous RNA states, such as ligand-free riboswitches that are functionally important but difficult to resolve with other approaches. The sequencing requirements of currently available MCM protocols scale at least quadratically with RNA length, precluding general application to transcriptomes or viral genomes at present. We propose a modify-cross-link-map (MXM) expansion to overcome this and other current limitations to resolving the in vivo 'RNA structurome'.

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RNA secondary structure modeling at consistent high accuracy using differential SHAPE

Cited by 87 publications

References 36 publications

Functionally conserved architecture of hepatitis C virus RNA genomes

Functionally conserved architecture of hepatitis C virus RNA genomes

High-throughput mutate-map-rescue evaluates SHAPE-directed RNA structure and uncovers excited states

RNA structure through multidimensional chemical mapping

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