Solution structure of RNase P RNA

Kazantsev, A. V.; Rambo, Robert P.; Karimpour, Sina; SantaLucia, John; Tainer, John A.; Pace, Norman R.

doi:10.1261/rna.2563511

Cited by 46 publications

(40 citation statements)

References 80 publications

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“…The SAXS profile for this RNA has been reanalyzed recently using multiple reconstruction methods (Zipper and Durschlag 2007) and consistently yields flattened prolate shapes that are often concave as seen for the three RNAs above. Similar SAXS evidence of elongated flat structures is available for the 1542-nt 16S ribosomal RNA , the z400-nt RNase P RNAs (Kazantsev et al 2011), and the 199-nt cis VS ribozyme . In addition, a recent analysis of the asphericity of high-resolution NMR and X-ray structures in the PDB database reveals that most RNAs (typically smaller than 1000 nt) have a prolate shape (Hyeon et al 2006).…”

Section: Discussionsupporting

confidence: 59%

Visualizing large RNA molecules in solution

Gopal¹,

Zhou²,

Knobler³

et al. 2011

RNA

101

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Single-stranded RNAs (ssRNAs) longer than a few hundred nucleotides do not have a unique structure in solution. Their equilibrium properties therefore reflect the average of an ensemble of structures. We use cryo-electron microscopy to image projections of individual long ssRNA molecules and characterize the anisotropy of their ensembles in solution. A flattened prolate volume is found to best represent the shapes of these ensembles. The measured sizes and anisotropies are in good agreement with complementary determinations using small-angle X-ray scattering and coarse-grained molecular dynamics simulations. A long viral ssRNA is compared with shorter noncoding transcripts to demonstrate that prolate geometry and flatness are generic properties independent of sequence length and origin. The anisotropy persists under physiological as well as low-ionic-strength conditions, revealing a direct correlation between secondary structure asymmetry and 3D shape and size. We discuss the physical origin of the generic anisotropy and its biological implications.

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Section: Discussionsupporting

confidence: 59%

Visualizing large RNA molecules in solution

Gopal¹,

Zhou²,

Knobler³

et al. 2011

RNA

101

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“…Despite the observation of other weak signals in these data that do not correspond to helices (Fig. 4), M2-net detects only a single false positive, an altP19c helix predicted for the catalytic domain of RNase P that disagrees with the tip of the P19 domain presumed in the conventional secondary structure of this molecule (28). The region including these helices has not been directly visualized by crystallographic analysis (28).…”

Section: Resultsmentioning

confidence: 87%

“…4), M2-net detects only a single false positive, an altP19c helix predicted for the catalytic domain of RNase P that disagrees with the tip of the P19 domain presumed in the conventional secondary structure of this molecule (28). The region including these helices has not been directly visualized by crystallographic analysis (28). Compensatory mutagenesis experiments indicate that the region does form the predicted alt-P19 in solution (Fig.…”

Section: Resultsmentioning

confidence: 99%

RNA structure inference through chemical mapping after accidental or intentional mutations

Cheng

Kladwang

Yesselman

et al. 2017

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

104

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Despite the critical roles RNA structures play in regulating gene expression, sequencing-based methods for experimentally determining RNA base pairs have remained inaccurate. Here, we describe a multidimensional chemical-mapping method called "mutate-and-map read out through next-generation sequencing" (M2-seq) that takes advantage of sparsely mutated nucleotides to induce structural perturbations at partner nucleotides and then detects these events through dimethyl sulfate (DMS) probing and mutational profiling. In special cases, fortuitous errors introduced during DNA template preparation and RNA transcription are sufficient to give M2-seq helix signatures; these signals were previously overlooked or mistaken for correlated double-DMS events. When mutations are enhanced through error-prone PCR, in vitro M2-seq experimentally resolves 33 of 68 helices in diverse structured RNAs including ribozyme domains, riboswitch aptamers, and viral RNA domains with a single false positive. These inferences do not require energy minimization algorithms and can be made by either direct visual inspection or by a neural-network-inspired algorithm called M2-net. Measurements on the P4-P6 domain of the Tetrahymena group I ribozyme embedded in Xenopus egg extract demonstrate the ability of M2-seq to detect RNA helices in a complex biological environment.RNA structure modeling | chemical mapping | neural network | mutational profiling | Xenopus egg extract I nference of RNA structures using experimental data is a crucial step in understanding RNA's biological functions throughout living organisms. Chemical-mapping methods have the potential to reveal RNA structural features in situ by probing which nucleotides are protected from attack by chemical modifiers. The resulting experimental data can be used to guide secondary-structure modeling by computational algorithms, raising the prospect of transcriptome-wide RNA structure determination (1, 2).Despite these advances, the accuracy of RNA structure inference through chemical mapping and sequencing remains under question (3-8). For example, models of the 9-kb HIV-1 RNA genome have been repeatedly revised with updates to the selective 2′-OH acylation by primer extension (SHAPE) protocol, data processing, and computational assumptions (2, 9-11), and the majority of this RNA's helices remain uncertain. Even for small RNA domains, SHAPE and dimethyl sulfate (DMS) (methylation of N1 and N3 atoms at A and C) have produced misleading secondary structures for ribosomal domains and blind modeling challenges that have been falsified through crystallography or mutagenesis (3,7,12,13). In alternative approaches based on photoactivated cross-linkers, many helix detections appear to be false positives, based on ribosome data in vitro and in vivo (14,15).The confidence and structural accuracy of chemical-mapping methods can be improved by applying perturbations to the RNA sequence before chemical modification. In the mutate-and-map strategy, mapping not just the target RNA sequence but also a compre...

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“…Specifically, SAXS data were collected on SMARCAL1(325-954) in buffer containing 20 mM HEPES (pH 7.6), 200 mM NaCl, 2 mM MgCl 2 , 0.5 mM TCEP, 5% glycerol, and 1% sucrose. The protein sample was prepared for SAXS as described (Kazantsev et al 2011) using a Shodex KW402.5 size exclusion column. The peak fraction was analyzed for SAXS as a 2/3 dilution series starting from 3 mg/mL.…”

Section: Homology Modelingmentioning

confidence: 99%

SMARCAL1 catalyzes fork regression and Holliday junction migration to maintain genome stability during DNA replication

Bétous¹,

Mason²,

Rambo³

et al. 2012

Genes Dev.

Self Cite

256

307

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SMARCAL1 (SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily A-like1) maintains genome integrity during DNA replication. Here we investigated its mechanism of action. We found that SMARCAL1 travels with elongating replication forks, and its absence leads to MUS81-dependent double-strand break formation. Binding to specific nucleic acid substrates activates SMARCAL1 activity in a reaction that requires its HARP2 (Hep-A-related protein 2) domain. Homology modeling indicates that the HARP domain is similar in structure to the DNA-binding domain of the PUR proteins. Limited proteolysis, small-angle X-ray scattering, and functional assays indicate that the core enzymatic unit consists of the HARP2 and ATPase domains that fold into a stable structure. Surprisingly, SMARCAL1 is capable of binding three-way and four-way Holliday junctions and model replication forks that lack a designed ssDNA region. Furthermore, SMARCAL1 remodels these DNA substrates by promoting branch migration and fork regression. SMARCAL1 mutations that cause Schimke immunoosseous dysplasia or that inactivate the HARP2 domain abrogate these activities. These results suggest that SMARCAL1 continuously surveys replication forks for damage. If damage is present, it remodels the fork to promote repair and restart. Failures in the process lead to activation of an alternative repair mechanism that depends on MUS81-catalyzed cleavage of the damaged fork.

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Solution structure of RNase P RNA

Cited by 46 publications

References 80 publications

Visualizing large RNA molecules in solution

Visualizing large RNA molecules in solution

RNA structure inference through chemical mapping after accidental or intentional mutations

SMARCAL1 catalyzes fork regression and Holliday junction migration to maintain genome stability during DNA replication

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