A mutate-and-map strategy for inferring base pairs in structured nucleic acids: proof of concept on a DNA/RNA helix

Integrated multiplexed assays of variant effect reveal determinants of catechol-O-methyltransferase gene expression

Multiplexed assays of variant effect are powerful methods to profile the consequences of rare variants on gene expression and organismal fitness. Yet, few studies have integrated several multiplexed assays to map variant effects on gene expression in coding sequences. Here, we pioneered a multiplexed assay based on polysome profiling to measure variant effects on translation at scale, uncovering single-nucleotide variants that increase or decrease ribosome load. By combining high-throughput ribosome load data with multiplexed mRNA and protein abundance readouts, we mapped the cis-regulatory landscape of thousands of catechol-O-methyltransferase (COMT) variants from RNA to protein and found numerous coding variants that alter COMT expression. Finally, we trained machine learning models to map signatures of variant effects on COMT gene expression and uncovered both directional and divergent impacts across expression layers. Our analyses reveal expression phenotypes for thousands of variants in COMT and highlight variant effects on both single and multiple layers of expression. Our findings prompt future studies that integrate several multiplexed assays for the readout of gene expression.

Integrated multiplexed assays of variant effect reveal cis-regulatory determinants of catechol-O-methyltransferase gene expression

Multiplexed assays of variant effect are powerful methods to profile the consequences of rare variants on gene expression and organismal fitness. Yet, few studies have integrated several multiplexed assays to map variant effects on gene expression in coding sequences. Here, we pioneered a multiplexed assay based on polysome profiling to measure variant effects on translation at scale, uncovering single-nucleotide variants that increase and decrease ribosome load. By combining high-throughput ribosome load data with multiplexed mRNA and protein abundance readouts, we mapped the cis-regulatory landscape of thousands of catechol-O-methyltransferase (COMT) variants from RNA to protein and found numerous coding variants that alter COMT expression. Finally, we trained machine learning models to map signatures of variant effects on COMT gene expression and uncovered both directional and divergent impacts across expression layers. Our analyses reveal expression phenotypes for thousands of variants in COMT and highlight variant effects on both single and multiple layers of expression. Our findings prompt future studies that integrate several multiplexed assays for the readout of gene expression.

RNA:RNA interaction in ternary complexes resolved by chemical probing

RNA regulation can be performed by a second targeting RNA molecule, such as in the microRNA regulation mechanism. Selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) probes the structure of RNA molecules and can resolve RNA:protein interactions, but RNA:RNA interactions have not yet been addressed with this technique. Here, we apply SHAPE to investigate RNA-mediated binding processes in RNA:RNA and RNA:RNA-RBP complexes. We use RNA:RNA binding by SHAPE (RABS) to investigate microRNA-34a (miR-34a) binding its mRNA target, the silent information regulator 1 (mSIRT1), both with and without the Argonaute protein, constituting the RNA-induced silencing complex (RISC). We show that the seed of the mRNA target must be bound to the microRNA loaded into RISC to enable further binding of the compensatory region by RISC, while the naked miR-34a is able to bind the compensatory region without seed interaction. The method presented here provides complementary structural evidence for the commonly performed luciferase-assay-based evaluation of microRNA binding-site efficiency and specificity on the mRNA target site and could therefore be used in conjunction with it. The method can be applied to any nucleic acid-mediated RNA- or RBP-binding process, such as splicing, antisense RNA binding, or regulation by RISC, providing important insight into the targeted RNA structure.

Programmable antivirals targeting critical conserved viral RNA secondary structures from influenza A virus and SARS-CoV-2

Influenza A virus's (IAV's) frequent genetic changes challenge vaccine strategies and engender resistance to current drugs. We sought to identify conserved and essential RNA secondary structures within IAV's genome that are predicted to have greater constraints on mutation in response to therapeutic targeting. We identified and genetically validated an RNA structure (packaging stem-loop 2 (PSL2)) that mediates in vitro packaging and in vivo disease and is conserved across all known IAV isolates. A PSL2-targeting locked nucleic acid (LNA), administered 3 d after, or 14 d before, a lethal IAV inoculum provided 100% survival in mice, led to the development of strong immunity to rechallenge with a tenfold lethal inoculum, evaded attempts to select for resistance and retained full potency against neuraminidase inhibitor-resistant virus. Use of an analogous approach to target SARS-CoV-2, prophylactic administration of LNAs specific for highly conserved RNA structures in the viral genome, protected hamsters from efficient transmission of the SARS-CoV-2 USA_WA1/2020 variant. These findings highlight the potential applicability of this approach to any virus of interest via a process we term 'programmable antivirals', with implications for antiviral prophylaxis and post-exposure therapy.

OUP accepted manuscript

Retrons are bacterial retroelements that produce single-stranded, reverse-transcribed DNA (RT-DNA) that is a critical part of a newly discovered phage defense system. Short retron RT-DNAs are produced from larger, structured RNAs via a unique 2′-5′ initiation and a mechanism for precise termination that is not yet understood. Interestingly, retron reverse transcriptases (RTs) typically lack an RNase H domain and, therefore, depend on endogenous RNase H1 to remove RNA templates from RT-DNA. We find evidence for an expanded role of RNase H1 in the mechanism of RT-DNA termination, beyond the mere removal of RNA from RT-DNA:RNA hybrids. We show that endogenous RNase H1 determines the termination point of the retron RT-DNA, with differing effects across retron subtypes, and that these effects can be recapitulated using a reduced, in vitro system. We exclude mechanisms of termination that rely on steric effects of RNase H1 or RNA secondary structure and, instead, propose a model in which the tertiary structure of the single-stranded RT-DNA and remaining RNA template results in termination. Finally, we show that this mechanism affects cellular function, as retron-based phage defense is weaker in the absence of RNase H1.

Folding heterogeneity in the essential human telomerase RNA three-way junction

Telomeres safeguard the genome by suppressing illicit DNA damage responses at chromosome termini. To compensate for incomplete DNA replication at telomeres, most continually dividing cells, including many cancers, express the telomerase ribonucleoprotein (RNP) complex. Telomerase maintains telomere length by catalyzing de novo synthesis of short DNA repeats using an internal telomerase RNA (TR) template. TRs from diverse species harbor structurally conserved domains that contribute to RNP biogenesis and function. In vertebrate TRs, the conserved regions 4 and 5 (CR4/5) fold into a three-way junction (TWJ) that binds directly to the telomerase catalytic protein subunit and is required for telomerase function. We have analyzed the structural properties of the human TR (hTR) CR4/5 domain using a combination of in vitro chemical mapping, secondary structural modeling, and single-molecule structural analysis. Our data suggest the essential P6.1 stem-loop within CR4/5 is not stably folded in the absence of the telomerase reverse transcriptase in vitro. Rather, the hTR CR4/5 domain adopts a heterogeneous ensemble of conformations. Finally, single-molecule FRET measurements of CR4/5 and a mutant designed to stabilize the P6.1 stem demonstrate that TERT binding selects for a structural conformation of CR4/5 that is not the dominant state of the TERT-free in vitro RNA ensemble.

Advances in RNA 3D Structure Modeling Using Experimental Data

RNA is a unique bio-macromolecule that can both record genetic information and perform biological functions in a variety of molecular processes, including transcription, splicing, translation, and even regulating protein function. RNAs adopt specific three-dimensional conformations to enable their functions. Experimental determination of high-resolution RNA structures using x-ray crystallography is both laborious and demands expertise, thus, hindering our comprehension of RNA structural biology. The computational modeling of RNA structure was a milestone in the birth of bioinformatics. Although computational modeling has been greatly improved over the last decade showing many successful cases, the accuracy of such computational modeling is not only length-dependent but also varies according to the complexity of the structure. To increase credibility, various experimental data were integrated into computational modeling. In this review, we summarize the experiments that can be integrated into RNA structure modeling as well as the computational methods based on these experimental data. We also demonstrate how computational modeling can help the experimental determination of RNA structure. We highlight the recent advances in computational modeling which can offer reliable structure models using high-throughput experimental data.

Viral RNA structure analysis using DMS-MaPseq

RNA structure is critically important to RNA viruses in every part of the replication cycle. RNA structure is also utilized by DNA viruses in order to regulate gene expression and interact with host factors. Advances in next-generation sequencing have greatly enhanced the utility of chemical probing in order to analyze RNA structure. This review will cover some recent viral RNA structural studies using chemical probing and next-generation sequencing as well as the advantages of dimethyl sulfate (DMS)-mutational profiling and sequencing (MaPseq). DMS-MaPseq is a robust assay that can easily modify RNA in vitro, in cell and in virion. A detailed protocol for whole-genome DMS-MaPseq from cells transfected with HIV-1 and the structure of TAR as determined by DMS-MaPseq is presented. DMS-MaPseq has the ability to answer a variety of integral questions about viral RNA, including how they change in different environments and when interacting with different host factors.

RNA structure inference through chemical mapping after accidental or intentional mutations

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 through multidimensional chemical mapping

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 (M2), 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'.

Direct identification of base-paired RNA nucleotides by correlated chemical probing

Many RNA molecules fold into complex secondary and tertiary structures that play critical roles in biological function. Among the best-established methods for examining RNA structure are chemical probing experiments, which can report on local nucleotide structure in a concise and extensible manner. While probing data are highly useful for inferring overall RNA secondary structure, these data do not directly measure through-space base-pairing interactions. We recently introduced an approach for single-molecule correlated chemical probing with dimethyl sulfate (DMS) that measures RNA interaction groups by mutational profiling (RING-MaP). RING-MaP experiments reveal diverse through-space interactions corresponding to both secondary and tertiary structure. Here we develop a framework for using RING-MaP data to directly and robustly identify canonical base pairs in RNA. When applied to three representative RNAs, this framework identified 20%-50% of accepted base pairs with a <10% false discovery rate, allowing detection of 88% of duplexes containing four or more base pairs, including pseudoknotted pairs. We further show that base pairs determined from RING-MaP analysis significantly improve secondary structure modeling. RING-MaP-based correlated chemical probing represents a direct, experimentally concise, and accurate approach for detection of individual base pairs and helices and should greatly facilitate structure modeling for complex RNAs.

Computational analysis of RNA structures with chemical probing data

RNAs play various roles, not only as the genetic codes to synthesize proteins, but also as the direct participants of biological functions determined by their underlying high-order structures. Although many computational methods have been proposed for analyzing RNA structures, their accuracy and efficiency are limited, especially when applied to the large RNAs and the genome-wide data sets. Recently, advances in parallel sequencing and high-throughput chemical probing technologies have prompted the development of numerous new algorithms, which can incorporate the auxiliary structural information obtained from those experiments. Their potential has been revealed by the secondary structure prediction of ribosomal RNAs and the genome-wide ncRNA function annotation. In this review, the existing probing-directed computational methods for RNA secondary and tertiary structure analysis are discussed.

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

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 near-crystallographic 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.

Transcriptome-wide mapping of pseudouridines: pseudouridine synthases modify specific mRNAs in S. cerevisiae

We developed a novel technique, called pseudouridine site identification sequencing (PSI-seq), for the transcriptome-wide mapping of pseudouridylation sites with single-base resolution from cellular RNAs based on the induced termination of reverse transcription specifically at pseudouridines following CMCT treatment. PSI-seq analysis of RNA samples from S. cerevisiae correctly detected all of the 43 known pseudouridines in yeast 18S and 25S ribosomal RNA with high specificity. Moreover, application of PSI-seq to the yeast transcriptome revealed the presence of site-specific pseudouridylation within dozens of mRNAs, including RPL11a, TEF1, and other genes implicated in translation. To identify the mechanisms responsible for mRNA pseudouridylation, we genetically deleted candidate pseudouridine synthase (Pus) enzymes and reconstituted their activities in vitro. These experiments demonstrated that the Pus1 enzyme was necessary and sufficient for pseudouridylation of RPL11a mRNA, whereas Pus4 modified TEF1 mRNA, and Pus6 pseudouridylated KAR2 mRNA. Finally, we determined that modification of RPL11a at Ψ -68 was observed in RNA from the related yeast S. mikitae, and Ψ -239 in TEF1 mRNA was maintained in S. mikitae as well as S. pombe, indicating that these pseudouridylations are ancient, evolutionarily conserved RNA modifications. This work establishes that site-specific pseudouridylation of eukaryotic mRNAs is a genetically programmed RNA modification that naturally occurs in multiple yeast transcripts via distinct mechanisms, suggesting that mRNA pseudouridylation may provide an important novel regulatory function. The approach and strategies that we report here should be generally applicable to the discovery of pseudouridylation, or other RNA modifications, in diverse biological contexts.

Interstrand cross-link and bioconjugate formation in RNA from a modified nucleotide

RNA oligonucleotides containing a phenyl selenide derivative of 5-methyluridine were chemically synthesized by solid-phase synthesis. The phenyl selenide is rapidly converted to an electrophilic, allylic phenyl seleneate under mild oxidative conditions. The phenyl seleneate yields interstrand cross-links when part of a duplex and is useful for synthesizing oligonucleotide conjugates. Formation of the latter is illustrated by reaction of an oligonucleotide containing the phenyl selenide with amino acids in the presence of mild oxidant. The products formed are analogous to those observed in tRNA that are believed to be formed posttranslationally via a biosynthetic intermediate that is chemically homologous to the phenyl seleneate.

Standardization of RNA chemical mapping experiments

Chemical mapping experiments offer powerful information about RNA structure but currently involve ad hoc assumptions in data processing. We show that simple dilutions, referencing standards (GAGUA hairpins), and HiTRACE/MAPseeker analysis allow rigorous overmodification correction, background subtraction, and normalization for electrophoretic data and a ligation bias correction needed for accurate deep sequencing data. Comparisons across six noncoding RNAs stringently test the proposed standardization of dimethyl sulfate (DMS), 2′-OH acylation (SHAPE), and carbodiimide measurements. Identification of new signatures for extrahelical bulges and DMS “hot spot” pockets (including tRNA A58, methylated in vivo) illustrates the utility and necessity of standardization for quantitative RNA mapping.

The mutate-and-map protocol for inferring base pairs in structured RNA

Chemical mapping is a widespread technique for structural analysis of nucleic acids in which a molecule's reactivity to different probes is quantified at single nucleotide resolution and used to constrain structural modeling. This experimental framework has been extensively revisited in the past decade with new strategies for high-throughput readouts, chemical modification, and rapid data analysis. Recently, we have coupled the technique to high-throughput mutagenesis. Point mutations of a base paired nucleotide can lead to exposure of not only that nucleotide but also its interaction partner. Systematically carrying out the mutation and mapping for the entire system gives an experimental approximation of the molecule's "contact map." Here, we give our in-house protocol for this "mutate-and-map" (M2) strategy, based on 96-well capillary electrophoresis, and we provide practical tips on interpreting the data to infer nucleic acid structure.

HiTRACE-Web: an online tool for robust analysis of high-throughput capillary electrophoresis

To facilitate the analysis of large-scale high-throughput capillary electrophoresis data, we previously proposed a suite of efficient analysis software named HiTRACE (High Throughput Robust Analysis of Capillary Electrophoresis). HiTRACE has been used extensively for quantitating data from RNA and DNA structure mapping experiments, including mutate-and-map contact inference, chromatin footprinting, the Eterna RNA design project and other high-throughput applications. However, HiTRACE is based on a suite of command-line MATLAB scripts that requires nontrivial efforts to learn, use and extend. Here, we present HiTRACE-Web, an online version of HiTRACE that includes standard features previously available in the command-line version and additional features such as automated band annotation and flexible adjustment of annotations, all via a user-friendly environment. By making use of parallelization, the on-line workflow is also faster than software implementations available to most users on their local computers. Free access: http://hitrace.org.

An RNA Mapping DataBase for curating RNA structure mapping experiments

SUMMARY

We have established an RNA mapping database (RMDB) to enable structural, thermodynamic and kinetic comparisons across single-nucleotide-resolution RNA structure mapping experiments. The volume of structure mapping data has greatly increased since the development of high-throughput sequencing techniques, accelerated software pipelines and large-scale mutagenesis. For scientists wishing to infer relationships between RNA sequence/structure and these mapping data, there is a need for a database that is curated, tagged with error estimates and interfaced with tools for sharing, visualization, search and meta-analysis. Through its on-line front-end, the RMDB allows users to explore single-nucleotide-resolution mapping data in heat-map, bar-graph and colored secondary structure graphics; to leverage these data to generate secondary structure hypotheses; and to download the data in standardized and computer-friendly files, including the RDAT and community-consensus SNRNASM formats. At the time of writing, the database houses 53 entries, describing more than 2848 experiments of 1098 RNA constructs in several solution conditions and is growing rapidly.

AVAILABILITY

Freely available on the web at http://rmdb.stanford.edu.

CONTACT

rhiju@stanford.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics Online.

Ultraviolet shadowing of RNA can cause significant chemical damage in seconds

Chemical purity of RNA samples is important for high-precision studies of RNA folding and catalytic behavior, but photodamage accrued during ultraviolet (UV) shadowing steps of sample preparation can reduce this purity. Here, we report the quantitation of UV-induced damage by using reverse transcription and single-nucleotide-resolution capillary electrophoresis. We found photolesions in a dozen natural and artificial RNAs; across multiple sequence contexts, dominantly at but not limited to pyrimidine doublets; and from multiple lamps recommended for UV shadowing. Irradiation time-courses revealed detectable damage within a few seconds of exposure for 254 nm lamps held at a distance of 5 to 10 cm from 0.5-mm thickness gels. Under these conditions, 200-nucleotide RNAs subjected to 20 seconds of UV shadowing incurred damage to 16-27% of molecules; and, due to a 'skin effect', the molecule-by-molecule distribution of lesions gave 4-fold higher variance than a Poisson distribution. Thicker gels, longer wavelength lamps, and shorter exposure times reduced but did not eliminate damage. These results suggest that RNA biophysical studies should report precautions taken to avoid artifactual heterogeneity from UV shadowing.

Automated RNA structure prediction uncovers a kink-turn linker in double glycine riboswitches

The tertiary structures of functional RNA molecules remain difficult to decipher. A new generation of automated RNA structure prediction methods may help address these challenges but have not yet been experimentally validated. Here we apply four prediction tools to a class of double glycine riboswitches that can bind two ligands cooperatively. A novel method (BPPalign), RMdetect, JAR3D, and Rosetta 3D modeling give consistent predictions for a new stem P0 and a kink-turn motif. These elements structure the linker between the RNAs' double aptamers. Chemical mapping on the Fusobacterium nucleatum riboswitch with N-methylisatoic anhydride, dimethyl sulfate and 1-cyclohexyl-3-(2-morpholinoethyl)carbodiimide metho-p-toluenesulfonate probing, mutate-and-map studies, and mutation/rescue experiments all provide strong evidence for the structured linker. Under solution conditions that permit rigorous thermodynamic analysis, disrupting this helix-junction-helix structure gives 120- and 6-30-fold poorer dissociation constants for the RNA's two glycine-binding transitions, corresponding to an overall energetic impact of 4.3 ± 0.5 kcal/mol. Prior biochemical and crystallography studies did not include this critical element due to over-truncation of the RNA. We speculate that several further undiscovered elements are likely to exist in the flanking regions of this and other functional RNAs, and automated prediction tools can play a useful role in their detection and dissection.

A two-dimensional mutate-and-map strategy for non-coding RNA structure

Non-coding RNAs fold into precise base-pairing patterns to carry out critical roles in genetic regulation and protein synthesis, but determining RNA structure remains difficult. Here, we show that coupling systematic mutagenesis with high-throughput chemical mapping enables accurate base-pair inference of domains from ribosomal RNA, ribozymes and riboswitches. For a six-RNA benchmark that has challenged previous chemical/computational methods, this 'mutate-and-map' strategy gives secondary structures that are in agreement with crystallography (helix error rates, 2%), including a blind test on a double-glycine riboswitch. Through modelling of partially ordered states, the method enables the first test of an interdomain helix-swap hypothesis for ligand-binding cooperativity in a glycine riboswitch. Finally, the data report on tertiary contacts within non-coding RNAs, and coupling to the Rosetta/FARFAR algorithm gives nucleotide-resolution three-dimensional models (helix root-mean-squared deviation, 5.7 Å) of an adenine riboswitch. These results establish a promising two-dimensional chemical strategy for inferring the secondary and tertiary structures that underlie non-coding RNA behaviour.

Understanding the errors of SHAPE-directed RNA structure modeling

Single-nucleotide-resolution chemical mapping for structured RNA is being rapidly advanced by new chemistries, faster readouts, and coupling to computational algorithms. Recent tests have shown that selective 2'-hydroxyl acylation by primer extension (SHAPE) can give near-zero error rates (0-2%) in modeling the helices of RNA secondary structure. Here, we benchmark the method using six molecules for which crystallographic data are available: tRNA(phe) and 5S rRNA from Escherichia coli, the P4-P6 domain of the Tetrahymena group I ribozyme, and ligand-bound domains from riboswitches for adenine, cyclic di-GMP, and glycine. SHAPE-directed modeling of these highly structured RNAs gave an overall false negative rate (FNR) of 17% and a false discovery rate (FDR) of 21%, with at least one helix prediction error in five of the six cases. Extensive variations of data processing, normalization, and modeling parameters did not significantly mitigate modeling errors. Only one varation, filtering out data collected with deoxyinosine triphosphate during primer extension, gave a modest improvement (FNR = 12%, and FDR = 14%). The residual structure modeling errors are explained by the insufficient information content of these RNAs' SHAPE data, as evaluated by a nonparametric bootstrapping analysis. Beyond these benchmark cases, bootstrapping suggests a low level of confidence (<50%) in the majority of helices in a previously proposed SHAPE-directed model for the HIV-1 RNA genome. Thus, SHAPE-directed RNA modeling is not always unambiguous, and helix-by-helix confidence estimates, as described herein, may be critical for interpreting results from this powerful methodology.

Modeling and automation of sequencing-based characterization of RNA structure

Sequence census methods reduce molecular measurements such as transcript abundance and protein-nucleic acid interactions to counting problems via DNA sequencing. We focus on a novel assay utilizing this approach, called selective 2'-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq), that can be used to characterize RNA secondary and tertiary structure. We describe a fully automated data analysis pipeline for SHAPE-Seq analysis that includes read processing, mapping, and structural inference based on a model of the experiment. Our methods rely on the solution of a series of convex optimization problems for which we develop efficient and effective numerical algorithms. Our results can be easily extended to other chemical probes of RNA structure, and also generalized to modeling polymerase drop-off in other sequence census-based experiments.

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

New regulatory roles continue to emerge for both natural and engineered noncoding RNAs, many of which have specific secondary and tertiary structures essential to their function. Thus there is a growing need to develop technologies that enable rapid characterization of structural features within complex RNA populations. We have developed a high-throughput technique, SHAPE-Seq, that can simultaneously measure quantitative, single nucleotide-resolution secondary and tertiary structural information for hundreds of RNA molecules of arbitrary sequence. SHAPE-Seq combines selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) chemistry with multiplexed paired-end deep sequencing of primer extension products. This generates millions of sequencing reads, which are then analyzed using a fully automated data analysis pipeline, based on a rigorous maximum likelihood model of the SHAPE-Seq experiment. We demonstrate the ability of SHAPE-Seq to accurately infer secondary and tertiary structural information, detect subtle conformational changes due to single nucleotide point mutations, and simultaneously measure the structures of a complex pool of different RNA molecules. SHAPE-Seq thus represents a powerful step toward making the study of RNA secondary and tertiary structures high throughput and accessible to a wide array of scientific pursuits, from fundamental biological investigations to engineering RNA for synthetic biological systems.

HiTRACE: high-throughput robust analysis for capillary electrophoresis

MOTIVATION

Capillary electrophoresis (CE) of nucleic acids is a workhorse technology underlying high-throughput genome analysis and large-scale chemical mapping for nucleic acid structural inference. Despite the wide availability of CE-based instruments, there remain challenges in leveraging their full power for quantitative analysis of RNA and DNA structure, thermodynamics and kinetics. In particular, the slow rate and poor automation of available analysis tools have bottlenecked a new generation of studies involving hundreds of CE profiles per experiment.

RESULTS

We propose a computational method called high-throughput robust analysis for capillary electrophoresis (HiTRACE) to automate the key tasks in large-scale nucleic acid CE analysis, including the profile alignment that has heretofore been a rate-limiting step in the highest throughput experiments. We illustrate the application of HiTRACE on 13 datasets representing 4 different RNAs, 3 chemical modification strategies and up to 480 single mutant variants; the largest datasets each include 87 360 bands. By applying a series of robust dynamic programming algorithms, HiTRACE outperforms prior tools in terms of alignment and fitting quality, as assessed by measures including the correlation between quantified band intensities between replicate datasets. Furthermore, while the smallest of these datasets required 7-10 h of manual intervention using prior approaches, HiTRACE quantitation of even the largest datasets herein was achieved in 3-12 min. The HiTRACE method, therefore, resolves a critical barrier to the efficient and accurate analysis of nucleic acid structure in experiments involving tens of thousands of electrophoretic bands.

A mutate-and-map strategy accurately infers the base pairs of a 35-nucleotide model RNA

We present a rapid experimental strategy for inferring base pairs in structured RNAs via an information-rich extension of classic chemical mapping approaches. The mutate-and-map method, previously applied to a DNA/RNA helix, systematically searches for single mutations that enhance the chemical accessibility of base-pairing partners distant in sequence. To test this strategy for structured RNAs, we have carried out mutate-and-map measurements for a 35-nt hairpin, called the MedLoop RNA, embedded within an 80-nt sequence. We demonstrate the synthesis of all 105 single mutants of the MedLoop RNA sequence and present high-throughput DMS, CMCT, and SHAPE modification measurements for this library at single-nucleotide resolution. The resulting two-dimensional data reveal visually clear, punctate features corresponding to RNA base pair interactions as well as more complex features; these signals can be qualitatively rationalized by comparison to secondary structure predictions. Finally, we present an automated, sequence-blind analysis that permits the confident identification of nine of the 10 MedLoop RNA base pairs at single-nucleotide resolution, while discriminating against all 1460 false-positive base pairs. These results establish the accuracy and information content of the mutate-and-map strategy and support its feasibility for rapidly characterizing the base-pairing patterns of larger and more complex RNA systems.