DMS-MaPseq for genome-wide or targeted RNA structure probing in vivo

miCLIP-MaPseq, a Substrate Identification Approach for Radical SAM RNA Methylating Enzymes

Although present across bacteria, the large family of radical SAM RNA methylating enzymes is largely uncharacterized. Escherichia coli RlmN, the founding member of the family, methylates an adenosine in 23S rRNA and several tRNAs to yield 2-methyladenosine (m²A). However, varied RNA substrate specificity among RlmN enzymes, combined with the ability of certain family members to generate 8-methyladenosine (m⁸A), makes functional predictions across this family challenging. Here, we present a method for unbiased substrate identification that exploits highly efficient, mechanism-based cross-linking between the enzyme and its RNA substrates. Additionally, by determining that the thermostable group II intron reverse transcriptase introduces mismatches at the site of the cross-link, we have identified the precise positions of RNA modification using mismatch profiling. These results illustrate the capability of our method to define enzyme-substrate pairs and determine modification sites of the largely uncharacterized radical SAM RNA methylating enzyme family.

New Era of Studying RNA Secondary Structure and Its Influence on Gene Regulation in Plants

The dynamic structure of RNA plays a central role in post-transcriptional regulation of gene expression such as RNA maturation, degradation, and translation. With the rise of next-generation sequencing, the study of RNA structure has been transformed from in vitro low-throughput RNA structure probing methods to in vivo high-throughput RNA structure profiling. The development of these methods enables incremental studies on the function of RNA structure to be performed, revealing new insights of novel regulatory mechanisms of RNA structure in plants. Genome-wide scale RNA structure profiling allows us to investigate general RNA structural features over 10s of 1000s of mRNAs and to compare RNA structuromes between plant species. Here, we provide a comprehensive and up-to-date overview of: (i) RNA structure probing methods; (ii) the biological functions of RNA structure; (iii) genome-wide RNA structural features corresponding to their regulatory mechanisms; and (iv) RNA structurome evolution in plants.

Quantitative Understanding of SHAPE Mechanism from RNA Structure and Dynamics Analysis

The selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) method probes RNA local structural and dynamic information at single nucleotide resolution. To gain quantitative insights into the relationship between nucleotide flexibility, RNA 3D structure, and SHAPE reactivity, we develop a 3D Structure-SHAPE Relationship model (3DSSR) to rebuild SHAPE profiles from 3D structures. The model starts from RNA structures and combines nucleotide interaction strength and conformational propensity, ligand (SHAPE reagent) accessibility, and base-pairing pattern through a composite function to quantify the correlation between SHAPE reactivity and nucleotide conformational stability. The 3DSSR model shows the relationship between SHAPE reactivity and RNA structure and energetics. Comparisons between the 3DSSR-predicted SHAPE profile and the experimental SHAPE data show correlation, suggesting that the extracted analytical function may have captured the key factors that determine the SHAPE reactivity profile. Furthermore, the theory offers an effective method to sieve RNA 3D models and exclude models that are incompatible with experimental SHAPE data.

Mapping platinum adducts on yeast ribosomal RNA using high-throughput sequencing

Methods to map small-molecule binding sites on cellular RNAs are important for understanding interactions with both endogenous and exogenous compounds. Pt(ii) reagents are well-known DNA and RNA crosslinking agents, but sequence-specific and genome-wide identification of Pt targets following in-cell treatment is challenging. Here we describe application of high-throughput 'Pt-Seq' to identify Pt-rRNA adducts following treatment of S. cerevisiae with cisplatin.

A Stress Response that Monitors and Regulates mRNA Structure Is Central to Cold Shock Adaptation

Temperature influences the structural and functional properties of cellular components, necessitating stress responses to restore homeostasis following temperature shift. Whereas the circuitry controlling the heat shock response is well understood, that controlling the E. coli cold shock adaptation program is not. We found that during the growth arrest phase (acclimation) that follows shift to low temperature, protein synthesis increases, and open reading frame (ORF)-wide mRNA secondary structure decreases. To identify the regulatory system controlling this process, we screened for players required for increased translation. We identified a two-member mRNA surveillance system that enables recovery of translation during acclimation: RNase R assures appropriate mRNA degradation and the Csps dynamically adjust mRNA secondary structure to globally modulate protein expression level. An autoregulatory switch in which Csps tune their own expression to cellular demand enables dynamic control of global translation. The universality of Csps in bacteria suggests broad utilization of this control mechanism.

Allele-specific SHAPE-MaP assessment of the effects of somatic variation and protein binding on mRNA structure

The impact of inherited and somatic mutations on messenger RNA (mRNA) structure remains poorly understood. Recent technological advances that leverage next-generation sequencing to obtain experimental structure data, such as SHAPE-MaP, can reveal structural effects of mutations, especially when these data are incorporated into structure modeling. Here, we analyze the ability of SHAPE-MaP to detect the relatively subtle structural changes caused by single-nucleotide mutations. We find that allele-specific sorting greatly improved our detection ability. Thus, we used SHAPE-MaP with a novel combination of clone-free robotic mutagenesis and allele-specific sorting to perform a rapid, comprehensive survey of noncoding somatic and inherited riboSNitches in two cancer-associated mRNAs, TPT1 and LCP1 Using rigorous thermodynamic modeling of the Boltzmann suboptimal ensemble, we identified a subset of mutations that change TPT1 and LCP1 RNA structure, with approximately 14% of all variants identified as riboSNitches. To confirm that these in vitro structures were biologically relevant, we tested how dependent TPT1 and LCP1 mRNA structures were on their environments. We performed SHAPE-MaP on TPT1 and LCP1 mRNAs in the presence or absence of cellular proteins and found that both mRNAs have similar overall folds in all conditions. RiboSNitches identified within these mRNAs in vitro likely exist under biological conditions. Overall, these data reveal a robust mRNA structural landscape where differences in environmental conditions and most sequence variants do not significantly alter RNA structural ensembles. Finally, predicting riboSNitches in mRNAs from sequence alone remains particularly challenging; these data will provide the community with benchmarks for further algorithmic development.

Pervasive Regulatory Functions of mRNA Structure Revealed by High-Resolution SHAPE Probing

mRNAs can fold into complex structures that regulate gene expression. Resolving such structures de novo has remained challenging and has limited our understanding of the prevalence and functions of mRNA structure. We use SHAPE-MaP experiments in living E. coli cells to derive quantitative, nucleotide-resolution structure models for 194 endogenous transcripts encompassing approximately 400 genes. Individual mRNAs have exceptionally diverse architectures, and most contain well-defined structures. Active translation destabilizes mRNA structure in cells. Nevertheless, mRNA structure remains similar between in-cell and cell-free environments, indicating broad potential for structure-mediated gene regulation. We find that the translation efficiency of endogenous genes is regulated by unfolding kinetics of structures overlapping the ribosome binding site. We discover conserved structured elements in 35% of UTRs, several of which we validate as novel protein binding motifs. RNA structure regulates every gene studied here in a meaningful way, implying that most functional structures remain to be discovered.

PATTERNA: transcriptome-wide search for functional RNA elements via structural data signatures

Establishing a link between RNA structure and function remains a great challenge in RNA biology. The emergence of high-throughput structure profiling experiments is revolutionizing our ability to decipher structure, yet principled approaches for extracting information on structural elements directly from these data sets are lacking. We present PATTERNA, an unsupervised pattern recognition algorithm that rapidly mines RNA structure motifs from profiling data. We demonstrate that PATTERNA detects motifs with an accuracy comparable to commonly used thermodynamic models and highlight its utility in automating data-directed structure modeling from large data sets. PATTERNA is versatile and compatible with diverse profiling techniques and experimental conditions.

Functional 5' UTR mRNA structures in eukaryotic translation regulation and how to find them

RNA molecules can fold into intricate shapes that can provide an additional layer of control of gene expression beyond that of their sequence. In this Review, we discuss the current mechanistic understanding of structures in 5' untranslated regions (UTRs) of eukaryotic mRNAs and the emerging methodologies used to explore them. These structures may regulate cap-dependent translation initiation through helicase-mediated remodelling of RNA structures and higher-order RNA interactions, as well as cap-independent translation initiation through internal ribosome entry sites (IRESs), mRNA modifications and other specialized translation pathways. We discuss known 5' UTR RNA structures and how new structure probing technologies coupled with prospective validation, particularly compensatory mutagenesis, are likely to identify classes of structured RNA elements that shape post-transcriptional control of gene expression and the development of multicellular organisms.

RNA2DMut: a web tool for the design and analysis of RNA structure mutations

With the widespread application of high-throughput sequencing, novel RNA sequences are being discovered at an astonishing rate. The analysis of function, however, lags behind. In both the cis- and trans-regulatory functions of RNA, secondary structure (2D base-pairing) plays essential regulatory roles. In order to test RNA function, it is essential to be able to design and analyze mutations that can affect structure. This was the motivation for the creation of the RNA2DMut web tool. With RNA2DMut, users can enter in RNA sequences to analyze, constrain mutations to specific residues, or limit changes to purines/pyrimidines. The sequence is analyzed at each base to determine the effect of every possible point mutation on 2D structure. The metrics used in RNA2DMut rely on the calculation of the Boltzmann structure ensemble and do not require a robust 2D model of RNA structure for designing mutations. This tool can facilitate a wide array of uses involving RNA: for example, in designing and evaluating mutants for biological assays, interrogating RNA-protein interactions, identifying key regions to alter in SELEX experiments, and improving RNA folding and crystallization properties for structural biology. Additional tools are available to help users introduce other mutations (e.g., indels and substitutions) and evaluate their effects on RNA structure. Example calculations are shown for five RNAs that require 2D structure for their function: the MALAT1 mascRNA, an influenza virus splicing regulatory motif, the EBER2 viral noncoding RNA, the Xist lncRNA repA region, and human Y RNA 5. RNA2DMut can be accessed at https://rna2dmut.bb.iastate.edu/.

Statistical modeling of RNA structure profiling experiments enables parsimonious reconstruction of structure landscapes

RNA plays key regulatory roles in diverse cellular processes, where its functionality often derives from folding into and converting between structures. Many RNAs further rely on co-existence of alternative structures, which govern their response to cellular signals. However, characterizing heterogeneous landscapes is difficult, both experimentally and computationally. Recently, structure profiling experiments have emerged as powerful and affordable structure characterization methods, which improve computational structure prediction. To date, efforts have centered on predicting one optimal structure, with much less progress made on multiple-structure prediction. Here, we report a probabilistic modeling approach that predicts a parsimonious set of co-existing structures and estimates their abundances from structure profiling data. We demonstrate robust landscape reconstruction and quantitative insights into structural dynamics by analyzing numerous data sets. This work establishes a framework for data-directed characterization of structure landscapes to aid experimentalists in performing structure-function studies.

Different experimental and computational approaches can be used to study RNA structures. Here, the authors present a computational method for data-directed reconstruction of complex RNA structure landscapes, which predicts a parsimonious set of co-existing structures and estimates their abundances from structure profiling data.

StructureFold2: Bringing chemical probing data into the computational fold of RNA structural analysis

The secondary structure of an RNA is often implicit to its function. Recently, various high-throughput RNA structure probing techniques have been developed to elucidate important RNA structure-function relationships genome-wide. These techniques produce unwieldy experimental data sets that require evaluation with unique computational pipelines. Herein, we present StructureFold2, a user-friendly set of analysis tools that makes precise data processing and detailed downstream analyses of such data sets both available and practical. StructureFold2 processes high-throughput reads sequenced from libraries prepared after experimental probing for reverse transcription (RT) stops generated by chemical modification of RNA at solvent accessible residues. This pipeline is able to analyze reads generated from a variety of structure-probing chemicals (e.g. DMS, glyoxal, SHAPE). Notably, StructureFold2 offers a new fully featured suite of utilities and tools to guide a user through multiple types of analyses. A particular emphasis is placed on analyzing the reactivity patterns of transcripts, complementing their use as folding restraints for predicting RNA secondary structure. StructureFold2 is hosted as a Github repository and is available at (https://github.com/StructureFold2/StructureFold2).

An ultraprocessive, accurate reverse transcriptase encoded by a metazoan group II intron

Group II introns and non-LTR retrotransposons encode a phylogenetically related family of highly processive reverse transcriptases (RTs) that are essential for mobility and persistence of these retroelements. Recent crystallographic studies on members of this RT family have revealed that they are structurally distinct from the retroviral RTs that are typically used in biotechnology. However, quantitative, structure-guided analysis of processivity, efficiency, and accuracy of this alternate RT family has been lacking. Here, we characterize the processivity of a group II intron maturase RT from Eubacterium rectale (E.r), for which high-resolution structural information is available. We find that the E.r. maturase RT (MarathonRT) efficiently copies transcripts at least 10 kb in length and displays superior intrinsic RT processivity compared to commercial enzymes such as Superscript IV (SSIV). The elevated processivity of MarathonRT is at least partly mediated by a loop structure in the finger subdomain that acts as a steric guard (the α-loop). Additionally, we find that a positively charged secondary RNA binding site on the surface of the RT diminishes the primer utilization efficiency of the enzyme, and that reengineering of this surface enhances capabilities of the MarathonRT. Finally, using single-molecule sequencing, we show that the error frequency of MarathonRT is comparable to that of other high-performance RTs, such as SSIV, which were tested in parallel. Our results provide a structural framework for understanding the enhanced processivity of retroelement RTs, and they demonstrate the potential for engineering a powerful new generation of RT tools for application in biotechnology and research.

The Secret Life of RNA: Lessons from Emerging Methodologies

The last past decade has witnessed a revolution in our appreciation of transcriptome complexity and regulation. This remarkable expansion in our knowledge largely originates from the advent of high-throughput methodologies, and the consecutive discovery that up to 90% of eukaryotic genomes are transcribed, thus generating an unanticipated large range of noncoding RNAs (Hangauer et al., 15(4):112, 2014). Besides leading to the identification of new noncoding RNA species, transcriptome-wide studies have uncovered novel layers of posttranscriptional regulatory mechanisms controlling RNA processing, maturation or translation, and each contributing to the precise and dynamic regulation of gene expression. Remarkably, the development of systems-level studies has been accompanied by tremendous progress in the visualization of individual RNA molecules in single cells, such that it is now possible to image RNA species with a single-molecule resolution from birth to translation or decay. Monitoring quantitatively, with unprecedented spatiotemporal resolution, the fate of individual molecules has been key to understanding the molecular mechanisms underlying the different steps of RNA regulation. This has also revealed biologically relevant, intracellular and intercellular heterogeneities in RNA distribution or regulation. More recently, the convergence of imaging and high-throughput technologies has led to the emergence of spatially resolved transcriptomic techniques that provide a means to perform large-scale analyses while preserving spatial information. By generating transcriptome-wide data on single-cell RNA content, or even subcellular RNA distribution, these methodologies are opening avenues to a wide range of network-level studies at the cell and organ-level, and promise to strongly improve disease diagnostic and treatment.In this introductory chapter, we highlight how recently developed technologies aiming at detecting and visualizing RNA molecules have contributed to the emergence of entirely new research fields, and to dramatic progress in our understanding of gene expression regulation.

Structure of a Thermostable Group II Intron Reverse Transcriptase with Template-Primer and Its Functional and Evolutionary Implications

Bacterial group II intron reverse transcriptases (RTs) function in both intron mobility and RNA splicing and are evolutionary predecessors of retrotransposon, telomerase, and retroviral RTs as well as the spliceosomal protein Prp8 in eukaryotes. Here we determined a crystal structure of a full-length thermostable group II intron RT in complex with an RNA template-DNA primer duplex and incoming deoxynucleotide triphosphate (dNTP) at 3.0-Å resolution. We find that the binding of template-primer and key aspects of the RT active site are surprisingly different from retroviral RTs but remarkably similar to viral RNA-dependent RNA polymerases. The structure reveals a host of features not seen previously in RTs that may contribute to distinctive biochemical properties of group II intron RTs, and it provides a prototype for many related bacterial and eukaryotic non-LTR retroelement RTs. It also reveals how protein structural features used for reverse transcription evolved to promote the splicing of both group II and spliceosomal introns.

Base-Resolution Mapping Reveals Distinct m1A Methylome in Nuclear- and Mitochondrial-Encoded Transcripts

Gene expression can be post-transcriptionally regulated via dynamic and reversible RNA modifications. N¹-methyladenosine (m¹A) is a recently identified mRNA modification; however, little is known about its precise location and biogenesis. Here, we develop a base-resolution m¹A profiling method, based on m¹A-induced misincorporation during reverse transcription, and report distinct classes of m¹A methylome in the human transcriptome. m¹A in 5' UTR, particularly those at the mRNA cap, associate with increased translation efficiency. A different, small subset of m¹A exhibit a GUUCRA tRNA-like motif, are evenly distributed in the transcriptome, and are dependent on the methyltransferase TRMT6/61A. Additionally, we show that m¹A is prevalent in the mitochondrial-encoded transcripts. Manipulation of m¹A level via TRMT61B, a mitochondria-localizing m¹A methyltransferase, demonstrates that m¹A in mitochondrial mRNA interferes with translation. Collectively, our approaches reveal distinct classes of m¹A methylome and provide a resource for functional studies of m¹A-mediated epitranscriptomic regulation.

The m1A landscape on cytosolic and mitochondrial mRNA at single-base resolution

Modifications on mRNA offer the potential of regulating mRNA fate post-transcriptionally. Recent studies suggested the widespread presence of N¹-methyladenosine (m¹A), which disrupts Watson-Crick base pairing, at internal sites of mRNAs. These studies lacked the resolution of identifying individual modified bases, and did not identify specific sequence motifs undergoing the modification or an enzymatic machinery catalysing them, rendering it challenging to validate and functionally characterize putative sites. Here we develop an approach that allows the transcriptome-wide mapping of m¹A at single-nucleotide resolution. Within the cytosol, m¹A is present in a low number of mRNAs, typically at low stoichiometries, and almost invariably in tRNA T-loop-like structures, where it is introduced by the TRMT6/TRMT61A complex. We identify a single m¹A site in the mitochondrial ND5 mRNA, catalysed by TRMT10C, with methylation levels that are highly tissue specific and tightly developmentally controlled. m¹A leads to translational repression, probably through a mechanism involving ribosomal scanning or translation. Our findings suggest that m¹A on mRNA, probably because of its disruptive impact on base pairing, leads to translational repression, and is generally avoided by cells, while revealing one case in mitochondria where tight spatiotemporal control over m¹A levels was adopted as a potential means of post-transcriptional regulation.

RNA Regulations and Functions Decoded by Transcriptome-wide RNA Structure Probing

RNA folds into intricate structures that are crucial for its functions and regulations. To date, a multitude of approaches for probing structures of the whole transcriptome, i.e., RNA structuromes, have been developed. Applications of these approaches to different cell lines and tissues have generated a rich resource for the study of RNA structure–function relationships at a systems biology level. In this review, we first introduce the designs of these methods and their applications to study different RNA structuromes. We emphasize their technological differences especially their unique advantages and caveats. We then summarize the structural insights in RNA functions and regulations obtained from the studies of RNA structuromes. And finally, we propose potential directions for future improvements and studies.

HnRNP A1 Alters the Structure of a Conserved Enterovirus IRES Domain to Stimulate Viral Translation

Enteroviruses use a type I Internal Ribosome Entry Site (IRES) structure to facilitate protein synthesis and promote genome replication. Type I IRES elements require auxiliary host proteins to organize RNA structure for 40S ribosomal subunit assembly. Heterogeneous nuclear ribonucleoprotein A1 stimulates enterovirus 71 (EV71) translation in part through specific interactions with its stem loop II (SLII) IRES domain. Here, we determined a conjoined NMR-small angle x-ray scattering structure of the EV71 SLII domain and a mutant that significantly attenuates viral replication by abrogating hnRNP A1 interactions. Native SLII adopts a locally compact structure wherein stacking interactions in a conserved 5'-AUAGC-3' bulge preorganize the adjacent helices at nearly orthogonal orientations. Mutating the bulge sequence to 5'-ACCCC-3' ablates base stacking in the loop and globally reorients the SLII structure. Biophysical titrations reveal that the 5'-AUAGC-3' bulge undergoes a conformational change to assemble a functional hnRNP A1-RNA complex. Importantly, IRES mutations that delete the bulge impair viral translation and completely inhibit replication. Thus, this work provides key details into how an EV71 IRES structure adapts to hijack a cellular protein, and it suggests that the SLII domain is a potential target for antiviral therapy.

Interpreting Reverse Transcriptase Termination and Mutation Events for Greater Insight into the Chemical Probing of RNA

Chemical probing has the power to provide insight into RNA conformation in vivo and in vitro, but interpreting the results depends on methods to detect the chemically modified nucleotides. Traditionally, the presence of modified bases was inferred from their ability to halt reverse transcriptase during primer extension and the locations of termination sites observed by electrophoresis or sequencing. More recently, modification-induced mutations have been used as a readout for chemical probing data. Given the variable propensity for mismatch incorporation and read-through with different reverse transcriptases, we examined how termination and mutation events compare to each other in the same chemical probing experiments. We found that mutations and terminations induced by dimethyl sulfate probing are both specific for methylated bases, but these two measures have surprisingly little correlation and represent largely nonoverlapping indicators of chemical modification data. We also show that specific biases for modified bases depend partly on local sequence context and that different reverse transcriptases show different biases toward reading a modification as a stop or a mutation. These results support approaches that incorporate analysis of both termination and mutation events into RNA probing experiments.

Facile single-stranded DNA sequencing of human plasma DNA via thermostable group II intron reverse transcriptase template switching

High-throughput single-stranded DNA sequencing (ssDNA-seq) of cell-free DNA from plasma and other bodily fluids is a powerful method for non-invasive prenatal testing, and diagnosis of cancers and other diseases. Here, we developed a facile ssDNA-seq method, which exploits a novel template-switching activity of thermostable group II intron reverse transcriptases (TGIRTs) for DNA-seq library construction. This activity enables TGIRT enzymes to initiate DNA synthesis directly at the 3′ end of a DNA strand while simultaneously attaching a DNA-seq adapter without end repair, tailing, or ligation. Initial experiments using this method to sequence E. coli genomic DNA showed that the TGIRT enzyme has surprisingly robust DNA polymerase activity. Further experiments showed that TGIRT-seq of plasma DNA from a healthy individual enables analysis of nucleosome positioning, transcription factor-binding sites, DNA methylation sites, and tissues-of-origin comparably to established methods, but with a simpler workflow that captures precise DNA ends.

Widespread Influence of 3'-End Structures on Mammalian mRNA Processing and Stability

The physiological relevance of structures within mammalian mRNAs has been elusive, as these mRNAs are less folded in cells than in vitro and have predicted secondary structures no more stable than those of random sequences. Here, we investigate the possibility that mRNA structures facilitate the 3'-end processing of thousands of human mRNAs by juxtaposing poly(A) signals (PASs) and cleavage sites that are otherwise too far apart. We find that RNA structures are predicted to be more prevalent within these extended 3'-end regions than within PAS-upstream regions and indeed are substantially more folded within cells, as determined by intracellular probing. Analyses of thousands of ectopically expressed variants demonstrate that this folding both enhances processing and increases mRNA metabolic stability. Even folds with predicted stabilities resembling those of random sequences can enhance processing. Structure-controlled processing can also regulate neighboring gene expression. Thus, RNA structure has widespread roles in mammalian mRNA biogenesis and metabolism.

Inhibition of Eukaryotic Translation by the Antitumor Natural Product Agelastatin A

Protein synthesis plays an essential role in cell proliferation, differentiation, and survival. Inhibitors of eukaryotic translation have entered the clinic, establishing the translation machinery as a promising target for chemotherapy. A recently discovered, structurally unique marine sponge-derived brominated alkaloid, (-)-agelastatin A (AglA), possesses potent antitumor activity. Its underlying mechanism of action, however, has remained unknown. Using a systematic top-down approach, we show that AglA selectively inhibits protein synthesis. Using a high-throughput chemical footprinting method, we mapped the AglA-binding site to the ribosomal A site. A 3.5 Å crystal structure of the 80S eukaryotic ribosome from S. cerevisiae in complex with AglA was obtained, revealing multiple conformational changes of the nucleotide bases in the ribosome accompanying the binding of AglA. Together, these results have unraveled the mechanism of inhibition of eukaryotic translation by AglA at atomic level, paving the way for future structural modifications to develop AglA analogs into novel anticancer agents.

Comparative and integrative analysis of RNA structural profiling data: current practices and emerging questions

BACKGROUND

Structure profiling experiments provide single-nucleotide information on RNA structure. Recent advances in chemistry combined with application of high-throughput sequencing have enabled structure profiling at transcriptome scale and in living cells, creating unprecedented opportunities for RNA biology. Propelled by these experimental advances, massive data with ever-increasing diversity and complexity have been generated, which give rise to new challenges in interpreting and analyzing these data.

RESULTS

We review current practices in analysis of structure profiling data with emphasis on comparative and integrative analysis as well as highlight emerging questions. Comparative analysis has revealed structural patterns across transcriptomes and has become an integral component of recent profiling studies. Additionally, profiling data can be integrated into traditional structure prediction algorithms to improve prediction accuracy.

CONCLUSIONS

To keep pace with experimental developments, methods to facilitate, enhance and refine such analyses are needed. Parallel advances in analysis methodology will complement profiling technologies and help them reach their full potential.