RNAscape: geometric mapping and customizable visualization of RNA structure

Abstract

Analyzing and visualizing the tertiary structure and complex interactions of RNA is essential for being able to mechanistically decipher their molecular functions in vivo. Secondary structure visualization software can portray many aspects of RNA; however, these layouts are often unable to preserve topological correspondence since they do not consider tertiary interactions between different regions of an RNA molecule. Likewise, quaternary interactions between two or more interacting RNA molecules are not considered in secondary structure visualization tools. The RNAscape webserver produces visualizations that can preserve topological correspondence while remaining both visually intuitive and structurally insightful. RNAscape achieves this by designing a mathematical structural mapping algorithm which prioritizes the helical segments, reflecting their tertiary organization. Non-helical segments are mapped in a way that minimizes structural clutter. RNAscape runs a plotting script that is designed to generate publication-quality images. RNAscape natively supports non-standard nucleotides, multiple base-pairing annotation styles and requires no programming experience. RNAscape can also be used to analyze RNA/DNA hybrid structures and DNA topologies, including G-quadruplexes. Users can upload their own three-dimensional structures or enter a Protein Data Bank (PDB) ID of an existing structure. The RNAscape webserver allows users to customize visualizations through various settings as desired. URL: https://rnascape.usc.edu/.

Graphical Abstract

Graphical Abstract.

Introduction

The structural diversity of RNA molecules influences their broad biological functions (1–3). This diversity (4) is primarily driven by its ability to form complicated tertiary interactions, a plethora of non-standard base-pairing conformations and quaternary interactions with other RNA, DNA or protein molecules. Visualizing RNA in two dimensions poses the challenge of capturing these complex interactions while remaining comprehensible and valuable to researchers.

One popular means of representing complicated RNA structures is through secondary structure diagrams. These two-dimensional (2D) diagrams are exclusively driven by base-pairing relationships and laid out in an abstract space. Extensive literature and software (5–15) describe secondary structure diagrams. However, these representations do not effectively capture tertiary molecular interactions, such as base pairing, stacking, and pseudoknot interactions. Therefore, although this approach scales relatively well for large RNA sequences (5), not considering tertiary interactions can lead to a diagram far from the biological structure and function. More specifically, nucleotides which are positioned relatively close together in three-dimensional (3D) space may appear far away in the visualization.

Some tools promise to capture tertiary interactions (16,17). Of these tools, RNAView (16), is widely known and has been a current standard linked in the Nucleic Acid Knowledge Base (NAKB) (18). However, RNAView (16) lacks a webserver, requires a complicated setup and usage pipeline, and cannot handle some complex topologies resulting in output that is not always interpretable or intuitive. Moreover, it is unable to provide publication-quality images. The only other available tool that retains tertiary interactions, RNAglib (17), is not deterministic and results in different outputs for repeat runs under the default configuration documented by the authors, which likely explains why it has not been adopted by the field compared to RNAView. A description of different tools which create various 2D diagrams of RNA molecules is provided in Supplementary Table S1.

RNAscape addresses and overcomes the outlined issues and limitations of existing approaches at several levels. The RNAscape algorithm includes a mapping process that conforms to the helical geometry of RNA structures. By doing so, it attempts to preserve the intuitive correspondence between the 2D mapping and 3D structure. At the same time, RNAscape optimizes each layout to place non-helical segments of the structure without sacrificing tertiary interactions. This enables visualizations that are compact while remaining as visually intuitive as possible (Figure 1, Supplementary Figures S1 and S3).

Figure 1.

RNAscape output for various structures from the PDB. The 3D structure at the top of each panel is from the PDB structure, with its corresponding RNAscape visualization shown below it. (A) tRNA from Sulfolobus tokodaii (PDB ID: 7VNV), (B) a single-stranded DNA molecule (PDB ID: 4NOE), (C) Dengue virus RNA promoter (PDB ID: 7UMD), (D) Pistol ribozyme (PDB ID: 6R47), (E) Riboswitch from Escherichia coli (PDB ID: 1Y26), (F) Cobalamin riboswitch regulatory element (PDB ID: 4FRN), (G) NAD-II riboswitch (PDB ID: 8HBA), (H) G-quadruplex (PDB ID: 2M18), (I) RNA kink-turn motif (PDB ID: 7EFG) and (J) the semi-symmetric peptidyl transferase center (PTC) of the large ribosomal subunit of Deinococcus radiodurans (PDB ID: 1NKW), also known as proto-ribosome (30). The molecular structure in (J) is shown along the two-fold pseudo-symmetry axis, with an additional orientation shown in Supplementary Figure S1.

The RNAscape webserver (Figure 2) offers various customization options for its visualizations. Users can zoom, pan, and rotate images directly on the webserver. In addition, one can easily customize a plot with different base-pairing annotations (16,19,20), residue colors, nucleotide or text-label sizes, and numbering schemas. RNAscape encourages users to iteratively refine an image. In addition, RNAscape allows the user to modify the calculated map. Upon completion, RNAscape visualizations can be exported to vector format (SVG) or image format (PNG), enabling further refinements by the user. Both Protein Data Bank (PDB) and macromolecular Crystallographic Information File (mmCIF) format files are supported to maximize compatibility. Additionally, RNAscape can directly fetch structures (biological assembly 1) from the PDB (21) based on a given PDB ID.

Figure 2.

RNAscape overview. (A) RNAscape algorithm for geometric mapping. RNAscape builds a 2D ladder representation for helical segments that closely adheres to their principal component analysis (PCA) projection. It adds non-helical segments to this representation by optimizing nearest neighbor counts. (B) RNAscape webserver for plotting flexible, publication-quality visualizations. A plotting script is used to plot the geometrically mapped points and incorporates desired user customizations. A user can also regenerate the plot with alternate settings and reuse a prior geometric mapping, saving time and compute power. (C) RNAscape frontend for user interaction and customization. RNAscape allows users to upload a file or input a PDB ID for processing and to adjust various settings including base-pairing annotations, residue colors, nucleotide or text-label sizes and numbering schema. RNAscape also provides an associated documentation. After processing, RNAscape supports interaction with output layouts including zooming, rotating, panning, and modifying the map. Users can download layouts and geometric mappings and view a log of non-Watson-Crick (non-WC) nucleotides.

RNAscape supports multiple base-pairing annotation conventions: Leontis-Westhof (LW) (16), Saenger (19), DSSR (Dissecting the Spatial Structure of RNA) (20) and a no-annotation option. Future updates to base-pairing conventions by the nucleic acid community can easily be incorporated. Modified/non-standard nucleotides are denoted by a white circle and annotated with a small letter code (based on its parent standard base or simply ‘x’ if this information is unavailable).

Materials and methods

Programming languages and general tools

The RNAscape webserver is a single-page web application. The backend (Figure 2A, B) is implemented in Python 3.9.18, and Django (22) is used to communicate with the backend. The frontend is (Figure 2C) designed in React v18.2.0 framework and implemented in Hypertext Markup Language (HTML)/Cascading Style Sheets (CSS)/JavaScript.

The RNAscape algorithm

Upon upload, the structure file is sent via Hypertext Transfer Protocol Secure (HTTPS) to the RNAscape webserver where backend processing occurs. If a user selects a PDB ID (21), its corresponding first biological assembly is downloaded by the backend (Figure 2A, B) for processing.

Pre-processing (Figure 3A). The DSSR program (v1.7.8) (20) is run on the structure file to detect helices and base pairs, and assign base-pairing annotations.

Figure 3.

RNAscape algorithm. (A) Pre-processing of uploaded/fetched structures. Structure files are obtained either through user upload or direct download from the PDB. DSSR is run on each structure to detect helical segments and assign base-pairing annotations. (B) Geometric mapping and post-processing of helical segments. For each helical segment, RNAscape estimates the ladder axis by connecting the centroids of the starting and ending nucleotides with a line segment. If a helix is bent, detected by a distance >10 Å between the midpoint of the ladder axis and corresponding helical segment's centroid, the ladder axis is split into two. Helical projections within 20 Å and 30º are optionally merged. Base pairs are uniformly spaced along each ladder axis, and cramped helices are lengthened. (C) Optimizing placement of non-helical regions followed by creation of annotated visualization. Hanging single stranded regions are mapped to their corresponding, connected helix and merged with the ladder. Loops are either preferentially bulged out in a radial curve or interpolated linearly based on a spatial density threshold. Loop direction is determined by minimizing the total nearest neighbor count of a given loop. Mapped points as well as pairing and backbone annotations are passed to the plotting script to create a visualization.

Helical regions (Figure 3B). The positioning of helices, as well as non-helical regions, involves multiple considerations. The 3D coordinates of each nucleotide are represented by the centroid of atoms belonging to it (i.e. for the nucleotide, ). The set of all nucleotide centroids is a combination of two subsets (i.e. (helical regions) and (non-helical regions)). Helical regions receive the highest priority and are placed in a way that reflects their spatial orientation while remaining visually intuitive. To do so, first, we run principal component analysis (PCA) exclusively on the helical segments () and project the points onto the plane determined by the first two components. In this process, the  sized matrix is converted to a matrix (which we can denote as ), which preserves the maximum spatial variance possible in two dimensions (23). Next, we convert into a more visually intuitive ‘ladder’ representation, which first involves estimating a ladder axis in the projection plane for each helix. An initial estimate is made by connecting the centroid of the first and last base pairs of a helical region using a line segment. consists of multiple helical regions (i.e. ). If the midpoint of a base-pair is , the ladder axis for is the vector rooted at the point .

However, for bent helices, this estimate may be imprecise. To account for this case, we measure the distance  between the centroid of the helical projection and the midpoint of the estimated ladder axis (i.e. . If this distance is greater than 10 Å, we re-estimate the ladder axis as a combination of two line segments: one connecting the first and central base-pair centroids and another between the central and last base-pair centroids. In theory, this process can be recursively performed. In practice, however, we observe that doing so once suffices. Next, if two helical projections are within a certain distance threshold (i.e. Å) and have similar orientations (i.e. ), we merge them and recompute the ladder axis as described above. Next, we uniformly distribute the base pairs in the ‘ladder’ formation along each ladder axis. Finally, for cases where the projection of a helix is skewed, resulting in an overly cramped ladder representation, we lengthen the ladder to reduce visual clutter. The final mapping for nucleotide points in helical regions can be denoted as

Non-helical regions (Figure 3C). Loops are either preferentially bulged out in a radial curve or interpolated linearly based on a spatial density threshold (see implementation in Data Availability), depending on the chosen setting. We choose bulging by default to reduce graph overlap and crowding. For bulging out, the structure mapping algorithm computes potential layouts and performs greedy optimization to select an optimal layout. This optimization considers the total nearest-neighbor count (within 10 Å) of all members of a loop, and the orientation with the lowest number of neighbors is selected. Let us assume that the loop is connected to two nucleotides which are part of a helical region, mapped to positions . Two possible circular layouts are computed for the loop based on and : bulging out in perpendicular directions (layout ) and (layout ), where denotes the unit vector which is perpendicular relative to the mapping plane. In each case, the center of the layout remains at the point (. The radius of the circular arc is either |(| or , if  Å or  Å, where is the number of points in the loop. Points are uniformly distributed on the circular arc. One of the two loop orientations is selected based on minimizing the neighbor count in helical segments as follows:

Hanging single stranded regions are linearly interpolated based on its connecting mapped helix. Additional adjustments are made for certain edge cases, such as, when a linearly interpolated non-helix nucleotide exactly overlaps with another nucleotide (see implementation in Data Availability). Structures containing no helices (generally rare) are mapped solely using a PCA.

Visualization (Figure 3C). The RNAscape backend utilizes the Matplotlib (24) and NetworkX (25) packages to plot visualizations. As input, the plotting algorithm requires the mapped points, base-pairing annotations, and user-selected visual settings for a structure. As output, it generates an image that is temporarily stored (up to 48 h) on the webserver and tied to a specific user session. Structure files are not stored. The image is served to the frontend via a Django (22) server, where it can be interacted with by the user. A user can also regenerate a plot with different visual settings. In this case, we reuse the mapping output and rerun the visualization script, resulting in a faster response time than the complete computation.

Results

Application of RNAscape to structures from the PDB

We present RNAscape output for various structures (Figures 1 and 4) from the PDB (21). In Figure 1A, tRNA from Sulfolobus tokodaii (PDB ID: 7VNV) is shown. RNAscape output preserves the L-shaped topology (as opposed to known ‘clover leaf’ shaped secondary structure (26) visualizations) and annotates non-standard bases and base-pairing geometries (critical in many RNA interactions (27)). RNAscape can also process unusual DNA structures, as shown by a single-stranded DNA with circular topology (PDB ID: 4NOE, Figure 1B). In Figure 1C, Dengue virus RNA promoter (PDB ID: 7UMD) is depicted, which is a single-stranded RNA molecule containing only standard RNA bases.

Figure 4.

RNAscape output for large-size structures from the PDB. The 3D structure at the top of each panel is from the PDB structure, with its corresponding RNAscape visualization shown below it. (A) Mycobacterium tuberculosis T-box in complex with tRNA (PDB ID: 6UFH, 244 nucleotides), (B) Mutant P4-P6 domain (DELC209) of Tetrahymena thermophila group I intron (PDB ID: 1HR2, 157 nucleotides), (C) Exon-free state of the Tetrahymena group I intron (PDB ID: 7R6N, 354 nucleotides), and (D) Twist-corrected RNA origami 5-helix Tile A (PDB ID: 7QDU, 552 nucleotides).

We present a few different examples of ribozymes and riboswitches (Figure 1D-G). RNA loop modeling (28) for riboswitches is an important area of research, and RNAscape visualizations (e.g. PDB IDs: 1Y26, 4FRN, 8HBA, Figure 1E–G) may aid in these efforts. The pistol ribozyme (PDB ID: 6R47, Figure 1D) and the Nicotinamide Adenine Dinucleotide-II (NAD-II) riboswitch (PDB ID: 8HBA, Figure 1G) illustrate how RNAscape places non-helical segments and can clearly depict their non-standard base pairs with helical segments. RNAscape natively supports multiple strands (e.g. PDB ID: 1Y26, Figure 1E). RNAscape is also able to visualize G-quadruplexes (PDB ID: 2M18, Figure 1E). An RNA structural motif which can serve as a binding site for proteins is the kink-turn motif (PDB ID: 7EFG) (29), and it is visualized in Figure 1I.

There has been a continued interest in structural studies of the ribosome which postulate the role of a proto-ribosome (30) in the origin of life. The proto-ribosome is a semi-symmetrical core of the ribosome comprised of RNA molecules representing the site for peptide bond formation, therefore known as peptidyl transferase center (PTC). The RNAscape visualization (Figure 1J, Supplementary Figure S1) for the same reflects the high degree of conformational symmetry, based on structural coordinates of the PTC provided by Bose et al. (30).

RNAscape can run on relatively large structures (structures of up to 50 MB are processed by the webserver). In Figure 4, we demonstrate its application to four different topologies of larger structures. In Figure 4A, a triangular topology of Mycobacterium tuberculosis ileS T-box in complex with tRNA (PDB ID: 6UFH, 244 nucleotides) is shown, followed by a diamond-like topology of mutant P4-P6 domain of Tetrahymena thermophila group I intron (PDB ID: 1HR2, Figure 4B, 157 nucleotides) and an exon free state of the Tetrahymena group I intron (PDB ID: 7R6N, Figure 4C, 354 nucleotides). Secondary structure representations will not resemble the structure at all for many of these cases (e.g. stacked ladders, PDB ID: 7QDU, Figure 4D, 552 nucleotides), while RNAscape is able to reflect the 3D topology of these large RNA molecules.

RNAscape user interface

The RNAscape webserver (Figure 2C) displays three primary items: header, file upload, and documentation panels. In the header, a user can click the ‘Run on Example Data’ button to view an example visualization (PDB ID: 3ZP8). In the file upload panel, a user can upload a structure using the file upload feature. This file may contain non-nucleic acid entities which will be ignored. Alternatively, a user can directly input a PDB ID to load its corresponding first assembly file. Clicking the ‘Run’ button runs the RNAscape pipeline on the uploaded structure file or provided PDB ID (biological assembly 1). After running RNAscape for a structure, a user has the option to add a second structure for side-by-side viewing. We demonstrate this capability for two structures of tRNA molecules (PDB IDs: 8UPT and 8UPY, Supplementary Figure S2), introduced by recent work (31) on the importance of tRNA shape. The documentation panel enables easy navigation and provides a quick start guide, tips, and examples for using RNAscape. It also includes detailed explanations for configurable settings.

Output images

The frontend (Figure 2C) natively supports touch-screen compatible image exploration. A user can zoom, center, or reset any zooming/panning via buttons above the display box. The image can also be rotated using a slider, and a ‘regenerate’ button is offered that replots the image, associated annotations, and user customizations in the desired rotation. To the right of the image, a legend is displayed that corresponds to the base-pairing annotation selected by the user. For the Saenger (19) base-pairing annotation, no legend is shown. The local strand direction (5′ to 3′) is indicated by the black arrows between nucleotides for all plots. Other interactions are shown in blue dotted lines. These colors are fully customizable by the user. The user also has the option of downloading RNAscape mapped points in a numerical format (.npz) processable by the NumPy (32) library. Additionally, a log is provided which contains a description of the non-standard/modified nucleotides in the plot and other associated information.

Base-pairing annotations

RNAscape offers three base-pairing annotation styles: LW (16,33), DSSR (20) and Saenger (19). All base-pairing annotations are calculated via DSSR, although any future updates to these conventions by the nucleic acid community can be easily incorporated. Annotations do not affect geometric mapping, and a user can forego an annotation altogether. The LW annotation contains two key parameters: bond orientation (cis/trans) and base edge type. Bond orientation is represented by a filled or unfilled marker. The edge types: Watson-Crick (W), Hoogsteen (H), or sugar (S), are represented by marker shapes (Figure 1).

The DSSR style differs in that base edges are delineated by major groove (M), minor groove (m), or Watson-Crick (W) edges. Bond orientation annotation is the same as in the LW (16,33) annotation. DSSR also reports local strand orientation as a base-pairing annotation feature. RNAscape always denotes local strand orientation by the backbone arrows (Figure 1). Non-standard pairings flagged as ‘not categorized’ by DSSR are not annotated. For the Saenger (19) annotation, each bond type is represented by a number corresponding to its Roman numeral annotation.

Customizable settings

Several custom settings options are available (Figure 2C). The Loop Bulging setting controls whether loops are bulged outwards or linearly interpolated (see Materials and Methods). Additionally, the post-processing step of merging proximate, similarly oriented ladders can be turned off (Figure 3B). Since these settings affect the geometric mapping, a user must click ‘Run’ to run the pipeline again if they are changed. Arrow size, circle size, and circle label size affect nucleotide appearance. Base-pairing marker sizes can also be adjusted. Through the number settings, a user instructs RNAscape to label residue numbers in the numbering schema defined by the structure file. Color, size, frequency, and spacing of these labels can also be modified. Color settings allow a user to customize the color of each nucleotide type: A, C, G, U/T and X (non-standard nucleotides). Colors used to denote both backbone chain and non-chain interactions and markers can also be modified. Furthermore, RNAscape provides a functionality to modify calculated maps. By clicking on the ‘Modify Mapping’ button, the user can move and adjust nucleotide locations to resolve, for instance, overlap and regenerate the output.

Discussion

The RNAscape webserver produces customizable, publication-quality visualizations of nucleic acid tertiary structure. It prioritizes the topology of a structure while striving to create a clean and optimized output, and it is designed to minimize user effort. RNAscape significantly deviates from any existing method in terms of its output quality, usability, and layout algorithm (Supplementary Table S1, Supplementary Figures S1 and S3). Users can refine visualizations on the webserver, and RNAscape also supports non-standard nucleotides and various base-pairing annotations. Further updates to base-pairing conventions may be easily incorporated. The RNAscape webserver allows a maximum file size of 50 MB. While potentially informative, the output for extremely large structures may not be well suited for presentation. We provide the RNAscape implementation via GitHub (see Data Availability) for those inclined to try the pipeline locally on even larger structures. We conclude with the hope that our effort facilitates advancement of the ever-growing field of RNA biology.

Data availability

RNAscape is freely available for all users at https://rnascape.usc.edu/. The backend implementation is also available on GitHub at https://github.com/timkartar/RNAscape and preserved through figshare at https://doi.org/10.6084/m9.figshare.25201889.

Supplementary data

Supplementary Data are available at NAR Online.

Funding

Andrew J. Viterbi Fellowship in Computational Biology and Bioinformatics (to R.M.); National Institutes of Health [R35GM130376 to R.R.]. Funding for open access charge: NIH [R35GM130376].

Conflict of interest statement. None declared.