JNSViewer-A JavaScript-based Nucleotide Sequence Viewer for DNA/RNA secondary structures.

Jieming Shi,Mitchell Graham,Xi Li,Nehul Yadav,Min Dong,Chun Liang

doi:10.1371/journal.pone.0179040

Jieming Shi, Mitchell Graham + Show 4 more

Open Access

https://doi.org/10.1371/journal.pone.0179040

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Abstract

Many tools are available for visualizing RNA or DNA secondary structures, but there is scarce implementation in JavaScript that provides seamless integration with the increasingly popular web computational platforms. We have developed JNSViewer, a highly interactive web service, which is bundled with several popular tools for DNA/RNA secondary structure prediction and can provide precise and interactive correspondence among nucleotides, dot-bracket data, secondary structure graphs, and genic annotations. In JNSViewer, users can perform RNA secondary structure predictions with different programs and settings, add customized genic annotations in GFF format to structure graphs, search for specific linear motifs, and extract relevant structure graphs of sub-sequences. JNSViewer also allows users to choose a transcript or specific segment of Arabidopsis thaliana genome sequences and predict the corresponding secondary structure. Popular genome browsers (i.e., JBrowse and BrowserGenome) were integrated into JNSViewer to provide powerful visualizations of chromosomal locations, genic annotations, and secondary structures. In addition, we used StructureFold with default settings to predict some RNA structures for Arabidopsis by incorporating in vivo high-throughput RNA structure profiling data and stored the results in our web server, which might be a useful resource for RNA secondary structure studies in plants. JNSViewer is available at http://bioinfolab.miamioh.edu/jnsviewer/index.html.

Highlights

RNA is an informational molecule that can fold into complicated shapes
Users can customize the prediction algorithm and set some advanced parameters in each of these programs on our web server. This design enables biologists to perform comparative secondary structure analysis with different prediction programs/ algorithms, or even with different parameters within the same program, which is important because: (1) no structure prediction algorithm is the best or superior one, always with tradeoff and pros and cons, and (2) consensus approaches are widely used in bioinformatics
If users want to be more flexible about the prediction algorithm, they can run different algorithms locally on their own computers or in the official web servers of the aforementioned 5 tools, and upload the secondary structure result files in Dot Bracket Notation (DBN) or Connectivity Table (CT) format to our server to view the structure graphs

Summary

Introduction

RNA is an informational molecule that can fold into complicated shapes. The pairing of local RNA nucleotides can create secondary structures, such as hairpins and stem–loops, and interactions among distantly located nucleotides can create tertiary structures [1]. RNA structures can influence transcription, splicing, cellular localization, and translation, and play a critical role in maturation, function, and regulation of various RNAs [1,2,3,4]. Protein-coding RNAs have some interesting secondary structure features.

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