Abstract
BackgroundFunctional characterization of single nucleotide variants (SNVs) involves two steps, the first step is to convert DNA to protein and the second step is to visualize protein sequences with their structures. As massively parallel sequencing has emerged as a leading technology in genomics, resulting in a significant increase in data volume, direct visualization of SNVs together with associated protein sequences/structures in a new user interface (UI) would be a more effective way to assess their potential effects on protein function.ResultsWe have developed BioVR, an easy-to-use interactive, virtual reality (VR)-assisted platform for integrated visual analysis of DNA/RNA/protein sequences and protein structures using Unity3D and the C# programming language. It utilizes the cutting-edge Oculus Rift, and Leap Motion hand detection, resulting in intuitive navigation and exploration of various types of biological data. Using Gria2 and its associated gene product as an example, we present this proof-of-concept software to integrate protein and nucleic acid data. For any amino acid or nucleotide of interest in the Gria2 sequence, it can be quickly linked to its corresponding location on Gria2 protein structure and visualized within VR.ConclusionsUsing innovative 3D techniques, we provide a VR-based platform for visualization of DNA/RNA sequences and protein structures in aggregate, which can be extended to view omics data.
Highlights
Functional characterization of single nucleotide variants (SNVs) involves two steps, the first step is to convert DNA to protein and the second step is to visualize protein sequences with their structures
Using the BuildTexture() method in {DNA | RNA}PanelController, the appropriate FASTA file is accessed and its nucleotide sequence is processed such that each texture coordinate of the DNA or RNA plane takes on a color that represents a specific nucleotide in the FASTA sequence
This tool aims to fill two knowledge gaps in bioinformatics: the first is in single-nucleotide variants (SNVs) analysis by integrating nucleic acid sequences with protein sequences/structures, and the second is in virtual reality (VR) visualization technology by applying VR to biomolecular data
Summary
Functional characterization of single nucleotide variants (SNVs) involves two steps, the first step is to convert DNA to protein and the second step is to visualize protein sequences with their structures. As massively parallel sequencing has emerged as a leading technology in genomics, resulting in a significant increase in data volume, direct visualization of SNVs together with associated protein sequences/structures in a new user interface (UI) would be a more effective way to assess their potential effects on protein function. The advent of massively parallel sequencing (MPS) technologies in the past decade has revolutionized the field of genomics, enabling fast and cost-effective generation of a large amount of sequence data. This technological innovation leads to the accumulation of vast quantities of genomic data, posing a tremendous challenge to scientists for effective mining of data to explain a phenomenon of interest. VR refers to a 3D simulated environment generated by a computer into which users are immersed, as opposed to a 3D rendering of a 2D
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