SAVoR: a server for sequencing annotation and visualization of RNA structures

Area of Science:

• Bioinformatics
• Molecular Biology
• Genomics

Background:

• RNA secondary structure dictates RNA functionality, processing, localization, and stability.
• Accurate RNA structure prediction is essential for understanding gene regulation.
• The rapid growth of RNA sequencing (RNA-seq) necessitates advanced analysis tools.

Purpose of the Study:

• To develop a web server for analyzing and visualizing RNA secondary structure in the context of RNA-seq data.
• To integrate RNA structure predictions with experimental sequencing data and genomic annotations.
• To provide a user-friendly platform for exploring RNA structure-function relationships.

Main Methods:

• Development of the Sequencing Annotation and Visualization of RNA structures (SAVoR) web server.
• Integration of RNA structure prediction algorithms with RNA-seq read alignment data.
• Computation of per-base values including read abundance and sequence variant frequency.
• Visualization of sequencing data on customizable secondary structure models.

Main Results:

• SAVoR seamlessly links RNA structure predictions with RNA-seq data and genomic annotations.
• The server generates informative, annotated models of RNA secondary structure.
• Per-base sequencing metrics can be visualized directly on predicted RNA structures.

Conclusions:

• SAVoR facilitates a deeper understanding of RNA biology by combining structural and sequencing information.
• The tool aids in the analysis and visualization of transcriptome data in the context of RNA secondary structure.
• SAVoR is a valuable resource for researchers studying RNA function and regulation.