A comprehensive database of high-throughput sequencing-based RNA secondary structure probing data (Structure Surfer)

Area of Science:

• Molecular Biology
• Bioinformatics

Background:

• RNA molecules fold into intricate 3D shapes crucial for cellular function.
• RNA secondary structure is determined by nucleotide base pairing.
• High-throughput sequencing methods now allow transcriptome-wide RNA structure analysis.

Purpose of the Study:

• To develop a unified tool for visualizing and comparing diverse RNA secondary structure data.
• To address the lack of a comprehensive interface for analyzing transcriptome-wide RNA structure datasets.

Main Methods:

• Developed Structure Surfer, a database and visualization tool.
• Integrated six transcriptome-wide RNA secondary structure datasets from human and mouse.
• Utilized four different high-throughput sequencing-based methods for data generation.
• Implemented specific analysis pipelines for each experimental method.

Main Results:

• Structure Surfer allows inspection of RNA secondary structure across multiple datasets.
• The tool facilitates querying individual loci and detecting trends across multiple sites.
• Demonstrated functionality by examining known structural elements and exploring use cases.

Conclusions:

• Structure Surfer offers an accessible database and visualization interface.
• Enables interrogation of mammalian transcriptome-wide RNA secondary structure information.
• Provides a valuable resource for researchers studying RNA structure and function.