RNAex: an RNA secondary structure prediction server enhanced by high-throughput structure-probing data

Area of Science:

• Computational Biology
• Bioinformatics
• Molecular Biology

Background:

• High-throughput technologies enable transcriptome-wide RNA structure probing.
• Predicting accurate RNA secondary structures requires complex data processing and expertise.
• Integrating experimental data with free energy models is crucial for precise structure determination.

Purpose of the Study:

• To develop an accessible web server, RNAex, for RNA secondary structure prediction.
• To enable non-specialists to utilize cutting-edge structure-probing data for predictions.
• To enhance RNA secondary structure predictions with in vivo and in vitro experimental data.

Main Methods:

• RNAex integrates experimental probing data with established structure-folding algorithms.
• Users can select from four folding methods: restrained MaxExpect, SeqFold, RNAstructure (Fold), and RNAfold.
• Raw sequencing data from probing experiments were re-mapped to the whole genome for each species.
• RNAex annotates predicted structures with RNA editing, modification, and SNP sites.

Main Results:

• RNAex provides a user-friendly interface for RNA secondary structure prediction.
• The server supports predictions for known and novel RNA transcripts across human, mouse, yeast, and Arabidopsis.
• Predictions are enhanced by incorporating experimental in vivo and in vitro data.

Conclusions:

• RNAex democratizes RNA secondary structure prediction by simplifying data integration and analysis.
• The server facilitates research by providing accurate, experimentally-enhanced structural predictions.
• RNAex is a valuable tool for researchers studying RNA structure and function across multiple species.