RNA sequencing and Prediction Tools for Circular RNAs Analysis.

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Circular RNAs (circRNAs) are noncoding RNA molecules formed via alternative splicing, implicated in regulating microRNAs, RNA-binding proteins, and protein-coding transcripts.
• Deregulation of circRNAs is linked to diseases like Alzheimer's and cancer, highlighting their clinical significance.
• The precise mechanisms of circRNA action are still under investigation.

Purpose of the Study:

• To review methods for detecting and analyzing circular RNAs (circRNAs).
• To highlight the importance of bioinformatics tools in identifying circRNAs from next-generation sequencing data.
• To introduce miARma-Seq as an efficient pipeline for circRNA identification.

Main Methods:

• High-throughput next-generation sequencing (NGS) for measuring circRNAs.
• RNA enrichment protocols, including RNase R treatment, for enhanced circRNA detection.
• Development and application of specialized bioinformatics tools for identifying junction-spanning sequences.

Main Results:

• NGS technology enables accurate quantification of circRNAs at a single-nucleotide level.
• Advanced protocols and bioinformatics approaches have significantly increased the discovery of diverse circRNAs across organisms.
• Comparative studies suggest using multiple prediction tools for robust circRNA identification.

Conclusions:

• Circular RNAs are significant regulatory molecules with implications in various diseases.
• Effective detection of circRNAs relies on advanced sequencing technologies, specialized enrichment methods, and sophisticated bioinformatics tools.
• Pipelines like miARma-Seq streamline the analysis of circRNAs, facilitating further research.