An updated resource for the detection of protein-coding circRNA with CircProPlus

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Protein-encoding circular RNAs (circRNAs) are non-canonical RNA molecules with significant physiological and pathological roles.
• Many protein-encoding circRNAs remain unidentified due to limitations in current detection tools.

Purpose of the Study:

• To develop CircProPlus, an automated computational pipeline for de novo detection of translated circRNAs.
• To evaluate the performance of CircProPlus when integrated with different circRNA detection tools, specifically CIRI2 and CirComPara2.

Main Methods:

• Development of CircProPlus, an enhanced automated pipeline for circRNA detection.
• Comparative analysis of circRNA detection tools (CIRI2, CirComPara2) within the CircProPlus framework.
• Testing on real RNA sequencing data across different species and library types.

Main Results:

• CircProPlus offers improved accessibility, flexibility, and productivity compared to previous methods.
• CirComPara2 consistently outperformed CIRI2 when used with CircProPlus for evaluating circRNA coding potential.
• The pipeline demonstrated robust performance in identifying circRNAs with protein-coding potential from diverse datasets.

Conclusions:

• CircProPlus is a powerful tool for the de novo detection of translated circRNAs.
• The integration of CirComPara2 with CircProPlus enhances the identification of circRNAs with coding potential.
• This approach advances the field of circRNA research by enabling more effective data mining.