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Related Experiment Video

Updated: Sep 6, 2025

Identification of Circular RNAs using RNA Sequencing
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Reconstruction of Full-Length circRNA Sequences Using Chimeric Alignment Information.

Md Tofazzal Hossain1,2,3, Jingjing Zhang1,2, Md Selim Reza1,2

  • 1Center for High Performance Computing, Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.

International Journal of Molecular Sciences
|June 24, 2022
PubMed
Summary

Circular RNAs (circRNAs) are vital disease biomarkers, but current identification methods lack full-length sequences. We developed circRNA-full, a novel tool that accurately reconstructs these crucial full-length sequences.

Keywords:
circular RNAfull-length sequencereconstruction of circRNA sequence

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Circular RNAs (circRNAs) are increasingly recognized as potential biomarkers for various diseases.
  • Existing methods for identifying circRNAs often fail to provide complete full-length sequences.
  • Accurate full-length circRNA sequences are essential for downstream functional and interaction analyses.

Purpose of the Study:

  • To develop a novel computational method for reconstructing full-length circular RNA sequences.
  • To improve the accuracy and efficiency of full-length circRNA sequence reconstruction.

Main Methods:

  • Developed circRNA-full, a new method utilizing chimeric alignment information from the STAR aligner.
  • Evaluated circRNA-full using long-reads RNA-seq data and comparing against existing tools like ciri-full.
  • Assessed reconstruction rate, precision, sensitivity, and F1 score for human and mouse data.

Main Results:

  • circRNA-full demonstrated superior performance in full-length circRNA sequence reconstruction compared to the existing tool ciri-full.
  • The method achieved higher reconstruction rates, precision, sensitivity, and F1 scores.
  • Effective reconstruction was validated on both human and mouse datasets.

Conclusions:

  • circRNA-full offers a significant advancement in reconstructing full-length circular RNA sequences.
  • This method is crucial for enabling comprehensive downstream analyses in circRNA research.
  • The tool provides a more accurate and reliable approach for studying circRNA functions and interactions.