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Circular RNA discovery with emerging sequencing and deep learning technologies

Nature Genetics volume 57, pages 1089–1102 (2025)Cite this article

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Abstract

Circular RNA (circRNA) represents a type of RNA molecule characterized by a closed-loop structure that is distinct from linear RNA counterparts. Recent studies have revealed the emerging role of these circular transcripts in gene regulation and disease pathogenesis. However, their low expression levels and high sequence similarity to linear RNAs present substantial challenges for circRNA detection and characterization. Recent advances in long-read and single-cell RNA sequencing technologies, coupled with sophisticated deep learning-based algorithms, have revolutionized the investigation of circRNAs at unprecedented resolution and scale. This Review summarizes recent breakthroughs in circRNA discovery, characterization and functional analysis algorithms. We also discuss the challenges associated with integrating large-scale circRNA sequencing data and explore the potential future development of artificial intelligence (AI)-driven algorithms to unlock the full potential of circRNA research in biomedical applications.

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Fig. 1: Identification, quantification and differential expression analysis of circRNAs.
Fig. 2: Characterization of circRNA isoform structures.
Fig. 3: Profiling the cellular heterogeneity of circRNAs.
Fig. 4: Functional characterization of circRNAs.
Fig. 5: Challenges and opportunities in large-scale analysis of circRNA data.

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Acknowledgements

This work was supported by grants from the National Natural Science Foundation of China (32130020 and 32025009 to F.Z. and 32200530 and 32422020 to J.Z.) and the National Key R&D Project (2021YFA1300500 and 2021YFA1302000 to J.Z.).

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Authors and Affiliations

  1. Institute of Zoology, Chinese Academy of Sciences, Beijing, China

    Jinyang Zhang & Fangqing Zhao

  2. Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China

    Fangqing Zhao

  3. University of Chinese Academy of Sciences, Beijing, China

    Fangqing Zhao

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  1. Jinyang Zhang
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  2. Fangqing Zhao
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F.Z. conceived the project. J.Z. conducted the initial literature research. All authors contributed to writing and edited the manuscript before submission.

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Zhang, J., Zhao, F. Circular RNA discovery with emerging sequencing and deep learning technologies. Nat Genet 57, 1089–1102 (2025). https://doi.org/10.1038/s41588-025-02157-7

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