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Comprehensive profiling of circular RNAs with nanopore sequencing and CIRI-long

Nature Biotechnology volume 39, pages 836–845 (2021)Cite this article

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An Author Correction to this article was published on 30 April 2021

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Abstract

Reconstructing the sequence of circular RNAs (circRNAs) from short RNA sequencing reads has proved challenging given the similarity of circRNAs and their corresponding linear messenger RNAs. Previous sequencing methods were unable to achieve high-throughput detection of full-length circRNAs. Here we describe a protocol for enrichment and full-length sequencing of circRNA isoforms using nanopore technology. Circular reverse transcription and size selection achieves a 20-fold higher enrichment of circRNAs from total RNA compared to previous methods. We developed an algorithm, called circRNA identifier using long-read sequencing data (CIRI-long), to reconstruct the sequence of circRNAs. The workflow was validated with simulated data and by comparison to Illumina sequencing as well as quantitative real-time RT–PCR. We used CIRI-long to analyze adult mouse brain samples and systematically profile circRNAs, including mitochondria-derived and transcriptional read-through circRNAs. We identified a new type of intronic self-ligated circRNA that exhibits special splicing and expression patterns. Our method takes advantage of nanopore long reads and enables unbiased reconstruction of full-length circRNA sequences.

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Fig. 1: Method overview.
Fig. 2: Experimental optimization of capture of full-length circRNAs.
Fig. 3: Validation of circRNAs using simulated and Illumina datasets.
Fig. 4: The hidden complexity of circular transcripts and splicing events.
Fig. 5: A new type of intronic self-ligated circRNAs.

Data availability

The sequence data generated in this study have been deposited to the National Genomics Data Center54 (China National Center for Bioinformation: https://bigd.big.ac.cn/gsa) with accession number CRA003317. Details of these datasets are included in Supplementary Table 1 and the Methods section.

Code availability

CIRI-long is implemented in Python and can be freely accessed at https://github.com/Kevinzjy/CIRI-long. The software is packaged with sample datasets and has been extensively tested on Linux.

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Acknowledgements

This work was supported by grants from the National Natural Science Foundation of China (32025009, 91940306, 31722031, 32071463, 91951209 and 91640117) and the National Key R&D Program (2018YFC0910400).

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Author notes

  1. These authors contributed equally: Jinyang Zhang, Lingling Hou, Zhenqiang Zuo.

Authors and Affiliations

  1. Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, China

    Jinyang Zhang, Lingling Hou, Zhenqiang Zuo, Peifeng Ji & Fangqing Zhao

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

    Jinyang Zhang & Fangqing Zhao

  3. Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China

    Xiaorong Zhang & Yuanchao Xue

  4. Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China

    Fangqing Zhao

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

    Fangqing Zhao

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Contributions

F.Z. conceived the project. J.Z. implemented the algorithm and performed data analysis. L.H., Z.Z., Y.X. and X.Z. performed the experiments and generated sequencing data. J.Z., J.P. and F.Z. wrote the manuscript with the contribution of all authors.

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Correspondence to Fangqing Zhao.

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Zhang, J., Hou, L., Zuo, Z. et al. Comprehensive profiling of circular RNAs with nanopore sequencing and CIRI-long. Nat Biotechnol 39, 836–845 (2021). https://doi.org/10.1038/s41587-021-00842-6

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