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.
This is a preview of subscription content, access via your institution
Open Access articles citing this article.
Experimental Hematology & Oncology Open Access 12 October 2023
Defining the landscape of circular RNAs in neuroblastoma unveils a global suppressive function of MYCN
Nature Communications Open Access 04 July 2023
Journal of Experimental & Clinical Cancer Research Open Access 12 May 2023
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Rent or buy this article
Prices vary by article type
Prices may be subject to local taxes which are calculated during checkout
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.
Kristensen, L. S. et al. The biogenesis, biology and characterization of circular RNAs. Nat. Rev. Genet. 20, 675–691 (2019).
Li, X., Yang, L. & Chen, L.-L. The biogenesis, functions, and challenges of circular RNAs. Mol. Cell 71, 428–442 (2018).
Memczak, S. et al. Circular RNAs are a large class of animal RNAs with regulatory potency. Nature 495, 333–338 (2013).
Westholm, J. O. et al. Genome-wide analysis of Drosophila circular RNAs reveals their structural and sequence properties and age-dependent neural accumulation. Cell Rep. 9, 1966–1980 (2014).
Barrett, S. P., Parker, K. R., Horn, C., Mata, M. & Salzman, J. ciRS-7 exonic sequence is embedded in a long non-coding RNA locus. PLoS Genet. 13, e1007114 (2017).
Ruan, H. et al. Comprehensive characterization of circular RNAs in ~1000 human cancer cell lines. Genome Med. 11, 1–14 (2019).
Du, W. W. et al. Foxo3 circular RNA retards cell cycle progression via forming ternary complexes with p21 and CDK2. Nucleic Acids Res. 44, 2846–2858 (2016).
Yang, W., Du, W. W., Li, X., Yee, A. J. & Yang, B. B. Foxo3 activity promoted by non-coding effects of circular RNA and Foxo3 pseudogene in the inhibition of tumor growth and angiogenesis. Oncogene 35, 3919–3931 (2016).
Legnini, I. et al. Circ-ZNF609 is a circular RNA that can be translated and functions in myogenesis. Mol. Cell 66, 22–37 (2017).
Liu, C.-X. et al. Structure and degradation of circular RNAs regulate PKR activation in innate immunity. Cell 177, 865–880 (2019).
Xu, X. et al. CircRNA inhibits DNA damage repair by interacting with host gene. Mol. Cancer 19, 128 (2020).
Liu, X. et al. Identification of mecciRNAs and their roles in the mitochondrial entry of proteins. Sci. China Life Sci. 63, 1429–1449 (2020).
Wu, Z. et al. Mitochondrial genome-derived circRNA mc-COX2 functions as an oncogene in chronic lymphocytic leukemia. Mol. Ther. Nucleic Acids 20, 801–811 (2020).
Zhao, Q. et al. Targeting mitochondria-located circRNA SCAR alleviates NASH via reducing mROS output. Cell 183, 76–93 (2020).
Wu, J. et al. CircAST: full-length assembly and quantification of alternatively spliced isoforms in circular RNAs. Genomics Proteomics Bioinformatics 17, 522–534 (2019).
Zheng, Y., Ji, P., Chen, S., Hou, L. & Zhao, F. Reconstruction of full-length circular RNAs enables isoform-level quantification. Genome Med. 11, 2 (2019).
Zhang, X.-O. et al. Diverse alternative back-splicing and alternative splicing landscape of circular RNAs. Genome Res. 26, 1277–1287 (2016).
Gao, Y. et al. Comprehensive identification of internal structure and alternative splicing events in circular RNAs. Nat. Commun. 7, 12060 (2016).
Tang, A. D. et al. Full-length transcript characterization of SF3B1 mutation in chronic lymphocytic leukemia reveals downregulation of retained introns. Nat. Commun. 11, 1438 (2020).
You, X. et al. Neural circular RNAs are derived from synaptic genes and regulated by development and plasticity. Nat. Neurosci. 18, 603–610 (2015).
Rahimi, K., Venø, M. T., Dupont, D. M. & Kjems, J. Nanopore sequencing of full-length circRNAs in human and mouse brains reveals circRNA-specific exon usage and intron retention. Preprint at bioRxiv https://doi.org/10.1101/567164 (2019).
Xiao, M.-S. & Wilusz, J. E. An improved method for circular RNA purification using RNase R that efficiently removes linear RNAs containing G-quadruplexes or structured 3′ ends. Nucleic Acids Res. 47, 8755–8769 (2019).
Lee, C. Generating consensus sequences from partial order multiple sequence alignment graphs. Bioinformatics 19, 999–1008 (2003).
Vaser, R., Sović, I., Nagarajan, N. & Šikić, M. Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res. 27, 737–746 (2017).
Zhang, J., Chen, S., Yang, J. & Zhao, F. Accurate quantification of circular RNAs identifies extensive circular isoform switching events. Nat. Commun. 11, 90 (2020).
Yang, C., Chu, J., Warren, R. L. & Birol, I. NanoSim: nanopore sequence read simulator based on statistical characterization. Gigascience 6, 1–6 (2017).
Wu, W., Ji, P. & Zhao, F. CircAtlas: an integrated resource of one million highly accurate circular RNAs from 1070 vertebrate transcriptomes. Genome Biol. 21, 101 (2020).
Gruner, H., Cortés-López, M., Cooper, D. A., Bauer, M. & Miura, P. CircRNA accumulation in the aging mouse brain. Sci. Rep. 6, 38907–38907 (2016).
Rybak-Wolf, A. et al. Circular RNAs in the mammalian brain are highly abundant, conserved, and dynamically expressed. Mol. Cell 58, 870–885 (2015).
Akers, N. K., Schadt, E. E. & Losic, B. STAR chimeric post for rapid detection of circular RNA and fusion transcripts. Bioinformatics 34, 2364–2370 (2018).
Ragan, C., Goodall, G. J., Shirokikh, N. E. & Preiss, T. Insights into the biogenesis and potential functions of exonic circular RNA. Sci. Rep. 9, 2048 (2019).
Lei, Q. et al. Evolutionary insights into RNA trans-splicing in vertebrates. Genome Biol. Evol. 8, 562–577 (2016).
Talhouarne, G. J. S. & Gall, J. G. Lariat intronic RNAs in the cytoplasm of vertebrate cells. Proc. Natl Acad. Sci. USA 115, E7970–E7977 (2018).
Taggart, A. J. et al. Large-scale analysis of branchpoint usage across species and cell lines. Genome Res. 27, 639–649 (2017).
Siepel, A. et al. Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 15, 1034–1050 (2005).
Ji, P. et al. Expanded expression landscape and prioritization of circular RNAs in mammals. Cell Rep. 26, 3444–3460 (2019).
Takenaga, K., Nakamura, Y., Tokunaga, K., Kageyama, H. & Sakiyama, S. Isolation and characterization of a cDNA that encodes mouse fibroblast tropomyosin isoform 2. Mol. Cell. Biol. 8, 5561–5565 (1988).
Pollard, K. S., Hubisz, M. J., Rosenbloom, K. R. & Siepel, A. Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res. 20, 110–121 (2010).
Frankish, A. et al. GENCODE reference annotation for the human and mouse genomes. Nucleic Acids Res. 47, D766–D773 (2019).
Gao, Y., Zhang, J. & Zhao, F. Circular RNA identification based on multiple seed matching. Brief. Bioinform. 19, 803–810 (2018).
Cheng, J., Metge, F. & Dieterich, C. Specific identification and quantification of circular RNAs from sequencing data. Bioinformatics 32, 1094–1096 (2016).
Hunter, J. D. Matplotlib: a 2D graphics environment. Comput. Sci. Eng. 9, 90–95 (2007).
Virtanen, P. et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat. Methods 17, 261–272 (2020).
Leger, A. & Leonardi, T. pycoQC, interactive quality control for Oxford Nanopore Sequencing. J. Open Source Softw. 4, 1236 (2019).
Li, H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018).
Benson, G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 27, 573–580 (1999).
Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint at https://arxiv.org/abs/1303.3997 (2013).
Hansen, T. B. et al. Natural RNA circles function as efficient microRNA sponges. Nature 495, 384–388 (2013).
Szabo, L. et al. Statistically based splicing detection reveals neural enrichment and tissue-specific induction of circular RNA during human fetal development. Genome Biol. 16, 126 (2015).
Li, M. et al. Quantifying circular RNA expression from RNA-seq data using model-based framework. Bioinformatics 33, 2131–2139 (2017).
Wang, K. et al. MapSplice: accurate mapping of RNA-seq reads for splice junction discovery. Nucleic Acids Res. 38, e178 (2010).
Song, X. et al. Circular RNA profile in gliomas revealed by identification tool UROBORUS. Nucleic Acids Res. 44, e87 (2016).
Hoffmann, S. et al. A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection. Genome Biol. 15, R34 (2014).
Wang, Y. et al. GSA: genome sequence archive. Genomics Proteomics Bioinformatics 15, 14–18 (2017).
Gao, Y. et al. CIRI: an efficient and unbiased algorithm for de novo circular RNA identification. Genome Biol. 16, 4 (2015).
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).
The authors declare no competing interests.
Peer review information Nature Biotechnology thanks the anonymous reviewers for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
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
This article is cited by
Experimental Hematology & Oncology (2023)
Nature Protocols (2023)
Nature Cell Biology (2023)
Journal of Experimental & Clinical Cancer Research (2023)
Defining the landscape of circular RNAs in neuroblastoma unveils a global suppressive function of MYCN
Nature Communications (2023)