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High throughput error corrected Nanopore single cell transcriptome sequencing

Author

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  • Kevin Lebrigand

    (Université Côte d’Azur, CNRS, Institut de Pharmacologie Moléculaire et Cellulaire)

  • Virginie Magnone

    (Université Côte d’Azur, CNRS, Institut de Pharmacologie Moléculaire et Cellulaire)

  • Pascal Barbry

    (Université Côte d’Azur, CNRS, Institut de Pharmacologie Moléculaire et Cellulaire)

  • Rainer Waldmann

    (Université Côte d’Azur, CNRS, Institut de Pharmacologie Moléculaire et Cellulaire)

Abstract

Droplet-based high throughput single cell sequencing techniques tremendously advanced our insight into cell-to-cell heterogeneity. However, those approaches only allow analysis of one extremity of the transcript after short read sequencing. In consequence, information on splicing and sequence heterogeneity is lost. To overcome this limitation, several approaches that use long-read sequencing were introduced recently. Yet, those techniques are limited by low sequencing depth and/or lacking or inaccurate assignment of unique molecular identifiers (UMIs), which are critical for elimination of PCR bias and artifacts. We introduce ScNaUmi-seq, an approach that combines the high throughput of Oxford Nanopore sequencing with an accurate cell barcode and UMI assignment strategy. UMI guided error correction allows to generate high accuracy full length sequence information with the 10x Genomics single cell isolation system at high sequencing depths. We analyzed transcript isoform diversity in embryonic mouse brain and show that ScNaUmi-seq allows defining splicing and SNVs (RNA editing) at a single cell level.

Suggested Citation

  • Kevin Lebrigand & Virginie Magnone & Pascal Barbry & Rainer Waldmann, 2020. "High throughput error corrected Nanopore single cell transcriptome sequencing," Nature Communications, Nature, vol. 11(1), pages 1-8, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-17800-6
    DOI: 10.1038/s41467-020-17800-6
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    1. Ashley Byrne & Daniel Le & Kostianna Sereti & Hari Menon & Samir Vaidya & Neha Patel & Jessica Lund & Ana Xavier-Magalhães & Minyi Shi & Yuxin Liang & Timothy Sterne-Weiler & Zora Modrusan & William S, 2024. "Single-cell long-read targeted sequencing reveals transcriptional variation in ovarian cancer," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Jasim Kada Benotmane & Jan Kueckelhaus & Paulina Will & Junyi Zhang & Vidhya M. Ravi & Kevin Joseph & Roman Sankowski & Jürgen Beck & Catalina Lee-Chang & Oliver Schnell & Dieter Henrik Heiland, 2023. "High-sensitive spatially resolved T cell receptor sequencing with SPTCR-seq," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    3. Yu Wang & Zhi-Ying Guan & Shao-Wen Shi & Yi-Rong Jiang & Jie Zhang & Yi Yang & Qiong Wu & Jie Wu & Jian-Bo Chen & Wei-Xin Ying & Qin-Qin Xu & Qian-Xi Fan & Hui-Feng Wang & Li Zhou & Ling Wang & Jin Fa, 2024. "Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    4. Livius Penter & Mehdi Borji & Adi Nagler & Haoxiang Lyu & Wesley S. Lu & Nicoletta Cieri & Katie Maurer & Giacomo Oliveira & Aziz M. Al’Khafaji & Kiran V. Garimella & Shuqiang Li & Donna S. Neuberg & , 2024. "Integrative genotyping of cancer and immune phenotypes by long-read sequencing," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    5. Zhuo-Xing Shi & Zhi-Chao Chen & Jia-Yong Zhong & Kun-Hua Hu & Ying-Feng Zheng & Ying Chen & Shang-Qian Xie & Xiao-Chen Bo & Feng Luo & Chong Tang & Chuan-Le Xiao & Yi-Zhi Liu, 2023. "High-throughput and high-accuracy single-cell RNA isoform analysis using PacBio circular consensus sequencing," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    6. Cheng-Kai Shiau & Lina Lu & Rachel Kieser & Kazutaka Fukumura & Timothy Pan & Hsiao-Yun Lin & Jie Yang & Eric L. Tong & GaHyun Lee & Yuanqing Yan & Jason T. Huse & Ruli Gao, 2023. "High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    7. Michal Kabza & Alexander Ritter & Ashley Byrne & Kostianna Sereti & Daniel Le & William Stephenson & Timothy Sterne-Weiler, 2024. "Accurate long-read transcript discovery and quantification at single-cell, pseudo-bulk and bulk resolution with Isosceles," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

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