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scNanoCOOL-seq: a long-read single-cell sequencing method for multi-omics profiling within individual cells

Cell Research volume 33, pages 879–882 (2023)Cite this article

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To prepare a long-read library compatible with nanopore sequencing platform, bisulfite-treated DNAs were tagged with only one adapter when performing random priming (Supplementary information, Table S1), two ends of short fragments might hybridize, and self-looped DNA was formed to prevent from being used as a template during PCR amplification.4 In this way, the read length we obtained and aligned was ~900 bp. To evaluate the feasibility of scNanoCOOL-seq, we profiled 189 HFF1 cells and 187 K562 cells with 70.6% and 54.5% of them passing quality control, respectively (Supplementary information, Table S2). In principle, since the GpC methyltransferase M.CviPI specifically methylates accessible GpC sites, endogenous DNA methylation levels can be represented by methylation levels of WCGs (W = A, T) and chromatin accessibility can be represented by methylation levels of GCHs (H = A, T, C). On average, 974,463 (3.4% of the total) and 821,965 (2.9% of the total) WCG sites were detected in individual K562 cells and HFF1 cells, respectively (Supplementary information, Fig. S1a). Differences between DNA methylation levels were reproducibly shown either by DNA methylation profiling analysis in and around gene bodies (Supplementary information, Fig. S1b) or by dimension reductions (Fig. 1b; Supplementary information, Fig. S1c). Besides, DNA methylation results obtained by scCOOL-seq and by scNanoCOOL-seq were in general consistent (Supplementary information, Fig. S1d, e). For chromatin accessibility detection, we focused on chromatin state around transcription start site (TSS) and locally open chromatin region referred to as nucleosome-depleted region (NDR). As shown in Supplementary information, Fig. S1f, TSS exhibits high chromatin accessibility, and an ordered nucleosome positioning pattern downstream of TSS was also observed. The NDRs called from scNanoCOOL-seq were verified by using publicly available ENCODE data (Supplementary information, Fig. S1g–i and Table S3); and they were also comparable to those obtained from NGS platform-based scCOOL-seq (Supplementary information, Fig. S1h). Differential NDR analysis reliably recalled transcription factors that specifically regulate gene expression in K562 or HFF1 cells (Supplementary information, Fig. S1j). In addition, we observed a positive correlation between promoter accessibility and their corresponding gene expression (Supplementary information, Fig. S1k, l). These results demonstrated that scNanoCOOL-seq performs well in simultaneously profiling DNA methylation and chromatin accessibility within individual cells. On average, expression of 3818 and 3739 genes were detected in each individual K562 cell or HFF1 cell, respectively; and single-cell RNA expression data sufficed to distinguish these two cell types (Fig. 1b; Supplementary information, Fig. S1m). We also demonstrated that scNanoCOOL-seq can be used to explore single-cell CNVs. At 10 Mb resolution, the CNV signature of K562 cells detected by scNanoCOOL-seq, as highlighted in the heatmap, is consistent with a previously published study (Supplementary information, Fig. S2a).5 Furthermore, we can also consistently infer the CNVs of K562 cells at 1 Mb resolution (Supplementary information, Fig. S2c). A lower coefficient of variance could be achieved by merging single cells into pseudo-bulk (Supplementary information, Fig. S2d).

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Fig. 1: Overview of scNanoCOOL-seq and its utility in profiling mouse blastocyst cells.

Data availability

All relevant data are available from the Sequence Read Archive database (accession number: PRJNA905717).

Code availability

All codes associated with this study have been deposited on GitHub (https://github.com/sherryxuePKU/scNanoCOOL-seq).

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Acknowledgements

This work was supported by the Basic Science Center Projects of the National Natural Science Foundation of China (32288102), and the Science and Technology Innovation “2030-Brain Science and Brain-like Research” major project (2021ZD0200102).

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Author notes

  1. These authors contributed equally: Jianli Lin, Xiaohui Xue.

Authors and Affiliations

  1. Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China

    Jianli Lin & Fuchou Tang

  2. Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China

    Jianli Lin, Xiaohui Xue, Yan Wang, Yuan Zhou, Haoling Xie, Mengya Liu, Lu Wen & Fuchou Tang

  3. Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China

    Jianli Lin, Xiaohui Xue, Yan Wang, Haoling Xie, Mengya Liu, Lu Wen & Fuchou Tang

  4. PKU-Tsinghua-NIBS Graduate Program, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China

    Xiaohui Xue & Fuchou Tang

  5. Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Science Key Lab, Beijing, China

    Jian Wu

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Contributions

F.T. conceived and supervised this project. J.L., X.X. and Y.Z. developed protocol. J.L. and Y.Z. performed experiments with help from Y.W. X.X. conducted bioinformatic analysis with assistance from H.X. and M.L. J.L., X.X. and F.T. wrote the manuscript with help from other authors.

Corresponding author

Correspondence to Fuchou Tang.

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The authors declare no competing interests.

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Lin, J., Xue, X., Wang, Y. et al. scNanoCOOL-seq: a long-read single-cell sequencing method for multi-omics profiling within individual cells. Cell Res 33, 879–882 (2023). https://doi.org/10.1038/s41422-023-00873-5

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