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Single-nucleus chromatin accessibility and gene expression co-profiling by ISSAAC-seq

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Abstract

Multimodal profiling of different molecular layers from the same single cell enables more comprehensive characterization of cellular heterogeneity compared with conventional single-modality approaches. A key example is co-detection of chromatin accessibility and gene expression that offers the opportunity to investigate cell type-resolved gene regulatory mechanisms. Here we describe a sensitive and robust protocol for in situ sequencing hetero RNA–DNA-hybrid after assay for transposase-accessible chromatin using sequencing (ISSAAC-seq) for the concurrent measurement of chromatin accessibility and gene expression from the same single nucleus. The method begins with dual Tn5 tagging of open chromatin regions and the RNA–cDNA hybrid produced by reverse transcription that take place in bulk nuclei. Then, various single-nucleus isolation strategies, including plate and droplet barcoding-based approaches, can be used based on the experimental purpose of the user. The protocol is highly modular with a flexible throughput ranging from several hundreds to tens of thousands of nuclei. The generated data are of high quality in both modalities. The entire workflow can be finished within 1 or 2 days, and the procedures work on multiple different single-nucleus isolation and barcoding platforms.

Key points

  • This protocol takes advantage of the hyperactive Tn5 transposase to tag open chromatin and RNA in bulk nuclei in situ. These steps are followed by single nucleus separation and barcoding on the users’ platform of choice and high-throughput sequencing.

  • Co-profiling chromatin accessibility and RNA enhances the characterization of cell states in complex tissues. The approach has been validated in multiple tissues and cell types and can be performed on a variety of single-cell isolation platforms.

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Fig. 1: A schematic view of the workflow.
Fig. 2: Sequences of the ISSAAC-seq library and the sequencing configurations.
Fig. 3: Examples of nuclei at different steps.
Fig. 4: Some examples of library size distributions from different experiments.
Fig. 5: A flow chart of the computational pipeline for the data preprocessing.
Fig. 6: Comparisons of the effect of different RT temperatures on the ISSAAC-seq data quality.
Fig. 7: Venn diagrams show the overlap of called cell barcodes between ATAC and RNA.
Fig. 8: Genome browser tracks of aggregated ISSAAC-seq data from indicated platforms.
Fig. 9: UMAP plots of ISSAAC-seq of mouse cortex using the 10x scATAC platform.
Fig. 10: UMAP plots of ISSAAC-seq of mouse cortex using the Bio-Rad dscATAC platform.

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Data availability

The data generated using the plate and 10x scATAC workflows are available for download via ArrayExpress under the accession no. E-MTAB-11264. Data generated using the Bio-Rad workflow and the improved RT condition can be found under the accession no. E-MTAB-15131. The data used to generate Figs. 7–9 are from ref. 37.

Code availability

The code used to process the data and the instructions to run the code are available in the GitHub repository at https://github.com/dbrg77/ISSAAC-seqV2.

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Acknowledgements

We thank all members of the Chen lab for discussion. The computational work was supported by the Center for Computational Science and Engineering at Southern University of Science and Technology. The cell and nucleus icons from Fig. 1 were created by Servier (https://smart.servier.com/) and are licensed under CC-BY 3.0 Unported (https://creativecommons.org/licenses/by/3.0/). This work was supported by the National Natural Science Foundation of China (grant no. 32322019 to X.C.; grant nos. 32200509 and 32470674 to W.X.), the Guangdong Program (grant no. 2021QN02Y165 to X.C.), Science and Technology Projects in Guangzhou (grant no. 2024A04J5074 to W.X.) and Shenzhen Medical Research Fund (grant no. C2301007 to X.C.).

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Authors and Affiliations

  1. GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Medical University, Guangdong, China

    Wei Xu

  2. Shenzhen Key Laboratory of Gene Regulation and Systems Biology, Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, Guangdong, China

    Wei Xu, Yukun Hu, Yunlong Zhang & Xi Chen

  3. Bio-Rad Laboratories, Life Science Group, Pleasanton, CA, USA

    Patricia M. Schnepp, Lok Man Lo, Qiang Zhang & Sherman M. Cheng

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Contributions

W.X. and X.C. conceived the project and designed the protocol; W.X. performed the experiment with help from Y.H., L.M.L., Q.Z. and S.M.C.; Y.Z., P.M.S. and X.C. performed the bioinformatics data analysis. X.C. and W.X. supervised the project. All authors contributed to the writing of the manuscript.

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Correspondence to Wei Xu or Xi Chen.

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P.M.S., L.M.L., Q.Z. and S.M.C. are employees of Bio-Rad Laboratories. The rest of the authors declare no competing interests.

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Nature Protocols thanks Stephania Contreras Castillo, Rong Fan and Leif Ludwig for their contribution to the peer review of this work.

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Key reference

Xu, W. et al. Nat. Methods 19, 1243–1249 (2022): https://doi.org/10.1038/s41592-022-01601-4

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Reporting Summary

Supplementary Tables

Supplementary Table 1: oligo sequences used in the protocol. Supplementary Table 2: detailed cost comparison between ISSAAC-seq and 10x Multiome.

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Xu, W., Hu, Y., Zhang, Y. et al. Single-nucleus chromatin accessibility and gene expression co-profiling by ISSAAC-seq. Nat Protoc (2026). https://doi.org/10.1038/s41596-025-01304-y

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