Seq-Scope: Repurposing Illumina sequencing flow cells for high-resolution spatial transcriptomics
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Abstract
Spatial transcriptomics technologies aim to advance gene expression studies by profiling the entire transcriptome with intact spatial information from a single histological slide. However, the application of spatial transcriptomics is limited by low resolution, limited transcript coverage, complex procedures, poor scalability and high costs of initial setup and/or individual experiments. Seq-Scope repurposes the Illumina sequencing platform for high-resolution, high-content spatial transcriptome analysis, overcoming these limitations. It offers submicrometer resolution, high capture efficiency, rapid turnaround time and precise annotation of histopathology at a much lower cost than commercial alternatives. This protocol details the implementation of Seq-Scope with an Illumina NovaSeq 6000 sequencing flow cell, allowing the profiling of multiple tissue sections in an area of 7 mm × 7 mm or larger. We describe the preparation of a fresh-frozen tissue section for both histological imaging and sequencing library preparation and provide a streamlined computational pipeline with comprehensive instructions to integrate histological and transcriptomic data for high-resolution spatial analysis. This includes the use of conventional software tools for single-cell and spatial analysis, as well as our recently developed segmentation-free method for analyzing spatial data at submicrometer resolution. Aside from array production and sequencing, which can be done in batches, tissue processing, library preparation and running the computational pipeline can be completed within 3 days by researchers with experience in molecular biology, histology and basic Unix skills. Given its adaptability across various biological tissues, Seq-Scope establishes itself as an invaluable tool for researchers in molecular biology and histology.
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Seq-Scope is a micrometer-resolution spatial transcriptome profiling technology that unbiasedly captures whole tissue transcriptome with high-fidelity mapping of transcriptional diversity.
“Seq-Scope is a micrometer-resolution spatial transcriptome profiling technology that unbiasedly captures whole tissue transcriptome with high-fidelity mapping of transcriptional diversity [14,15].”
From Fluorescence-Guided Spatial Mapping of p21-Expressing Senescent Cells in Aged Liver at Single-Cell Resolution (2026) · cites this paper as [15]
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“Data were processed as described previously using NovaScope pipeline [14,15].”
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- Authors
- Kim, Y., Cheng, W., Cho, C.-S., Hwang, Y., Si, Y., Park, A., Schrank, M., Hsu, J.-E., Anacleto, A., Xi, J., Kim, M., Pedersen, E., Koues, O. I., Wilson, T., Lee, C., Jun, G., Kang, H. M., & Lee, J. H.
- Affiliations
- University of Michigan (US)
- Harvard University (US)
- The University of Texas Health Science Center at Houston (US)
- Corresponding author
- Kang, Hyun Min
- Lee, Jun Hee
- ORCID
- Venue
- Nature Protocols
- Published
- 2024-10-31
- Volume
- 20
- Issue
- 3
- Pages
- 643-689
- ISSN
- 1750-2799 (ISSN-L)
- 1754-2189
- PMC
- PMC11896753
- OpenAlex
- W4403948432
- Semantic Scholar
- dd4eb40dd8012f442cce77f943b264ed0c08c814
- Cited by
- 44
- References
- 56
- Citations by year
- 2026: 18 · 2025: 21 · 2024: 5
- FWCI
- 1.79
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Nature Protocols (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion)
- Digital Commons-TMC (Texas Medical Center) (submittedVersion)
- PubMed Central (submittedVersion, cc-by-nc-nd)
- Funders
- A. Alfred Taubman Medical Research Institute (Taubman Institute Innovation Project)
- U.S. Department of Health & Human Services | National Institutes of Health (T32AG000114, K01AG061236 R01AG079163, R01HG011031 HHSN268201800002I)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- spatial transcriptomics, submicron resolution, library preparation
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