Seq-Scope-eXpanded: spatial omics beyond optical resolution

Sequencing-based spatial transcriptomics (sST) enables transcriptome-wide gene expression mapping but falls short of reaching the optical resolution (200-300 nm) of imaging-based methods. Here, we present Seq-Scope-X (Seq-Scope-eXpanded), which empowers submicrometer-resolution Seq-Scope with tissue expansion to surpass this limitation. By physically enlarging tissues, Seq-Scope-X minimizes transcript diffusion effects and increases spatial feature density by an additional order of magnitude. In liver tissue, this approach resolves nuclear and cytoplasmic compartments in nearly every single cell, uncovering widespread differences between nuclear and cytoplasmic transcriptome patterns. Independently confirmed by imaging-based methods, these results suggest that individual hepatocytes can dynamically switch their metabolic roles. Seq-Scope-X also works in brain and colon, and can be adapted for spatial proteomics, profiling hundreds of barcode-tagged antibody stains at microscopic resolutions in mouse spleens and human tonsils. Together, these findings establish Seq-Scope-X as a powerful platform for ultra-high-resolution whole-transcriptome and proteome profiling, expanding the spatial precision achievable for studying cellular architecture, function, and disease mechanisms.

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Publication Details

Journal
Nature Communications
Published
2026-02-10
DOI
https://doi.org/10.1038/s41467-026-69346-8
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Seq-Scope-eXpanded: spatial omics beyond optical resolution

Yichen Si, Olesya Plazyo, Jer-En Hsu, Robert L. Modlin et al.
Nature Communications
Single-cell and spatial transcriptomics
article

Seq-Scope-eXpanded: spatial omics beyond optical resolution

Yichen Si, Olesya Plazyo, Jer-En Hsu, Robert L. Modlin, Johann Eli Gudjonsson, Weiqiu Cheng, Yongha Hwang, Chun‐Seok Cho, S. Y. Yeo, Rosane M. B. Teles, Angelo Anacleto, Yongsung Kim, Qianlu Feng, Daniel Kim, Myungjin Kim, Mitchell Schrank, Hyun Min Kang, Qingyang Zhao, Chang H. Kim, Xiaoya Zhao, Anna Park, Hee-Sun Han, Alex William Schrader, Jun Yong Lee
article en

Abstract

Sequencing-based spatial transcriptomics (sST) enables transcriptome-wide gene expression mapping but falls short of reaching the optical resolution (200-300 nm) of imaging-based methods. Here, we present Seq-Scope-X (Seq-Scope-eXpanded), which empowers submicrometer-resolution Seq-Scope with tissue expansion to surpass this limitation. By physically enlarging tissues, Seq-Scope-X minimizes transcript diffusion effects and increases spatial feature density by an additional order of magnitude. In liver tissue, this approach resolves nuclear and cytoplasmic compartments in nearly every single cell, uncovering widespread differences between nuclear and cytoplasmic transcriptome patterns. Independently confirmed by imaging-based methods, these results suggest that individual hepatocytes can dynamically switch their metabolic roles. Seq-Scope-X also works in brain and colon, and can be adapted for spatial proteomics, profiling hundreds of barcode-tagged antibody stains at microscopic resolutions in mouse spleens and human tonsils. Together, these findings establish Seq-Scope-X as a powerful platform for ultra-high-resolution whole-transcriptome and proteome profiling, expanding the spatial precision achievable for studying cellular architecture, function, and disease mechanisms.

Nature CommunicationsVol. 17(1)
University of Illinois Urbana-Champaign (US), University of California, Los Angeles (US), University of Michigan (US), ENT and Allergy (US), Statistical Service (CY)
Openalex Percentile: Top 61%
Single-cell and spatial transcriptomics
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