Seq-Scope-eXpanded: spatial omics beyond optical resolution

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Authors: Angelo Anacleto, Weiqiu Cheng, Qianlu Feng, Anna Park, Chun‐Seok Cho, Yongha Hwang, Yongsung Kim, Yichen Si, Jer-En Hsu, Qingyang Zhao, Xiaoya Zhao, Daniel Kim
+12 more Mitchell Schrank, Alex William Schrader, S. Y. Yeo, Rosane M. B. Teles, Robert L. Modlin, Olesya Plazyo, Jóhann E. Guðjónsson, Myungjin Kim, Chang H. Kim, Hee-Sun Han, Hyun Min Kang, Jun Yong Lee
Cited by: 3
References: 60

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. High spatial resolution is essential for resolving cellular and subcellular organization in tissues. Here, authors present Seq-Scope-X, which integrates tissue expansion with Seq-Scope to achieve an order-of-magnitude improvement in resolution of spatial transcriptomics and proteomics.

Fields of Study & Subjects

Single-cell and spatial transcriptomics Cell Image Analysis Techniques Gene expression and cancer classification

Publication details

Journal / source
Nature Communications
Publisher
Springer Science and Business Media LLC
Volume
17
Issue
1
Publication date
10 February 2026
Language
EN