ReviewNature protocols2025
Seq-Scope: repurposing Illumina sequencing flow cells for high-resolution spatial transcriptomics.
Review in Nature protocols, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective.Briefings in bioinformatics · 2025Pooled it
- Unlocking the full potential of spatial omics in plants: practical challenges, solutions, and a path forward.The Plant cell · 2026Review
- Caerin 1.1/1.9 Inhibits Growth and Biofilm Formation of Carbapenem-Resistant Klebsiella pneumoniae and Induces Coordinated Transcriptomic Stress Responses.Current microbiology · 2026Article
- Review
- The developing tendon and enthesis are hypoxic and rely on hypoxia-inducible factor 1a during postnatal development.Development (Cambridge, England) · 2026Article
- Decoding Cardiac Development and Maturation at Single-Cell and Spatial Transcriptomic Resolution.Circulation research · 2026Review
- SMURF: soft-segmentation for single-cell reconstruction and topological analysis of spatial transcriptomic data.Nature communications · 2026Article
- Review
- Fluorescence-Guided Spatial Mapping of p21-Expressing Senescent Cells in Aged Liver at Single-Cell Resolution.Biomolecules · 2026Article
- SAGE: Spatially Aware Gene Selection and Dual-View Embedding Fusion for Domain Identification in Spatial Transcriptomics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Seq-Scope-eXpanded: spatial omics beyond optical resolution.Nature communications · 2026Article
- Isolation, identification, and whole genome sequencing analysis of influenza A virus clinical isolates from Shanghai, China, during 2022-2023.Virology journal · 2026Article
- Spatial omics at the forefront: emerging technologies, analytical innovations, and clinical applications.Cancer cell · 2026Review
- CellMap: precision mapping of cellular landscape in spatial transcriptomics.Nucleic acids research · 2026Article
- Decoding cardiac homeostasis and injury: the evolving landscape of spatial transcriptomics.Frontiers in cell and developmental biology · 2026Review
- The Alzheimer's therapeutic Lecanemab attenuates Aβ pathology by inducing an amyloid-clearing program in microglia.Nature neuroscience · 2026Article
- The developing tendon and enthesis are hypoxic and rely on hypoxia-inducible factor 1a (bioRxiv : the preprint server for biology · 2025Article
- Biophysical simulation enables segmentation and nervous system atlas mapping for image first spatial omics.NPJ systems biology and applications · 2025Article
- Epigallocatechin-3-gallate ameliorates lipopolysaccharide-induced inflammation via the 67LR/JAK2/STAT3 signaling pathway.Scientific reports · 2025Article
- CellSP enables module discovery and visualization for subcellular spatial transcriptomics data.Communications biology · 2025Article
Corrections and comments
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Authors and funding
18 authors.
Funding
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.