ArticleNature methods2025
Repurposing large-format microarrays for scalable spatial transcriptomics.
Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Integrating delivery systems and microenvironmental cues to accelerate clinical translation of cardiac reprogramming.Materials today. Bio · 2026Review
- Review
- NicheTrans: spatial-aware cross-omics translation.Nature methods · 2026Article
- Reference Regulatory Element-Guided Gene Expression Analysis for Mechanistic Inference of Gene Regulatory Networks.bioRxiv : the preprint server for biology · 2026Article
- Secreted phospholipase PLA2G5 acts as a hemolytic factor in sepsis.The Journal of clinical investigation · 2026Article
- Artificial intelligence-assisted spatial omics-based biomimetic nanoplatform for intelligent and precise intervention in the immunosuppressive core region of ovarian cancer.NPJ precision oncology · 2026Review
- Bridging the dimensional gap from planar spatial transcriptomics to 3D cell atlases.Nature methods · 2026Article
- Multi-Omics Insights into Chronic Rhinosinusitis with Nasal Polyps: A Review of Lipidomics, Proteomics, and Transcriptomics.Journal of inflammation research · 2026Review
- Spatial Transcriptomics to Study Virus-Host Interactions.Annual review of virology · 2025Review
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Authors and funding
4 authors.
Funding
Abstract
Spatiomolecular analyses are key to study tissue functions and malfunctions. However, we lack profiling tools for spatial transcriptomics that are easy to adopt, low cost and scalable in terms of sample size and number. Here, we describe a method, Array-seq, to repurpose classical oligonucleotide microarrays for spatial transcriptomics profiling. We generate Array-seq slides from microarrays carrying custom-design probes that contain common sequences flanking unique barcodes at known coordinates. Then we perform a simple, two-step reaction that produces mRNA capture probes across all spots on the microarray. We demonstrate that Array-seq yields spatial transcriptomes with high detection sensitivity and localization specificity using histological sections from mouse tissues as test systems. Moreover, we show that the large surface area of Array-seq slides yields spatial transcriptomes (i) at high throughput by profiling multi-organ sections, (ii) in three dimensions by processing serial sections from one sample, and (iii) across whole human organs. Thus, by combining classical DNA microarrays and next-generation sequencing, we have created a simple and flexible platform for spatiomolecular studies of small-to-large specimens at scale.
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Registered trials
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