STRAND: a comprehensive subcellular-resolved spatial transcriptome RNA architecture and navigation database

Subcellular RNA localization serves as a critical regulatory layer governing cellular polarization, local translation, and functional compartmentalization. Recent advances in high-resolution spatial transcriptomics have provided unprecedented opportunities to resolve these intracellular architectures at single-molecule resolution. However, relevant datasets are dispersed across studies and repositories, vary substantially in processing procedures and standards, severely limiting their cross-study reuse. To bridge this gap, we present STRAND (Subcellular-Resolved Spatial Transcriptome RNA Architecture and Navigation Database), a curated data resource and analysis platform for the automated harvesting, quality control, and interpretation of subcellular spatial transcriptomics data. Through an agent-assisted curation pipeline, STRAND has assembled 35 subcellular-resolution datasets from six major platforms, covering 17 tissue types in human and mouse and totalling ∼4.9 billion transcript coordinates. Building upon this standardized data resource, STRAND provides an analytical workflow spanning cell segmentation evaluation, cell-type annotation, RNA localization/colocalization pattern annotation, and subcellular compartment inference. Two case studies demonstrate that STRAND successfully identifies established RNA localization patterns in cultured cell lines and detects drug-induced RNA relocalization in cardiomyocytes. STRAND is openly available at https://strand.phasep.pro.

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Publication Details

Journal
Nucleic Acids Research
Published
2026-10-30
DOI
https://doi.org/10.1093/nar/gkag1054
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

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article

STRAND: a comprehensive subcellular-resolved spatial transcriptome RNA architecture and navigation database

Yuying Huo, Xiangyu Li, Tingting Li, Zhaoxu Wu et al.
2 links
Nucleic Acids Research
Single-cell and spatial transcriptomics
article

STRAND: a comprehensive subcellular-resolved spatial transcriptome RNA architecture and navigation database

Yuying Huo, Xiangyu Li, Tingting Li, Zhaoxu Wu, Wenqian Xu
article en

Abstract

Subcellular RNA localization serves as a critical regulatory layer governing cellular polarization, local translation, and functional compartmentalization. Recent advances in high-resolution spatial transcriptomics have provided unprecedented opportunities to resolve these intracellular architectures at single-molecule resolution. However, relevant datasets are dispersed across studies and repositories, vary substantially in processing procedures and standards, severely limiting their cross-study reuse. To bridge this gap, we present STRAND (Subcellular-Resolved Spatial Transcriptome RNA Architecture and Navigation Database), a curated data resource and analysis platform for the automated harvesting, quality control, and interpretation of subcellular spatial transcriptomics data. Through an agent-assisted curation pipeline, STRAND has assembled 35 subcellular-resolution datasets from six major platforms, covering 17 tissue types in human and mouse and totalling ∼4.9 billion transcript coordinates. Building upon this standardized data resource, STRAND provides an analytical workflow spanning cell segmentation evaluation, cell-type annotation, RNA localization/colocalization pattern annotation, and subcellular compartment inference. Two case studies demonstrate that STRAND successfully identifies established RNA localization patterns in cultured cell lines and detects drug-induced RNA relocalization in cardiomyocytes. STRAND is openly available at https://strand.phasep.pro.

Nucleic Acids Research
Peking University (CN), Beijing Jiaotong University (CN), National Health and Family Planning Commission (CN), Ministry of Education (ME), State Key Laboratory of Natural and Biomimetic Drugs (CN)
National Natural Science Foundation of China, Natural Science Foundation of Beijing Municipality, Peking University, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 22%
Single-cell and spatial transcriptomics
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