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.
Authors
- Yuying Huo
- Xiangyu Li (ORCID: https://orcid.org/0000-0002-6017-0701)
- Tingting Li (ORCID: https://orcid.org/0000-0003-4266-0317)
- Zhaoxu Wu
- Wenqian Xu
Institutions
- 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)
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
Funders
- 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