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So3D: a comprehensive three-dimensional spatial omics resource for decoding tissue architecture in physiology and
Hongying Zhao1, Xiangzhe Yin1, Siyao Wang1
1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Nucleic Acids Research
|October 8, 2025
Summary
This study introduces So3D, a 3D spatial omics resource for building tissue architecture and analyzing cellular processes in 3D space. It offers tools to map gene expression, cell types, and communication networks within tissues.
Area of Science:
- Spatial Omics
- 3D Tissue Architecture
- Bioinformatics Resources
Background:
- Cells organize in 3D structures crucial for tissue and organ function.
- Understanding cellular states and interactions in 3D is vital for biological research.
- Existing resources often lack comprehensive 3D spatial context.
Purpose of the Study:
- To develop a comprehensive 3D spatial omics resource, named So3D.
- To enable the construction and analysis of 3D tissue architecture.
- To dissect biological processes and intercellular interactions within 3D spatial contexts.
Main Methods:
- Systematic collection of 72 3D spatial transcriptome datasets (1,132,902 spots, 882 slices, 4 species).
- Integration with matched single-cell RNA sequencing data (763,893 cells, 28 datasets).
- Development of flexible analysis modules for 3D tissue data retrieval and analysis.
Main Results:
- So3D provides tools for inferring 3D spatial domains and gene expression patterns.
- Enables mapping of cell type distribution and cell-cell communication networks in 3D.
- Facilitates functional annotation of biological pathways within 3D tissue contexts.
Conclusions:
- So3D offers comprehensive insights into 3D spatial domains, gene expression, and cellular communication.
- It serves as an efficient tool for understanding tissue microenvironments.
- The resource aids in the discovery of novel biomarkers and biological insights from 3D spatial data.
