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Updated: Jun 9, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
Published on: July 6, 2022
stSNV: a comprehensive resource of SNVs in spatial transcriptome
Changbo Yang1, Yujie Liu2, Xiaohua Wang3
1College of Bioinformatics Science and Technology, Harbin Medical University, No.157 Baojian Road, Harbin, Heilongjiang 150081, China.
Abstract:
Single nucleotide variants (SNVs), as important components of genetic variation, affect gene expression, function and phenotype. Mining and summarizing the spatial distribution of SNVs in diseased and normal tissues for a better understanding of their characteristics and potential roles in cell-lineage determination, aging, or disease occurrence is significant. Herein, we have developed a comprehensive spatial mutation resource stSNV (http://bio-bigdata.hrbmu.edu.cn/stSNV/index.jsp), which provides an atlas of spatial SNVs in major diseased and normal tissues of human and mouse. stSNV documents 42 202 spatial mutated genes involving 898 908 SNVs called from 730 067 spots within 450 slices from 19 diseased and 28 normal tissues. Importantly, potential characteristics of SNVs are explored and provided by analyzing the perturbation of the SNVs to gene expression, spatial communication, biological function, region-specific mutated genes, spatial mutant signatures, SNV-cell co-localization and mutation core region. All these spatial mutation data and in-depth analyses have been integrated into a user-friendly interface, visualized through intuitive tables and various image formats. Flexible tools are developed to explore co-localization among clusters, genes, cell types and SNVs in the same slice. In summary, stSNV as a valuable resource helps to dissect intra-tissue genetic heterogeneity and lays the groundwork for understanding the SNVs' biological regulatory mechanisms.
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