Spatial2GWAS：连接空间转录组区域与GWAS性状的数据库。

IF 13.1 2区生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

Nucleic Acids Research Pub Date : 2025-10-22 DOI:10.1093/nar/gkaf1047

Xi Hu,Aoqi Wang,Huan Yu,Pora Kim,Xiaobo Zhou

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引用次数: 0

摘要

组织区域内基因表达的空间异质性对生物功能有重要影响，从而影响疾病的发病机制。然而，空间分解转录组和表型之间的系统关联，特别是在复杂疾病中，仍未得到充分探索。在此，我们开发了spatial2GWAS (http://www.spatial2gwas.cn)，这是一个将空间转录组（ST）区域与GWAS性状联系起来的综合资源。在数据库中，我们收集了来自5种技术的1196个ST切片（人和小鼠）和跨越18个表型类别的812个GWAS性状，确定了29 701个ST切片-GWAS性状对，包含47 492个显著区域。功能分析揭示了细胞类型组成、基因表达、GO/KEGG通路激活以及性状相关和不相关空间区域之间的细胞-细胞通讯方向的不同模式。该数据库为可视化空间区域和GWAS性状关联提供了一个友好的界面，支持切片和GWAS信息、与GWAS性状相关基因共表达的基因和空间区域的高级查询。Spatial2GWAS旨在系统探索复杂性状的空间机制，并为区域特异性生物学功能和潜在治疗靶点提供见解。该数据库连接了ST和高级表型，促进了对复杂人类疾病组织异质性的理解。

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Spatial2GWAS: a database for linking spatial transcriptomic regions with GWAS traits.

Spatial heterogeneity of gene expression within tissue regions has a critical influence on biological functions, thereby affecting disease pathogenesis. However, systematic associations between spatially resolved transcriptomes and phenotypes, especially in complex diseases, remain underexplored. Here, we developed spatial2GWAS (http://www.spatial2gwas.cn), a comprehensive resource linking spatial transcriptomic (ST) regions with GWAS traits. In the database, we collected 1196 ST slices (human and mouse) from five technologies and 812 GWAS traits spanning 18 phenotype categories and identified 29 701 ST slice-GWAS trait pairs containing 47 492 significant regions. Functional analyses reveal distinct patterns of cell type composition, gene expression, GO/KEGG pathway activation, and cell-cell communication direction between trait-related and unrelated spatial regions. The database provides a user-friendly interface for visualization of spatial regions and GWAS trait associations, supporting advanced queries by slice and GWAS information, genes co-expressed with GWAS trait-associated genes, and spatial regions. Spatial2GWAS aims to enable systematic exploration of spatial mechanisms underlying complex traits and offer insights into region-specific biological functions and potential therapeutic targets. This database bridges ST and high-level phenotypes, advancing the understanding of tissue heterogeneity in complex human diseases.

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来源期刊

Nucleic Acids Research 生物-生化与分子生物学

CiteScore

27.10

自引率

4.70%

发文量

1057

审稿时长

2 months

期刊介绍： Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.