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Related Experiment Video

Updated: Jan 11, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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Spatial GWAS Atlas: a knowledgebase for decoding the genetic architecture of complex traits in spatial resolution.

Hongen Kang1, Xiaoxi Jing1, Jiecong Lin1

  • 1Changping Laboratory, Beijing 102206, China.

Nucleic Acids Research
|November 17, 2025
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Summary

The Spatial GWAS Atlas integrates genome-wide association studies (GWAS) with spatial transcriptomics (ST) to map trait-associated cells. This resource reveals the cellular and spatial basis of complex traits for disease research.

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Area of Science:

  • Genomics
  • Systems Biology
  • Bioinformatics

Background:

  • Genome-wide association studies (GWAS) identify numerous variants linked to complex traits, predominantly in noncoding regions with tissue-specific effects.
  • The spatial distribution of these genetic effects within tissue architecture is poorly understood.
  • Spatial transcriptomics (ST) preserves spatial coordinates while profiling gene expression, enabling localization of genetic effects.

Purpose of the Study:

  • To introduce the Spatial GWAS Atlas, a novel resource integrating GWAS summary statistics with ST data.
  • To map trait-associated cells at single-cell resolution within their spatial context.
  • To facilitate the dissection of the cellular and spatial basis of complex traits.

Main Methods:

  • Systematic integration of 3854 curated GWAS datasets with 635 ST datasets across species, tissues, and platforms.
  • Leveraging spatial transcriptomics to link genetic association signals to specific cell types and locations within tissues.
  • Development of a database with search, browsing, and visualization functionalities.

Main Results:

  • Identification of extensive trait-region and trait-spot associations by integrating diverse GWAS and ST data.
  • Demonstration of the ability to map genetic effects to specific cells and spatial locations.
  • Establishment of a comprehensive resource for exploring genotype-phenotype relationships in a spatial context.

Conclusions:

  • The Spatial GWAS Atlas is the first resource to systematically integrate GWAS and ST data for mapping trait-associated cells.
  • This atlas enables high-resolution dissection of the cellular and spatial underpinnings of complex traits.
  • The resource supports mechanistic studies, therapeutic target discovery, and precision medicine.