Database Commons

a catalog of biological databases

e.g., animal; RNA; Methylation; China

Database Profile

General information

Full name: Genome-Wide SNP-trait Associations Atlas
Description: GWAS Atlas is a public and manually curated database of published genome-wide SNP-trait associations for plants and animals.
Year founded: 2019
Last update: 2019
Real time : Checking...
Country/Region: China

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Contact information

University/Institution: Beijing Institute of Genomics, Chinese Academy of Sciences
Address: 1 Beichen West Road, Chaoyang District, Beijing 100101, China
City: Beijing
Province/State: Beijing
Country/Region: China
Contact name (PI/Team): Shuhui Song
Contact email (PI/Helpdesk):


GWAS Atlas: a curated resource of genome-wide variant-trait associations in plants and animals. [PMID: 31566222]
Tian D, Wang P, Tang B, Teng X, Li C, Liu X, Zou D, Song S, Zhang Z.

GWAS Atlas ( is a manually curated resource of genome-wide variant-trait associations for a wide range of species. Unlike existing related resources, it features comprehensive integration of a high-quality collection of 75 467 variant-trait associations for 614 traits across 7 cultivated plants (cotton, Japanese apricot, maize, rapeseed, rice, sorghum and soybean) and two domesticated animals (goat and pig), which were manually curated from 254 publications. We integrated these associations into GWAS Atlas and presented them in terms of variants, genes, traits, studies and publications. More importantly, all associations and traits were annotated and organized based on a suite of ontologies (Plant Trait Ontology, Animal Trait Ontology for Livestock, etc.). Taken together, GWAS Atlas integrates high-quality curated GWAS associations for animals and plants and provides user-friendly web interfaces for data browsing and downloading, accordingly serving as a valuable resource for genetic research of important traits and breeding application.

Nucleic Acids Res. 2020:48(D1) | 27 Citations (from Europe PMC, 2022-05-14)


All databases:
693/5177 (86.633%)
Genotype phenotype and variation:
86/752 (88.697%)
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Record metadata

Created on: 2018-01-28
Curated by:
Dong Zou [2019-12-03]
Zhang Zhang [2019-11-12]
Dong Zou [2019-09-09]
Zhang Zhang [2019-06-21]
huma shireen [2018-04-16]
Zhaohua Li [2018-01-27]