GWAS Atlas
GWAS Atlas provides a curated repository of genome-wide variant-trait associations across multiple plant and animal species to support genetic association and trait-mapping research.
Key Features:
- Curated associations: Manually curated genome-wide variant-trait associations extracted from the scientific literature.
- Data integration: Integration of association data from 254 scientific publications.
- Association scope: Contains 75,467 variant-trait associations covering 614 traits.
- Species coverage: Includes seven cultivated plant species (cotton, Japanese apricot, maize, rapeseed, rice, sorghum, soybean) and two domesticated animals (goat, pig).
- Ontology annotation: Trait annotations use the Plant Trait Ontology and the Animal Trait Ontology for Livestock for structured classification.
- Entity mapping: Associations are cataloged with mappings to variants, genes, traits, studies, and publications.
Scientific Applications:
- Variant-trait exploration: Enable exploration of variant-trait associations to investigate complex biological processes.
- Agronomic marker identification: Identify genetic markers associated with important crop and agronomic traits.
- Livestock marker identification: Identify genetic markers associated with traits in goat and pig.
- Breeding and trait improvement: Support marker-assisted breeding and trait-improvement efforts.
Methodology:
Associations were extracted and integrated from 254 publications, subjected to manual curation, annotated using the Plant Trait Ontology and the Animal Trait Ontology for Livestock, and cataloged with mappings to variants, genes, traits, studies, and publications.
Topics
Details
- Added:
- 11/14/2019
- Last Updated:
- 12/9/2020
Operations
Publications
Tian D, Wang P, Tang B, Teng X, Li C, Liu X, Zou D, Song S, Zhang Z. GWAS Atlas: a curated resource of genome-wide variant-trait associations in plants and animals. Nucleic Acids Research. 2019;48(D1):D927-D932. doi:10.1093/nar/gkz828. PMID:31566222. PMCID:PMC6943065.
Downloads
- Downloads pagehttps://bigd.big.ac.cn/gwas/downloads