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AtMAD: Arabidopsis thaliana multi-omics association database.
Yiheng Lan1,2, Ruikun Sun2, Jian Ouyang2
1Key Laboratory of Saline-alkali Vegetation Ecology Restoration, Ministry of Education, Northeast Forestry University, Harbin, Heilongjiang 150040, China.
Nucleic Acids Research
|November 21, 2020
Summary
A new database, AtMAD, integrates multi-omics data for Arabidopsis thaliana, revealing extensive genetic associations. This resource aids in understanding plant biological mechanisms and identifying key genetic variants for specific traits.
Area of Science:
- Plant biology
- Genomics
- Bioinformatics
Background:
- Multi-omics data integration is crucial for understanding complex biological systems.
- Arabidopsis thaliana is a model organism with abundant multi-omics data, yet lacks a unified association resource.
- Previous studies have analyzed individual omics layers, limiting comprehensive mechanistic insights.
Purpose of the Study:
- To develop a comprehensive, public repository for multi-omics associations in Arabidopsis thaliana.
- To facilitate the identification of various quantitative trait loci (eQTLs, emQTLs) and genome-wide associations (GWAS, TWAS, EWAS).
- To provide a platform for exploring genotype-phenotype relationships and biological mechanisms.
Main Methods:
- Development of the Arabidopsis thaliana Multi-omics Association Database (AtMAD).
- Integration of genomics, transcriptomics, methylomics, pathway, and phenomics data.
- Systematic analysis of associations including eQTLs, emQTLs, mQTLs, GWAS, TWAS, and EWAS.
Main Results:
- AtMAD stores large-scale multi-omics associations for Arabidopsis.
- Identified 11,796 cis-eQTLs and 10,119 trans-eQTLs.
- Discovered 265,776 expression-methylation quantitative trait loci (emQTLs) and 122,344 pathway-mQTLs, alongside numerous GWAS, TWAS, and EWAS associations.
Conclusions:
- AtMAD provides a valuable resource for multi-omics data integration in Arabidopsis.
- The database enables novel insights into plant biological mechanisms through associated networks.
- Facilitates discovery of candidate genes and variants linked to specific phenotypes.
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