AtMAD

AtMAD integrates genomics, transcriptomics, methylomics, pathway, and phenotype data for Arabidopsis thaliana to quantify large-scale associations such as eQTLs, emQTLs, pathway-mQTLs, GWAS, TWAS, and EWAS.

Key Features:

• Multi-Omics Integration: AtMAD integrates genomics, transcriptomics, methylomics, and phenomics datasets to provide a holistic view of biological processes in Arabidopsis thaliana.
• Association Identification: Facilitates identification of cis-eQTLs, trans-eQTLs, environment-eQTLs, pathway-mQTLs, emQTLs, and supports Genome-Wide Association Studies (GWAS), Transcriptome-Wide Association Studies (TWAS), and Epigenome-Wide Association Studies (EWAS).
• Extensive Data Repository: Contains 11,796 cis-eQTLs, 10,119 trans-eQTLs, 68,837 environment-eQTL associations, 149,622 GWAS-eQTL associations, 265,776 emQTLs, 122,344 pathway-mQTLs, 62,754 significant phenotype-gene associations for TWAS, and 3,993,379 significant phenotype-methylation associations for EWAS.
• Candidate Variant Identification: Identifies candidate variants, methylations, and genes associated with specific phenotypes or biological processes, many of which are supported by experimental evidence.

Scientific Applications:

• Gene regulation analysis: Exploration of gene regulation and expression patterns in Arabidopsis thaliana.
• Environment-eQTL analysis: Understanding the impact of environmental factors on gene expression via environment-eQTLs.
• emQTL analysis: Identification of methylation changes linked to gene expression (emQTLs).
• Genetic association discovery: Discovery of genetic variants associated with phenotypic traits through GWAS and TWAS.

Methodology:

AtMAD applies a multi-omics association strategy that integrates diverse genomic, transcriptomic, methylomic, pathway, and phenotype datasets to identify associations across omics layers.