Atrial fibrillation (AF) increases risk of heart failure, stroke and death, and AF has been found to have a significant heritable component. Genome wide association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) associated with increased risk of AF. However, the causative variants, relevant genes and mechanisms by which they promote AF remain unclear. To enhance our understanding of the causative genes involved in heritable AF, we propose to evaluate the impact of SNPs identified in recent GWAS on the expression of messenger RNA, miRNA and related proteins in the target tissue of interest, human left atria, taken from a unique biorepository of over 1000 human atrial tissues from cardiac surgery patients. Specific aims are: 1) To determine how AF phenotypes alter the human atrial transcriptome, and 2) To identify and test candidate functional genetic variants that alter atrial transcript expression. Aim 1 studies will use state-of-the-art technology (RNA-seq, miRNA-seq) and bioinformatics to determine AF phenotype associations with gene transcripts, including lowly expressed transcripts and mRNA isoforms, and miRNAs, and co-regulated gene modules. We will test the functional effects of regulating selected genes using siRNA knockdown and cDNA transfection strategies in an atrial myocyte cell line, human ESC-derived atrial cells and in human atrial fibroblasts to determine whether altered expression of these genes affects downstream gene expression and selected biological pathways. Aim 2 studies will identify genetic variants associated with atrial gene expression by expression quantitative trait locus (eQTL), and allelic expression imbalance analyses. Candidate variants will be validated in reporter gene transfection studies. The proposed interdisciplinary studies are a logical and important follow up to recent GWAS that will provide novel, unbiased mechanistic insights into the impact of SNPs highly associated with AF on atrial RNA expression patterns. We expect our studies to identify functional links between AF-associated genetic loci and gene expression, and to identify SNPs, genes, and pathways that are causally related to the etiology and progression of AF and that may represent new targets for AF treatment and prevention.