Genome-wide association studies have found over 100 genetic loci associated with atrial fibrillation (AF). The majority of these loci contain non-coding variants. It is thought that the variants interfere with regulatory element function, thus altering transcription levels of target genes. These target genes usually reside within the same conformational DNA structure called topologically associated domain. Furthermore, 9 of the associated loci are in the vicinity of key cardiac transcription factors (TFs) (e.g. ZFHX3, TBX5, PITX2, NKX2-5) which indicates the potential involvement of a TF network in the mechanism of AF development. One such a cardiac TF is T-box transcription factor 5 (TBX5), which is required for the development of the chamber myocardial phenotype and specification of the conduction system. Variants of loci associated with AF are found in close proximity to genes such as TBX5, suggesting that abnormal dosages of TFs could predispose to atrial arrhythmias. In this thesis, we developed an approach to prioritize target genes of disease-associated variant regions, based on chromosome conformation and expression data, thus prioritizing potential AF-target genes. Using regulatory element prediction, chromatin accessibility data and a regulatory element reporter assay, we prioritize AF-associated variants with regulatory potential and subsequently allele-specific regulatory potential. We demonstrate the validity of the prioritized target genes and variant regions with regulatory potential of several AF-associated loci in vivo using CRISPR-Cas9. Furthermore, we characterized a TBX5-p.G125R mutation model of an atypical HOS family with high prevalence of AF. Using this model, we find promiscuous TF binding sites leading to distinct deregulation of target and “off-target” genes and resulting in the observed atrial and junctional arrhythmias. Although in vivo modeling was instrumental in finding AF-associated target genes and TF network deregulation, such modeling is currently insufficient to determine the effect of multiple synergistic SNPs in parallel, which in all likelihood represents the true pathological mechanism of AF in the general population. Nevertheless, this work shows the relevance of dissecting AF-associated loci and brings the field one step closer to unraveling the mechanisms underlying AF.