Introduction: Prominent arrhythmias are features of arrhythmogenic cardiomyopathy (ACM) and arrhythmogenic dilated cardiomyopathy (aDCM). Despite clinicopathological differences, these diseases share common genetic causes. Hypothesis: This study aimed to identify variants in ACM and aDCM and map the candidate genetic regulators using a mouse genetic reference population (GRP). Methods: Whole exome sequencing was performed on 226 individuals with ACM and 102 patients with aDCM. Bioinformatics analysis was applied to identify the pathogenic or likely pathogenic variants followed by direct sequencing confirmation. Expression quantitative trait loci (eQTLs) mapping to heart transcriptomes of GRP of BXD recombinant inbred (RI) mice was conducted in GeneNetwork (http://www.genenetwork.org). Results: In the ACM cohort, a total of 82 variants (MAF<0.01) in 24 genes have been confirmed being positive in 42 probands. Depending on the frequency of the identified variants, the top 10 genes (excluding TTN) with the most pathogenic variants were PKP2, MYH6, FLNC, RYR2, MYH7B, PLEC, JPH2, SYNE1, NRAP and POSTN. In the aDCM cohort, 141 pathogenic variants have been identified and 91 patients harbored at least 1 deleterious variant. The top 10 genes were RYR2, FLNC, MYH7, DSP, SCN5A,MYPN, NEBL, CTNNA3, ACAP6 and SLC22A5. We analyzed the distribution of the first principal component (PC1) of mRNA expression levels of those 10 genes (eigentraits) from each cohort in the heart across BXD strains. Interval mapping for PC1 eigentraits for ACM identified a significant eQTL (P<0.05) in the mouse genome at 24-36 Mb of chromosome (Chr) 6. In aDCM, interval mapping for PC1 eigentraits identified 3 suggestive eQTLs at Chr 5 (44-53 Mb), Chr 6 (32-34 Mb) and Chr 15 (82-84 Mb). Further gene exploration of these eQTLs suggested that Mtpn, Lep, Cyb5r3, Tspo, Slit2, and Ppargc1a could be common regulators that interact with those top ACM and aDCM genes. Conclusions: This study identified diverse genes in ACM and aDCM cases. Our joint human and mouse analysis using a systems genetics approach identified genetic regulators that could affected expression of genes with pathogenic variants in ACM and aDCM patients.