Abstract Body: Congenital heart disease (CHD) is the most common birth defect, affecting ~ 1% of all live births. However, the genetic causes of ~56% of cases remain unknown. Coding and non-coding variants of unknown significance (VUSs) may contribute to a substantial fraction of these cases without clearly identified etiology. Current methods for testing the functional significance of VUSs are resource-intensive, creating a barrier to testing this hypothesis. Here, we developed a platform that combines genome editing with genetically barcoded iPSCs to enhance the throughput and accuracy of VUS functional assessment. First, we generated a genetically barcoded iPSC pool by introducing 12-bp random barcode within the 3’UTR of GAPDH, which can be detected by 10x GEX 3’ single-cell RNA-seq. Then we introduced the genetic variants of CHD into the barcoded iPSCs. The barcoded iPSC lines were pooled, differentiated to cardiomyocytes (CM), and analyzed by single-cell RNA-seq. To test this platform, we assessed 16 iPSC lines including 10 WT, 2 GATA4^+/-, 2 GATA4^-/-, and 2 WAC^+/- in a pool. The 10 WT lines displayed very consistent iPSC-CM cell state distributions, whereas GATA4 Hom and Het altered the distribution of iPSC-CM cell states. Heterozygous inactivation of WAC, a CHD candidate gene, also changed CM cluster and state proportions. We deployed this platform to interrogate RBFOX2 missense VUS and CHD de novo non-coding variants (ncDNVs). A subset of these VUS altered cardiac differentiation, suggesting that they are pathogenic. Collectively, we established a scalable and reliable platform to dissect the CHD VUS impact on cardiac differentiation. The approaches that we develop will have broad applicability to deciphering variant impact in cardiovascular and other human diseases.