Abstract
Genome-wide association studies (GWASs) are the most widely used method to identify genetic risk loci associated with orofacial clefts (OFC). However, despite the increasing size of cohort, GWASs are still insufficient to detect all the heritability, suggesting there are more associations under the current stringent statistical threshold. In this study, we obtained an integrated epigenomic dataset based on the chromatin conformation of a human oral epithelial cell line (HIOEC) using RNA-seq, ATAC-seq, H3K27ac ChIP-seq, and DLO Hi-C. Presumably, this epigenomic dataset could reveal the missing functional variants located in the oral epithelial cell active enhancers/promoters along with their risk target genes, despite relatively less-stringent statistical association with OFC. Taken a non-syndromic cleft palate only (NSCPO) GWAS data of the Chinese Han population as an example, 3664 SNPs that cannot reach the strict significance threshold were subjected to this functional identification pipeline. In total, 254 potential risk SNPs residing in active cis-regulatory elements interacting with 1 718 promoters of oral epithelium-expressed genes were screened. Gapped k-mer machine learning based on enhancers interacting with epithelium-expressed genes along with in vivo and in vitro reporter assays were employed as functional validation. Among all the potential SNPs, we chose and confirmed that the risk alleles of rs560789 and rs174570 reduced the epithelial-specific enhancer activity by preventing the binding of transcription factors related to epithelial development. In summary, we established chromatin conformation datasets of human oral epithelial cells and provided a framework for testing and understanding how regulatory variants impart risk for clefts.