Integrative multiomic analysis on single-nucleotide variants identifies candidate genes for human craniofacial malformation
Abstract
Craniofacial malformation (CFM) is a congenital defect encompassing a wide range of phenotypic presentations and is largely driven by genetics. Despite the discovery of more than 300 causal genes, there are a myriad of CFM cases with unknown genetic etiology. The complex gene regulations and heterogeneous cellular interactions in the developing head complicate disease-gene identification and prenatal genetic diagnosis. Recent progress in multiomic profiling of human embryogenesis enables the discovery of novel candidates from established GWAS data. Here, we developed an approach to prioritize GWAS variants using the epigenomes and single-cell transcriptomes of embryonic tissues and progenitor cells by implementing machine learning classifiers and combinatorial analysis. Systematic evaluation revealed significant improvement in the machine learning model performance after integrating transcriptome of neural crest cells (NCCs) and cranial placodes, as well as epigenomic profile of early craniofacial tissues. We identified 249 genes from the best-performing classifier, which include documented CFM-associated genes. Gene regulatory network (GRN) inference showed that 24 candidate genes were involved in NCC- and placode-specific regulons, of which 15 (F11R, ISL1, KANK4, L1TD1, LAMB1, MIA, PRDM1, S100A10, S100A11, STOM, STT3B, TESK2, USP43, WDR86, ZNF439) were novel candidates for human CFM. Motif analysis revealed putative functional SNPs contributing to CFM pathogenesis by disrupting transcription factor binding motifs in neural crest and placodes. Our analyses suggested that PRDM1 and ISL1 are strong candidates for human CFM, as supported by other animal functional studies. This study demonstrates a successful method for disease gene identification using epigenomic and single-cell transcriptomic profiles, and sheds light on the linkage between early cell lineages and the pathogenic process of CFM.
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H., Y. M., H., S. K. K., K., T. K., W., C. K., H., S. M. (2025). Integrative multiomic analysis on single-nucleotide variants identifies candidate genes for human craniofacial malformation. arXiv preprint arXiv:10.64898/2025.12.29.696805.
Yam, M. H., So, K. K. H., Tong, K. K., Choy, K. W., and Sham, M. H.. "Integrative multiomic analysis on single-nucleotide variants identifies candidate genes for human craniofacial malformation." arXiv preprint arXiv:10.64898/2025.12.29.696805 (2025).