Introduction: Microtia, a prevalent congenital maxillofacial deformity, significantly impacts the physical and psychological health of children. Its etiology, especially in non-syndromic cases, remains a complex and partially understood domain, complicating etiological treatment. Recent studies pointed to a genetic predisposition in non-syndromic microtia, yet research on susceptible or pathogenic genes is limited. Objectives: This study focused on identifying key biomarker genes in microtia cartilage to elucidate pathogenesis and assist in prenatal diagnosis. Methods: We first collated two bulk transcriptome datasets from the GEO database, followed by functional enrichment analysis and Weighted Gene Co-expression Network Analysis (WGCNA) to pinpoint differentially expressed genes (DEGs) and gene modules. The subsequent intersection of DEGs with WGCNA modules, aided by support vector machine-recursive feature elimination (SVM-RFE) and protein-protein interaction (PPI) networks, predicted potential susceptibility genes for microtia. Finally, we integrated bulk RNA sequencing with single-cell data Results: We identified Conclusion: Our findings implicate