Spatiotemporal MicroRNA-Gene Expression Network Related to Orofacial Clefts.

Craniofacial structures change dynamically in morphology during development through the coordinated regulation of various cellular molecules. However, it remains unclear how these complex mechanisms are regulated in a spatiotemporal manner. Here we applied natural cubic splines to model gene and microRNA (miRNA) expression from embryonic day (E) 10.5 to E14.5 in the proximal and distal regions of the maxillary processes to identify spatiotemporal patterns of gene and miRNA expression, followed by constructing corresponding regulatory networks. Three major groups of differentially expressed genes (DEGs) were identified, including 3,927 temporal, 314 spatial, and 494 spatiotemporal DEGs. Unsupervised clustering further resolved these spatiotemporal DEGs into 8 clusters with distinct expression patterns. Interestingly, we found 2 clusters of differentially expressed miRNAs: 1 had 80 miRNAs monotonically decreasing and the other had 97 increasing across developmental stages. To evaluate the phenotypic relevance of these DEGs during craniofacial development, we integrated data from the CleftGeneDB database and constructed the regulatory networks of genes related to orofacial clefts. Our analysis revealed 2 hub miRNAs, mmu-miR-325-3p and mmu-miR-384-5p, that repressed cleft-related genes , , , , and , while their expression increased over time. On the contrary, 2 hub miRNAs, mmu-miR-218-5p and mmu-miR-338-5p, repressed cleft-related genes , , , , and , while their expression decreased over time. Our experiments indicated that these miRNA mimics significantly inhibited cell proliferation in mouse embryonic palatal mesenchymal (MEPM) cells and O9-1 cells through the regulation of genes associated with cleft palate and validated the role of our regulatory networks in orofacial clefts. To facilitate interactive exploration of these data, we developed a user-friendly web tool to visualize the gene and miRNA expression patterns across developmental stages, as well as the regulatory networks (https://fyan.shinyapps.io/facebase_shiny/). Taken together, our results provide a valuable resource that serves as a reference map for future research in craniofacial development.