biostudies-literatureYan FNIDCR NIH HHSNLM NIH HHSNational Institute of Dental and Craniofacial ResearchCancer Prevention and Research Institute of Texas1398-1407https://www.ebi.ac.uk/biostudies/studies/S-EPMC9516630biostudies-literatureUnknown101(11)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 <i>Adamts3</i>, <i>Runx2</i>, <i>Fgfr2</i>, <i>Acvr1</i>, and <i>Edn2</i>, 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 <i>Pbx2</i>, <i>Ermp1</i>, <i>Snai1</i>, <i>Tbx2</i>, and <i>Bmi1</i>, 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.Journal of dental researchSpatiotemporal MicroRNA-Gene Expression Network Related to Orofacial Clefts.PMC9516630R01 DE030122CPRIT RP180734R03DE028340R03DE027393R03DE026509R01LM012806R03 DE026208R01 LM012806R03 DE026509R01 DE029818R03DE027711R01DE030122R03 DE028103R03DE026208R03 DE027711R03 DE027393R03 DE028340R03DE028103CPRIT RP210045Suzuki AJia PSimon LMIwaya CZhao ZIwata JYan FfalseSpatiotemporal 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 <i>Adamts3</i>, <i>Runx2</i>, <i>Fgfr2</i>, <i>Acvr1</i>, and <i>Edn2</i>, 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 <i>Pbx2</i>, <i>Ermp1</i>, <i>Snai1</i>, <i>Tbx2</i>, and <i>Bmi1</i>, 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.2022-01-01T00:00:00Z2022 Oct2026-05-28T02:02:13.659Z2025-04-05T15:24:29.704ZS-EPMC95166303577401010.1177/00220345221105816