Bioinformatics analysis of pathogenic genes of congenital microtia

Abstract

Objective Bioinformatics methods were used to annotate the suspicious pathogenic genes of congenital microtia in detail, and construct the protein-protein interaction (PPI) networks to clarify the function and interaction of pathogenic genes, so as to predict the potential pathogenic genes. Methods The pathogenic genes of congenital microtia were searched using the mouse genome informatics (MGI). The results were summarized into the STRING database to construct PPI networks. The Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were carried out. Results Sixty-eight congenital microtia-related pathogenic genes such as FGF8, EYA1 and HOXA2 were searched by MGI. The PPI network contained 65 nodes and 174 edges. The average node degree was 5.35. The clustering coefficient was 0.437 and the PPI enrichment P = 0. The key node proteins were screened in PPI networks. The top ten were CTNNB1, FGF8, EGFR, BCL2, PAX6, FGF3, FGF10, WNT5A, FGFR1 and MAPK1. GO analysis and KEGG pathway analysis showed: the pathogenic genes were involved in the biological process of ear morphogenesis, ear development and embryonic organ morphogenesis. They also get involved in the molecular regulation, including sequence-specific DNA binding and regulatory region DNA binding. Expression of different genes were located in nucleus and other sub-microscopic cell components. Pathogenic genes were also involved in cancer pathway, melanoma, MAPK signaling pathways, RAS signaling pathways and other signaling pathways. Conclusions By using bioinformatics tools, we constructed the PPI networks of the congenital microtia pathogenic genes, and obtained detailed GO enrichment and KEGG pathway data. The key nodes contained the confirmed pathogenic genes of congenital microtia, which preliminarily proved the feasibility of the bioinformatics method in this study. We found some nodes were closely linked with FGF and WNT, which may be potential mutant genes of congenital microtia, although further study is needed. Key words: Congenital microtia; Bioinformatics; Protein-protein interaction