先天性小耳畸形致病基因的生物信息学分析

Bioinformatics analysis of pathogenic genes of congenital microtia

目的通过生物信息学方法对先天性小耳畸形可疑致病基因进行详细地功能注释分类,构建蛋白相互联系(protein-protein interaction,PPI)网络,以明确致病基因的功能和相互作用关系,预测潜在的致病基因。方法(1)利用小鼠基因组信息学(MGI)数据库检索先天性小耳畸形致病基因,将结果汇总输入STRING数据库构建PPI网络,进行基因本体(Gene ontology,GO)富集分析、KEGG通路分析。结果(1)通过MGI检索获得FGF8、EYA1、HOXA2等68个小耳畸形致病基因。(2)PPI互作网络包含65个节点蛋白和174条互作连线,平均节点度是5.35,集聚系数是0.437,PPI富集P值为0。(3)PPI网络中初步筛选关键节点蛋白,前10项依次为CTNNB1、FGF8、EGFR、BCL2、PAX6、FGF3、FGF10、WNT5A、FGFR1和MAPK1。(4)GO分析和KEGG通路分析显示:致病基因参与耳形态发生、耳发育、胚胎器官形态发生等生物过程;参与结合序列特异性DNA、结合调节区域DNA等分子功能;不同基因表达的产物位于细胞核、细胞器腔等亚显微细胞组件;致病基因参与癌症通路、黑色素瘤等疾病、MAPK、RAS等信号通路途径。结论通过生物信息学工具,构建了先天性小耳畸形致病基因的PPI网络,以及详细的GO、KEGG富集分析数据,关键节点中包含了已被证实的先天性小耳畸形致病基因,初步证明本研究使用生物信息学方法的可行性;部分节点与FGF、WNT等联系密切,可能为先天性小耳畸形潜在的突变基因。

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.