遗传 ›› 2008, Vol. 30 ›› Issue (6): 788-794.doi: 10.3724/SP.J.1005.2008.00788

• 研究报告 • 上一篇    下一篇

干扰素信号传导通路与其基因组多态性网络模型的建立

崔建军; 田庚善; 田地; 曾争   

  1. 北京大学第一医院感染疾病科, 北京 100034

  • 收稿日期:2007-11-30 修回日期:2008-01-08 出版日期:2008-06-10 发布日期:2008-06-10
  • 通讯作者: 曾争

An integrated biological model for interferon signaling pathway and its gene polymorphisms

CUI Jian-Jun; TIAN Geng-Shan; TIAN Di; ZENG Zheng

  

  1. Department of Infectious Disease, Peking University First Hospital, Beijing 100034, China
  • Received:2007-11-30 Revised:2008-01-08 Online:2008-06-10 Published:2008-06-10
  • Contact: ZENG Zheng

摘要:

通过检索Pubmed、Embase数据库, 整合文献资料, 运用Teranode Design Suite(TDS)生物软件, 建立干扰素(IFN)发挥生物学作用的信号传导通路。应用SNP Trawler软件搜索通路中相关基因的SNP信息, 并以属性形式在通路模型中给以显示。结果构建了融合基因的遗传信息尤其是SNP相关信息的IFN发挥生物学作用的信号传导通路的网络模型, 此模型共包含JAK-STAT, MAPK-p38和PI3K 3条主要传导通路, 干扰素通过不同的信号传导通路发挥不同的生物活性, 其中Ⅰ型干扰素通过这3条通路发挥抗病毒、抗细胞增殖及免疫调节等重要作用, 而Ⅱ型干扰素则通过JAK-STAT和MAPK-p38路径发挥生物学作用, Ⅲ型干扰素则仅通过PI3K通路发挥生物学作用; 这3条传导通路包含98个基因和19 693个SNPs, 组成了复杂的基因间相互作用网络。此通路模型的成功建立, 一方面为研究SNP对IFN生物学作用的影响而预测IFN疗效提供理论基础, 另一方面为实现个体化诊疗、发现新的药物作用靶点及开发新的药物奠定基础。

关键词: 干扰素, 信号传导通路, 模型, 基因多态性

Abstract:

To construct a systemic structural model for interferon (IFN) signaling pathways with gene’s single nucleotide polymorphisms (SNPs) information, it is visual to investigate the effects of gene-gene interaction on IFN signaling path-ways. The genes function information was retrieved from Pubmed and Embase database. The IFN signaling pathways were constructed by applying Teranode Design Suite (TDS) biological software. The SNPs information of genes in pathways was retrieved by using SNP Trawler biological software. The biological systemic structural model for IFN signaling pathways, involving in genetic information, particularly their SNPs information, was constructed successfully. It contained JAK-STAT, MAPK-p38 and PI3K pathways, through which IFNs play variable biological roles. Type-I-IFN makes an important role in against viral infection, cell proliferation and immunoregulation by these three pathways. However, the biological activities of type-II-IFN are through JAK-STAT and MAPK-p38 pathways, and type-III-IFN is only through PI3K pathway. These pathways contained 98 genes and 19 693 SNPs information, which consist of a complicate gene-gene interactional network. In conclusion, this software model not only helps us intensively research the effects of SNPs on IFN biological roles and predict IFN therapeutic effect, but also set up a good foundation for translational medicine, discovering new target of drugs and developing new drugs.