畜牧兽医学报 ›› 2018, Vol. 49 ›› Issue (4): 794-803.doi: 10.11843/j.issn.0366-6964.2018.04.017

• 预防兽医 • 上一篇    下一篇

人工感染沙门菌牦牛脾中相关差异表达基因筛选

陈通1, 朱育星1, 蔡雯祎1, 杨琦玥1, 邓志和1, 兰道亮2*   

  1. 1. 西南民族大学 生命科学与技术学院, 成都 610041;
    2. 西南民族大学 青藏高原研究院, 成都 610041
  • 收稿日期:2017-11-23 出版日期:2018-04-23 发布日期:2018-04-23
  • 通讯作者: 兰道亮,研究员,博士,主要从事高原动物功能基因组学研究,E-mail:landaoliang@163.com
  • 作者简介:陈通(1992-),男,江苏扬州人,硕士生,主要从事高原动物功能基因组研究,E-mail:827533489@qq.com;朱育星(1992-),女,四川凉山人,硕士生,主要从事高原动物功能基因组研究,E-mail:549850163@qq.com。
  • 基金资助:

    四川省青年科技基金项目(2014JQ0043);西南民族大学中央高校基本科研业务费专项资金(2015NZYTD01)

Screening of Differentially Expressed Genes Associated with Salmonella Infection from Spleen of Artificially Infected Yak

CHEN Tong1, ZHU Yu-xing1, CAI Wen-yi1, YANG Qi-yue1, DENG Zhi-he1, LAN Dao-liang2*   

  1. 1. College of Life Science and Technology, Southwest Minzu University, Chengdu 610041, China;
    2. Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu 610041, China
  • Received:2017-11-23 Online:2018-04-23 Published:2018-04-23

摘要:

旨在从基因组转录水平解析牦牛抗沙门菌感染相关免疫基因及其调控网络。以牦牛沙门菌为模式病原体,以牦牛为研究对象,在12、24、48 h三个不同时间段利用RNA-Seq测序技术对感染牦牛的外周免疫器官脾进行转录组测序。通过比较分析三个时间段感染牦牛和健康牦牛转录组数据,筛选出差异基因,然后对这些差异基因进行GO、KEGG功能分析,并进行共表达网络分析。结果共筛选出413个差异基因,其中185个表现为上调,228个表现为下调,GO分析显示,与生物过程相关的类别比例最大,其中最为富集的是细胞过程、代谢过程、生物调节、生物过程的调控及单一有机体过程。KEGG分析显示,各时间段富集前20的通路中,与感染、免疫相关的通路占有较大比例,这些通路涉及的差异基因主要为趋化因子。WGCNA分析显示,处于网络枢纽的基因共66个,处于网络中心的基因是SCOCNOCT。本研究在组学层面上探讨了牦牛脾细胞与沙门菌的分子互作机制。

Abstract:

The present study was designed to analyze the immune genes against Salmonella infection and their regulatory network in yak at the genomic transcriptional level. Using yak Salmonella as the model pathogen and yak as the object, transcriptome sequencing was performed on the central immune organ of spleen in infected yak by RNA-Seq sequencing technology at three different periods of 12, 24, and 48 hours, respectively. Transcriptome data from the three different periods were compared between the infected and the control healthy yaks and differentially expressed genes were screened out. The GO and KEGG functional analysis of these differentially expressed genes were conducted and the co-expression network was further analyzed. Results showed that 413 differentially expressed genes were selected, of which 185 were up-regulated and 228 were down regulated. GO analysis showed that genes related to biological process accounted for the largest percentage, among which the most enriched ones were those involved in cellular process, metabolic process, biological regulation, regulation of biological process and single organism process. KEGG analysis revealed that infection-and immune-related pathways presented a larger portion in the top 20 pathways enriched in all three periods, and the major genes involved in these pathways were chemokines. WGCNA analysis showed 66 genes in network hubs, and those in the network center were SCOC and NOCT. The present study explored the molecular interaction mechanism of spleen cells against Salmonella in yak at the omics level.

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