肖润颖,肖建华,王比男,李寒梅,郭海春,莫鸿英,黎小弟,任懂平,付枭,柳红艳,黎丽.基于转录组学的不明原因复发性流产关键基因及机制分析.[J].中南医学科学杂志.,2021,(2):162-168.
基于转录组学的不明原因复发性流产关键基因及机制分析
Analysis of key genes and mechanism of unexplained recurrent abortion based on transcriptome
  
DOI:10.15972/j.cnki.43-1509/r.2021.02.009
中文关键词:  复发性流产  转录组测序技术  基因表达谱  单核苷酸多态性 [
英文关键词:recurrent abortion  RNA-seq  gene expression profile  single nucleotide polymorphisms
基金项目:
作者单位
肖润颖 南华大学衡阳医学院病原生物学研究所,湖南省衡阳市 421001 
肖建华 南华大学衡阳医学院病原生物学研究所,湖南省衡阳市 421001 
王比男 长沙市妇幼保健院,湖南省长沙市 410007 
李寒梅 长沙市妇幼保健院,湖南省长沙市 410007 
郭海春 长沙市妇幼保健院,湖南省长沙市 410007 
莫鸿英 长沙市妇幼保健院,湖南省长沙市 410007 
黎小弟 长沙市妇幼保健院,湖南省长沙市 410007 
任懂平 优生贝北京 
付枭 长沙市妇幼保健院,湖南省长沙市 410007 
柳红艳 长沙市妇幼保健院,湖南省长沙市 410007 
黎丽 南华大学衡阳医学院病原生物学研究所,湖南省衡阳市 421001
长沙市妇幼保健院,湖南省长沙市 410007 
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中文摘要:
      目的研究不明原因复发性流产(URSA)患者蜕膜组织与正常蜕膜组织转录组的差异基因表达,探究其发病涉及的主要基因和关键通路。方法应用转录组测序技术(RNA-Seq)检测URSA组和对照组蜕膜组织的差异基因表达情况,通过GO、KEGG、GSEA、PPI网络分析等方法找到其关键差异基因及通路。采用单核苷酸多态性(SNP)芯片技术对关键差异基因单核苷酸多态性位点(SNP)的多态性进行检测。结果共筛到1 057个差异表达基因(DEGs),上调基因469个,下调基因588个。GO分析显示,DEGs主要参与T细胞活化、分化和免疫应答过程的负调控等生物学过程。KEGG分析显示,DEGs主要富集到Toll样受体信号通路、抗原加工和递呈、同种异体移植排斥反应等信号通路。基因集富集分析(GSEA)与蛋白相互作用网络(PPI网络)分析筛选出的关键节点基因主要与JAK-STAT、MAPK等信号通路及Treg细胞活化及抑制功能相关;其中DUSP1、MAFB、TIGIT、HLA-DPA1、白细胞介素-2受体α(IL-2RA)等可能是影响URSA发生发展的关键基因。SNP芯片筛选出HLA-DPA1 rs1042866、HLA-DPA1 rs2567279及IL-2RA rs2025346等基因位点在两组间分布的差异具有显著性(P<0.05),且HLA-DPA1 rs1042866的多态性变异(C>T)可能降低了URSA的发病风险(P<0.05),而HLA-DPA1 rs2567279的多态性变异(T>C)及IL-2RA rs2025346的多态性变异(G>A)则可能提高了URSA的发病风险(P<0.05)。结论URSA患者蜕膜组织与正常蜕膜组织转录组的基因表达的差异具有显著性,DUSP1、MAFB、TIGIT、HLA-DPA1、IL-2RA等可能是影响URSA发生发展的关键基因,主要与免疫调节功能相关。HLA-DPA1 rs1042866、rs2567279及IL-2RA rs2025346基因位点多态性变异可能与URSA的发病风险有关。
英文摘要:
      To explore the main genes and key pathways involved in the pathogenesis of unexplained recurrent spontaneous abortion (URSA) by studying the differences gene expression between decidual tissues of URSA patients and normal decidual tissues. MethodsHigh-throughput RNA-sequencing (RNA-seq) technologies was used to detect the differential gene expression in decidua of URSA group and control group, and the key differential genes and pathways were found by GO, KEGG, GSEA and PPI network analysis. Single nucleotide polymorphisms (SNP) chip technology was used to detect the single nucleotide polymorphisms (SNPs) of key differential genes. ResultsA total of 1 057 differentially expressed genes (DEGs) were screened, including 469 up-regulated genes and 588 down regulated genes. GO analysis showed that DEGs were mainly involved in T cell activation, differentiation and negative regulation of immune response. KEGG analysis showed that DEGs were mainly enriched in Toll like receptor signaling pathway, antigen processing and presentation, allograft rejection and other signaling pathways. PPI network analysis combined with GSEA analysis showed that the key node genes were mainly related to JAK-STAT, MAPK signaling pathways and the activation and inhibition of Treg cell; DUSP1, MAFB, TIGIT, HLA-DPA1 and IL-2RA may be the key genes affecting the occurrence and development of URSA. The distribution of HLA-DPA1 rs1042866, HLA-DPA1 rs2567279 and IL-2RA rs2025346 were significantly different between the two groups (P<0.05). The polymorphism of HLA-DPA1 rs1042866 (C>T) may reduce the risk of URSA (P<0.05), while the polymorphism of HLA-DPA1 rs2567279 (T>C) and IL-2RA rs2025346(G>A) may increase the risk of URSA (P<0.05). ConclusionThere is a significant difference in gene expression between decidual tissue and normal decidual tissue in patients with URSA. DUSP1, MAFB, TIGIT, HLA-DPA1 and IL-2RA may be the key genes affecting the occurrence and development of URSA, which are mainly related to immunomodulatory function. The polymorphisms of HLA-DPA1 rs1042866, rs2567279 and IL-2RA rs2025346 gene loci may be related to the risk of URSA.
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