Bioinformatics Analysis of Differentially Expressed Genes, Methylated Genes, and miRNAs in Unexplained Recurrent Spontaneous Abortion
Bioinformatics Analysis of Differentially Expressed Genes, Methylated Genes, and miRNAs in Unexplained Recurrent Spontaneous Abortion
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DOI：
10.1089/cmb.2019.0158
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发表时间：
2019-07-15
影响因子：
1.7
通讯作者：
Huang, Wei
中科院分区：
文献类型：
--
作者：
Chen, Hengxi;Cheng, Shuting;Huang, Wei
大约一半的原因不明的复发性自然流产仍然无法解释（URSA）。本研究的目的是对URSA中差异表达基因（DE-genes）、DE-methylated基因和DE-miRNAs的生物学特性和相关通路提供新的见解，并构建一个miRNA-mRNAs分子网络。从GEO数据集获得四个数据集（GSE 22490，GSE 121950，GSE 73025和GSE 43256）。我们使用R软件中的LIMMA包鉴定DE基因、DE甲基化基因和DE-miRNA。使用大卫进行功能和富集分析。通过STRING进行蛋白质-蛋白质网络。利用DIANA-microT-CDS预测DE-miRNA的靶基因。然后构建miRNA-mRNAs网络。在两个表达谱数据集（GSE 121950和GSE 22490）中有137个基因重叠。我们发现了10个重叠的DE-甲基化基因和DE-基因相反的表达变化趋势。这10个基因均为高甲基化低表达基因。通路分析表明DE基因在破骨细胞分化、利什曼病、NF-κ B信号通路、Toll样受体信号通路和结核病中富集。基于蛋白质-蛋白质相互作用分析，TLR 8、TLR 2、CD 86、TLR 4、IL 10、CD 163、FCGR 1A、CXCL 8、FCGR 3A、HCK、PLEK和MNDA被鉴定为DE-基因的枢纽基因。我们筛选出47个DE-miRNAs和42个DE-miRNAs预测的靶基因与137个DE-基因之间的重叠DE-基因。构建miRNA-mRNAs网络。本研究鉴定了参与URSA发生和进展的几种基因和miRNA，包括FCGR 1A、FCGR 3A、CXCL 8、HCK、PLEK、IL 10、hsa-miR-498和hsa-miR-4530。虽然需要进一步的体内和体外验证，我们的研究结果可能为未来的研究提供了理论基础。
Approximately half of the unexplained recurrent spontaneous abortions remain unexplained (URSAs). We aimed to provide novel insights into the biological characteristics and related pathways of differentially expressed genes (DE-genes), DE-methylated genes, and DE-miRNAs in URSA, and construct a molecular miRNAs-mRNAs network. Four data sets (GSE22490, GSE121950, GSE73025, and GSE43256) were gained from GEO data sets. We identified the DE-genes, DE-methylated genes, and DE-miRNAs using the LIMMA package in R software. Function and enrichment analyses were conducted using DAVID. A protein-protein network was performed by STRING. We predicted the target genes of DE-miRNA using DIANA-microT-CDS. Then, we constructed miRNAs-mRNAs network. There were 137 genes that overlapped in two expression profile data sets (GSE121950 and GSE22490). We found 10 overlapping DE-methylated genes and DE-genes with opposite expression alteration trends. All those 10 genes were hypermethylated lowly expressed genes. Pathway analysis illustrated that DE-genes were enriched in osteoclast differentiation, leishmaniasis, NF-kappa B signaling pathway, Toll-like receptor signaling pathway, and tuberculosis. Based on protein-protein interaction analysis, TLR8, TLR2, CD86, TLR4, IL10, CD163, FCGR1A, CXCL8, FCGR3A, HCK, PLEK, and MNDA were identified as hub genes for DE-genes. We screened out 47 DE-miRNAs and 42 overlapping DE-genes between predicted target genes of DE-miRNAs and the 137 DE-genes. We then constructed miRNAs-mRNAs network. This study identified several genes and miRNAs involved in the development and progression of URSA, including FCGR1A, FCGR3A, CXCL8, HCK, PLEK, IL10, hsa-miR-498, and hsa-miR-4530. Although further in vivo and in vitro validations are required, our results may provide a theoretical basis for future studies.