Network analysis reveals important genes in human placenta. Issue 8 (18th May 2021)

• Record Type: Journal Article
• Authors: Lin, Peihong; Lai, Xuedan; Wu, Ling; Liu, Wei; Lin, Shiqiang; Ye, Jianwen
• Is Part Of: Journal of obstetrics and gynaecology research. Volume 47:Issue 8(2021)
• Page Start: 2607
• Page End: 2615
• Publication Date: 2021-05-18
• Subjects: cytotrophoblast -- extravillous trophoblast -- fetal growth restriction -- gestational diabetes mellitus -- preeclampsia -- preterm birth -- syncytiotrophoblast -- transcriptome -- villous stromal cell; Gynecology -- Periodicals; Obstetrics -- Periodicals; 618.1005
• DOI: 10.1111/jog.14820
• Languages: English
• ISSNs: 1341-8076

Abstract

Abstract: Aim: To determine which genes are important in placenta by network analysis. Methods: Placenta expressing genes were screened from RNA‐Seq data. Protein–protein interaction data were downloaded from STRING (v11.0) database. Google PageRank (PR) algorithm was used to identify important placental genes from protein interaction network. Six placental disease‐related datasets were downloaded from NCBI GEO database, and the differential expression of the 99 genes was identified. Results: We calculated PR for each placenta expressing gene and defined the top 99 genes with high PR as important genes. GAPDH has the highest PR. The 99 genes had different expression pattern in placental cell types. FN1 is up‐regulated in 8 w EVT compared to 8 w CTB and 24 w EVT compared to 8 w EVT. HSPA4 is down‐regulated in 8 w EVT compared to 8 w CTB and 24 w EVT compared to 8 w EVT. MIB2, TLR4, and UBB are consistently changed in preeclampsia (PE). UBB and ACTG1 were identified to be down‐regulated in fetal growth restriction (FGR). SOD1 is down‐regulated in preterm birth placenta. Conclusion: Our findings confirmed that the importance of these genes in placenta‐related diseases, and provide new candidates ( MIB2, UBB, ACTG1, and SOD1 ) for placenta‐related disease diagnosis and treatment.