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Network analysis reveals important genes in human placenta

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...

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Published in:The journal of obstetrics and gynaecology research 2021-08, Vol.47 (8), p.2607-2615
Main Authors: Lin, Peihong, Lai, Xuedan, Wu, Ling, Liu, Wei, Lin, Shiqiang, Ye, Jianwen
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cited_by cdi_FETCH-LOGICAL-c3770-7549eb3e18223dd4ce7f60975bda65ff14f584b887573ebe5e0bc720e51611383
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container_end_page 2615
container_issue 8
container_start_page 2607
container_title The journal of obstetrics and gynaecology research
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creator Lin, Peihong
Lai, Xuedan
Wu, Ling
Liu, Wei
Lin, Shiqiang
Ye, Jianwen
description 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.
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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.</description><identifier>ISSN: 1341-8076</identifier><identifier>EISSN: 1447-0756</identifier><identifier>DOI: 10.1111/jog.14820</identifier><identifier>PMID: 34005840</identifier><language>eng</language><publisher>Kyoto, Japan: John Wiley &amp; Sons Australia, Ltd</publisher><subject>Actins - genetics ; cytotrophoblast ; extravillous trophoblast ; Female ; fetal growth restriction ; Fetuses ; gestational diabetes mellitus ; Glyceraldehyde-3-phosphate dehydrogenase ; Humans ; Infant, Newborn ; Placenta ; Placenta Diseases ; Pre-eclampsia ; Pre-Eclampsia - genetics ; Preeclampsia ; Pregnancy ; Premature Birth ; preterm birth ; Proteins ; Superoxide dismutase ; Superoxide Dismutase-1 - genetics ; syncytiotrophoblast ; TLR4 protein ; Toll-like receptors ; transcriptome ; Trophoblasts ; Ubiquitin - genetics ; Ubiquitin-Protein Ligases - genetics ; villous stromal cell</subject><ispartof>The journal of obstetrics and gynaecology research, 2021-08, Vol.47 (8), p.2607-2615</ispartof><rights>2021 Japan Society of Obstetrics and Gynecology</rights><rights>2021 Japan Society of Obstetrics and Gynecology.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3770-7549eb3e18223dd4ce7f60975bda65ff14f584b887573ebe5e0bc720e51611383</citedby><cites>FETCH-LOGICAL-c3770-7549eb3e18223dd4ce7f60975bda65ff14f584b887573ebe5e0bc720e51611383</cites><orcidid>0000-0001-8982-2796</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34005840$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lin, Peihong</creatorcontrib><creatorcontrib>Lai, Xuedan</creatorcontrib><creatorcontrib>Wu, Ling</creatorcontrib><creatorcontrib>Liu, Wei</creatorcontrib><creatorcontrib>Lin, Shiqiang</creatorcontrib><creatorcontrib>Ye, Jianwen</creatorcontrib><title>Network analysis reveals important genes in human placenta</title><title>The journal of obstetrics and gynaecology research</title><addtitle>J Obstet Gynaecol Res</addtitle><description>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.</description><subject>Actins - genetics</subject><subject>cytotrophoblast</subject><subject>extravillous trophoblast</subject><subject>Female</subject><subject>fetal growth restriction</subject><subject>Fetuses</subject><subject>gestational diabetes mellitus</subject><subject>Glyceraldehyde-3-phosphate dehydrogenase</subject><subject>Humans</subject><subject>Infant, Newborn</subject><subject>Placenta</subject><subject>Placenta Diseases</subject><subject>Pre-eclampsia</subject><subject>Pre-Eclampsia - genetics</subject><subject>Preeclampsia</subject><subject>Pregnancy</subject><subject>Premature Birth</subject><subject>preterm birth</subject><subject>Proteins</subject><subject>Superoxide dismutase</subject><subject>Superoxide Dismutase-1 - genetics</subject><subject>syncytiotrophoblast</subject><subject>TLR4 protein</subject><subject>Toll-like receptors</subject><subject>transcriptome</subject><subject>Trophoblasts</subject><subject>Ubiquitin - genetics</subject><subject>Ubiquitin-Protein Ligases - genetics</subject><subject>villous stromal cell</subject><issn>1341-8076</issn><issn>1447-0756</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp10L1OwzAUBWALgWgpDLwAisQCQ9rr2I4dNlRBAVV0gTlykpuSkp9iJ1R9e1xSGJDwYlv6fHR9CDmnMKZuTVbNcky5CuCADCnn0gcpwkN3Zpz6CmQ4ICfWrgCojKg6JgPGAYTiMCQ3z9huGvPu6VqXW1tYz-An6tJ6RbVuTKvr1ltije5ee29dpWtvXeoU61afkqPcQTzb7yPyen_3Mn3w54vZ4_R27qdMSvCl4BEmDKkKApZlPEWZhxBJkWQ6FHlOee5GSZSSQjJMUCAkqQwABQ0pZYqNyFWfuzbNR4e2javCpliWusams3EgAhVRkFw4evmHrprOuJ_tlJChCmQUOXXdq9Q01hrM47UpKm22MYV4V6h7tYy_C3X2Yp_YJRVmv_KnQQcmPdgUJW7_T4qfFrM-8guCJX12</recordid><startdate>202108</startdate><enddate>202108</enddate><creator>Lin, Peihong</creator><creator>Lai, Xuedan</creator><creator>Wu, Ling</creator><creator>Liu, Wei</creator><creator>Lin, Shiqiang</creator><creator>Ye, Jianwen</creator><general>John Wiley &amp; 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Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>The journal of obstetrics and gynaecology research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lin, Peihong</au><au>Lai, Xuedan</au><au>Wu, Ling</au><au>Liu, Wei</au><au>Lin, Shiqiang</au><au>Ye, Jianwen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Network analysis reveals important genes in human placenta</atitle><jtitle>The journal of obstetrics and gynaecology research</jtitle><addtitle>J Obstet Gynaecol Res</addtitle><date>2021-08</date><risdate>2021</risdate><volume>47</volume><issue>8</issue><spage>2607</spage><epage>2615</epage><pages>2607-2615</pages><issn>1341-8076</issn><eissn>1447-0756</eissn><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.</abstract><cop>Kyoto, Japan</cop><pub>John Wiley &amp; Sons Australia, Ltd</pub><pmid>34005840</pmid><doi>10.1111/jog.14820</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0001-8982-2796</orcidid></addata></record>
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subjects Actins - genetics
cytotrophoblast
extravillous trophoblast
Female
fetal growth restriction
Fetuses
gestational diabetes mellitus
Glyceraldehyde-3-phosphate dehydrogenase
Humans
Infant, Newborn
Placenta
Placenta Diseases
Pre-eclampsia
Pre-Eclampsia - genetics
Preeclampsia
Pregnancy
Premature Birth
preterm birth
Proteins
Superoxide dismutase
Superoxide Dismutase-1 - genetics
syncytiotrophoblast
TLR4 protein
Toll-like receptors
transcriptome
Trophoblasts
Ubiquitin - genetics
Ubiquitin-Protein Ligases - genetics
villous stromal cell
title Network analysis reveals important genes in human placenta
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