Jia-Rong Gao1, Xiu-Juan Qin2, Hui Jiang2, Ya-Chen Gao3, Ming-Fei Guo2, Nan-Nan Jiang2. 1. Department of Pharmacy, The first affiliated hospital of Anhui university of Chinese medicine, 117 Meishan Road, Hefei, China. Electronic address: 1036951872@qq.com. 2. Department of Pharmacy, The first affiliated hospital of Anhui university of Chinese medicine, 117 Meishan Road, Hefei, China. 3. Department of Nephrology, The first affiliated hospital of Anhui university of Chinese medicine, 117 Meishan Road, Hefei, China.
Abstract
BACKGROUND: Chronic glomerulonephritis (CGN) is the most common form of primary glomerular disease with unclear molecular mechanisms, which related to immune-mediated inflammatory diseases. Our study intended to identify potential long non-coding RNAs (lncRNAs) and genes, and to determine the potential molecular mechanisms of CGN pathogenesis. METHODS: The microarray of GSE64265 and GSE46295 were downloaded from the Gene Expression Omnibus database, GSE64265 including 3 rats control kidney tissues and 5 rats model kidney tissues, GSE46295 including 3 rats control kidney tissues and 3 rats model kidney tissues, which was on the basis of GPL1355 platform. Identification of differentially expressed lncRNAs and mRNAs were performed between the 2 groups. Gene ontology (GO) and pathway enrichment analyses were performed to analyze the biological functions and pathways for the differentially expressed mRNAs. LncRNA-mRNA weighted co-expression network was constructed using the WGCNA package to analyses for the genes in the modules. The protein-protein interaction (PPI) network was visualized. RESULTS: A total of 40 significantly up-regulated and 24 down-regulated lncRNAs, 653 up-regulated and 128 down-regulated mRNAs were identified. Additionally, Cdk1, with the highest connectivity degree in PPI network, was noteworthy enriched in cell cycle. Seven lncRNAs: NONRATT026650, LOC102547664, NONRATT77021989, NONRATT012453, LOC102551856, LOC102553536 and NONRATT7047175 were observed in the modules of lncRNA-mRNA weighted co-expression network. CONCLUSIONS: LncRNAs NONRATT026650, LOC102547664, NONRATT77021989, NONRATT012453, LOC102551856, LOC102553536 and NONRATT7047175 were differentially expressed and might play important roles in the development of CGN. Key genes, such as Cd44, Rftn1, Runx1, may be crucial biomarkers for CGN.
BACKGROUND: Chronic glomerulonephritis (CGN) is the most common form of primary glomerular disease with unclear molecular mechanisms, which related to immune-mediated inflammatory diseases. Our study intended to identify potential long non-coding RNAs (lncRNAs) and genes, and to determine the potential molecular mechanisms of CGN pathogenesis. METHODS: The microarray of GSE64265 and GSE46295 were downloaded from the Gene Expression Omnibus database, GSE64265 including 3 rats control kidney tissues and 5 rats model kidney tissues, GSE46295 including 3 rats control kidney tissues and 3 rats model kidney tissues, which was on the basis of GPL1355 platform. Identification of differentially expressed lncRNAs and mRNAs were performed between the 2 groups. Gene ontology (GO) and pathway enrichment analyses were performed to analyze the biological functions and pathways for the differentially expressed mRNAs. LncRNA-mRNA weighted co-expression network was constructed using the WGCNA package to analyses for the genes in the modules. The protein-protein interaction (PPI) network was visualized. RESULTS: A total of 40 significantly up-regulated and 24 down-regulated lncRNAs, 653 up-regulated and 128 down-regulated mRNAs were identified. Additionally, Cdk1, with the highest connectivity degree in PPI network, was noteworthy enriched in cell cycle. Seven lncRNAs: NONRATT026650, LOC102547664, NONRATT77021989, NONRATT012453, LOC102551856, LOC102553536 and NONRATT7047175 were observed in the modules of lncRNA-mRNA weighted co-expression network. CONCLUSIONS: LncRNAs NONRATT026650, LOC102547664, NONRATT77021989, NONRATT012453, LOC102551856, LOC102553536 and NONRATT7047175 were differentially expressed and might play important roles in the development of CGN. Key genes, such as Cd44, Rftn1, Runx1, may be crucial biomarkers for CGN.