scholarly journals Bioinformatic Analysis of Circular RNA-Associated ceRNA Network Associated with Hepatocellular Carcinoma

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Jiacheng Wu ◽  
Shui Liu ◽  
Yien Xiang ◽  
Xianzhi Qu ◽  
Yingjun Xie ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Pathway Analysis ◽  
Target Genes ◽  
Kegg Pathway ◽  
Interaction Network ◽  
Bioinformatic Analysis ◽  
Differentially Expressed ◽  
Qrt Pcr ◽  
Cerna Network ◽  
Kegg Pathway Analysis

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide and is associated with a high mortality rate and poor treatment efficacy. In an attempt to investigate the mechanisms involved in the pathogenesis of HCC, bioinformatic analysis and validation by qRT-PCR were performed. Three circRNA GEO datasets and one miRNA GEO dataset were selected for this purpose. Upon combined biological prediction, a total of 11 differentially expressed circRNAs, 15 differentially expressed miRNAs, and 560 target genes were screened to construct a circRNA-related ceRNA network. GO analysis and KEGG pathway analysis were performed for the 560 target genes. To further screen key genes, a protein-protein interaction network of the target genes was constructed using STRING, and the genes and modules with higher degree were identified by MCODE and CytoHubba plugins of Cytoscape. Subsequently, a module was screened out and subjected to GO enrichment analysis and KEGG pathway analysis. This module included eight genes, which were further screened using TCGA. Finally, UBE2L3 was selected as a key gene and the hsa_circ_0009910–miR-1261–UBE2L3 regulatory axis was established. The relative expression of the regulatory axis members was confirmed by qRT-PCR in 30 pairs of samples, including HCC tissues and adjacent nontumor tissues. The results suggested that hsa_circ_0009910, which was upregulated in HCC tissues, participates in the pathogenesis of HCC by acting as a sponge of miR-1261 to regulate the expression of UBE2L3. Overall, this study provides support for the possible mechanisms of progression in HCC.

scholarly journals Reconstruction of lncRNA-miRNA-mRNA network based on competitive endogenous RNA reveals functional lncRNAs in melanoma

2020 ◽  
Author(s):  
Junyou Zhu ◽  
Jin Deng ◽  
Lijun Zhang ◽  
Jingling Zhao ◽  
Fei Zhou ◽  
...  
Keyword(s):  
Pathway Analysis ◽  
Kegg Pathway ◽  
Skin Tumor ◽  
Pcr Assay ◽  
Diagnostic Biomarkers ◽  
Hub Gene ◽  
Qrt Pcr ◽  
Cerna Network ◽  
Kegg Pathway Analysis ◽  
Competitive Endogenous Rna

Abstract Background: Melanoma is the most common and dangerous skin tumor, and its pathogenesis is not fully understood. Methods: To identify the key lncRNAs in melanoma, we reconstructed a global triple network based on the ceRNA theory. GO and KEGG pathway analysis were performed using DAVID. And, we verified our findings through qRT-PCR assay. Results: According to ceRNA theory, 898 DEMs,53 DELs and 16 DEMis were selected to reconstruct the ceRNA network. MALAT1, LINC00943, and LINC00261 were selected as hub gene in the ceRNA network. Conclusions: In this study, we found that MALAT1, LINC00943 and LINC00261 were closely associated with tumorigenesis and development of melanoma, and therefore, could be used as potential diagnostic biomarkers and therapeutic targets.

scholarly journals Screening and Functional Prediction of Key Candidate Genes in Hepatitis B Virus-Associated Hepatocellular Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xia Chen ◽  
Ling Liao ◽  
Yuwei Li ◽  
Hengliu Huang ◽  
Qing Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Pathway Analysis ◽  
Kegg Pathway ◽  
Metabolic Process ◽  
Hub Genes ◽  
Kegg Pathway Analysis ◽  
B Virus

Background. The molecular mechanism by which hepatitis B virus (HBV) induces hepatocellular carcinoma (HCC) is still unknown. The genomic expression profile and bioinformatics methods were used to investigate the potential pathogenesis and therapeutic targets for HBV-associated HCC (HBV-HCC). Methods. The microarray dataset GSE55092 was downloaded from the Gene Expression Omnibus (GEO) database. The data was analyzed by the bioinformatics software to find differentially expressed genes (DEGs). Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, ingenuity pathway analysis (IPA), and protein-protein interaction (PPI) network analysis were then performed on DEGs. The hub genes were identified using Centiscape2.2 and Molecular Complex Detection (MCODE) in the Cytoscape software (Cytoscape_v3.7.2). The survival data of these hub genes was downloaded from the Gene Expression Profiling Interactive Analysis (GEPIA). Results. A total of 2264 mRNA transcripts were differentially expressed, including 764 upregulated and 1500 downregulated in tumor tissues. GO analysis revealed that these DEGs were related to the small-molecule metabolic process, xenobiotic metabolic process, and cellular nitrogen compound metabolic process. KEGG pathway analysis revealed that metabolic pathways, complement and coagulation cascades, and chemical carcinogenesis were involved. Diseases and biofunctions showed that DEGs were mainly associated with the following diseases or biological function abnormalities: cancer, organismal injury and abnormalities, gastrointestinal disease, and hepatic system disease. The top 10 upstream regulators were predicted to be activated or inhibited by Z-score and identified 25 networks. The 10 genes with the highest degree of connectivity were defined as the hub genes. Cox regression revealed that all the 10 genes (CDC20, BUB1B, KIF11, TTK, EZH2, ZWINT, NDC80, TPX2, MELK, and KIF20A) were related to the overall survival. Conclusion. Our study provided a registry of genes that play important roles in regulating the development of HBV-HCC, assisting us in understanding the molecular mechanisms that underlie the carcinogenesis and progression of HCC.

scholarly journals Bioinformatics analysis for the identification of differentially expressed genes and related signaling pathways in H. pylori-CagA transfected gastric cancer cells

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11203
Author(s):  
Dingyu Chen ◽  
Chao Li ◽  
Yan Zhao ◽  
Jianjiang Zhou ◽  
Qinrong Wang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Helicobacter Pylori ◽  
Differentially Expressed Genes ◽  
Pathway Analysis ◽  
Kegg Pathway ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Ags Cells ◽  
Kegg Pathway Analysis ◽  
Key Genes

Aim Helicobacter pylori cytotoxin-associated protein A (CagA) is an important virulence factor known to induce gastric cancer development. However, the cause and the underlying molecular events of CagA induction remain unclear. Here, we applied integrated bioinformatics to identify the key genes involved in the process of CagA-induced gastric epithelial cell inflammation and can ceration to comprehend the potential molecular mechanisms involved. Materials and Methods AGS cells were transected with pcDNA3.1 and pcDNA3.1::CagA for 24 h. The transfected cells were subjected to transcriptome sequencing to obtain the expressed genes. Differentially expressed genes (DEG) with adjusted P value < 0.05, — logFC —> 2 were screened, and the R package was applied for gene ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The differential gene protein–protein interaction (PPI) network was constructed using the STRING Cytoscape application, which conducted visual analysis to create the key function networks and identify the key genes. Next, the Kaplan–Meier plotter survival analysis tool was employed to analyze the survival of the key genes derived from the PPI network. Further analysis of the key gene expressions in gastric cancer and normal tissues were performed based on The Cancer Genome Atlas (TCGA) database and RT-qPCR verification. Results After transfection of AGS cells, the cell morphology changes in a hummingbird shape and causes the level of CagA phosphorylation to increase. Transcriptomics identified 6882 DEG, of which 4052 were upregulated and 2830 were downregulated, among which q-value < 0.05, FC > 2, and FC under the condition of ≤2. Accordingly, 1062 DEG were screened, of which 594 were upregulated and 468 were downregulated. The DEG participated in a total of 151 biological processes, 56 cell components, and 40 molecular functions. The KEGG pathway analysis revealed that the DEG were involved in 21 pathways. The PPI network analysis revealed three highly interconnected clusters. In addition, 30 DEG with the highest degree were analyzed in the TCGA database. As a result, 12 DEG were found to be highly expressed in gastric cancer, while seven DEG were related to the poor prognosis of gastric cancer. RT-qPCR verification results showed that Helicobacter pylori CagA caused up-regulation of BPTF, caspase3, CDH1, CTNNB1, and POLR2A expression. Conclusion The current comprehensive analysis provides new insights for exploring the effect of CagA in human gastric cancer, which could help us understand the molecular mechanism underlying the occurrence and development of gastric cancer caused by Helicobacter pylori.

scholarly journals Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jia Wang ◽  
Rui Peng ◽  
Zheng Zhang ◽  
Yixi Zhang ◽  
Yuke Dai ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Kegg Pathway ◽  
Expression Profiles ◽  
Primary Liver Cancer ◽  
Interaction Network ◽  
Chemical Carcinogenesis ◽  
Parameter Analysis ◽  
Qrt Pcr ◽  
Key Genes

Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer and has poor outcomes. However, the potential molecular biological process underpinning the occurrence and development of HCC is still largely unknown. The purpose of this study was to identify the core genes related to HCC and explore their potential molecular events using bioinformatics methods. HCC-related expression profiles GSE25097 and GSE84005 were selected from the Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) between 306 HCC tissues and 281 corresponding noncancerous tissues were identified using GEO2R online tools. The protein-protein interaction network (PPIN) was constructed and visualized using the STRING database. Gene Ontology (GO) and KEGG pathway enrichment analyses of the DEGs were carried out using DAVID 6.8 and KOBAS 3.0. Additionally, module analysis and centrality parameter analysis were performed by Cytoscape. The expression differences of key genes in normal hepatocyte cells and HCC cells were verified by quantitative real-time fluorescence polymerase chain reaction (qRT-PCR). Additionally, survival analysis of key genes was performed by GEPIA. Our results showed that a total of 291 DEGs were identified including 99 upregulated genes and 192 downregulated genes. Our results showed that the PPIN of HCC was made up of 287 nodes and 2527 edges. GO analysis showed that these genes were mainly enriched in the molecular function of protein binding. Additionally, KEGG pathway analysis also revealed that DEGs were mainly involved in the metabolic, cell cycle, and chemical carcinogenesis pathways. Interestingly, a significant module with high centrality features including 10 key genes was found. Among these, CDK1, NDC80, HMMR, CDKN3, and PTTG1, which were only upregulated in HCC patients, have attracted much attention. Furthermore, qRT-PCR also confirmed the upregulation of these five key genes in the normal human hepatocyte cell line (HL-7702) and HCC cell lines (SMMC-7721, MHCC-97L, and MHCC-97H); patients with upregulated expression of these five key genes had significantly poorer survival and prognosis. CDK1, NDC80, HMMR, CDKN3, and PTTG1 can be used as molecular markers for HCC. This finding provides potential strategies for clinical diagnosis, accurate treatment, and prognosis analysis of liver cancer.

scholarly journals Unraveling proteome changes and potential regulatory proteins of bovine follicular Granulosa cells by mass spectrometry and multi-omics analysis

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Shuning Hou ◽  
Qingling Hao ◽  
Zhiwei Zhu ◽  
Dongmei Xu ◽  
Wenzhong Liu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Pathway Analysis ◽  
Kegg Pathway ◽  
Follicular Development ◽  
Regulatory Proteins ◽  
Differentially Expressed ◽  
Omics Data ◽  
Kegg Pathway Analysis ◽  
Omics Data Analysis

Abstract Background In previous study, we performed next-gene sequencing to investigate the differentially expressed transcripts of bovine follicular granulosa cells (GCs) at dominant follicle (DF) and subordinate follicle (SF) stages during first follicular wave. Present study is designed to further identify the key regulatory proteins and signaling pathways associated with follicular development using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) and multi-omics data analysis approach. Methods DF and SF from three cattle were collected by daily ultrasonography. The GCs were isolated from each follicle, total proteins were digested by trypsin, and then proteomic analyzed via LC-MS/MS, respectively. Proteins identified were retrieved from Uniprot-COW fasta database, and differentially expressed proteins were used to functional enrichment and KEGG pathway analysis. Proteome data and transcriptome data obtained from previous studies were integrated. Results Total 3409 proteins were identified from 30,321 peptides (FDR ≤0.01) obtained from LC-MS/MS analysis and 259 of them were found to be differentially expressed at different stage of follicular development (fold Change > 2, P < 0.05). KEGG pathway analysis of proteome data revealed important signaling pathways associated with follicular development, multi-omics data analysis results showed 13 proteins were identified as being differentially expressed in DF versus SF. Conclusions This study represents the first investigation of transcriptome and proteome of bovine follicles and offers essential information for future investigation of DF and SF in cattle. It also will enrich the theory of animal follicular development.

Potential Diagnostic and Therapeutic Targets for Hepatocellular Carcinoma Based on Exosome-Derived Competitive Endogenous RNA Network

2021 ◽  
Author(s):  
Yuan Tian ◽  
Dongliang Yang ◽  
Tieshan Wang ◽  
He Bu ◽  
JinBao Wu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Target Genes ◽  
Immune Escape ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Therapeutic Targets ◽  
Differentially Expressed ◽  
Cerna Network ◽  
Differentially Expressed Mirnas ◽  
Competitive Endogenous Rna

Abstract Background: Hepatocellular carcinoma (HCC) is one of the most malignant tumors in the world. The pathogenesis of HCC is complex and closely related to chronic uncontrollable inflammation. As a bridge between inflammation and cancer, circulating exosomes play a vital role in early tumorigenesis, metastasis, and immune escape. Studies have shown that exosomes containing specific RNAs may be potential diagnostic and therapeutic targets for HCC. Purpose The current research investigated key circRNA through exosome-derived competitive endogenous RNA network based on the ExoRBase database. Methods: The circRNA, lncRNA, and mRNA expression profiles of human blood samples were downloaded from the ExoRBase database. At the standard of P<0.05 and log FC>0, differentially expressed genes (DEGs) were further identified between normal human and HCC patients. The co-expressed pairs of DEGs were predicted by TargetScan, miRcode, and StarBase databases. The ceRNA network was constructed by Cytoscape software. Subsequently, target genes corresponding to circRNA in the ceRNA network were annotated and analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG). The potential transcription factors were screened by FunRich database. Results: At the criterion of P<0.05 and log FC>0, 13 differentially expressed circRNAs(DECs) were identified with 9 up-regulated and 4 down-regulated. The co-expressed differentially expressed miRNAs-mRNAs (DEMis-DEMs) (620 pairs), differentially expressed miRNAs- LncRNAs (DEMis-DElncRNA) (684 pairs) and DEMis-DECs (53 pairs) were finally predicted to construct the ceRNA network. The GO analysis indicated that target genes in the ceRNA network were mainly enriched in the molecular function of protein serine/threonine kinase activity. KEGG pathway analysis suggested target genes were enriched in two pathways of MAPK and central carbon metabolism. Conclusion: The study provides a valuable reference for HCC through the ceRNA network in exosomes. Besides, hsa_circ_0000284 may be potential diagnostic markers of HCC.

scholarly journals Network Pharmacology Analysis of the active components and anticancer targets of Rhubarb

2021 ◽  
Author(s):  
Hu Junrui ◽  
Duan Yongqiang ◽  
Cui Gongning ◽  
Luo Qiang ◽  
Xi Shanshan ◽  
...  
Keyword(s):  
Pathway Analysis ◽  
Drug Targets ◽  
Target Genes ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Components ◽  
Active Compounds ◽  
Cellular Targets ◽  
Kegg Pathway Analysis

AbstractTo investigate the mechanisms and active components governing the anticancer activity of rhubarb.The TCMSP database was screened to identify the active components of rhubarb and Swiss target predictions were generated to predict their cellular targets. TTD and OMIM databases were used to predict tumor-related target genes. "Cytoscape" was used to construct drug targets. PPI network analysis, GO enrichment analysis and KEGG pathway analysis of the key targets were investigated using String and David databases. A total of 33 components and 116 corresponding targets were screened. Amongst them, the key active compounds in rhubarb included emodin, aloe emodin, β-sitosterol, emodin methyl ether and rhein, which were predicted to target TP53, AKT1, STAT3, PIK3CA, HRAS, and VEGFA. GO analysis revealed that the cellular targets clustered into 159 biological processes, including those involved in cellular composition (n=24) and molecular functions (n=42, P<0.01). KEGG pathway analysis revealed 85 (P < 0.01) pathways related to cancer. The active compounds in rhubarb target TP53, AKT1 and PIK3CA. Rhubarb therefore regulates cancer development through an array of biological pathways.

scholarly journals Identification of major depressive disorder disease-related genes and functional pathways based on system dynamic changes of network connectivity

2020 ◽  
Author(s):  
Ruijie Geng ◽  
Xiao Huang
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Pathway Analysis ◽  
Healthy Subjects ◽  
Kegg Pathway ◽  
Network Connectivity ◽  
Differentially Expressed ◽  
Therapeutic Drug ◽  
Major Depressive ◽  
Kegg Pathway Analysis

Abstract Objective: Major depressive disorder (MDD) is a leading psychiatric disorder that involves complex abnormal biological functions and neural networks. This study aimed to compare the changes in the network connectivity of different brain tissues under different pathological conditions, analyzed the biological pathways and genes that are significantly related to disease progression, and further predicted the potential therapeutic drug targets.Methods: Expression of differentially expressed genes (DEGs) were analyzed with postmortem cingulate cortex (ACC) and prefrontal cortex (PFC) mRNA expression profile datasets downloaded from the Gene Expression Omnibus (GEO) database, including 76 MDD patients and 76 healthy subjects in ACC and 63 MDD patients and 63 healthy subjects in PFC. The co-expression network construction was based on system network analysis. The function of the genes was annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Human Protein Reference Database (HPRD, http://www.hprd.org/) was used for gene interaction relationship mapping.Results: We filtered 586 DEGs in ACC and 616 DEGs in PFC for further analysis. By constructing the Co-expression network, we found that the gene connectivity was significantly reduced under disease conditions (P=0.04 in PFC and P=1.227e-09 in ACC). Crosstalk analysis showed that CD19, PTDSS2 and NDST2 were significantly differentially expressed in ACC and PFC of MDD patients. Among them, CD19 and PTDSS2 have been targeted by several drugs in the Drugbank database. KEGG pathway analysis demonstrated that the function of CD19 and PTDSS2 were enriched with the pathway of Glycerophospholipid metabolism and T cell receptor signaling pathway. Conclusion: Co-expression network and tissue comparing analysis can identify signaling pathways and cross talk genes related to MDD, which may provide novel insight for understanding the molecular mechanisms of MDD.

scholarly journals Construction of a circRNA - Mediated ceRNA Network Reveals Novel Biomarkers for Aortic Dissection

2021 ◽  
Author(s):  
De-Bin Liu ◽  
You-Fu He ◽  
Gui-Jian Chen ◽  
Hua Huang ◽  
Xu-Ling Xie ◽  
...  
Keyword(s):  
Aortic Dissection ◽  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Kegg Pathway ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Qrt Pcr ◽  
Cerna Network ◽  
Arterial Blood

Abstract Background Aortic dissection (AD) is a rare and lethal disorder with its genetic basis remains largely unknown. Many studies have confirmed that circular RNAs (circRNAs) play important roles in various physiological and pathological processes. However, the roles of circRNAs in AD are still unclear and need further investigation. The present study aimed to elucidate the underlying molecular mechanisms of circRNAs regulation in aortic dissection based on the circRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network. Methods Expression profiles of circRNAs (GSE97745), miRNAs (GSE92427), and mRNAs (GSE52093) were downloaded from Gene Expression Omnibus (GEO) databases, and the differentially expressed RNAs (DERNAs) were subsequently identified in AD by bioinformatics analysis. Further bioinformatics analyses, including circRNA-miRNA-mRNA ceRNA network, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, were used to predict the potential functions of circRNA-associated ceRNA regulatory network. RNA was isolated from human arterial blood samples after which quantitative real-time PCR (qRT-PCR) was performed to confirm the DERNAs. Results We identified 14 (5 up-regulated and 9 down-regulated) differentially expressed circRNAs (DEcircRNAs), 17 (8 up-regulated and 9 down-regulated) differentially expressed miRNAs (DEmiRNAs) and 527 (297 up-regulated and 230 down-regulated) differentially expressed mRNAs (DEmRNAs) when AD samples were compared with normal ascending aorta samples (adjusted P-value < 0.05 and | log2FC |> 1.0). KEGG pathway analysis indicated that DEmRNAs were related to focal adhesion and extracellular matrix (ECM) receptor interaction signaling pathways. Simultaneously, the present study successfully constructed a ceRNA regulatory network based on 1 circRNAs (hsa_circRNA_082317), 1 miRNAs (hsa-miR-149-3p) and 10 mRNAs (MLEC, ENTPD7, SLC16A3, SLC7A8, TBC1D16, PAQR4, MAPK13, PIK3R2, ITGA5, SERPINA1) in AD. Furthermore, qRT-PCR demonstrated that hsa_circRNA_082317 andα5 integrin (ITGA5) were significantly up-regulated in AD (n = 3), and hsa-miR-149-3p was dramatically down-regulated in AD (n = 3). The expression of hsa-miR-149-3p target mRNA, ITGA5, was positively modulated by hsa_circRNA_082317. Conclusion This is the first study to demonstrate the circRNA-associated ceRNA regulatory network is altered in AD, implying that circRNAs may play important roles in regulating the onset and progression of AD and thus may serve as potential biomarkers for the diagnosis and treatment of AD.

Ouabain rescues rat nephrogenesis during intrauterine growth restriction by regulating the complement and coagulation cascades and calcium signaling pathway

2015 ◽  
Vol 7 (1) ◽  
pp. 91-101 ◽  
Author(s):  
L. Chen ◽  
J. Yue ◽  
X. Han ◽  
J. Li ◽  
Y. Hu
Keyword(s):  
Calcium Signaling ◽  
Signaling Pathway ◽  
Pathway Analysis ◽  
Intrauterine Growth Restriction ◽  
Kegg Pathway ◽  
Growth Restriction ◽  
Differentially Expressed ◽  
Intrauterine Growth ◽  
Kegg Pathway Analysis ◽  
Calcium Signaling Pathway

Intrauterine growth restriction (IUGR) is associated with a reduction in the numbers of nephrons in neonates, which increases the risk of hypertension. Our previous study showed that ouabain protects the development of the embryonic kidney during IUGR. To explore this molecular mechanism, IUGR rats were induced by protein and calorie restriction throughout pregnancy, and ouabain was delivered using a mini osmotic pump. RNA sequencing technology was used to identify the differentially expressed genes (DEGs) of the embryonic kidneys. DEGs were submitted to the Database for Annotation and Visualization and Integrated Discovery, and gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted. Maternal malnutrition significantly reduced fetal weight, but ouabain treatment had no significant effect on body weight. A total of 322 (177 upregulated and 145 downregulated) DEGs were detected between control and the IUGR group. Meanwhile, 318 DEGs were found to be differentially expressed (180 increased and 138 decreased) between the IUGR group and the ouabain-treated group. KEGG pathway analysis indicated that maternal undernutrition mainly disrupts the complement and coagulation cascades and the calcium signaling pathway, which could be protected by ouabain treatment. Taken together, these two biological pathways may play an important role in nephrogenesis, indicating potential novel therapeutic targets against the unfavorable effects of IUGR.

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