Comparing the continuous representation of time-series expression profiles to identify differentially expressed genes

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.

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Expression profiles of differentially expressed genes affecting fecundity in goat ovarian tissues

Genetics and Molecular Research ◽

10.4238/2015.december.28.23 ◽

2015 ◽

Vol 14 (4) ◽

pp. 18743-18752 ◽

Cited By ~ 3

Author(s):

Y.H. Ling ◽

Q. Quan ◽

H. Xiang ◽

L. Zhu ◽

M.X. Chu ◽

...

Keyword(s):

Differentially Expressed Genes ◽

Expression Profiles ◽

Differentially Expressed

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Genomic Expression Profiling of Colorectal Cancer in Silico

10.21203/rs.3.rs-310514/v1 ◽

2021 ◽

Author(s):

Feifei Liu ◽

Yu Wang ◽

Wenxue Li ◽

Diancheng Li ◽

Yuwei Xin ◽

...

Keyword(s):

Colorectal Cancer ◽

Survival Analysis ◽

Mrna Expression ◽

Differentially Expressed Genes ◽

Expression Profiles ◽

Functional Enrichment ◽

Differentially Expressed ◽

Analysis Tool ◽

Hub Genes ◽

Normal Tissues

Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies of the digestive system; the progression and prognosis of which are affected by a complicated network of genes and pathways. The aim of this study was to identify potential hub genes associated with the progression and prognosis of colorectal cancer (CRC).Methods: We obtained gene expression profiles from GEO database to search differentially expressed genes (DEGs) between CRC tissues and normal tissue. Subsequently, we conducted a functional enrichment analysis, generated a protein–protein interaction (PPI) network to identify the hub genes, and analyzed the expression validation of the hub genes. Kaplan–Meier plotter survival analysis tool was performed to evaluate the prognostic value of hub genes expression in CRC patients.Results: A total of 370 samples, involving CRC and normal tissues were enrolled in this article. 283 differentially expressed genes (DEGs), including 62 upregulated genes and 221 downregulated genes between CRC and normal tissues were selected. We finally filtered out 6 hub genes, including INSL5, MTIM, GCG, SPP1, HSD11B2, and MAOB. In the database of TCGA-COAD, the mRNA expression of INSL5, MT1M, HSD11B2, MAOB in tumor is lower than that in normal; the mRNA expression of SPP1 in tumor is higher than that in normal. In the HPA database, the expression of INSL5, GCG, HSD11B2, MAOB in tumor is lower than that in normal tissues; the expression of SPP1 in the tumor is higher than that in normal tissues. Survival analysis revealed that INSL5, GCG, SPP1 and MT1M may serve as prognostic biomarkers in CRC. Conclusions: We screened out six hub genes to predict the occurrence and prognosis of patients with CRC using bioinformatics methods, which may provide new targets and ideas for diagnosis, prognosis and individualized treatment for CRC.

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Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Hashimoto’s Thyroiditis

10.21203/rs.3.rs-1023446/v1 ◽

2021 ◽

Author(s):

Li Guoquan ◽

Du Junwei ◽

He Qi ◽

Fu Xinghao ◽

Ji Feihong ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Inflammatory Responses ◽

Expression Profiles ◽

Treatment Options ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Chronic Lymphocytic Thyroiditis ◽

Hub Genes

Abstract BackgroundHashimoto's thyroiditis (HT), also known as chronic lymphocytic thyroiditis, is a common autoimmune disease, which mainly occurs in women. The early manifestation was hyperthyroidism, however, hypothyroidism may occur if HT was not controlled for a long time. Numerous studies have shown that multiple factors, including genetic, environmental, and autoimmune factors, were involved in the pathogenesis of the disease, but the exact mechanisms were not yet clear. The aim of this study was to identify differentially expressed genes (DEGs) by comprehensive analysis and to provide specific insights into HT. MethodsTwo gene expression profiles (GSE6339, GSE138198) about HT were downloaded from the Gene Expression Omnibus (GEO) database. The DEGs were assessed between the HT and normal groups using the GEO2R. The DEGs were then sent to the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub genes were discovered using Cytoscape and CytoHubba. Finally, NetworkAnalyst was utilized to create the hub genes' targeted microRNAs (miRNAs). ResultsA total of 62 DEGs were discovered, including 60 up-regulated and 2 down-regulated DEGs. The signaling pathways were mainly engaged in cytokine interaction and cytotoxicity, and the DEGs were mostly enriched in immunological and inflammatory responses. IL2RA, CXCL9, IL10RA, CCL3, CCL4, CCL2, STAT1, CD4, CSF1R, and ITGAX were chosen as hub genes based on the results of the protein-protein interaction (PPI) network and CytoHubba. Five miRNAs, including mir-24-3p, mir-223-3p, mir-155-5p, mir-34a-5p, mir-26b-5p, and mir-6499-3p, were suggested as likely important miRNAs in HT. ConclusionsThese hub genes, pathways and miRNAs contribute to a better understanding of the pathophysiology of HT and offer potential treatment options for HT.

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Insight into Molecular Profile Changes after Skeletal Muscle Contusion Using Microarray and Bioinformatics Analyses

10.21203/rs.3.rs-85830/v1 ◽

2020 ◽

Author(s):

Na Li ◽

Ru-feng Bai ◽

Chun Li ◽

Li-hong Dang ◽

Qiu-xiang Du ◽

...

Keyword(s):

Gene Expression ◽

Network Analysis ◽

Differentially Expressed Genes ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Healing Process ◽

Differentially Expressed ◽

Molecular Profile ◽

Wound Age ◽

Functional Modules

Abstract Background: Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. This study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process.Methods: A total of 33 rats were divided randomly into control (n = 3), mild contusion (n = 15), and severe contusion (n = 15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n = 3 per subgroup). Then full genome microarray of RNA isolated from muscle tissue was performed to access the gene expression changes during healing process.Results: A total of 2,844 and 2,298 differentially expressed genes were identified in the mild and severe contusion groups, respectively. The analysis of the overlapping differentially expressed genes showed that there are common mechanisms of transcriptomic repair of mild and severe contusion within 48 h post-contusion. This was supported by the results of principal component analysis, hierarchical clustering, and weighted gene co‐expression network analysis of the 1,620 coexpressed genes in mildly and severely contused muscle. From these analyses, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. We then performed an analysis of the functions of genes (including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway annotation, and protein–protein interaction network analysis) in the functional modules and temporal clusters, and the hub genes in each module–cluster pair were identified. Interestingly, we found that genes downregulated within 24−48 h of the healing process were largely associated with metabolic processes, especially oxidative phosphorylation of reduced nicotinamide adenine dinucleotide phosphate, which has been rarely reported. Conclusions: These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.

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Gene Expression Profiles of Papillary Thyroid Microcarcinoma

International Surgery ◽

10.9738/intsurg-d-17-00049.1 ◽

2017 ◽

Vol 102 (1-2) ◽

pp. 39-46 ◽

Cited By ~ 1

Author(s):

Woo Young Kim ◽

Jae Bok Lee ◽

Seung Pil Jung ◽

Hoon Yub Kim ◽

Sang Uk Woo ◽

...

Keyword(s):

Gene Expression ◽

Gene Expression Profile ◽

Differentially Expressed Genes ◽

Expression Profile ◽

Expression Profiles ◽

Differentially Expressed ◽

Papillary Thyroid Microcarcinoma ◽

Papillary Thyroid ◽

Normal Thyroid ◽

Thyroid Microcarcinoma

The objective was to identify gene expression profile of papillary thyroid microcarcinoma. To help improve diagnosis of papillary thyroid microcarcinoma, we performed gene expression profiling and compared it to pair normal thyroid tissues. We performed microarray analysis with 6 papillary thyroid microcarcinoma and 6 pair normal thyroid tissues. Differentially expressed genes were selected using paired t test, linear models for microarray data, and significance analysis of microarrays. Real-time quantitative reverse transcription–polymerase chain reaction was used to validate the representative 10 genes (MET, TIMP1, QPCT, PROS1, LRP4, SDC4, CITED1, DPP4, LRRK2, RUNX2). We identified 91 differentially expressed genes (84 upregulated and 7 downregulated) in the gene expression profile and validated 10 genes of the profile. We identified a significant genetic difference between papillary thyroid microcarcinoma and normal tissue by 10 upregulated genes greater than 2-fold (P < 0.05).

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A Comprehensive Data Analysis of Differentially Regulated Genes in Melanoma

10.21203/rs.3.rs-19035/v1 ◽

2020 ◽

Author(s):

Yanjie Han ◽

Xinxin Li ◽

Jiliang Yan ◽

Chunyan Ma ◽

Xin Wang ◽

...

Keyword(s):

Differentially Expressed Genes ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Growth Factor Receptor ◽

Principal Component ◽

Distant Metastases ◽

The Cancer Genome Atlas ◽

Differentially Expressed ◽

Hub Genes ◽

Ppi Networks

Abstract Background: Melanoma is the most deadly tumor in skin tumors and is prone to distant metastases. The incidence of melanoma has increased rapidly in the past few decades, and current trends indicate that this growth is continuing. This study was aimed to explore the molecular mechanisms of melanoma pathogenesis and discover underlying pathways and genes associated with melanoma.Methods: We used high-throughput expression data to study differential expression profiles of related genes in melanoma. The differentially expressed genes (DEGs) of melanoma in GSE15605, GSE46517, GSE7553 and the Cancer Genome Atlas (TCGA) datasets were analyzed. Differentially expressed genes (DEGs) were identified by paired t-test. Then the DEGs were performed cluster and principal component analyses and protein–protein interaction (PPI) network construction. After that, we analyzed the differential genes through bioinformatics and got hub genes. Finally, the expression of hub genes was confirmed in the TCGA databases and collected patient tissue samples.Results: Total 144 up-regulated DEGs and 16 down-regulated DEGs were identified. A total of 17 gene ontology analysis (GO) terms and 11 pathways were closely related to melanoma. Pathway of pathways in cancer was enriched in 8 DEGs, such as junction plakoglobin (JUP) and epidermal growth factor receptor (EGFR). In the PPI networks, 9 hub genes were obtained, such as loricrin (LOR), filaggrin (FLG), keratin 5 (KRT5), corneodesmosin (CDSN), desmoglein 1 (DSG1), desmoglein 3 (DSG3), keratin 1 (KRT1), involucrin (IVL) and EGFR. The pathway of pathways in cancer and its enriched DEGs may play important roles in the process of melanoma. The hub genes of DEGs may become promising melanoma candidate genes. Five key genes FLG, DSG1, DSG3, IVL and EGFR were identified in the TCGA database and melanoma tissues.Conclusions: The results suggested that FLG, DSG1, DSG3, IVL and EGFR might play important roles and potentially be valuable in the prognosis and treatment of melanoma.

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Identification of time‑series differentially expressed genes and pathways associated with heart failure post‑myocardial infarction using integrated bioinformatics analysis

Molecular Medicine Reports ◽

10.3892/mmr.2019.10190 ◽

2019 ◽

Author(s):

Xuefei Li ◽

Bin Li ◽

Hong Jiang

Keyword(s):

Myocardial Infarction ◽

Heart Failure ◽

Time Series ◽

Differentially Expressed Genes ◽

Bioinformatics Analysis ◽

Post Myocardial Infarction ◽

Differentially Expressed

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The expression of native and cultured RPE grown on different matrices

Physiological Genomics ◽

10.1152/physiolgenomics.00179.2003 ◽

2004 ◽

Vol 17 (2) ◽

pp. 170-182 ◽

Cited By ~ 21

Author(s):

Jane Tian ◽

Kazuki Ishibashi ◽

James T. Handa

Keyword(s):

Cluster Analysis ◽

Differentially Expressed Genes ◽

Cultured Cells ◽

Expression Profiles ◽

Retinal Pigment ◽

Collagen Iv ◽

Collagen I ◽

Differentially Expressed ◽

Rpe Cells ◽

Laser Capture

The purpose of this work was to determine the expression profiles of retinal pigment epithelial (RPE) cells grown on different matrices and to assess the degree of culture-induced artifact by comparing the profiles to native RPE. Visually confluent ARPE-19 cells were grown on plastic, Matrigel, collagen I, collagen IV, laminin, and fibronectin for 1 wk, and serum was withdrawn for 3 days. Morphologically normal, macular RPE cells were laser-capture microdissected from three human eye globes. Total RNA was extracted from 5,000 cells and reverse transcribed, and radiolabeled cDNA probes were hybridized to an array containing 4,325 known genes. Arrays were assessed by cluster analysis and significance analysis of microarrays (SAM). Real-time RT-PCR was used to validate differentially expressed genes. Despite similar morphology, ARPE-19 demonstrated different expression profiles when grown on different matrices. Cluster analysis showed that cells grown on collagen IV, laminin, and fibronectin had similar profiles that were distinct from cells grown on collagen I. Cells grown on plastic clustered closest to native RPE. This expression pattern was confirmed with supervised cluster analyses. The number of differentially expressed genes, function of differentially expressed genes, and profile of expressed and unexpressed genes suggest that the overall expression profile of cultured cells is significantly different from native RPE. RPE cells grown on collagen IV, laminin, and fibronectin have profiles more similar than cells grown on plastic, Matrigel, or collagen I. The overall mRNA phenotype, however, is different from morphologically normal, native macular RPE.

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Dihydroartemisinin Inhibits Proliferation and Induces Apoptosis of Human Hepatocellular Carcinoma Cell by Upregulating Tumor Necrosis Factor via JNK/NF-κB Pathways

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2019/9581327 ◽

2019 ◽

Vol 2019 ◽

pp. 1-9 ◽

Cited By ~ 4

Author(s):

Long Wu ◽

Yanlei Cheng ◽

Junjian Deng ◽

Weiping Tao ◽

Junjie Ye

Keyword(s):

Hepatocellular Carcinoma ◽

Cell Proliferation ◽

Differentially Expressed Genes ◽

Carcinoma Cell ◽

Expression Profiles ◽

Human Hepatocellular Carcinoma ◽

Differentially Expressed ◽

Venn Diagram ◽

Dependent Manner ◽

Hepatocellular Carcinoma Cell

Background. Dihydroartemisinin (DHA) is a predominant compound in Artemisia annua L., and it has been shown to inhibit tumorigenesis. Methods. In this study, the antitumor potential of DHA was investigated in the MHCC97-L hepatocellular carcinoma cell line. Cells were treated at various concentrations of DHA, and then the cell cycle, viability, and DNA synthesis were measured to evaluate cell proliferation. Furthermore, the expression of genes and proteins related to proliferation and apoptosis was measured to determine the effects of DHA. Finally, the mechanism was investigated using RNA-sequencing to identify differentially expressed genes and signaling pathways, and JNK/NF-κB pathways were evaluated with Western blotting. Results. Cells were treated with a concentration range of DHA from 1 to 100 μM, and cell proliferation was suppressed in a dose-dependent manner. In addition, the genes and proteins involved in typical cellular functions of MHCC97-L cells were significantly inhibited. DHA treatment downregulated the angiogenic gene ANGPTL2 and the cell proliferation genes CCND1, E2F1, PCNA, and BCL2. DHA treatment significantly upregulated the apoptotic genes CASP3, CASP8, CASP9, and TNF. Global gene expression profiles identified 2064 differentially expressed genes (DEGs). Among them, 744 were upregulated and 1320 were downregulated. Furthermore, MAPK, NF-kappa B, and TNF pathways were enriched based on the DEGs, and the consensus DEG was identified as TNF using a Venn diagram of those pathways. DHA promoted phosphorylation of JNK, inhibited nuclear p65, and then significantly induced TNF-α synthesis. Conclusion. DHA inhibited cell proliferation and induced apoptosis in human hepatocellular carcinoma cells by upregulating TNF expression via JNK/NF-κB pathways.

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