scholarly journals In-depth investigation on abiotic stress-responsive differentially expressed genes in Arabidopsis roots through GEO database

2020 ◽  
Vol 15 (1) ◽  
pp. 294-302
Author(s):  
Meili Guo ◽  
Xin Liu ◽  
Jiahui Wang ◽  
Lei Li ◽  
Yusu Jiang ◽  
...  
Keyword(s):  
Abiotic Stress ◽  
Differentially Expressed Genes ◽  
Differentially Expressed ◽  
Geo Database

Potential genes and pathways along with immune cells infiltration in the progression of atherosclerosis identified via microarray gene expression dataset re-analysis

Vascular ◽  
2020 ◽  
Vol 28 (5) ◽  
pp. 643-654 ◽  
Author(s):  
Jing Xu ◽  
Yuejin Yang
Keyword(s):  
Differentially Expressed Genes ◽  
Immune Cells ◽  
Interaction Network ◽  
Wilcoxon Test ◽  
Differentially Expressed ◽  
P Value ◽  
The Novel ◽  
Microarray Gene Expression ◽  
Progression Of Atherosclerosis ◽  
Geo Database

Objective Atherosclerosis is a chronic inflammatory process characterized by the accumulation and formation of lipid-rich plaques within the layers of the arterial wall. Although numerous studies have reported the underlying pathogenesis, no data-based studies have been conducted to analyze the potential genes and immune cells infiltration in the different stages of atherosclerosis via bioinformatics analysis. Methods In this study, we downloaded GSE100927 and GSE28829 from NCBI-GEO database. Gene ontology and pathway enrichment were performed via the DAVID database. The protein interaction network was constructed via STRING. Enriched hub genes were analyzed by the Cytoscape software. The evaluation of the infiltrating immune cells in the dataset samples was performed by the CIBERSORT algorithm. Results We identified 114 common upregulated differentially expressed genes and 22 common downregulated differentially expressed genes. (adjust p value < 0.01 and log FC ≥ 1). A cluster of 10 genes including CYBA, SLC11A1, FCER1G, ITGAM, ITGB2, CD53, ITGAX, VAMP8, CLEC5A, and CD300A were found to be significant. Through the deconvolution algorithm CIBERSORT, we analyzed the significant alteration of immune cells infiltration in the progression of atherosclerosis with the threshold of the Wilcoxon test at p value <0.05. Conclusions These results may reveal the underlying correlations between genes and immune cells in atherosclerosis, which enable us to investigate the novel insights for the development of treatments and drugs.

scholarly journals De-novo transcriptome analysis unveils differentially expressed genes regulating drought and salt stress response in Panicum sumatrense

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rasmita Rani Das ◽  
Seema Pradhan ◽  
Ajay Parida
Keyword(s):  
Gene Expression ◽  
Salt Stress ◽  
Abiotic Stress ◽  
Stress Tolerance ◽  
Differentially Expressed Genes ◽  
Salinity Stress ◽  
Abiotic Stress Tolerance ◽  
Differentially Expressed ◽  
Little Millet ◽  
Drought And Salt Stress

AbstractScreening the transcriptome of drought tolerant variety of little millet (Panicum sumatrense), a marginally cultivated, nutritionally rich, susbsistent crop, can identify genes responsible for its hardiness and enable identification of new sources of genetic variation which can be used for crop improvement. RNA-Seq generated ~ 230 million reads from control and treated tissues, which were assembled into 86,614 unigenes. In silico differential gene expression analysis created an overview of patterns of gene expression during exposure to drought and salt stress. Separate gene expression profiles for leaf and root tissue revealed the differences in regulatory mechanisms operating in these tissues during exposure to abiotic stress. Several transcription factors were identified and studied for differential expression. 61 differentially expressed genes were found to be common to both tissues under drought and salinity stress and were further validated using qRT-PCR. Transcriptome of P. sumatrense was also used to mine for genic SSR markers relevant to abiotic stress tolerance. This study is first report on a detailed analysis of molecular mechanisms of drought and salinity stress tolerance in a little millet variety. Resources generated in this study can be used as potential candidates for further characterization and to improve abiotic stress tolerance in food crops.

scholarly journals Study on the Differentially Expressed Genes and Signaling Pathways in Systemic Lupus Erythematosus Using Integrated Bioinformatics Method

2020 ◽  
Author(s):  
Jing Liang ◽  
Xin Zhang ◽  
Wenjia Zhao
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Lupus Erythematosus ◽  
Scientific Research ◽  
Differentially Expressed ◽  
Statistical Hypothesis ◽  
Systemic Lupus ◽  
Ppi Networks ◽  
Geo Database

Abstract Background: Systemic lupus erythematosus (SLE) is a chronic immune connective tissue disease, which is common in women of childbearing age and easy to cause multiple organ inflammatory injury. The occurrence of prostate cancer is the result of multiple factors and genes, but we have little understanding of the mechanism involved. In this study, we deeply explored and analyzed the existing gene data in GEO database in order to find the key genes and new therapeutic targets of SLE.Results: The expression profile dataset of GDS4185, GDS4888, GDS4889 and GDS4890 containing 99 specimens, 42 cases of SLE patients and 57 cases of normal volunteers, were downloaded from the Gene Expression Omnibus (GEO) website. The differentially expressed genes (DEGs) in different tissues was analyzed by statistical hypothesis T test. The gene ontology (GO) enrichment analysis was carried out by the DAVID online tool. KEGG pathway annotation of DEGs was carried out by the KOBAS online computing database. The protein–protein interaction (PPI) networks of the DEGs were built from the STRING website and Cytoscape software. A total of 839 DEGs were calculated from the four GEO datasets. The GO and KEGG analysis indicated that the functions of DEGs mostly participated in the Osteoclast differentiation, HTLV-I infection, Measles, FoxO signaling pathway, Herpes simplex infection, Primary immunodeficiency, Jak-STAT signaling pathway. The following 14 closely related genes, HERC5, TP53, CDC20, GNB2, GNB4, PPP2R1A, GNAI2, PMCH, SOCS3, HERC6, STAT1, SOCS1, ISG15, IFIT3, were key nodes from the PPI network. These genes may have synergistic or indirect interactions with each other in the process of biological metabolism inducing the pathogenesis of SLE.Conclusion: Mining geo database has great scientific research value. In the future, scientific research must fully excavate a variety of database analysis methods. In this study, the screened candidate genes provide effective theoretical basis for the diagnosis, treatment, expected evaluation and related laboratory research of SLE, which are worthy of further experimental verification.

scholarly journals Integrated bioinformatics analysis for differentially expressed genes and signaling pathways identification in gastric cancer

2019 ◽  
Author(s):  
ChenChen Yang ◽  
Aifeng Gong
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Differentially Expressed Genes ◽  
Kegg Pathway ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Mrna Levels ◽  
Pcr Assay ◽  
Microarray Datasets ◽  
Geo Database

Abstract Background Gastric cancer (GC) has a high mortality rate in cancer-related deaths worldwide. Here, we identified several vital candidate genes related to gastric cancer development and revealed the potential pathogenic mechanisms using integrated bioinformatics analysis.Methods Two microarray datasets from Gene Expression Omnibus (GEO) database integrated. Limma package was used to analyze differentially expressed genes (DEGs) between GC and matched normal specimens. DAVID was utilized to conduct Gene ontology (GO) and KEGG enrichment analysis. The relative expression of OLFM4, IGF2BP3, CLDN1and MMP1were analyzed based on TCGA database provided by UALCAN. Western blot and quantitative real time PCR assay were performed to determine the protein and mRNA levels of OLFM4, IGF2BP3, CLDN1and MMP1 in GC tissues and cell lines, respectively.Results We downloaded the expression profiles of GSE103236 and GSE118897 from the Gene Expression Omnibus (GEO) database. Two integrated microarray datasets were used to obtain differentially expressed genes (DEGs), and bioinformatics methods were used for in-depth analysis. After gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments analysis, we identified 61 DEGs in common, of which the expression of 34 genes were elevated and 27 genes were decreased. GO analysis displayed that the biological functions of DEGs mainly focused on negative regulation of growth, fatty acid binding, cellular response to zinc ion and calcium-independent cell-cell adhesion. KEGG pathway analysis demonstrated that these DEGs mainly related to the Wnt and tumor signaling pathway. Interestingly, we found 4 genes were most significantly upregulated in the DEGs, which were OLFM4, IGF2BP3, CLDN1 and MMP1.Then, we confirmed the upregulation of these genes in STAD based on sample types. In the final, western blot and qRT-PCR assay were performed to determine the protein and mRNA levels of OLFM4, IGF2BP3, CLDN1 and MMP1 in GC tissues and cell lines.Conclusion In our study, using integrated bioinformatics to screen DEGs in gastric cancer could benefit us for understanding the pathogenic mechanism underlying gastric cancer progression. Meanwhile, we also identified four significantly upregulated genes in DEGs from both two datasets, which might be used as the biomarkers for early diagnosis and prevention of gastric cancer.

scholarly journals The Screening of Critical Related Genes in Celiac Disease Based on Intraepithelial Lymphocytes Investigation: A Bioinformatics Analysis

2019 ◽  
Vol 8 ◽  
pp. 1407
Author(s):  
Mohammad Rostami-Nejad ◽  
Reza Vafaee ◽  
Mohammad Javad Ehsani-Ardakani ◽  
Nika Aghamohammadi ◽  
Aliasghar Keramatinia ◽  
...  
Keyword(s):  
Celiac Disease ◽  
Differentially Expressed Genes ◽  
Bioinformatics Analysis ◽  
Intraepithelial Lymphocytes ◽  
Gene Expression Omnibus ◽  
T Cell Differentiation ◽  
Differentially Expressed ◽  
Protein Protein Interaction ◽  
Critical Nodes ◽  
Geo Database

Background: Celiac disease (CD) is an immunological intestinal disorder, which is characterized by response to gluten. In addition to the environmental factors and dysbiosis of the gut microbiota, genetic susceptibility has an important role in the pathogenesis of this multifactorial disorder. Therefore, this study aims to present the crucial involved genes in CD pathogenesis. Materials and Methods: In this bioinformatics analysis study, significant differentially expressed genes of intraepithelial lymphocytes (IELs) samples of celiac patients versus normal patients from Gene Expression Omnibus (GEO) database were screened via the protein-protein interaction (PPI) network. The critical nodes based on degree values, betweenness centrality, and fold changes were determined and enriched by ClueGO to find relative biological terms. Results: According to the network analysis, five central nodes including IL2, PIK3CA, PRDM10, AKT1, and SRC and eight significant differentially expressed genes (DEGs) were determined as the critical genes related to CD. Also, CD4+, CD25+, alpha-beta regulatory T cell differentiation are identified as prominent biological terms in the celiac disease patients. Conclusion: There is a possible biomarker panel related to CD that can be used as a therapeutic or diagnostic tool to manage the disease. [GMJ.2019;8:e1407]

scholarly journals Combined Analysis of Expression Profiles in a Mouse Model and Patients Identified BHMT2 as a New Regulator of Lipid Metabolism in Metabolic-Associated Fatty Liver Disease

2021 ◽  
Vol 9 ◽  
Author(s):  
Yongqiang Ma ◽  
Zhi Tan ◽  
Qiang Li ◽  
Wenling Fan ◽  
Guangshun Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lipid Metabolism ◽  
Liver Disease ◽  
Fatty Liver ◽  
Differentially Expressed Genes ◽  
Fatty Liver Disease ◽  
Target Genes ◽  
Differentially Expressed ◽  
Overlapping Genes ◽  
Geo Database

Metabolic associated fatty liver disease (MAFLD) is associated with obesity, type 2 diabetes mellitus, and other metabolic syndromes. Farnesoid X receptor (FXR, NR1H4) plays a prominent role in hepatic lipid metabolism. This study combined the expression of liver genes in FXR knockout (KO) mice and MAFLD patients to identify new pathogenic pathways for MAFLD based on genome-wide transcriptional profiling. In addition, the roles of new target genes in the MAFLD pathogenic pathway were also explored. Two groups of differentially expressed genes were obtained from FXR-KO mice and MAFLD patients by transcriptional analysis of liver tissue samples. The similarities and differences between the two groups of differentially expressed genes were analyzed to identify novel pathogenic pathways and target genes. After the integration analysis of differentially expressed genes, we identified 134 overlapping genes, many of which have been reported to play an important role in lipid metabolism. Our unique analysis method of comparing differential gene expression between FXR-KO mice and patients with MAFLD is useful to identify target genes and pathways that may be strongly implicated in the pathogenesis of MAFLD. The overlapping genes with high specificity were screened using the Gene Expression Omnibus (GEO) database. Through comparison and analysis with the GEO database, we determined that BHMT2 and PKLR could be highly correlated with MAFLD. Clinical data analysis and RNA interference testing in vitro confirmed that BHMT2 may a new regulator of lipid metabolism in MAFLD pathogenesis. These results may provide new ideas for understanding the pathogenesis of MAFLD and thus provide new targets for the treatment of MAFLD.

scholarly journals Genome-Wide Distribution, Expression and Function Analysis of the U-Box Gene Family in Brassica oleracea L.

Genes ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 1000 ◽  
Author(s):  
Dengke Hu ◽  
Qinqin Xie ◽  
Qianying Liu ◽  
Tonghong Zuo ◽  
Hecui Zhang ◽  
...  
Keyword(s):  
Abiotic Stress ◽  
Gene Family ◽  
Brassica Oleracea ◽  
Differentially Expressed Genes ◽  
Function Analysis ◽  
Protein Family ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Evolutionary Analysis ◽  
Genome Wide

The plant U-box (PUB) protein family plays an important role in plant growth and development. The U-box gene family has been well studied in Arabidopsis thaliana, Brassica rapa, rice, etc., but there have been no systematic studies in Brassica oleracea. In this study, we performed genome-wide identification and evolutionary analysis of the U-box protein family of B. oleracea. Firstly, based on the Brassica database (BRAD) and the Bolbase database, 99 Brassica oleracea PUB genes were identified and divided into seven groups (I–VII). The BoPUB genes are unevenly distributed on the nine chromosomes of B. oleracea, and there are tandem repeat genes, leading to family expansion from the A. thaliana genome to the B. oleracea genome. The protein interaction network, GO annotation, and KEGG pathway enrichment analysis indicated that the biological processes and specific functions of the BoPUB genes may mainly involve abiotic stress. RNA-seq transcriptome data of different pollination times revealed spatiotemporal expression specificity of the BoPUB genes. The differential expression profile was consistent with the results of RT-qPCR analysis. Additionally, a large number of pollen-specific cis-acting elements were found in promoters of differentially expressed genes (DEG), which verified that these significantly differentially expressed genes after self-pollination (SP) were likely to participate in the self-incompatibility (SI) process, including gene encoding ARC1, a well-known downstream protein of SI in B. oleracea. Our study provides valuable information indicating that the BoPUB genes participates not only in the abiotic stress response, but are also involved in pollination.

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