WebGestalt2: an updated and expanded version of the Web-based Gene Set Analysis Toolkit

Duncan, Dexter T.; Prodduturi, Naresh; Zhang, Bing

doi:10.1186/1471-2105-11-s4-p10

Cited by 125 publications

(89 citation statements)

References 1 publication

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“…Investigation of the types of genes affected by high-confidence somatic CNVs was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses (23,24) (Fig. 4 and Table S4).…”

Section: Resultsmentioning

confidence: 99%

Extensive genetic variation in somatic human tissues

O’Huallachain

Karczewski

Weissman

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

140

118

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Genetic variation between individuals has been extensively investigated, but differences between tissues within individuals are far less understood. It is commonly assumed that all healthy cells that arise from the same zygote possess the same genomic content, with a few known exceptions in the immune system and germ line. However, a growing body of evidence shows that genomic variation exists between differentiated tissues. We investigated the scope of somatic genomic variation between tissues within humans. Analysis of copy number variation by high-resolution array-comparative genomic hybridization in diverse tissues from six unrelated subjects reveals a significant number of intraindividual genomic changes between tissues. Many (79%) of these events affect genes. Our results have important consequences for understanding normal genetic and phenotypic variation within individuals, and they have significant implications for both the etiology of genetic diseases such as cancer and for immortalized cell lines that might be used in research and therapeutics.somatic mosiacism | genomic rearrangement

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Section: Resultsmentioning

confidence: 99%

Extensive genetic variation in somatic human tissues

O’Huallachain

Karczewski

Weissman

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

140

118

View full text Add to dashboard Cite

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“…In the functional analysis, GO terms with P values greater than 0.01 were discarded. The enriched terms with more than five genes present and P values < 0.01 were considered to be statistically significant in the pathway enrichment analysis (Duncan et al, 2010). The two analyses were performed using the database for annotation, visualization, and integrated discovery (DAVID, http://david.abcc.ncifcrf.gov/tools.jsp) (Huang et al, 2008).…”

Section: Functional Enrichment Analysismentioning

confidence: 99%

Potential hippocampal genes and pathways involved in Alzheimer’s disease: a bioinformatic analysis

Zhang¹,

Guo²,

Chu³

et al. 2015

Genet. Mol. Res.

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ABSTRACT. Alzheimer's disease (AD) is a neurodegenerative disorder and the most common cause of dementia in elderly people. Numerous studies have focused on the dysregulated genes in AD, but the pathogenesis is still unknown. In this study, we explored critical hippocampal genes and pathways that might potentially be involved in the pathogenesis of AD. Four transcriptome datasets for the hippocampus of patients with AD were downloaded from ArrayExpress, and the gene signature was identified by integrated analysis of multiple transcriptomes using novel genome-wide relative significance and genome-wide global significance models. A protein-protein interaction network was constructed, and five clusters were selected. The biological functions and pathways were identified by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. A total of 6994 genes were screened, and the top 300 genes were subjected to further analysis. Four significant KEGG pathways were identified, including oxidative phosphorylation and Parkinson's (2015) disease, Huntington's disease, and Alzheimer's disease pathways. The hub network of cluster 1 with the highest average rank value was defined. The genes (NDUFB3, NDUFA9, NDUFV1, NDUFV2, NDUFS3, NDUFA10, COX7B, and UQCR1) were considered critical with high degree in cluster 1 as well as being shared by the four significant pathways. The oxidative phosphorylation process was also involved in the other three pathways and is considered to be relevant to energy-related AD pathology in the hippocampus. This research provides a perspective from which to explore critical genes and pathways for potential AD therapies.

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“…edu/webgestalt/) (22) was used in order to identify miRNAs that were associated with the DEGs. A threshold of adjusted P<0.05 was used.…”

Section: Selection Of Mirnas Targeted To Degsmentioning

confidence: 99%

Regulatory mechanisms underlying sepsis progression in patients with tumor necrosis factor-α genetic variations

Liu

Han

et al. 2016

Experimental and Therapeutic Medicine

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Abstract. The present study aimed to investigate the regulatory mechanisms underlying sepsis progression in patients with tumor necrosis factor (TNF)-α genetic variations. The GSE5760 expression profile data, which was downloaded from the Gene Expression Omnibus database, contained 30 wild-type (WT) and 28 mutation (MUT) samples. Differentially expressed genes (DEGs) between the two types of samples were identified using the Student's t-test, and the corresponding microRNAs (miRNAs) were screened using WebGestalt software. An integrated miRNA-DEG network was constructed using the Cytoscape software, based on the interactions between the DEGs, as identified using the Search Tool for the Retrieval of Interacting Genes/Proteins database, and the correlation between miRNAs and their target genes. Furthermore, Gene Ontology and pathway enrichment analyses were conducted for the DEGs using the Database for Annotation, Visualization and Integrated Discovery and the KEGG Orthology Based Annotation System, respectively. A total of 390 DEGS between the WT and MUT samples, along with 11 -associated miRNAs, were identified. The integrated miRNA-DEG network consisted of 38 DEGs and 11 miRNAs. Within this network, COPS2 was found to be associated with transcriptional functions, while FUS was found to be involved in mRNA metabolic processes. Other DEGs, including FBXW7 and CUL3, were enriched in the ubiquitin-mediated proteolysis pathway. In addition, miR-15 was predicted to target COPS2 and CUL3. The results of the present study suggested that COPS2, FUS, FBXW7 and CUL3 may be associated with sepsis in patients with TNF-α genetic variations. In the progression of sepsis, FBXW7 and CUL3 may participate in the ubiquitin-mediated proteolysis pathway, whereas COPS2 may regulate the phosphorylation and ubiquitination of the FUS protein. Furthermore, COPS2 and CUL3 may be novel targets of miR-15.

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WebGestalt2: an updated and expanded version of the Web-based Gene Set Analysis Toolkit

Cited by 125 publications

References 1 publication

Extensive genetic variation in somatic human tissues

Extensive genetic variation in somatic human tissues

Potential hippocampal genes and pathways involved in Alzheimer’s disease: a bioinformatic analysis

Regulatory mechanisms underlying sepsis progression in patients with tumor necrosis factor-α genetic variations

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