Globaltest and GOEAST: two different approaches for Gene Ontology analysis

Hulsegge, Ina; Kommadath, Arun; Smits, M.A.

doi:10.1186/1753-6561-3-s4-s10

Cited by 134 publications

(110 citation statements)

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“…Gene ontology (GO) analysis (http://www.geneontology.org/) is a functional method for the analysis of large-scale transcriptomic or genomic data (19). The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database (http://www.genome.jp/kegg/pathway.html) contains information on the mechanism of molecules or genes (20).…”

Section: Predication Of Tgsmentioning

confidence: 99%

Hsa-miR-137, hsa-miR-520e and hsa-miR-590-3p perform crucial roles in Lynch syndrome

Zhou

et al. 2016

Oncology Letters

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Abstract. The aim of the present study was to identify the differentially expressed microRNAs (DEMs) between Lynch syndrome (LS) and the normal colonic (N-C) control samples, predict the target genes (TGs) and analyze the potential functions of the DEMs and TGs. The miRNA expression dataset GSE30454, which included data of 13 LS and 20 N-C tissue samples, was downloaded from the Gene Expression Omnibus. The classical t-test in Linear Models for Microarray Data package was used for DEM identification. TG prediction was performed using 5 databases. The regulatory network of the DEMs and their TGs was constructed using Cytoscape. Functional and pathway enrichment analysis was performed. The transcription factors (TFs), tumor-associated genes (TAG) and tumor suppressor genes (TSGs) were then identified. Three key DEMs hsa-miR-137, hsa-miR-520e, and hsa-miR-590-3p were identified. Hsa-miR-520e and hsa-miR-137 had 4 common TGs, including SNF related kinase, metal-regulatory transcription factor 1 (MTF1), round spermatid basic protein 1 and YTH N6-methyladenosine RNA binding protein 3; hsa-miR-590-3p and hsa-miR-137 had 14 common TGs, including NCK adaptor protein 1 (NCK1), EPH receptor A7, and stress-associated endoplasmic reticulum protein 1; hsa-miR-590-3p and hsa-miR-520e had 12 common TGs, including Krüppel-like factor (KLF) 13, twinfilin actin binding protein 1, and nuclear factor I B. Through the functional and pathway enrichments analysis, MTF1 was involved in regulation of gene expression and metabolic processes, and sequence-specific DNA binding TF activity. KLF13 was involved in regulation of gene expression and regulation of cellular metabolic processes. NCK1 was enriched in the axon guidance pathway. In addition, the functional and pathway enrichment analysis showed certain TGs, such as hypoxia-inducible factor 1α, AKT serine/threonine kinase 2, and rapamycin-insensitive companion of mammalian target of rapamycin, participated in the mTOR signaling pathway. The 3 key DEMs hsa-miR-137, hsa-miR-520e, and hsa-miR-590-3p may have important roles in the process of LS.

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Section: Predication Of Tgsmentioning

confidence: 99%

Hsa-miR-137, hsa-miR-520e and hsa-miR-590-3p perform crucial roles in Lynch syndrome

Zhou

et al. 2016

Oncology Letters

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“…The underlying function of DEGs was predicted by the Gene Ontology (GO) (Hulsegge et al, 2009) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) (Kanehisa, 2002) pathway en-richment analysis using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) tool (http://www.david.niaid.nih.gov) (Huang et al, 2009). P value < 0.01 was set as the cut-off criterion.…”

Section: Functional Enrichment Analysis Of Degsmentioning

confidence: 99%

Integrated miRNA-mRNA analysis of Epstein-Barr virus-positive nasopharyngeal carcinoma

2015

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ABSTRACT. This study aims to identify the crucial miRNAs in Epstein-Barr virus-positive nasopharyngeal carcinoma (NPC) and their target genes. Gene expression profile data (GSE12452) that included 31 NPC and 10 normal nasopharyngeal tissue specimens were downloaded. Differentially expressed genes (DEGs) were identified using significance analysis of microarrays. The underlying function of DEGs was predicted via Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. The miRNA sequencing dataset GSE14738 was also downloaded, and expression levels of miRNA were calculated by the number of reads mapped to each miRNA. The selected miRNAs were integrated into the miRecords 6029 Integrated miRNA-mRNA analysis of NPC ©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 14 (2): 6028-6036 (2015) database to obtain their target genes. Target genes associated with DEGs were used to construct the interaction network via Cytoscape. A total of 1437 DEGs between NPC and control were identified, most of which were enriched in cell cycle and extracellular matrix-receptor interaction signaling pathways. Furthermore, 112 miRNAs were considered upregulated in NPC samples. A total of 2228 relationships between 39 miRNAs and 1247 target genes were obtained, of which 182 relationships between 32 miRNAs and 97 target genes were chosen to construct an interaction network. The interactions between DEGs and the let-7 or miR-29 families appeared strongest in this network, where CDC25A, COL3A1, and COL1A1 were regulated by several let-7 family members, while COL4A1 and COL5A2 were regulated by several miR-29 family members. The let-7 and miR-29 families may be related to the development of NPC by regulating the genes involved in cell cycle and ECM-receptor interaction.

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“…For functional analysis of the obtained genes, DAVID (Database for Annotation, Visualization and Integrated Discovery) 28 was performed for GO (Gene Ontology) 29 enrichment analysis. GO categories were classified into Biological Process (BP), Molecular Function (MF) and Cellular Component (CC) GO-terms.…”

Section: Gene Functional Enrichment Analysismentioning

confidence: 99%

Identification of mutant genes with high‐frequency, high‐risk, and high‐expression in lung adenocarcinoma

Yang

et al. 2014

Thoracic Cancer

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Background: To identify mutant genes with high-frequency-risk-expression between lung adenocarcinoma and normal samples. Methods:The ribonucleic acid RNA-Seq data GSE34914 and GSE37765 were downloaded from the Gene Expression Omnibus database, including 12 lung adenocarcinoma samples and six controls. All RNA-Seq reads were processed and the geneexpression level was calculated. Single nucleotide variation (SNV) was analyzed and the locations of mutant sites were recorded. In addition, the frequency and risk-level of mutant genes were calculated. Gene Ontology (GO) functional analysis was performed. The reported cancer genes were searched in tumor suppressor genes, Cancer Genes, and the Catalogue of Somatic Mutations in Cancer (COSMIC) database. Results: The SNV annotations of somatic mutation sites showed that 70% of mutation sites in the exon region occurred in the coding sequence (CDS). Thyroid hormone receptor interactor (TRIP)12 was identified with the highest frequency. A total of 118 mutant genes with high frequency and high-risk were selected and significantly enriched into several GO terms. No base mutation of cyclin C (CCNC) or RAB11A was recorded. At fragments per kilobase per million reads (FPKM) ≥ 56.5, reported tumor suppressor genes catenin (cadherin-associated protein), delta (CTNND)1, dual specificity phosphatase (DUSP)6, malate dehydrogenase (MDH)1 and RNA binding motif protein (RBM)5, were identified. Notably, signal transducer and activator of transcription 2 (STAT2) was the only transcription factor (TF) with high-risk mutation and its expression was detected. Conclusion: For the mutant genes with high-frequency-risk-expression, CTNND1, DUSP6, MDH1 and RBM5 were identified. TRIP12 might be a potential cancer-related gene, and expression of TF STAT2 with high-risk was detected. These mutant gene candidates might promote the development of lung adenocarcinoma and provide new diagnostic potential targets for treatment.

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Globaltest and GOEAST: two different approaches for Gene Ontology analysis

Cited by 134 publications

References 9 publications

Hsa-miR-137, hsa-miR-520e and hsa-miR-590-3p perform crucial roles in Lynch syndrome

Hsa-miR-137, hsa-miR-520e and hsa-miR-590-3p perform crucial roles in Lynch syndrome

Integrated miRNA-mRNA analysis of Epstein-Barr virus-positive nasopharyngeal carcinoma

Identification of mutant genes with high‐frequency, high‐risk, and high‐expression in lung adenocarcinoma

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