Functional Enrichment Analysis of Regulatory Elements

García-Moreno, Adrián; López-Domínguez, Raúl; Villatoro-García, Juan Antonio; Ramírez-Mena, Alberto; Aparicio‐Puerta, Ernesto; Hackenberg, Michael; Pascual-Montano, Alberto; Carmona-Sáez, Pedro

doi:10.3390/biomedicines10030590

Cited by 84 publications

(60 citation statements)

References 56 publications

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“…Functional enrichment analysis is a set of statistical methods to extract biological information from omics data in terms of functional categories. These methods are widely used for the analysis of gene and protein lists and regulatory elements ( Garcia-Moreno et al., 2022 ). Taken together our results on functional enrichment analysis ( Figure 5 and Supplementary Figures S2 , S3 ), differential methylation ( Table 3 ) and unique m6A in infected cells ( Table 4 ) indicate that the cell response to viral infection not only changes the levels of mRNAs, as previously shown ( Wyler et al., 2021 ), but also its epitranscriptional pattern.…”

Section: Discussionmentioning

confidence: 99%

The epitranscriptome of Vero cells infected with SARS-CoV-2 assessed by direct RNA sequencing reveals m6A pattern changes and DRACH motif biases in viral and cellular RNAs

Campos

Alves

Maricato

et al. 2022

Front. Cell. Infect. Microbiol.

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The epitranscriptomics of the SARS-CoV-2 infected cell reveals its response to viral replication. Among various types of RNA nucleotide modifications, the m6A is the most common and is involved in several crucial processes of RNA intracellular location, maturation, half-life and translatability. This epitranscriptome contains a mixture of viral RNAs and cellular transcripts. In a previous study we presented the analysis of the SARS-CoV-2 RNA m6A methylation based on direct RNA sequencing and characterized DRACH motif mutations in different viral lineages. Here we present the analysis of the m6A transcript methylation of Vero cells (derived from African Green Monkeys) and Calu-3 cells (human) upon infection by SARS-CoV-2 using direct RNA sequencing data. Analysis of these data by nonparametric statistics and two computational methods (m6anet and EpiNano) show that m6A levels are higher in RNAs of infected cells. Functional enrichment analysis reveals increased m6A methylation of transcripts involved in translation, peptide and amine metabolism. This analysis allowed the identification of differentially methylated transcripts and m6A unique sites in the infected cell transcripts. Results here presented indicate that the cell response to viral infection not only changes the levels of mRNAs, as previously shown, but also its epitranscriptional pattern. Also, transcriptome-wide analysis shows strong nucleotide biases in DRACH motifs of cellular transcripts, both in Vero and Calu-3 cells, which use the signature GGACU whereas in viral RNAs the signature is GAACU. We hypothesize that the differences of DRACH motif biases, might force the convergent evolution of the viral genome resulting in better adaptation to target sequence preferences of writer, reader and eraser enzymes. To our knowledge, this is the first report on m6A epitranscriptome of the SARS-CoV-2 infected Vero cells by direct RNA sequencing, which is the sensu stricto RNA-seq.

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Section: Discussionmentioning

confidence: 99%

The epitranscriptome of Vero cells infected with SARS-CoV-2 assessed by direct RNA sequencing reveals m6A pattern changes and DRACH motif biases in viral and cellular RNAs

Campos

Alves

Maricato

et al. 2022

Front. Cell. Infect. Microbiol.

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“…The GO and KEGG pathway enrichment analysis diagrams of DEGs were plotted using the clusterProfler package of the R software. A hub gene-pathway network was constructed for DEGs using the web-based tool GeneCodis4 [ 24 ].…”

Section: Methodsmentioning

confidence: 99%

ESM1 Is a Promising Therapeutic Target and Prognostic Indicator for Esophageal Carcinogenesis/Esophageal Squamous Cell Carcinoma

Dong

Zhang

et al. 2022

BioMed Research International

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Objective. Endothelial cell-specific molecule 1 (ESM1) has been implicated as an oncogene in several types of cancer. However, the potential role of ESM1 in esophageal carcinogenesis (ESCA)/esophageal squamous cell carcinoma (ESCC) is still unclear. Methods. The expression, function, and survival data of ESM1 were observed using a bioinformatics approach. Subsequently, the expression level of ESM1 in surgical esophageal tumors and adjacent normal tissues was detected by qRT–PCR and immunofluorescence. We further revealed protein expression by immunohistochemistry (IHC), which is related to the prognosis of patients with ESCC using survival analysis. In vitro, knockdown of ESM1 in KYSE150 and KYSE510 cell lines, colony formation assays, wound healing assays, and Transwell assays were performed. Results. ESM1 is significantly elevated in 12 of 20 types of human cancer. ESM1 is highly expressed in tumor tissue compared with adjacent normal tissue and was identified as a hub gene in ESCA. Clinical outcome endpoints of overall survival (OS), progression-free interval (PFI), and disease-specific survival (DSS) curves showed that patients whose ESM1 expression was high had a lower clinical survival rate. The ESM1 high-expression group has a certain correlation with clinical stage and grade. The IHC of ESM1 further demonstrated that the higher the expression was, the worse the N classification and pTNM stage in patients with ESCC, which had a distinctly poorer overall 5-year survival rate. Univariate analysis showed that age, N classification, pTNM stage, and ESM1 expression were all prognostic factors, although multivariate Cox regression analysis showed that only pTNM stage was an independent prognostic factor. In vitro, silencing ESM1 suppressed the proliferation, migration, and invasion of KYSE150 and KYSE510 cells. Conclusions. ESM1 is a hub gene in the initiation and progression of ESCA/ESCC that promotes the proliferation, migration, and invasion of esophageal cancer cells and may be a promising therapeutic target and prognostic indicator.

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“…Enrichment analysis. In order to identify biological processes, molecular functions and cellular components of the module's genes, GeneCodis [30] online tool was utilized. As well as, pathway enrichment analysis was done using this tool based on Reactome [31] database.…”

Section: Ppi Network Reconstruction and Module Extractionmentioning

confidence: 99%

“…Enrichment analysis of genes. Gene Ontology (GO) and pathway enrichment analysis was done for the extracted module thanks to the GeneCodis [30] online tool. The results show that this module signi cantly enriched in "Activation of the pre-replicative complex" biological process, "MCM complex" cellular component and "DNA replication origin binding" molecular function.…”

Section: Tablementioning

confidence: 99%

Application of Protein-Protein interaction network analysis in order to identify Cervical cancer mRNA and miRNA biomarkers

Tabrizi-Nezhadi

MotieGhader

Maleki

2022

Preprint

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Background: Cervical cancer (CC) is one of the most common and serious cancers in the world. This cancer includes two histological types including Squamous cell carcinoma (SCC) and adenocarcinoma (ADC). In this project SCC have been studied. The current study aimed to identify novel potential candidate mRNA and miRNA biomarkers for CC based on a Protein-Protein Interaction (PPI) and miRNA-mRNA networks analysis.Results: In the current project, transcriptome profile for normal and CC samples was utilized. First, the PPI network was constructed for the 1335 DEGs, and then a significant gene module was extracted from the PPI network. Next, a list of miRNAs which are targeting module's genes are collected from the miRTarBase online database and a miRNA-mRNA regulatory network was formed. Afterward, CC driver genes were selected from the module's genes (MCM2, MCM10, POLA1, and TONSL) and introduced as potential candidate biomarkers for CC. As well as, two hub miRNAs including miR-193b-3p and miR-615-3p were selected from the miRNA-mRNA regulatory network and reported as potential candidate biomarkers for CC. Conclusion: In summary, six potential candidate RNA-based biomarkers consist of four genes containing MCM2, MCM10, POLA1, and TONSL and two miRNAs containing miR-193b-3p and miR-615-3p are opposed as potential candidate biomarker for CC.

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Functional Enrichment Analysis of Regulatory Elements

Cited by 84 publications

References 56 publications

The epitranscriptome of Vero cells infected with SARS-CoV-2 assessed by direct RNA sequencing reveals m6A pattern changes and DRACH motif biases in viral and cellular RNAs

The epitranscriptome of Vero cells infected with SARS-CoV-2 assessed by direct RNA sequencing reveals m6A pattern changes and DRACH motif biases in viral and cellular RNAs

ESM1 Is a Promising Therapeutic Target and Prognostic Indicator for Esophageal Carcinogenesis/Esophageal Squamous Cell Carcinoma

Application of Protein-Protein interaction network analysis in order to identify Cervical cancer mRNA and miRNA biomarkers

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