GOMA: functional enrichment analysis tool based on GO modules

Background: Peroxiredoxins (Prxs) comprise antioxidant factors that are widely found in prokaryotes and eukaryotes. Abnormal expression of Prxs is closely related to tumorigenesis. Methods: This study examined the prognostic value and expression of Prxs in lung cancer by Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, Kaplan-Meier Plotter, cBioPortal and Functional Enrichment Analysis Tool (FunRich) databases. Results: We found that Prx1/2/3/4/5 were overexpressed in both lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) relative to normal lung cells. However, the expression level of Prx6 was lower in LUAD and higher in LUSC than normal lung cells. The level of Prx3 and Prx6 were associated with pathological stage. Prognostic analysis showed that elevated Prx1 and Prx2 expression were correlated with low Overall Survival (OS), whereas high Prx5 and Prx6 expression level predicted high OS. Conclusions: Our results effectively revealed the level of Prxs in lung cancer and its influence on the prognosis of lung carcinoma, contributing to the study of the role of Prxs in tumorigenesis.

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DNA methylation profile of liver of mice conceived by in vitro fertilization

Journal of Developmental Origins of Health and Disease ◽

10.1017/s2040174421000313 ◽

2021 ◽

pp. 1-9

Author(s):

Saúl Lira-Albarrán ◽

Xiaowei Liu ◽

Seok Hee Lee ◽

Paolo Rinaudo

Keyword(s):

Dna Methylation ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Global Dna Methylation ◽

Analysis Tool ◽

Gene Promoters ◽

Vitro Fertilization ◽

Natural Mating

Abstract Offspring generated by in vitro fertilization (IVF) are believed to be healthy but display a possible predisposition to chronic diseases, like hypertension and glucose intolerance. Since epigenetic changes are believed to underlie such phenotype, this study aimed at describing global DNA methylation changes in the liver of adult mice generated by natural mating (FB group) or by IVF. Embryos were generated by IVF or natural mating. At 30 weeks of age, mice were sacrificed. The liver was removed, and global DNA methylation was assessed using whole-genome bisulfite sequencing (WGBS). Genomic Regions for Enrichment Analysis Tool (GREAT) and G:Profilerβ were used to identify differentially methylated regions (DMRs) and for functional enrichment analysis. Overrepresented gene ontology terms were summarized with REVIGO, while canonical pathways (CPs) were identified with Ingenuity® Pathway Analysis. Overall, 2692 DMRs (4.91%) were different between the groups. The majority of DMRs (84.92%) were hypomethylated in the IVF group. Surprisingly, only 0.16% of CpG islands were differentially methylated and only a few DMRs were located on known gene promoters (n = 283) or enhancers (n = 190). Notably, the long-interspersed element (LINE), short-interspersed element (SINE), and long terminal repeat (LTR1) transposable elements showed reduced methylation (P < 0.05) in IVF livers. Cellular metabolic process, hepatic fibrosis, and insulin receptor signaling were some of the principal biological processes and CPs modified by IVF. In summary, IVF modifies the DNA methylation signature in the adult liver, resulting in hypomethylation of genes involved in metabolism and gene transcription regulation. These findings may shed light on the mechanisms underlying the developmental origin of health and disease.

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NeVOmics: An Enrichment Tool for Gene Ontology and Functional Network Analysis and Visualization of Data from OMICs Technologies

Genes ◽

10.3390/genes9120569 ◽

2018 ◽

Vol 9 (12) ◽

pp. 569 ◽

Cited By ~ 2

Author(s):

Eduardo Zúñiga-León ◽

Ulises Carrasco-Navarro ◽

Francisco Fierro

Keyword(s):

Gene Ontology ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Analysis Tool ◽

Bioinformatic Tools ◽

Large Gene ◽

Large Sets ◽

Visualization Of Data ◽

Relationship Of

The increasing number of OMICs studies demands bioinformatic tools that aid in the analysis of large sets of genes or proteins to understand their roles in the cell and establish functional networks and pathways. In the last decade, over-representation or enrichment tools have played a successful role in the functional analysis of large gene/protein lists, which is evidenced by thousands of publications citing these tools. However, in most cases the results of these analyses are long lists of biological terms associated to proteins that are difficult to digest and interpret. Here we present NeVOmics, Network-based Visualization for Omics, a functional enrichment analysis tool that identifies statistically over-represented biological terms within a given gene/protein set. This tool provides a hypergeometric distribution test to calculate significantly enriched biological terms, and facilitates analysis on cluster distribution and relationship of proteins to processes and pathways. NeVOmics is adapted to use updated information from the two main annotation databases: Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG). NeVOmics compares favorably to other Gene Ontology and enrichment tools regarding coverage in the identification of biological terms. NeVOmics can also build different network-based graphical representations from the enrichment results, which makes it an integrative tool that greatly facilitates interpretation of results obtained by OMICs approaches. NeVOmics is freely accessible at https://github.com/bioinfproject/bioinfo/.

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Relationship Between Insulin Resistance and Endometrial Cancer: Determination of Key Genes and Pathways

10.21203/rs.3.rs-864828/v1 ◽

2021 ◽

Author(s):

Dou-Dou Ding ◽

Quan Zhou ◽

Ze He ◽

Hong-Xia He ◽

Man-Zhen Zuo

Keyword(s):

Insulin Resistance ◽

Endometrial Cancer ◽

Endometrial Carcinoma ◽

Metabolic Diseases ◽

Single Gene ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Analysis Tool ◽

Key Genes

Abstract Introduction:Epidemiological studies have found that the occurrence of endometrial cancer(EC) is closely related to metabolic diseases, and insulin resistance (IR) plays an important role in the pathogenesis of endometrium, but the specific pathogenesis is still unclear. The purpose of this study is to reveal the relationship between insulin resistance and endothelial cells by gene screening technology. Material and methods:We analyzed one endometrial carcinoma database (GSE106191) and one insulin-resistant database (GSE63992), with Gene Expression Omnibus (GEO) database and Venny online analysis tool, then, we found an add-up to 148 different genes. Functional enrichment analysis of these genes using DAVID showed that they were participated in transcription factor activity,signaling pathways and response to factors, etc. Then used cytoHubba in Cytoscape,we got 25 hub genes.Results: The results showed that the survival time of OGT, IGSF3, TRO, NEURL2 and PIK3C2B was significantly and closely related to EC, and the percentage of gene changes of five central genes ranged from 3% to 10% of a single gene, was also related to the infiltration of seven kinds of immune cells in endometrial carcinoma.Conclusion:The five key genes (OGT,IGSF3, PIK3C2B,TRO and NEURL2) are involved in immune infiltration in the progression of endometrial carcinoma, and there is also a certain mutation probability in gene mutation. This may be the pathogenesis of insulin resistance and endometrial cancer.

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Bias in miRNA enrichment analysis related to gene functional annotations

10.1101/2021.08.16.456527 ◽

2021 ◽

Author(s):

Konstantinos Zagganas ◽

Georgios K Georgakilas ◽

Thanasis Vergoulis ◽

Theodore Dalamagas

Keyword(s):

Gene Annotation ◽

Target Prediction ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Randomization Test ◽

Functional Enrichment ◽

Data Sets ◽

Analysis Tool ◽

Statistical Measure ◽

Rest Api

Motivation: miRNA functional enrichment is a type of analysis that is used to predict which biological functions may be affected by a group of miRNAs or validate whether a list of dysreg- ulated miRNAs are linked to a diseased state. The standard method for functional enrichment analysis uses the hypergeometric distribution to produce p-values, depicting the strength of the association between a group of miRNAs and a biological function. However, in 2015, it was shown that this approach suffers from a bias related to miRNA targets produced by target prediction algorithms and a new randomization test was proposed. Results: In this paper, we demonstrate the existence of another underlying bias which affects gene annotation data sets; additionally, we show that the statistical measure used for the estab- lished randomization test is not sensitive enough to account for it. For this reason, we propose the use of an alternative statistical measure, the "two-sided overlap", and we show that it is able to alleviate the aforementioned issue. Finally, we develop BUFET2, a miRNA enrichment analysis tool that leverages this measure (along with the old one); it is based on BUFET, a fast and scalable implementation of the established randomization test. Availability and Implementation: BUFET2 is written in C++ and is packaged with a Python wrapper script that facilitates experiment execution. Moreover, BUFET2 also comes pre-packaged in a Linux Docker image published on Docker Hub, thus eliminating the need for code compilation. Finally, BUFET2 is also publicly available to execute through a REST API. All datasets used in the experiments throught this paper are openly accessible on Zenodo (https://doi.org/10.5281/zenodo.5175819).

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Systems Biology Approaches Reveal a Multi-stress Responsive WRKY Transcription Factor and Stress Associated Gene Co-expression Networks in Chickpea

Current Bioinformatics ◽

10.2174/1574893614666190204152500 ◽

2019 ◽

Vol 14 (7) ◽

pp. 591-601 ◽

Cited By ~ 1

Author(s):

Aravind K. Konda ◽

Parasappa R. Sabale ◽

Khela R. Soren ◽

Shanmugavadivel P. Subramaniam ◽

Pallavi Singh ◽

...

Keyword(s):

Expression Pattern ◽

Gene Networks ◽

Molecular Mechanisms ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Wrky Transcription Factor ◽

Functional Enrichment ◽

Differentially Expressed ◽

Callose Deposition ◽

Significant Probability

Background: Chickpea is a nutritional rich premier pulse crop but its production encounters setbacks due to various stresses and understanding of molecular mechanisms can be ascribed foremost importance. Objective: The investigation was carried out to identify the differentially expressed WRKY TFs in chickpea in response to herbicide stress and decipher their interacting partners. Methods: For this purpose, transcriptome wide identification of WRKY TFs in chickpea was done. Behavior of the differentially expressed TFs was compared between other stress conditions. Orthology based cofunctional gene networks were derived from Arabidopsis. Gene ontology and functional enrichment analysis was performed using Blast2GO and STRING software. Gene Coexpression Network (GCN) was constructed in chickpea using publicly available transcriptome data. Expression pattern of the identified gene network was studied in chickpea-Fusarium interactions. Results: A unique WRKY TF (Ca_08086) was found to be significantly (q value = 0.02) upregulated not only under herbicide stress but also in other stresses. Co-functional network of 14 genes, namely Ca_08086, Ca_19657, Ca_01317, Ca_20172, Ca_12226, Ca_15326, Ca_04218, Ca_07256, Ca_14620, Ca_12474, Ca_11595, Ca_15291, Ca_11762 and Ca_03543 were identified. GCN revealed 95 hub genes based on the significant probability scores. Functional annotation indicated role in callose deposition and response to chitin. Interestingly, contrasting expression pattern of the 14 network genes was observed in wilt resistant and susceptible chickpea genotypes, infected with Fusarium. Conclusion: This is the first report of identification of a multi-stress responsive WRKY TF and its associated GCN in chickpea.

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Structural variations in papaya genomes

BMC Genomics ◽

10.1186/s12864-021-07665-4 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Zhenyang Liao ◽

Xunxiao Zhang ◽

Shengcheng Zhang ◽

Zhicong Lin ◽

Xingtan Zhang ◽

...

Keyword(s):

Agronomic Traits ◽

Enrichment Analysis ◽

Copy Number Variant ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Structural Variations ◽

Reproduction Traits ◽

Depth Study ◽

Environmental Adaptability ◽

The Impact

Abstract Background Structural variations (SVs) are a type of mutations that have not been widely detected in plant genomes and studies in animals have shown their role in the process of domestication. An in-depth study of SVs will help us to further understand the impact of SVs on the phenotype and environmental adaptability during papaya domestication and provide genomic resources for the development of molecular markers. Results We detected a total of 8083 SVs, including 5260 deletions, 552 tandem duplications and 2271 insertions with deletion being the predominant, indicating the universality of deletion in the evolution of papaya genome. The distribution of these SVs is non-random in each chromosome. A total of 1794 genes overlaps with SV, of which 1350 genes are expressed in at least one tissue. The weighted correlation network analysis (WGCNA) of these expressed genes reveals co-expression relationship between SVs-genes and different tissues, and functional enrichment analysis shows their role in biological growth and environmental responses. We also identified some domesticated SVs genes related to environmental adaptability, sexual reproduction, and important agronomic traits during the domestication of papaya. Analysis of artificially selected copy number variant genes (CNV-genes) also revealed genes associated with plant growth and environmental stress. Conclusions SVs played an indispensable role in the process of papaya domestication, especially in the reproduction traits of hermaphrodite plants. The detection of genome-wide SVs and CNV-genes between cultivated gynodioecious populations and wild dioecious populations provides a reference for further understanding of the evolution process from male to hermaphrodite in papaya.

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CCTs as new biomarkers for the prognosis of head and neck squamous cancer

Open Medicine ◽

10.1515/med-2020-0114 ◽

2020 ◽

Vol 15 (1) ◽

pp. 672-688

Author(s):

Yanbo Dong ◽

Siyu Lu ◽

Zhenxiao Wang ◽

Liangfa Liu

Keyword(s):

Head And Neck ◽

Survival Data ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Advanced Tumor Stage ◽

Expression Levels ◽

T Complex ◽

Advanced Tumor ◽

Squamous Cancer

AbstractThe chaperonin-containing T-complex protein 1 (CCT) subunits participate in diverse diseases. However, little is known about their expression and prognostic values in human head and neck squamous cancer (HNSC). This article aims to evaluate the effects of CCT subunits regarding their prognostic values for HNSC. We mined the transcriptional and survival data of CCTs in HNSC patients from online databases. A protein–protein interaction network was constructed and a functional enrichment analysis of target genes was performed. We observed that the mRNA expression levels of CCT1/2/3/4/5/6/7/8 were higher in HNSC tissues than in normal tissues. Survival analysis revealed that the high mRNA transcriptional levels of CCT3/4/5/6/7/8 were associated with a low overall survival. The expression levels of CCT4/7 were correlated with advanced tumor stage. And the overexpression of CCT4 was associated with higher N stage of patients. Validation of CCTs’ differential expression and prognostic values was achieved by the Human Protein Atlas and GEO datasets. Mechanistic exploration of CCT subunits by the functional enrichment analysis suggests that these genes may influence the HNSC prognosis by regulating PI3K-Akt and other pathways. This study implies that CCT3/4/6/7/8 are promising biomarkers for the prognosis of HNSC.

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Investigation and Functional Enrichment Analysis of the Human Host Interaction Network with Common Gram-Negative Respiratory Pathogens Predicts Possible Association with Lung Adenocarcinoma

Pathophysiology ◽

10.3390/pathophysiology28010003 ◽

2021 ◽

Vol 28 (1) ◽

pp. 20-33

Author(s):

Lydia-Eirini Giannakou ◽

Athanasios-Stefanos Giannopoulos ◽

Chrissi Hatzoglou ◽

Konstantinos I. Gourgoulianis ◽

Erasmia Rouka ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Cell Junctions ◽

Respiratory Pathogens ◽

Gram Negative ◽

Human Proteins ◽

Apoptotic Pathways

Haemophilus influenzae (Hi), Moraxella catarrhalis (MorCa) and Pseudomonas aeruginosa (Psa) are three of the most common gram-negative bacteria responsible for human respiratory diseases. In this study, we aimed to identify, using the functional enrichment analysis (FEA), the human gene interaction network with the aforementioned bacteria in order to elucidate the full spectrum of induced pathogenicity. The Human Pathogen Interaction Database (HPIDB 3.0) was used to identify the human proteins that interact with the three pathogens. FEA was performed via the ToppFun tool of the ToppGene Suite and the GeneCodis database so as to identify enriched gene ontologies (GO) of biological processes (BP), cellular components (CC) and diseases. In total, 11 human proteins were found to interact with the bacterial pathogens. FEA of BP GOs revealed associations with mitochondrial membrane permeability relative to apoptotic pathways. FEA of CC GOs revealed associations with focal adhesion, cell junctions and exosomes. The most significantly enriched annotations in diseases and pathways were lung adenocarcinoma and cell cycle, respectively. Our results suggest that the Hi, MorCa and Psa pathogens could be related to the pathogenesis and/or progression of lung adenocarcinoma via the targeting of the epithelial cellular junctions and the subsequent deregulation of the cell adhesion and apoptotic pathways. These hypotheses should be experimentally validated.

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