scholarly journals Gene Ontology term enrichment analysis of gene expression changes observed in the TRAMP mouse model of prostate cancer upon treatement with green tea catechins

2010 ◽  
Vol 24 (S1) ◽  
Author(s):  
Stephen Vincent Speicher ◽  
Kam D Dahlquist
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Gene Ontology ◽  
Mouse Model ◽  
Enrichment Analysis ◽  
Gene Ontology Term ◽  
Ontology Term ◽  
Tramp Mouse ◽  
Term Enrichment Analysis ◽  
Term Enrichment

scholarly journals Transcriptome analysis of sevoflurane exposure effects at the different brain regions

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0236771
Author(s):  
Hiroto Yamamoto ◽  
Yutaro Uchida ◽  
Tomoki Chiba ◽  
Ryota Kurimoto ◽  
Takahide Matsushima ◽  
...  
Keyword(s):  
Gene Ontology ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Brain Regions ◽  
Rna Seq ◽  
Ontology Term ◽  
Binding Motifs ◽  
Term Enrichment Analysis ◽  
Term Enrichment ◽  
Differently Expressed Genes

Backgrounds Sevoflurane is a most frequently used volatile anesthetics, but its molecular mechanisms of action remain unclear. We hypothesized that specific genes play regulatory roles in brain exposed to sevoflurane. Thus, we aimed to evaluate the effects of sevoflurane inhalation and identify potential regulatory genes by RNA-seq analysis. Methods Eight-week old mice were exposed to sevoflurane. RNA from medial prefrontal cortex, striatum, hypothalamus, and hippocampus were analysed using RNA-seq. Differently expressed genes were extracted and their gene ontology terms were analysed using Metascape. These our anesthetized mouse data and the transcriptome array data of the cerebral cortex of sleeping mice were compared. Finally, the activities of transcription factors were evaluated using a weighted parametric gene set analysis (wPGSA). JASPAR was used to confirm the existence of binding motifs in the upstream sequences of the differently expressed genes. Results The gene ontology term enrichment analysis result suggests that sevoflurane inhalation upregulated angiogenesis and downregulated neural differentiation in each region of brain. The comparison with the brains of sleeping mice showed that the gene expression changes were specific to anesthetized mice. Focusing on individual genes, sevoflurane induced Klf4 upregulation in all sampled parts of brain. wPGSA supported the function of KLF4 as a transcription factor, and KLF4-binding motifs were present in many regulatory regions of the differentially expressed genes. Conclusions Klf4 was upregulated by sevoflurane inhalation in the mouse brain. The roles of KLF4 might be key to elucidating the mechanisms of sevoflurane induced functional modification in the brain.

DiNGO: standalone application for Gene Ontology and Human Phenotype Ontology term enrichment analysis

2019 ◽  
Author(s):  
Radoslav Davidović ◽  
Vladimir Perovic ◽  
Branislava Gemovic ◽  
Nevena Veljkovic
Keyword(s):  
Gene Ontology ◽  
Source Code ◽  
Enrichment Analysis ◽  
Human Phenotype Ontology ◽  
Supplementary Information ◽  
Phenotype Ontology ◽  
Ontology Term ◽  
Human Phenotype ◽  
Term Enrichment Analysis ◽  
Term Enrichment

Abstract Summary Although various tools for Gene Ontology (GO) term enrichment analysis are available, there is still room for improvement. Hence, we present DiNGO, a standalone application based on an open source code from BiNGO, a widely-used application to assess the overrepresentation of GO categories. Besides facilitating GO term enrichment analyses, DiNGO has been developed to allow for convenient Human Phenotype Ontology (HPO) term overrepresentation investigation. This is an important contribution considering the increasing interest in HPO in scientific research and its potential in clinical settings. DiNGO supports gene/protein identifier conversion and an automatic updating of GO and HPO annotation resources. Finally, DiNGO can rapidly process a large amount of data due to its multithread design. Availability and Implementation DiNGO is implemented in the JAVA language, and its source code, example datasets and instructions are available on GitHub: https://github.com/radoslav180/DiNGO. A pre-compiled jar file is available at: https://www.vin.bg.ac.rs/180/tools/DiNGO.php Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Transcriptome Analysis Reveals Dynamic Cultivar-Dependent Patterns of Gene Expression in Potato Spindle Tuber Viroid-Infected Pepper

Plants ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 2687
Author(s):  
Nikol Hadjieva ◽  
Elena Apostolova ◽  
Vesselin Baev ◽  
Galina Yahubyan ◽  
Mariyana Gozmanova
Keyword(s):  
Gene Expression ◽  
Gene Ontology ◽  
Differentially Expressed Genes ◽  
Transcriptome Analysis ◽  
Quantitative Polymerase Chain Reaction ◽  
Potato Spindle Tuber Viroid ◽  
Fine Tuning ◽  
Differentially Expressed ◽  
Gene Ontology Term ◽  
Ontology Term

Potato spindle tuber viroid (PSTVd) infects various plants. PSTVd pathogenesis is associated with interference with the cellular metabolism and defense signaling pathways via direct interaction with host factors or via the transcriptional or post-transcriptional modulation of gene expression. To better understand host defense mechanisms to PSTVd infection, we analyzed the gene expression in two pepper cultivars, Capsicum annuum Kurtovska kapia (KK) and Djulunska shipka (DS), which exhibit mild symptoms of PSTVd infection. Deep sequencing-based transcriptome analysis revealed differential gene expression upon infection, with some genes displaying contrasting expression patterns in KK and DS plants. More genes were downregulated in DS plants upon infection than in KK plants, which could underlie the more severe symptoms seen in DS plants. Gene ontology enrichment analysis revealed that most of the downregulated differentially expressed genes in both cultivars were enriched in the gene ontology term photosynthesis. The genes upregulated in DS plants fell in the biological process of gene ontology term defense response. We validated the expression of six overlapping differentially expressed genes that are involved in photosynthesis, plant hormone signaling, and defense pathways by quantitative polymerase chain reaction. The observed differences in the responses of the two cultivars to PSTVd infection expand the understanding of the fine-tuning of plant gene expression that is needed to overcome the infection.

scholarly journals Tomato and Lycopene Feeding Impact Expression of Lipid and Cholesterol Metabolism Genes in Early TRAMP Mouse Model Prostate Carcinogenesis (OR05-05-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Nancy Moran ◽  
Jennifer M Thomas-Ahner ◽  
Hsueh-Li Tan ◽  
Ceasar Silva ◽  
Noor Hason ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Lipid Metabolism ◽  
Mouse Model ◽  
Cholesterol Metabolism ◽  
Agricultural Research ◽  
Transcriptional Responses ◽  
Tramp Mouse ◽  
Prostate Carcinogenesis ◽  
Early Carcinogenesis

Abstract Objectives Epidemiologic evidence suggests consuming tomato and lycopene are associated with a reduced risk of advanced and lethal prostate cancer. Prior studies of prostate cancer prevention in the TRAMP mouse model indicate that lifelong tomato- or lycopene-feeding reduce incidence of early carcinoma by up to 70%, and this effect is dependent on the expression of Bco2 (beta-carotene oxygenase 2, a carotenoid metabolic enzyme). We hypothesize that gene expression patterns will reveal the mechanisms by which these diets act to disrupt early carcinogenesis. Methods To define the early transcriptional responses in the dorsolateral mouse prostate, TRAMP and wild-type littermate mice were crossed with Bco2+/+ or Bco2−/− mice (C57/Bl6 background). All 4 crosses were fed either control, lycopene, or 10% tomato powder diets from weaning at 3 weeks until 8 weeks. Expression of 84 genes was measured by a prostate cancer-focused PCR array (n = 5/group). Protein expression was measured by Western blotting (n = 4/group) and serum carotenoids by HPLC (n = 3–4/group). Statistical effects of TRAMP and Bco2 genotypes and diet treatment on final body mass (n = 6/group), serum lycopene, and gene expression were analyzed by ANOVA (alpha = 0.05). Results Body masses were not influenced by genotypes or diets. Serum lycopene concentrations were subject to a Bco2 genotype effect (P = 0.004), with greater lycopene being present in Bco2−/− mice than Bco2 +/+mice, but did not differ by TRAMP genotype nor between lycopene vs tomato diets. The TRAMP genotype influenced the expression of 49 genes, diet impacted expression of 11 genes, and Bco2 genotype influenced expression of 2 genes. Expression of 4 genes, Apc, Mto1, Nfkb1, and Rbm39, were subject to a significant Bco2 x diet interaction. Expression of 5 genes related to lipid metabolism, Fasn, Acaca, Srebf1, Hmgcr, and Ptgs1, were impacted by a diet effect. Conclusions Semi-targeted analyses suggest tomato and lycopene may affect lipid metabolism in early carcinogenesis. Future studies may elaborate upon specific pathways modulated by tomato and lycopene in early prostate carcinogenesis. Funding Sources NIH/National Cancer Institute, NIH/National Center for Complementary and Integrative Health, USDA/Agricultural Research Service.

scholarly journals TFTenricher: a python toolbox for annotation enrichment analysis of transcription factor target genes

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Rasmus Magnusson ◽  
Zelmina Lubovac-Pilav
Keyword(s):  
Gene Ontology ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Ontology Term ◽  
Term Enrichment ◽  
Transcription Factor Target ◽  
Downstream Processes ◽  
Biological Context

Abstract Background Transcription factors (TFs) are the upstream regulators that orchestrate gene expression, and therefore a centrepiece in bioinformatics studies. While a core strategy to understand the biological context of genes and proteins includes annotation enrichment analysis, such as Gene Ontology term enrichment, these methods are not well suited for analysing groups of TFs. This is particularly true since such methods do not aim to include downstream processes, and given a set of TFs, the expected top ontologies would revolve around transcription processes. Results We present the TFTenricher, a Python toolbox that focuses specifically at identifying gene ontology terms, cellular pathways, and diseases that are over-represented among genes downstream of user-defined sets of human TFs. We evaluated the inference of downstream gene targets with respect to false positive annotations, and found an inference based on co-expression to best predict downstream processes. Based on these downstream genes, the TFTenricher uses some of the most common databases for gene functionalities, including GO, KEGG and Reactome, to calculate functional enrichments. By applying the TFTenricher to differential expression of TFs in 21 diseases, we found significant terms associated with disease mechanism, while the gene set enrichment analysis on the same dataset predominantly identified processes related to transcription. Conclusions and availability The TFTenricher package enables users to search for biological context in any set of TFs and their downstream genes. The TFTenricher is available as a Python 3 toolbox at https://github.com/rasma774/Tftenricher, under a GNU GPL license and with minimal dependencies.

Differential gene expression in prostate tissue according to vasectomy.

2016 ◽  
Vol 34 (2_suppl) ◽  
pp. 298-298
Author(s):  
Kathryn M Wilson ◽  
Travis Gerke ◽  
Ericka Ebot ◽  
Jennifer A Sinnott ◽  
Jennifer R. Rider ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Cancer Diagnosis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Prostate Tissue ◽  
Gene Set Enrichment ◽  
Normal Prostate ◽  
Gene Sets ◽  
Normal Prostate Tissue

298 Background: We previously found that vasectomy was associated with an increased risk of prostate cancer, and particularly, risk of lethal prostate cancer in the Health Professionals Follow-up Study (HPFS). However, the possible biological basis for this finding is unclear. In this study, we explored possible biological mechanisms by assessing differences in gene expression in the prostate tissue of men with and without a history of vasectomy prostate cancer diagnosis. Methods: Within the HPFS, vasectomy data and gene expression data (20,254 genes) was available from archival tumor tissue from 263 cases, 124 of whom also had data for adjacent normal tissue. To relate expression of individual genes to vasectomy we used linear regression adjusting for age and year at diagnosis. We ran gene set enrichment analysis to identify pathways of genes associated with vasectomy. Results: Among 263 cases, 67 (25%) reported a vasectomy prior to cancer diagnosis. Mean age at diagnosis was 66 years among men without and 65 years among men with vasectomy. Median time between vasectomy and prostate cancer diagnosis was 25 years. Gene expression in tumor tissue was not associated with vasectomy status. In adjacent normal tissue, three individual genes were associated with vasectomy with Bonferroni-corrected p-values of < 0.10: RAPGEF6, OR4C3, and SLC35F4. Gene set enrichment analysis found five pathways upregulated and seven pathways downregulated in men with vasectomy compared to those without in normal prostate tissue with a FDR < 0.05. Upregulated pathways included several immune-related gene sets and G-protein-coupled receptor gene sets. Conclusions: We identified significant differences in gene expression profiles in normal prostate tissue according to vasectomy status among men treated for prostate cancer. The fact that such differences existed several decades after vasectomy provides support for the idea that vasectomy may play a role in the etiology of prostate cancer.

scholarly journals Prevention of Prostate Cancer with Oleanane Synthetic Triterpenoid CDDO-Me in the TRAMP Mouse Model of Prostate Cancer

Cancers ◽  
2011 ◽  
Vol 3 (3) ◽  
pp. 3353-3369 ◽  
Author(s):  
Xiaohua Gao ◽  
Dorrah Deeb ◽  
Yongbo Liu ◽  
Ali S. Arbab ◽  
George W. Divine ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mouse Model ◽  
Tramp Mouse

scholarly journals Hypothalamic transcriptome analysis reveals the neuroendocrine mechanisms in controlling broodiness of Muscovy duck (Cairina moschata)

2018 ◽  
Author(s):  
Pengfei Ye ◽  
Min Li ◽  
Wang Liao ◽  
Kai Ge ◽  
Sihua Jin ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Gene Expression ◽  
Trend Analysis ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Egg Laying ◽  
Bird Conservation ◽  
Muscovy Duck ◽  
Ontology Term ◽  
Gabaergic Synapse

AbstractBroodiness, one of the maternal behaviors and instincts for natural breeding in birds, is an interesting topic in reproductive biology. Broodiness in poultry is characterized by persistent nesting, usually associated with cessation of egg laying. The study of avian broodiness is essential for bird conservation breeding and commercial poultry industry. In this study, we examined the hypothalamus transcriptome of Muscovy duck in three reproductive stages, including egg-laying anaphase (LA), brooding prophase (BP) and brooding metaphase (BM). Differences in gene expression during the transition from egg-laying to broodiness were examined, and 155, 379, 292 differently expressed genes (DEGs) were obtained by pairwise comparisons of LA-vs-BP, LA-vs-BM and BP-vs-BM, respectively (fold change≥ 1.5, P < 0.05). Gene Ontology Term (GO) enrichment analysis suggested a possible role of oxidative stress in the hypothalamus might invoke reproductive costs that potentially change genes expression. KEGG analysis revealed glutamatergic synapse, dopaminergic synapse, serotonergic synapse and GABAergic synapse pathway were significantly enriched, and regulator genes were identified. Eight gene expression patterns were illustrated by trend analysis and further clustered into three clusters. Additional six hub genes were identified through combining trend analysis and protein-protein interaction (PPI) analysis. Our results suggested that the cyclical mechanisms of reproductive function conversion include effects of oxidative stress, biosynthesis of neurotransmitters or their receptors, and interactions between glucocorticoids and thyroid hormones and regulatory genes. These candidate genes and biological pathways may be used as targets for artificial manipulation and marker-assisted breeding in the reproductive behavior.

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