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.

scholarly journals Gastroesophageal reflux activates the NF-κB pathway and impairs esophageal barrier function in mice

2013 ◽  
Vol 305 (1) ◽  
pp. G58-G65 ◽  
Author(s):  
Yu Fang ◽  
Hao Chen ◽  
Yuhui Hu ◽  
Zorka Djukic ◽  
Whitney Tevebaugh ◽  
...  
Keyword(s):  
Gastroesophageal Reflux ◽  
Barrier Function ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Esophageal Epithelium ◽  
Gene Set Enrichment ◽  
Gene Sets ◽  
Epithelial Resistance

The barrier function of the esophageal epithelium is a major defense against gastroesophageal reflux disease. Previous studies have shown that reflux damage is reflected in a decrease in transepithelial electrical resistance associated with tight junction alterations in the esophageal epithelium. To develop novel therapies, it is critical to understand the molecular mechanisms whereby contact with a refluxate impairs esophageal barrier function. In this study, surgical models of duodenal and mixed reflux were developed in mice. Mouse esophageal epithelium was analyzed by gene microarray. Gene set enrichment analysis showed upregulation of inflammation-related gene sets and the NF-κB pathway due to reflux. Significance analysis of microarrays revealed upregulation of NF-κB target genes. Overexpression of NF-κB subunits (p50 and p65) and NF-κB target genes (matrix metalloproteinases-3 and -9, IL-1β, IL-6, and IL-8) confirmed activation of the NF-κB pathway in the esophageal epithelium. In addition, real-time PCR, Western blotting, and immunohistochemical staining also showed downregulation and mislocalization of claudins-1 and -4. In a second animal experiment, treatment with an NF-κB inhibitor, BAY 11-7085 (20 mg·kg−1·day−1 ip for 10 days), counteracted the effects of duodenal and mixed reflux on epithelial resistance and NF-κB-regulated cytokines. We conclude that gastroesophageal reflux activates the NF-κB pathway and impairs esophageal barrier function in mice and that targeting the NF-κB pathway may strengthen esophageal barrier function against reflux.

scholarly journals Dysregulation of post-transcriptional modification by copy number variable microRNAs in schizophrenia with enhanced glycation stress

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Akane Yoshikawa ◽  
Itaru Kushima ◽  
Mitsuhiro Miyashita ◽  
Kazuya Toriumi ◽  
Kazuhiro Suzuki ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Copy Number ◽  
Mirna Target ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Synaptic Function ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Genome Wide

AbstractPreviously, we identified a subpopulation of schizophrenia (SCZ) showing increased levels of plasma pentosidine, a marker of glycation and oxidative stress. However, its causative genetic factors remain largely unknown. Recently, it has been suggested that dysregulated posttranslational modification by copy number variable microRNAs (CNV-miRNAs) may contribute to the etiology of SCZ. Here, an integrative genome-wide CNV-miRNA analysis was performed to investigate the etiology of SCZ with accumulated plasma pentosidine (PEN-SCZ). The number of CNV-miRNAs and the gene ontology (GO) in the context of miRNAs within CNVs were compared between PEN-SCZ and non-PEN-SCZ groups. Gene set enrichment analysis of miRNA target genes was further performed to evaluate the pathways affected in PEN-SCZ. We show that miRNAs were significantly enriched within CNVs in the PEN-SCZ versus non-PEN-SCZ groups (p = 0.032). Of note, as per GO analysis, the dysregulated neurodevelopmental events in the two groups may have different origins. Additionally, gene set enrichment analysis of miRNA target genes revealed that miRNAs involved in glycation/oxidative stress and synaptic neurotransmission, especially glutamate/GABA receptor signaling, were possibly affected in PEN-SCZ. To the best of our knowledge, this is the first genome-wide CNV-miRNA study suggesting the role of CNV-miRNAs in the etiology of PEN-SCZ, through effects on genes related to glycation/oxidative stress and synaptic function. Our findings provide supportive evidence that glycation/oxidative stress possibly caused by genetic defects related to the posttranscriptional modification may lead to synaptic dysfunction. Therefore, targeting miRNAs may be one of the promising approaches for the treatment of PEN-SCZ.

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.

scholarly journals GSKB: A gene set database for pathway analysis in mouse

2016 ◽  
Author(s):  
Liming Lai ◽  
Jason Hennessey ◽  
Valerie Bares ◽  
Eun Woo Son ◽  
Yuguang Ban ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Pathway Analysis ◽  
Target Genes ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set ◽  
Link Type ◽  
Transcription Factor Target

ABSTRACTInterpretation of high-throughput genomics data based on biological pathways constitutes a constant challenge, partly because of the lack of supporting pathway database. In this study, we created a functional genomics knowledgebase in mouse, which includes 33,261 pathways and gene sets compiled from 40 sources such as Gene Ontology, KEGG, GeneSetDB, PANTHER, microRNA and transcription factor target genes, etc. In addition, we also manually collected and curated 8,747 lists of differentially expressed genes from 2,526 published gene expression studies to enable the detection of similarity to previously reported gene expression signatures. These two types of data constitute a Gene Set Knowledgebase (GSKB), which can be readily used by various pathway analysis software such as gene set enrichment analysis (GSEA). Using our knowledgebase, we were able to detect the correct microRNA (miR-29) pathway that was suppressed using antisense oligonucleotides and confirmed its role in inhibiting fibrogenesis, which might involve upregulation of transcription factor SMAD3. The knowledgebase can be queried as a source of published gene lists for further meta-analysis. Through meta-analysis of 56 published gene lists related to retina cells, we revealed two fundamentally different types of gene expression changes. One is related to stress and inflammatory response blamed for causing blindness in many diseases; the other associated with visual perception by normal retina cells. GSKB is available online at http://ge-lab.org/gs/, and also as a Bioconductor package (gskb, https://bioconductor.org/packages/gskb/). This database enables in-depth interpretation of mouse genomics data both in terms of known pathways and the context of thousands of published expression signatures.

scholarly journals Transcriptional Effects of Psychoactive Drugs on Genes Involved in Neurogenesis

2020 ◽  
Vol 21 (21) ◽  
pp. 8333
Author(s):  
Chiara C. Bortolasci ◽  
Briana Spolding ◽  
Srisaiyini Kidnapillai ◽  
Timothy Connor ◽  
Trang T.T. Truong ◽  
...  
Keyword(s):  
Gene Ontology ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gas Chromatography Mass Spectrometry ◽  
Transcriptional Level ◽  
Psychoactive Drugs ◽  
Gene Set ◽  
Expression Of Genes

Although neurogenesis is affected in several psychiatric diseases, the effects and mechanisms of action of psychoactive drugs on neurogenesis remain unknown and/or controversial. This study aims to evaluate the effects of psychoactive drugs on the expression of genes involved in neurogenesis. Neuronal-like cells (NT2-N) were treated with amisulpride (10 µM), aripiprazole (0.1 µM), clozapine (10 µM), lamotrigine (50 µM), lithium (2.5 mM), quetiapine (50 µM), risperidone (0.1 µM), or valproate (0.5 mM) for 24 h. Genome wide mRNA expression was quantified and analysed using gene set enrichment analysis, with the neurogenesis gene set retrieved from the Gene Ontology database and the Mammalian Adult Neurogenesis Gene Ontology (MANGO) database. Transcription factors that are more likely to regulate these genes were investigated to better understand the biological processes driving neurogenesis. Targeted metabolomics were performed using gas chromatography-mass spectrometry. Six of the eight drugs decreased the expression of genes involved in neurogenesis in both databases. This suggests that acute treatment with these psychoactive drugs negatively regulates the expression of genes involved in neurogenesis in vitro. SOX2 and three of its target genes (CCND1, BMP4, and DKK1) were also decreased after treatment with quetiapine. This can, at least in part, explain the mechanisms by which these drugs decrease neurogenesis at a transcriptional level in vitro. These results were supported by the finding of increased metabolite markers of mature neurons following treatment with most of the drugs tested, suggesting increased proportions of mature relative to immature neurons consistent with reduced neurogenesis.

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 Interaction with the DNA Binding Domain of MLL and a Small Molecular Drug Induces Proteolysis of MLL-Fusion Proteins and Ablates Leukemic Stem Cell Activity

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1549-1549
Author(s):  
Jasper de Boer ◽  
Sandra Cantilena
Keyword(s):  
Fusion Protein ◽  
Cell Lines ◽  
Fusion Proteins ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Self Renewal ◽  
Gene Set ◽  
Cellular Machinery

Abstract Introduction Leukemias harbouring 11q23 abnormalities causing mixed-lineage leukaemia gene (MLL) rearrangements are associated with poor clinical outcomes. Despite being an aggressive leukaemia, the MLL rearranged infant ALL has among the lowest mutation rates reported for any cancer. This means that to improve survival for patients with this aggressive leukaemia we need drugs that target the abnormal proteins produced by the MLL fusion gene or that interact with the abnormal MLL fusion protein to shut down the cellular machinery that drives these leukemias. Indeed, targeting MLL fusion dependent gene pathways has become a major focus. Our previous studies have shown that inhibition of MLL-fusions, in a conditional mouse model of MLL-ENL driven acute myeloid leukaemia, resulted in a block in self-renewal of the leukemic cells and ablated the leukaemia in the mice. This led us to hypothesise that if, we could achieve pharmacological inactivation of the MLL fusion proteins, we could achieve improved clinical outcomes. To achieve this, we set out a drug screening programme in acute leukaemia with the aim to discover drugs that can inactivate MLL-fusion oncoproteins. Results Our drug discovery pipeline screened clinical approved drugs for their ability to inhibit the function of the MLL fusion protein. This lead to the discovery of a drug that interacts with the DNA binding domain within the MLL fusion protein. This interaction destabilises the MLL fusion protein so that the fusion protein gets degraded within 24 hours of addition of the drug. So far, we have shown that we can inhibit and induce the degradation of MLL-AF9, MLL-AF6 and MLL-AF4 (and WT MLL) in the human MLL rearranged cell lines (THP-1, SHI-I and MV4-11), in primary immortalized cells in which the MLL-AF9 is overexpressed from a lentiviral backbone and in patient derived leukemic samples. Inactivation/degradation of the MLL fusion protein should shut down the cellular machinery that drives these leukemias. It is well established that MLL-fusions lead to abhorrent upregulation of its target genes HOXA9, MEIS1 and c-MYB. Treatment of MLL rearranged cells resulted in the downregulation of these MLL-fusion target genes within 24hrs of addition of the drug. Furthermore, Gene Set Enrichment Analysis of drug treated MLL-AF9 cells showed strong negative enrichment to various published MLL fusion target gene sets. Inactivation of MLL fusion protein should also result in block in self-renewal as we have previously shown in our conditional mouse model. Indeed, Gene Set Enrichment Analysis showed negative enrichment to published Leukemic Stem Cell gene set. To analyse the impact of drug treatment on self-renewal, we used a well-established self-renewal assay, whereby self-renewal is assessed by their ability to form colonies derived from single cells in methylcellulose. While treatment had no significant impact on the colony formation of CD34 positive cord blood progenitors, the drug was able to block the colony formation ability of MLL rearranged cell lines while only slowing a slight reduction in in the colony numbers of non MLL rearranged cell lines. Conclusion Overall, the data indicates that we may have discovered a new targeted treatment for MLL rearranged leukemia, which shows excellent clinical properties. We have successfully generated Patient Derived Xenografts (PDX) models and we are currently testing this drug to verify its effectiveness in the treatment on PDX. We will include this data in our presentation. Disclosures No relevant conflicts of interest to declare.

Identification of key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma

2020 ◽  
Vol 15 ◽  
Author(s):  
Wei Han ◽  
Dongchen Lu ◽  
Chonggao Wang ◽  
Mengdi Cui ◽  
Kai Lu
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differential Expression Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Integrated Analysis ◽  
Papillary Thyroid ◽  
Gene Set Enrichment ◽  
Mirna Expression Data

Background: In the past decades, the incidence of thyroid cancer (TC) has been gradually increasing, owing to the widespread use of ultrasound scanning devices. However, the key mRNAs, miRNAs, and mRNA-miRNA network in papillary thyroid carcinoma (PTC) has not been fully understood. Material and Methods: In this study, multiple bioinformatics methods were employed, including differential expression analysis, gene set enrichment analysis, and miRNA-mRNA interaction network construction. Results: First, we investigated the key miRNAs that regulated significantly more differentially expressed genes based on GSEA method. Second, we searched for the key miRNAs based on the mRNA-miRNA interaction subnetwork involved in PTC. We identified hsa-mir-1275, hsa-mir-1291, hsa-mir-206 and hsa-mir-375 as the key miRNAs involved in PTC pathogenesis. Conclusion: The integrated analysis of the gene and miRNA expression data not only identified key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma, but also improved our understanding of the pathogenesis of PTC.

scholarly journals Placental Transcriptome Adaptations to Maternal Nutrient Restriction in Sheep

2021 ◽  
Vol 22 (14) ◽  
pp. 7654
Author(s):  
Chelsie B. Steinhauser ◽  
Colleen A. Lambo ◽  
Katharine Askelson ◽  
Gregory W. Burns ◽  
Susanta K. Behura ◽  
...  
Keyword(s):  
Mhc Class Ii ◽  
Killer Cell ◽  
National Research Council ◽  
Enrichment Analysis ◽  
Nutrient Utilization ◽  
Gene Set Enrichment Analysis ◽  
Nutrient Restriction ◽  
Placental Development ◽  
Gene Set Enrichment ◽  
Pregnant Sheep

Placental development is modified in response to maternal nutrient restriction (NR), resulting in a spectrum of fetal growth rates. Pregnant sheep carrying singleton fetuses and fed either 100% (n = 8) or 50% (NR; n = 28) of their National Research Council (NRC) recommended intake from days 35–135 of pregnancy were used to elucidate placentome transcriptome alterations at both day 70 and day 135. NR fetuses were further designated into upper (NR NonSGA; n = 7) and lower quartiles (NR SGA; n = 7) based on day 135 fetal weight. At day 70 of pregnancy, there were 22 genes dysregulated between NR SGA and 100% NRC placentomes, 27 genes between NR NonSGA and 100% NRC placentomes, and 22 genes between NR SGA and NR NonSGA placentomes. These genes mediated molecular functions such as MHC class II protein binding, signaling receptor binding, and cytokine activity. Gene set enrichment analysis (GSEA) revealed significant overrepresentation of genes for natural-killer-cell-mediated cytotoxicity in NR SGA compared to 100% NRC placentomes, and alterations in nutrient utilization pathways between NR SGA and NR NonSGA placentomes at day 70. Results identify novel factors associated with impaired function in SGA placentomes and potential for placentomes from NR NonSGA pregnancies to adapt to nutritional hardship.

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