GeneTrail 3: advanced high-throughput enrichment analysis

Gerstner, Nico; Kehl, Tim; Lenhof, Kerstin; Müller, Anne; Mayer, Carolin; Eckhart, Lea; Grammes, Nadja; Diener, Caroline; Hart, Martin; Hahn, Oliver; Walter, Jörn; Wyss‐Coray, Tony; Meese, Eckart; Keller, Andreas; Lenhof, Hans‐Peter

doi:10.1093/nar/gkaa306

Cited by 80 publications

(77 citation statements)

References 28 publications

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“…Concerning the functions of the identified miR-155 target genes, we performed an over-representation analysis (FDR adjusted ( 40 )) using the online pathway enrichment analysis tool Genetrail 3.0 ( 27 ). Six out of the 17 identified targets (DDX17, EZH1, JMY, KDM5B, TADA2B, TAF7) were significantly enriched in the GO molecular function term ‘transcription coregulator activity’ ( P = 6.89E−04).…”

Section: Resultsmentioning

confidence: 99%

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Quantitative and time-resolved miRNA pattern of early human T cell activation

Diener

Hart

Kehl

et al. 2020

Nucleic Acids Research

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T cells are central to the immune response against various pathogens and cancer cells. Complex networks of transcriptional and post-transcriptional regulators, including microRNAs (miRNAs), coordinate the T cell activation process. Available miRNA datasets, however, do not sufficiently dissolve the dynamic changes of miRNA controlled networks upon T cell activation. Here, we established a quantitative and time-resolved expression pattern for the entire miRNome over a period of 24 h upon human T-cell activation. Based on our time-resolved datasets, we identified central miRNAs and specified common miRNA expression profiles. We found the most prominent quantitative expression changes for miR-155-5p with a range from initially 40 molecules/cell to 1600 molecules/cell upon T-cell activation. We established a comprehensive dynamic regulatory network of both the up- and downstream regulation of miR-155. Upstream, we highlight IRF4 and its complexes with SPI1 and BATF as central for the transcriptional regulation of miR-155. Downstream of miR-155-5p, we verified 17 of its target genes by the time-resolved data recorded after T cell activation. Our data provide comprehensive insights into the range of stimulus induced miRNA abundance changes and lay the ground to identify efficient points of intervention for modifying the T cell response.

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Section: Resultsmentioning

confidence: 99%

“…These were then combined using standard hierarchical clustering with Ward's minimum variance method ( 26 ). In both clustering steps, we use the Euclidean distance for the gradients of two consecutive time points as a distance measure ( 27 ).…”

Section: Methodsmentioning

confidence: 99%

Quantitative and time-resolved miRNA pattern of early human T cell activation

Diener

Hart

Kehl

et al. 2020

Nucleic Acids Research

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“…Seurat default Log (fold change) > 0.25 (absolute value), adjusted P value (Bonferroni correction) < 0.05, and expression in greater than 10% of cells were required to consider a gene differentially expressed. Biological pathway and gene ontology enrichment analysis was performed using Enrichr 155 , Metascape 156 , or GeneTrail 3 157 with input species set to Homo sapiens 156 and using standard parameters. Docking, processing, and viral defense genes relevant to SARS-CoV-2 were chosen based on ladecola, et al 16 .…”

Section: Methodsmentioning

confidence: 99%

Broad transcriptional dysregulation of brain and choroid plexus cell types with COVID-19

Yang

Kern

et al. 2020

Preprint

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Though SARS-CoV-2 primarily targets the respiratory system, it is increasingly appreciated that patients may suffer neurological symptoms of varied severity. However, an unbiased understanding of the molecular processes across brain cell types that could contribute to these symptoms in COVID-19 patients is still missing. Here, we profile 47,678 droplet-based single-nucleus transcriptomes from the frontal cortex and choroid plexus across 10 non-viral, 4 COVID-19, and 1 influenza patient. We complement transcriptomic data with immunohistochemical staining for the presence of SARS-CoV-2. We find that all major cortex parenchymal and choroid plexus cell types are affected transcriptionally with COVID-19. This arises, in part, from SARS-CoV-2 infection of the cortical brain vasculature, meninges, and choroid plexus, stimulating increased inflammatory signaling into the brain. In parallel, peripheral immune cells infiltrate the brain, microglia activate programs mediating the phagocytosis of live neurons, and astrocytes dysregulate genes involved in neurotransmitter homeostasis. Among neurons, layer 2/3 excitatory neurons--evolutionarily expanded in humans--show a specific downregulation of genes encoding major SNARE and synaptic vesicle components, predicting compromised synaptic transmission. These perturbations are not observed in terminal influenza. Many COVID-19 gene expression changes are shared with those in chronic brain disorders and reside in genetic variants associated with cognitive function, schizophrenia, and depression. Our findings and public dataset provide a molecular framework and new opportunities to understand COVID-19 related neurological disease.

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“…The datasets for each tissue were then compared in order to study the intersection of pathways. In addition, enrichment analysis was performed based on gene ontology (GO) biological process using the tool GeneTrail3 [ 17 ], which takes as input the lists of DEGs along with their log 2 FC values. The unweighted version of the gene set enrichment analysis (GSEA) was used, which is a non-parametric hypothesis test that sorts the input list of genes based on their expression values.…”

Section: Methodsmentioning

confidence: 99%

“…Thus far, studies of gene expression at the RNA level have been performed in human tissues and different ataxia mouse models. These studies concluded to a number of candidate involved biological pathways, including glutamate signaling, calcium signaling, synaptic transmission, DNA repair pathways, cell cycle, metabolic processes, and receptor-mediated signaling pathways [ 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. To our knowledge, none of the above studies or any other study at the whole or coding transcriptome expression level, aimed to identify implicated pathways for SA.…”

Section: Introductionmentioning

confidence: 99%

Analyzing Gene Expression Profiles from Ataxia and Spasticity Phenotypes to Reveal Spastic Ataxia Related Pathways

Kakouri

Votsi

Tomazou

et al. 2020

IJMS

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Spastic ataxia (SA) is a group of rare neurodegenerative diseases, characterized by mixed features of generalized ataxia and spasticity. The pathogenetic mechanisms that drive the development of the majority of these diseases remain unclear, although a number of studies have highlighted the involvement of mitochondrial and lipid metabolism, as well as calcium signaling. Our group has previously published the GBA2 c.1780G > C (p.Asp594His) missense variant as the cause of spastic ataxia in a Cypriot consanguineous family, and more recently the biochemical characterization of this variant in patients’ lymphoblastoid cell lines. GBA2 is a crucial enzyme of sphingolipid metabolism. However, it is unknown if GBA2 has additional functions and therefore additional pathways may be involved in the disease development. The current study introduces bioinformatics approaches to better understand the pathogenetic mechanisms of the disease. We analyzed publicly available human gene expression datasets of diseases presented with ‘ataxia’ or ‘spasticity’ in their clinical phenotype and we performed pathway analysis in order to: (a) search for candidate perturbed pathways of SA; and (b) evaluate the role of sphingolipid signaling pathway and sphingolipid metabolism in the disease development, through the identification of differentially expressed genes in patients compared to controls. Our results demonstrate consistent differential expression of genes that participate in the sphingolipid pathways and highlight alterations in the pathway level that might be associated with the disease phenotype. Through enrichment analysis, we discuss additional pathways that are connected to sphingolipid pathways, such as PI3K-Akt signaling, MAPK signaling, calcium signaling, and lipid and carbohydrate metabolism as the most enriched for ataxia and spasticity phenotypes.

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GeneTrail 3: advanced high-throughput enrichment analysis

Cited by 80 publications

References 28 publications

Quantitative and time-resolved miRNA pattern of early human T cell activation

Quantitative and time-resolved miRNA pattern of early human T cell activation

Broad transcriptional dysregulation of brain and choroid plexus cell types with COVID-19

Analyzing Gene Expression Profiles from Ataxia and Spasticity Phenotypes to Reveal Spastic Ataxia Related Pathways

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