gprofiler2 -- an R package for gene list functional enrichment analysis and namespace conversion toolset g:Profiler

Alzheimer’s disease (AD) is the leading cause of dementia in aging individuals. Yet, the pathophysiological processes involved in AD onset and progression are still poorly understood. Among numerous strategies, a comprehensive overview of gene expression alterations in the diseased brain could contribute for a better understanding of the AD pathology. In this work, we probed the differential expression of genes in different brain regions of healthy and AD adult subjects using data from three large transcriptomic studies: Mayo Clinic, Mount Sinai Brain Bank (MSBB), and ROSMAP. Using a combination of differential expression of gene and isoform switch analyses, we provide a detailed landscape of gene expression alterations in the temporal and frontal lobes, harboring brain areas affected at early and late stages of the AD pathology, respectively. Next, we took advantage of an indirect approach to assign the complex gene expression changes revealed in bulk RNAseq to individual cell types/subtypes of the adult brain. This strategy allowed us to identify previously overlooked gene expression changes in the brain of AD patients. Among these alterations, we show isoform switches in the AD causal gene amyloid-beta precursor protein (APP) and the risk gene bridging integrator 1 (BIN1), which could have important functional consequences in neuronal cells. Altogether, our work proposes a novel integrative strategy to analyze RNAseq data in AD and other neurodegenerative diseases based on both gene/transcript expression and regional/cell-type specificities.

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“…For gene ontology analysis, R library gprofiler2 55 was used. Using gost function, correction_method = “fdr” and significant=TRUE.…”

Section: Methodsmentioning

confidence: 99%

Differential transcript usage unravels gene expression alterations in Alzheimer’s disease human brains

et al. 2021

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“…Permutational multivariate analysis of variance (PERMANOVA) was calculated using the vegan package [ 34 ]. GO analysis was carried out using the gprofiler2 package [ 35 ]. Gene Set Enrichment Analysis (GSEA) was carried out using GSEA software (Broad Institute, version 4.0.2) and Reactome, KEGG and Biocarta pathways databases [ 36 ].…”

Section: Methodsmentioning

confidence: 99%

Localized skin inflammation during cutaneous leishmaniasis drives a chronic, systemic IFN-γ signature

et al. 2021

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Cutaneous leishmaniasis is a localized infection controlled by CD4+ T cells that produce IFN-γ within lesions. Phagocytic cells recruited to lesions, such as monocytes, are then exposed to IFN-γ which triggers their ability to kill the intracellular parasites. Consistent with this, transcriptional analysis of patient lesions identified an interferon stimulated gene (ISG) signature. To determine whether localized L. braziliensis infection triggers a systemic immune response that may influence the disease, we performed RNA sequencing (RNA-seq) on the blood of L. braziliensis-infected patients and healthy controls. Functional enrichment analysis identified an ISG signature as the dominant transcriptional response in the blood of patients. This ISG signature was associated with an increase in monocyte- and macrophage-specific marker genes in the blood and elevated serum levels IFN-γ. A cytotoxicity signature, which is a dominant feature in the lesions, was also observed in the blood and correlated with an increased abundance of cytolytic cells. Thus, two transcriptional signatures present in lesions were found systemically, although with a substantially reduced number of differentially expressed genes (DEGs). Finally, we found that the number of DEGs and ISGs in leishmaniasis was similar to tuberculosis–another localized infection–but significantly less than observed in malaria. In contrast, the cytolytic signature and increased cytolytic cell abundance was not found in tuberculosis or malaria. Our results indicate that systemic signatures can reflect what is occurring in leishmanial lesions. Furthermore, the presence of an ISG signature in blood monocytes and macrophages suggests a mechanism to limit systemic spread of the parasite, as well as enhance parasite control by pre-activating cells prior to lesion entry.

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“…Gene ontology-enrichment was performed using the gProfiler2 R package [ 43 ]. TF target genes were determined using Chromatin Immuno-Precipitation on chip (ChIP-chip) data from Gonçalves et al [ 28 ].…”

Section: Methodsmentioning

confidence: 99%

CRISPRi screens reveal genes modulating yeast growth in lignocellulose hydrolysate

Gutmann

Jann

Pereira

et al. 2021

Biotechnol Biofuels

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Background Baker’s yeast is a widely used eukaryotic cell factory, producing a diverse range of compounds including biofuels and fine chemicals. The use of lignocellulose as feedstock offers the opportunity to run these processes in an environmentally sustainable way. However, the required hydrolysis pretreatment of lignocellulosic material releases toxic compounds that hamper yeast growth and consequently productivity. Results Here, we employ CRISPR interference in S. cerevisiae to identify genes modulating fermentative growth in plant hydrolysate and in presence of lignocellulosic toxins. We find that at least one-third of hydrolysate-associated gene functions are explained by effects of known toxic compounds, such as the decreased growth of YAP1 or HAA1, or increased growth of DOT6 knock-down strains in hydrolysate. Conclusion Our study confirms previously known genetic elements and uncovers new targets towards designing more robust yeast strains for the utilization of lignocellulose hydrolysate as sustainable feedstock, and, more broadly, paves the way for applying CRISPRi screens to improve industrial fermentation processes.

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gprofiler2 -- an R package for gene list functional enrichment analysis and namespace conversion toolset g:Profiler

Cited by 494 publications

References 27 publications

Differential transcript usage unravels gene expression alterations in Alzheimer’s disease human brains

Differential transcript usage unravels gene expression alterations in Alzheimer’s disease human brains

Localized skin inflammation during cutaneous leishmaniasis drives a chronic, systemic IFN-γ signature

CRISPRi screens reveal genes modulating yeast growth in lignocellulose hydrolysate

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