Differential Gene Set Enrichment Analysis: a statistical approach to quantify the relative enrichment of two gene sets

Joly, James H.; Lowry, William E.; Graham, Nicholas A.

doi:10.1093/bioinformatics/btaa658

Cited by 26 publications

(17 citation statements)

References 29 publications

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“…While it is perhaps not surprising that genes related to neuronal physiology were perturbed in MECP2 low neurons in the Rett brain, considering previously reported phenotypes from both in vivo and in vitro phenotypes, the alteration of metabolism in Rett brain is relatively unexplored and warranted further investigation. This pattern of metabolic disruption at the RNA level could portend metabolic defects in the neurons, as it has been previously established that metabolic dysfunction can present at the level of RNA expression of important metabolic enzymes [20,21].…”

Section: Methods To Isolate and Profile Neurons With And Without Expression Of Mecp2 From Individual Rett Patient Brainsmentioning

confidence: 89%

Defining dysfunction due to loss of MECP2 in Rett Patient Brain

Korsakova¹,

Morales²,

McDaniel³

et al. 2021

Preprint

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Rett Syndrome is characterized by a postnatal loss of neurophysiological function and regression of childhood development. Because the syndrome is X-linked and males with MECP2 mutations generally do not survive birth, the study of this syndrome has been complicated by the fact that in female brain, a portion of neurons express wild type MECP2, and another portion express a non-functional allele of MECP2. Therefore, bulk-RNA-sequencing of Rett brain is confounded by the presence of chimerism of neurons for functional MECP2 in neurons. We developed an approach that allows for single-nuclei transcriptional profiling of individual neurons and a direct comparison between neurons that express functional MECP2 with those that express the disease-causing allele. We found that mutant neurons from Rett brain show patterns of aberrant expression of synaptic and metabolic genes, both of which can be detected in in vitro models of Rett Syndrome. We used these resources to identify a role for POU2F1/OCT1 transcription factor in mediating the response to stress due to loss of MECP2, highlighting a potential key molecular regulator of stress in Rett neurons. Together, our new sorting approach enables us to highlight defective molecular and metabolic pathways in Rett brain neurons and suggests that in vitro models could serve as valuable tools to further study this syndrome and potentially for development of novel therapeutics.

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Section: Methods To Isolate and Profile Neurons With And Without Expression Of Mecp2 From Individual Rett Patient Brainsmentioning

confidence: 89%

Defining dysfunction due to loss of MECP2 in Rett Patient Brain

Korsakova¹,

Morales²,

McDaniel³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Analyzing gene set enrichment is an important analytical exercise for classifying common biological insights, such as biological processes and chromosomal locations associated with different interlinked diseases 21 . Through EnrichR ( https://maayanlab.cloud/Enrichr/ )—a comprehensive gene set enrichment web tool, GO enrichment and functional enrichment (biological processes, cellular composition, and molecular functions) studies were conducted 22 to characterize biological mechanisms and signaling pathways for shared DEGs.…”

Section: Methodsmentioning

confidence: 99%

Identification of the effects of COVID-19 on patients with pulmonary fibrosis and lung cancer: a bioinformatics analysis and literature review

Yang

Niu

2022

Sci Rep

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Coronavirus disease 2019 (COVID-19) poses a serious threat to human health and life. The effective prevention and treatment of COVID-19 complications have become crucial to saving patients’ lives. During the phase of mass spread of the epidemic, a large number of patients with pulmonary fibrosis and lung cancers were inevitably infected with the SARS-CoV-2 virus. Lung cancers have the highest tumor morbidity and mortality rates worldwide, and pulmonary fibrosis itself is one of the complications of COVID-19. Idiopathic lung fibrosis (IPF) and various lung cancers (primary and metastatic) become risk factors for complications of COVID-19 and significantly increase mortality in patients. Therefore, we applied bioinformatics and systems biology approaches to identify molecular biomarkers and common pathways in COVID-19, IPF, colorectal cancer (CRC) lung metastasis, SCLC and NSCLC. We identified 79 DEGs between COVID-19, IPF, CRC lung metastasis, SCLC and NSCLC. Meanwhile, based on the transcriptome features of DSigDB and common DEGs, we identified 10 drug candidates. In this study, 79 DEGs are the common core genes of the 5 diseases. The 10 drugs were found to have positive effects in treating COVID-19 and lung cancer, potentially reducing the risk of pulmonary fibrosis.

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“…To evaluate the association between gene sets and biological signals, we performed the GSEA analysis [ 10 ]. After downloading GSEA_4.1.0 and c5: GO gene sets (c5.all.v7.1.symbols.…”

Section: Methodsmentioning

confidence: 99%

Identification of tubulointerstitial genes and ceRNA networks involved in diabetic nephropathy via integrated bioinformatics approaches

et al. 2022

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Background Diabetic nephropathy (DN) is the major cause of end-stage renal disease worldwide. The mechanism of tubulointerstitial lesions in DN is not fully elucidated. This article aims to identify novel genes and clarify the molecular mechanisms for the progression of DN through integrated bioinformatics approaches. Method We downloaded microarray datasets from Gene Expression Omnibus (GEO) database and identified the differentially expressed genes (DEGs). Enrichment analyses, construction of Protein–protein interaction (PPI) network, and visualization of the co-expressed network between mRNAs and microRNAs (miRNAs) were performed. Additionally, we validated the expression of hub genes and analyzed the Receiver Operating Characteristic (ROC) curve in another GEO dataset. Clinical analysis and ceRNA networks were further analyzed. Results Totally 463 DEGs were identified, and enrichment analyses demonstrated that extracellular matrix structural constituents, regulation of immune effector process, positive regulation of cytokine production, phagosome, and complement and coagulation cascades were the major enriched pathways in DN. Three hub genes (CD53, CSF2RB, and LAPTM5) were obtained, and their expression levels were validated by GEO datasets. Pearson analysis showed that these genes were negatively correlated with the glomerular filtration rate (GFR). After literature searching, the ceRNA networks among circRNAs/IncRNAs, miRNAs, and mRNAs were constructed. The predicted RNA pathway of NEAT1/XIST-hsa-miR-155-5p/hsa-miR-486-5p-CSF2RB provides an important perspective and insights into the molecular mechanism of DN. Conclusion In conclusion, we identified three genes, namely CD53, CSF2RB, and LAPTM5, as hub genes of tubulointerstitial lesions in DN. They may be closely related to the pathogenesis of DN and the predicted RNA regulatory pathway of NEAT1/XIST-hsa-miR-155-5p/hsa-miR-486-5p-CSF2RB presents a biomarker axis to the occurrence and development of DN.

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Differential Gene Set Enrichment Analysis: a statistical approach to quantify the relative enrichment of two gene sets

Cited by 26 publications

References 29 publications

Defining dysfunction due to loss of MECP2 in Rett Patient Brain

Defining dysfunction due to loss of MECP2 in Rett Patient Brain

Identification of the effects of COVID-19 on patients with pulmonary fibrosis and lung cancer: a bioinformatics analysis and literature review

Identification of tubulointerstitial genes and ceRNA networks involved in diabetic nephropathy via integrated bioinformatics approaches

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