ArticleScientific data2020
Consensus transcriptional regulatory networks of coronavirus-infected human cells.
Article in Scientific data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.
- Gene Expression Meta-Analysis Reveals Interferon-Induced Genes Associated With SARS Infection in Lungs.Frontiers in immunologyPooled it
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- Single-nucleus transcriptional profiling of the placenta reveals the syncytiotrophoblast stress response to COVID-19.American journal of obstetrics and gynecology · 2025Article
- Islet single-cell transcriptomic profiling during obesity-induced beta cell expansion in female mice.iScience · 2025Article
- Histone proteoform analysis reveals epigenetic changes in adult mouse brown adipose tissue in response to cold stress.Epigenetics & chromatin · 2024Article
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- Histone proteoform analysis reveals epigenetic changes in adult mouse brown adipose tissue in response to cold stress.bioRxiv : the preprint server for biology · 2024Article
- Spatial Transcriptomics Resolve an Emphysema-Specific Lymphoid Follicle B Cell Signature in Chronic Obstructive Pulmonary Disease.American journal of respiratory and critical care medicine · 2024Article
- SHP2 promotes sarcoidosis severity by inhibiting SKP2-targeted ubiquitination of TBET in CD8Science translational medicine · 2023Article
- Molecular basis for the repurposing of histamine H2-receptor antagonist to treat COVID-19.Journal of biomolecular structure & dynamics · 2022Article
- Transcriptional regulatory networks of circulating immune cells in type 1 diabetes: A community knowledgebase.iScience · 2022Article
- Enrichment analysis on regulatory subspaces: A novel direction for the superior description of cellular responses to SARS-CoV-2.Computers in biology and medicine · 2022Article
- Identification of transcriptional regulatory network associated with response of host epithelial cells to SARS-CoV-2.Scientific reports · 2021Article
- Role of miR-2392 in driving SARS-CoV-2 infection.Cell reports · 2021Article
- Conserved immunomodulatory transcriptional networks underlie antipsychotic-induced weight gain.Translational psychiatry · 2021Article
- Systematic analysis of SARS-CoV-2 infection of an ACE2-negative human airway cell.Cell reports · 2021Article
- A human liver chimeric mouse model for non-alcoholic fatty liver disease.JHEP reports : innovation in hepatology · 2021Article
- Comparative transcriptome analysis reveals key epigenetic targets in SARS-CoV-2 infection.NPJ systems biology and applications · 2021Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Establishing consensus around the transcriptional interface between coronavirus (CoV) infection and human cellular signaling pathways can catalyze the development of novel anti-CoV therapeutics. Here, we used publicly archived transcriptomic datasets to compute consensus regulatory signatures, or consensomes, that rank human genes based on their rates of differential expression in MERS-CoV (MERS), SARS-CoV-1 (SARS1) and SARS-CoV-2 (SARS2)-infected cells. Validating the CoV consensomes, we show that high confidence transcriptional targets (HCTs) of MERS, SARS1 and SARS2 infection intersect with HCTs of signaling pathway nodes with known roles in CoV infection. Among a series of novel use cases, we gather evidence for hypotheses that SARS2 infection efficiently represses E2F family HCTs encoding key drivers of DNA replication and the cell cycle; that progesterone receptor signaling antagonizes SARS2-induced inflammatory signaling in the airway epithelium; and that SARS2 HCTs are enriched for genes involved in epithelial to mesenchymal transition. The CoV infection consensomes and HCT intersection analyses are freely accessible through the Signaling Pathways Project knowledgebase, and as Cytoscape-style networks in the Network Data Exchange repository.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.