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An integrative analysis identifying transcriptional features and key genes involved in COVID-19.

ABSTRACT: Aim: To elucidate the transcriptional characteristics of COVID-19. Materials & methods: We utilized an integrative approach to comprehensively analyze the transcriptional features of both COVID-19 patients and SARS-CoV-2 infected cells. Results: Widespread infiltration of immune cells was observed. We identified 233 genes that were codifferentially expressed in both bronchoalveolar lavage fluid and lung samples of COVID-19 patients. Functional analysis suggested upregulated genes were related to immune response such as neutrophil activation and antivirus response, while downregulated genes were associated with cell adhesion. Finally, we identified LCN2, STAT1 and UBE2L6 as core genes during SARS-CoV-2 infection. Conclusion: The identification of core genes involved in COVID-19 can provide us with more insights into the molecular features of COVID-19.

SUBMITTER: Li G

PROVIDER: S-EPMC7714049 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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An integrative analysis identifying transcriptional features and key genes involved in COVID-19.

Li Guoping G Wang Junyi J He Xiang X Zhang Lei L Ran Qin Q Xiong Anying A Wu Dehong D Hu Lingjuan L Song Qi Q Zhu Dong D

Epigenomics 20201126 22

Aim: To elucidate the transcriptional characteristics of COVID-19. Materials & methods: We utilized an integrative approach to comprehensively analyze the transcriptional features of both COVID-19 patients and SARS-CoV-2 infected cells. Results: Widespread infiltration of immune cells was observed. We identified 233 genes that were codifferentially expressed in both bronchoalveolar lavage fluid and lung samples of COVID-19 patients. Functional analysis suggested upregulated ...[more]

PMID: 33242255

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Project description:Novel coronavirus pneumonia (COVID-19) is a new type of viral pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that has spread rapidly and become a global pandemic. Heart failure (HF) is the ultimate period of the development of various cardiovascular diseases. There are several research have found that SARS-CoV-2 infection may induce cardiac complications including enhanced cardiac stress biomarkers and heart failure. Our research aims at identifying underlying biological processes and key targets in COVID-19-associated heart failure via bioinformatics analysis. A total of three heart failure datasets and three COVID-19 datasets were obtained using the Gene Expression Omnibus (GEO) database. Batch effects cross each sample were eliminated with surrogate variable analysis algorithm. Then, we identified key modules of COVID-19 datasets and heart failure datasets through weighted gene co-expression network analysis. HF-associated as well as COVID-19-associated key modules were intersected for determining the shared genes of COVID-19-associated heart failure. The pivotal genes associated with COVID-19-related heart failure were determined by intersecting the shared genes with the HF-associated hub genes selected through WGCNA. Furthermore, we conducted GO as well as KEGG enrichment analysis on shared genes of COVID-19-associated heart failure. Two COVID-19-associated key modules as well as three HF-associated key modules were determined. In addition, eleven shared genes for COVID-19-associated heart failure were determined. In conclusion, our work screened two critical genes, namely PYGM and BLM, which may be possible intervention targets for COVID-19-associated heart failure. According to functional enrichment results, the shared genes of COVID-19-associated heart failure showed high enrichment in starch and sucrose metabolism, homologous recombination, Fanconi anemia pathway, and insulin resistance indicate the probably biological processes linked to COVID-19-associated heart failure. These results provided further insights in possible interventional and therapeutic targets of COVID-19-associated heart failure.

Dataset Information

An integrative analysis identifying transcriptional features and key genes involved in COVID-19.

Publications

An integrative analysis identifying transcriptional features and key genes involved in COVID-19.

Similar Datasets

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