Abstract
Microbes and viruses are known to alter host transcriptomes by means of infection. In light of recent challenges posed by the COVID-19 pandemic, a deeper understanding of the disease at the transcriptome level is needed. However, research about transcriptome reprogramming by post-transcriptional regulation is very limited. In this study, computational methods developed by our lab were applied to RNA-seq data to detect transcript variants (i.e., alternative splicing (AS) and alternative polyadenylation (APA) events). The RNA-seq data were obtained from a publicly available source, and they consist of mock-treated and SARS-CoV-2 infected (COVID-19) lung alveolar (A549) cells. Data analysis results show that more AS events are found in SARS-CoV-2 infected cells than in mock-treated cells, whereas fewer APA events are detected in SARS-CoV-2 infected cells. A combination of conventional differential gene expression analysis and transcript variants analysis revealed that most of the genes with transcript variants are not differentially expressed. This indicates that no strong correlation exists between differential gene expression and the AS/APA events in the mock-treated or SARS-CoV-2 infected samples. These genes with transcript variants can be applied as another layer of molecular signatures for COVID-19 studies. In addition, the transcript variants are enriched in important biological pathways that were not detected in the studies that only focused on differential gene expression analysis. Therefore, the pathways may lead to new molecular mechanisms of SARS-CoV-2 pathogenesis.
Highlights
The whole world is suffering from the COVID-19 pandemic, but the molecular mechanisms of COVID-19 pathogenesis are not clear
We were able to identify distinct molecular signatures that were not otherwise found by traditional differential gene expression analysis. These novel molecular signatures may contribute to COVID-19 pathobiology
The results from the data analyses demonstrate that several transcriptional and post-transcriptional signatures identified in this study are highly correlated with SARS-CoV-2 pathogenesis and prognosis
Summary
Recent research on the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Has focused primarily on gene expression profiling in various human cell lines and patient samples in an effort to understand the molecular basis of SARS-CoV-2 pathogenesis [1,2,3]. As the SARS-CoV-2 virus can trigger different levels of changes in humans, a thorough understanding of molecular signatures beyond gene expression profiling is needed to comprehensively dissect the pathogenesis of SARS-CoV-2 coronavirus. Immune activation to viral infection is regulated by changes in gene expression and post-transcriptional regulation, such as AS and APA [5,6]. During viral infection by the influenza A virus, the virus can induce widespread AS in the host genes [5,7,8]
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