Genome-Wide Profiling Reveals Alternative Polyadenylation of Innate Immune-Related mRNA in Patients With COVID-19

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has caused many deaths worldwide. To date, the mechanism of viral immune escape remains unclear, which is a great obstacle to developing effective clinical treatment. RNA processing mechanisms, including alternative polyadenylation (APA) and alternative splicing (AS), are crucial in the regulation of most human genes in many types of infectious diseases. Because the role of APA and AS in response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remains unknown, we performed de novo identification of dynamic APA sites using a public dataset of human peripheral blood mononuclear cell (PBMC) RNA-Seq data in COVID-19 patients. We found that genes with APA were enriched in innate immunity -related gene ontology categories such as neutrophil activation, regulation of the MAPK cascade and cytokine production, response to interferon-gamma and the innate immune response. We also reported genome-wide AS events and enriched viral transcription-related categories upon SARS-CoV-2 infection. Interestingly, we found that APA events may give better predictions than AS in COVID-19 patients, suggesting that APA could act as a potential therapeutic target and novel biomarker in those patients. Our study is the first to annotate genes with APA and AS in COVID-19 patients and highlights the roles of APA variation in SARS-CoV-2 infection.

Variant- and Vaccination-Specific Alternative Splicing Profiles in SARS-CoV-2 Infections

“…This data depth accords a robust framework to navigate through the complex transcriptional landscape, enabling the detection of genes with low expression levels, and unraveling rare alternative splicing events. Building upon recent studies 13,15,16,49,52 that highlighted the potential targeting of the mRNA splicing machinery by viruses and reported a dysregulation of alternative splicing in COVID-19 patients, our transcriptomic analysis including healthy controls and patients reinforced the global dynamic alterations of alternative splicing in COVID-19 patients. A notable extent of these changes was observed in those infected with the Omicron variant.…”

Whole blood transcriptome signature predicts severe forms of COVID-19: Results from the COVIDeF cohort study

“…This signature corresponds to a differential inflammatory profile between patients with severe and mild outcome, with the implication of humoral immune response, complement activation and interferon signalling pathway. This signature includes the over expression of inflammation markers previously reported in patients with severe COVID-19 pneumonia, such as IFI27 (Shojaei et al 2023 ) or CD177 (Jackson et al 2022 ; Wang et al 2022 ; Lévy et al 2019 ; An et al 2021 ; An et al 2022 ).This signature shows a gradient of expression from mild to intermediate and severe forms. Thus, the inflammatory signature observed in patients with severe COVID-19 pneumonia seems to be present early in the course of the disease, and to reflect the risk of developing a severe outcome.…”

Role of different types of RNA molecules in the severity prediction of SARS-CoV-2 patients

“…Next set of features are related to the prediction of treatment stage of the COVID-19 patients. Same analysis on those genes shows that they are closely related to the biological processes such as neutral amino acid transport [95] , regulation of cellular protein metabolic process [84] , negative regulation of cellular macromolecule biosynthetic process [93] , endosome to lysosome transport [50] , chondrocyte morphogenesis involved in endochondral bone morphogenesis, growth plate cartilage chondrocyte morphogenesis, ferrochelatase activity, chondrocyte morphogenesis, phosphatase activator activity [116] , regulation of protein kinase activity [52] , [79] , negative regulation of cellular metabolic process [11] , [8] , response to inorganic substance [111] , [22] , toll-like receptor 9 signaling pathway [1] , [25] , [49] , [70] , [90] , positive regulation of NIK/NF-kappaB signaling [54] , myeloid dendritic cell activation [6] , [85] , regulation of transcription from RNA polymerase II promoter, protein localization to cilium, positive regulation of cell morphogenesis involved in differentiation, mRNA/RNA polyadenylation [102] , [5] , protein localization to cilium, phosphatidylinositol binding, optic cup structural organization [2] , endosome to plasma membrane transport vesicle, SET domain binding, negative regulation of phosphorus metabolic process [110] , regulation of fatty acid transport/ long-chain fatty acid transport [101] , [108] , [32] , [94] , positive regulation of mRNA catabolic process [87] , positive regulation of mRNA metabolic process [54] , transcription from RNA polymerase II promoter, positive regulation of cellular biosynthetic process, negative regulation of RNA metabolic process, negative regulation of nitrogen compound metabolic process [16] , [76] and negative regulation of cellular macromolecule biosynthetic process [30] .…”