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SARS-CoV-2 infection mediates differential expression of human endogenous retroviruses and long interspersed nuclear elements
Jez L. Marston, … , Luis P. Iñiguez, Douglas F. Nixon
Jez L. Marston, … , Luis P. Iñiguez, Douglas F. Nixon
Published November 3, 2021
Citation Information: JCI Insight. 2021;6(24):e147170. https://doi.org/10.1172/jci.insight.147170.
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Research Article COVID-19 Infectious disease

SARS-CoV-2 infection mediates differential expression of human endogenous retroviruses and long interspersed nuclear elements

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Abstract

SARS-CoV-2 promotes an imbalanced host response that underlies the development and severity of COVID-19. Infections with viruses are known to modulate transposable elements (TEs), which can exert downstream effects by modulating host gene expression, innate immune sensing, or activities encoded by their protein products. We investigated the impact of SARS-CoV-2 infection on TE expression using RNA-Seq data from cell lines and from primary patient samples. Using a bioinformatics tool, Telescope, we showed that SARS-CoV-2 infection led to upregulation or downregulation of TE transcripts, a subset of which differed from cells infected with SARS, Middle East respiratory syndrome coronavirus (MERS-CoV or MERS), influenza A virus (IAV), respiratory syncytial virus (RSV), and human parainfluenza virus type 3 (HPIV3). Differential expression of key retroelements specifically identified distinct virus families, such as Coronaviridae, with unique retroelement expression subdividing viral species. Analysis of ChIP-Seq data showed that TEs differentially expressed in SARS-CoV-2 infection were enriched for binding sites for transcription factors involved in immune responses and for pioneer transcription factors. In samples from patients with COVID-19, there was significant TE overexpression in bronchoalveolar lavage fluid and downregulation in PBMCs. Thus, although the host gene transcriptome is altered by infection with SARS-CoV-2, the retrotranscriptome may contain the most distinctive features of the cellular response to SARS-CoV-2 infection.

Authors

Jez L. Marston, Matthew Greenig, Manvendra Singh, Matthew L. Bendall, Rodrigo R.R. Duarte, Cédric Feschotte, Luis P. Iñiguez, Douglas F. Nixon

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Figure 2

Network analysis of gene and retroelement expression changes induced by various viral infections.

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Network analysis of gene and retroelement expression changes induced by ...
(A) Selected gene clusters produced from the comparison of the transcriptomes of Calu-3 cells in 4 infection conditions (MOCK; SARS_Cov2; SARS; MERS). For each cluster, the scaled mean expression value (z score) for each gene in each group is plotted as a point. Box plots show the median expression z score (dark line) and the first and third quartiles (edges) of the cluster’s gene expression values in each condition. (B) Overrepresentation analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (left) and Gene Ontology (GO) terms (right) for selected Calu-3 clusters. Terms in the heatmap are shaded according to –log10(P), using the P value obtained from a hypergeometric test for each term’s overrepresentation in each cluster’s set of genes. Terms with P > 0.05 are not shaded. (C) Selected gene clusters from the comparison of the transcriptomes of A549 cells in 5 infection conditions (MOCK; SARS_Cov2; IAV; RSV; HPIV3). (D) KEGG and GO enrichment analysis results for selected A549 cell clusters. (E) Selected gene clusters from the comparison of the transcriptomes of A549-ACE2 cells in 4 infection conditions (MOCK; MOI 0.2; MOI 2; MOI 2 + ruxolitinib). (F) KEGG and GO enrichment analysis results for selected A549-ACE2 cell clusters.

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