Cell deconvolution-based integrated time-series network of whole blood transcriptome reveals systemic antiviral activities and cell-specific immunological changes against PRRSV infection

基于细胞反卷积的全血转录组整合时间序列网络揭示了针对猪繁殖与呼吸综合征病毒(PRRSV)感染的系统性抗病毒活性和细胞特异性免疫学变化

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Abstract

Porcine reproductive and respiratory syndrome (PRRS) causes significant economic losses in the swine industry. However, the molecular mechanisms behind the common and cell type-specific systemic responses during PRRS virus (PRRSV) infection are not well understood. In this study, we collected viremia data, antibody levels, and whole-blood RNA-seq data obtained from eight PRRSV-infected piglets. We utilised a cell deconvolution approach to calculate cell type enrichment, constructed a time-serial gene co-expression network with differentially expressed genes, and conducted functional annotations. Three significant modules were identified within the network. The changes associated with viremia revealed an upregulated expression of genes related to antiviral activity. In the T-cell- and NK-cell-specific modules, infection led to an increased T-cell population and upregulation of genes related to T-cell defence responses. Conversely, in the monocyte- and neutrophil-specific module, genes involved in inflammatory responses were downregulated due to a decrease in monocyte proportion. This study highlights the time-series antiviral activities associated with viremia and the transcriptomic changes associated with immune responses in specific cell types. The findings provide comprehensive insights into host responses to PRRSV infection, including diagnostic biomarkers.

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