SARS-CoV-2 genomic and subgenomic RNA (sgRNA) transcripts hijack the host cell's machinery. Subcellular localization of its viral RNA could, thus, play important roles in viral replication and host antiviral immune response. We perform computational modeling of SARS-CoV-2 viral RNA subcellular residency across eight subcellular neighborhoods. We compare hundreds of SARS-CoV-2 genomes with the human transcriptome and other coronaviruses. We predict the SARS-CoV-2 RNA genome and sgRNAs to be enriched toward the host mitochondrial matrix and nucleolus, and that the 5′ and 3′ viral untranslated regions contain the strongest, most distinct localization signals. We interpret the mitochondrial residency signal as an indicator of intracellular RNA trafficking with respect to double-membrane vesicles, a critical stage in the coronavirus life cycle. Our computational analysis serves as a hypothesis generation tool to suggest models for SARS-CoV-2 biology and inform experimental efforts to combat the virus. A record of this paper’s Transparent Peer Review process is included in the Supplemental Information.

SARS-CoV-2 基因组和亚基因组 RNA (sgRNA) 转录物劫持宿主细胞的机器。因此，其病毒RNA的亚细胞定位可能在病毒复制和宿主抗病毒免疫反应中发挥重要作用。我们对 SARS-CoV-2 病毒 RNA 亚细胞驻留的八个亚细胞邻域进行了计算建模。我们将数百个 SARS-CoV-2 基因组与人类转录组和其他冠状病毒进行了比较。我们预测 SARS-CoV-2 RNA 基因组和 sgRNA 将向宿主线粒体基质和核仁富集，并且 5' 和 3' 病毒非翻译区包含最强、最独特的定位信号。我们将线粒体驻留信号解释为双膜囊泡细胞内 RNA 运输的指标，这是冠状病毒生命周期的关键阶段。我们的计算分析可作为假设生成工具，为 SARS-CoV-2 生物学模型提出建议，并为对抗该病毒的实验工作提供信息。本文的透明同行评审过程的记录包含在补充信息中。