Transcriptogram analysis reveals relationship between viral titer and gene sets responses during Corona-virus infection.
Transcriptogram analysis reveals relationship between viral titer and gene sets responses during Corona-virus infection.
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转录图分析揭示了冠状病毒感染期间病毒滴度与基因组反应之间的关系。
DOI：
10.1101/2020.06.16.155267
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Glazier,JamesA
中科院分区：
文献类型：
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作者：
deAlmeida,RitaMC;Thomas,GilbertoL;Glazier,JamesA
为了了解冠状病毒感染后良性和严重结果之间的差异，我们迫切需要澄清和量化组织和免疫反应的时间过程的方法。在这里，我们重新分析了西姆斯和合作者在2013年为SARS-CoV-1体外感染人肺上皮细胞系生成的72小时时间序列微阵列。转录图是一种分析全基因组基因表达数据的生物信息学工具，它使我们能够为基因差异表达的机制相关性定义一个适当的上下文相关阈值。在不事先知道哪些基因是相关的情况下，经典分析检测每个基因的显著差异表达，给我们留下了太多的基因和假设是有用的。使用基于转录图的自上而下的方法，我们确定了三个主要的差异表达基因集，包括219个主要的免疫反应相关基因。我们确定了线粒体活性改变的时间尺度，先天性和适应性免疫系统的信号传导和转录调节及其与病毒滴度的关系。这些方法可以应用于SARS-CoV-2的RNA数据集，以研究不同组织类型中差异反应的起源，或由于免疫或预先存在的条件，或比较细胞培养，类器官培养，动物模型和人源性样品。
To understand the difference between benign and severe outcomes after Coronavirus infection, we urgently need ways to clarify and quantify the time course of tissue and immune responses. Here we re-analyze 72-hour time-series microarrays generated in 2013 by Sims and collaborators for SARS-CoV-1in vitroinfection of a human lung epithelial cell line. Transcriptograms, a Bioinformatics tool to analyze genome-wide gene expression data, allow us to define an appropriate context-dependent threshold for mechanistic relevance of gene differential expression. Without knowing in advance which genes are relevant, classical analyses detecteverygene with statistically-significant differential expression, leaving us with too many genes and hypotheses to be useful. Using a Transcriptogram-based top-down approach, we identified three major, differentially-expressed gene sets comprising 219 mainly immune-response-related genes. We identified timescales for alterations in mitochondrial activity, signaling and transcription regulation of the innate and adaptive immune systems and their relationship to viral titer. The methods can be applied to RNA data sets for SARS-CoV-2 to investigate the origin of differential responses in different tissue types, or due to immune or preexisting conditions or to compare cell culture, organoid culture, animal models and human-derived samples.