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单细胞分辨率下遗传控制对免疫刺激和糖皮质激素的动态转录反应。

Genetic control of the dynamic transcriptional response to immune stimuli and glucocorticoids at single-cell resolution.

机构信息

Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan 48201, USA.

Department of Psychology, Wayne State University, Detroit, Michigan 48201, USA.

出版信息

Genome Res. 2023 Jun;33(6):839-856. doi: 10.1101/gr.276765.122. Epub 2023 Jul 13.

DOI:10.1101/gr.276765.122
PMID:37442575
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10519413/
Abstract

Synthetic glucocorticoids, such as dexamethasone, have been used as a treatment for many immune conditions, such as asthma and, more recently, severe COVID-19. Single-cell data can capture more fine-grained details on transcriptional variability and dynamics to gain a better understanding of the molecular underpinnings of inter-individual variation in drug response. Here, we used single-cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated peripheral blood mononuclear cells from 96 African American children. We used novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we showed that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and showed widespread genetic regulation of the transcriptional dynamics of the gene expression response.

摘要

合成糖皮质激素,如地塞米松,已被用于治疗许多免疫疾病,如哮喘,以及最近的严重 COVID-19。单细胞数据可以更详细地捕捉转录变异性和动态,从而更好地了解药物反应个体间差异的分子基础。在这里,我们使用单细胞 RNA-seq 来研究 96 名非裔美国儿童激活外周血单核细胞中糖皮质激素转录反应的动态。我们使用新的统计方法来计算基因表达变异性的独立于均值的度量和转录反应拟时的度量。使用这些方法,我们表明糖皮质激素逆转了免疫刺激对基因表达均值和变异性的影响。我们基于对角线性判别分析的新的基因表达反应动力学度量,根据转录谱将单个细胞按反应状态分开,并允许我们根据反应拟时识别基因表达的不同动态模式。我们确定了调节基因表达均值和变异性的遗传变异,包括治疗特异性效应,并表明基因表达反应的转录动力学受到广泛的遗传调控。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee81/10519413/e1e95f95b287/839f08.jpg
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