Estimating RNA numbers in single cells by RNA fluorescent tagging and flow cytometry
Estimating RNA numbers in single cells by RNA fluorescent tagging and flow cytometry
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DOI：
10.1016/j.mimet.2019.105745
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发表时间：
2019-11-01
影响因子：
2.2
通讯作者：
Ribeiro, Andre S.
中科院分区：
文献类型：
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作者：
Bahrudeen, Mohamed N. M.;Chauhan, Vatsala;Ribeiro, Andre S.
估计单细胞 RNA 数量的统计数据已成为基因表达动态信息的关键来源。 MS2d-GFP 标记是体内单 RNA 检测信息最丰富的方法之一。到目前为止，它需要显微镜和费力的半手动图像分析，这限制了可收集的数据量。为了克服这一限制，我们提出了一种新的方法，用于根据表达 MS2d-GFP 标记的 RNA 的细胞的流式细胞术数据来量化 RNA 数量的单细胞分布的平均值、标准差和偏度。该定量方法基于来自整数值 RNA 数量的显微镜单细胞数据的流式细胞术数据的缩放，被证明可以轻松产生关于 RNA 数量的体内单细胞分布的精确大数据，因此可以帮助转录动力学的研究。
Estimating the statistics of single-cell RNA numbers has become a key source of information on gene expression dynamics. One of the most informative methods of in vivo single-RNA detection is MS2d-GFP tagging. So far, it requires microscopy and laborious semi-manual image analysis, which hampers the amount of collectable data. To overcome this limitation, we present a new methodology for quantifying the mean, standard deviation, and skewness of single-cell distributions of RNA numbers, from flow cytometry data on cells expressing RNA tagged with MS2d-GFP. The quantification method, based on scaling flow-cytometry data from microscopy single-cell data on integer-valued RNA numbers, is shown to readily produce precise, big data on in vivo single-cell distributions of RNA numbers and, thus, can assist in studies of transcription dynamics.