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Estimating RNA numbers in single cells by RNA fluorescent tagging and flow cytometry

Research output: Contribution to journalArticleScientificpeer-review


Original languageEnglish
Article number105745
JournalJournal of Microbiological Methods
Publication statusPublished - 22 Oct 2019
Publication typeA1 Journal article-refereed


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.


  • Flow cytometry, MS2d-GFP RNA tagging, Single-cell RNA numbers, Time-lapse microscopy

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Field of science, Statistics Finland

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